Mississippi State University Scholars Junction Theses and Dissertations Theses and Dissertations 5-13-2022 Assessment of mechanical engineering skills: a synthesis of industry and academic graduate level curriculum requirements Francie Baker Mississippi State University, francie.a.baker@gmail.com Follow this and additional works at: https://scholarsjunction.msstate.edu/td Part of the Engineering Education Commons, and the Other Mechanical Engineering Commons Recommended Citation Baker, Francie, "Assessment of mechanical engineering skills: a synthesis of industry and academic graduate level curriculum requirements" (2022). Theses and Dissertations. 5441. https://scholarsjunction.msstate.edu/td/5441 This Dissertation - Open Access is brought to you for free and open access by the Theses and Dissertations at Scholars Junction. It has been accepted for inclusion in Theses and Dissertations by an authorized administrator of Scholars Junction. For more information, please contact scholcomm@msstate.libanswers.com. Template C v4.3 (beta): Created by T. Robinson 01/2021 Assessment of mechanical engineering skills: a synthesis of industry and academic graduate level curriculum requirements TITLE PAGE Francie Baker Approved by: Alta Knizley (Co-Major Professor) Yucheng Liu (Co-Major Professor) Mahnas J. Mohammadi-Aragh John Turner Tonya W. Stone (Graduate Coordinator) Jason M. Keith (Dean, Bagley College of Engineering) A Dissertation Submitted to the Faculty of Mississippi State University in Partial Fulfillment of the Requirements for the Degree of Doctor of Philosophy in Mechanical Engineering in the Bagley College of Engineering Mississippi State, Mississippi May 2022 Copyright by COPYRIGHT PAGE Francie Baker 2022 Name: Francie Baker ABSTRACT Date of Degree: May 13, 2022 Institution: Mississippi State University Major Field: Mechanical Engineering Major Professors: Alta Knizley, Yucheng Liu Title of Study: Assessment of mechanical engineering skills: a synthesis of industry and academic graduate level curriculum requirements Pages in Study: 203 Candidate for Degree of Doctor of Philosophy Students who graduate with an advanced degree in mechanical engineering are a diverse group in their path to post-baccalaureate degree attainment. Some students choose to obtain their master’s or Ph.D. post bachelors, but before they enter the workplace. Others enter the workforce and return as full-time students or progress on their advanced degrees while maintaining part- or full-time employment. Current accreditation standards for undergraduate degree programs are part of a changing landscape of standards and professional requirements that have adapted and continue to adapt as programs prepare students to work in professional engineering fields. Advanced degrees do not have the same set of standards as accredited undergraduate programs that are modified and examined for continuous improvement of the preparation of students for professional and academic careers. Without this overall agreement, what are advanced degree programs offering students and what skills should the programs be addressing the most? This research develops an understand of what the technical, professional, and academic requirements are expected for students seeking employment or continuing to advance in their chosen careers. ii DEDICATION This dissertation is dedicated to my daughter, who has spent the first three years of her life sharing my attention with this pursuit and my husband, who changed more than his fair share of diapers to allow me time to study. This work is also dedicated to my best friend, who served as the best shoulder to virtually cry on through all the challenges of the last few years and my mom, who never let me quit. And finally, my dad, who passed away before this journey began, but has always been with me in spirit. iii ACKNOWLEDGEMENTS I’d like to acknowledge my undergraduate research advisor, Dr. Bratoljub Milosavljevic, for his support to pursue graduate research and education (even outside the field of physical chemistry). I’d also like to acknowledge my graduate committee. Dr. Liu for accepting me as an advisee and finding a research path that could build on my background in education and newfound love of mechanical engineering while at a distance. Dr. Knizley for helping me to the finish line and demonstrating care and compassion to guide me through for all the challenges at the end. Dr. Turner for his belief and support, and Dr. Mohammadi-Aragh for her motivational passion for engineering education. iv TABLE OF CONTENTS DEDICATION ................................................................................................................................ ii ACKNOWLEDGEMENTS ........................................................................................................... iii LIST OF TABLES ....................................................................................................................... viii LIST OF FIGURES .........................................................................................................................x CHAPTER I. INTRODUCTION .............................................................................................................1 1.1 Summary ................................................................................................................1 1.2 Research Questions ...............................................................................................1 1.3 Introduction ...........................................................................................................4 1.4 Mechanical Engineering Skills and Programmatic Outcomes ..............................5 1.4.1 Systematic Evaluation Techniques ..................................................................5 1.4.1.1 Systematically Assess Skills ......................................................................6 1.4.2 Professional and Technical Skills of Engineers ..............................................8 1.4.2.1 Professional Skills/ Soft Skills of Engineers .............................................8 1.4.2.2 Graduation Skills of Mechanical Engineers ..............................................9 1.4.2.2.1 Requirements of Mechanical Engineering Degrees ......................9 1.4.2.2.2 Undergraduate ABET Criteria as it applies to ME ........................9 1.4.2.2.2.1 Graduate-level ABET Criteria as it applies to Mechanical Engineering ..................................................................................10 1.4.2.2.2.2 International Criteria of Mechanical Engineering ..............11 1.4.2.3 Core Skills for Employment of Engineers ...............................................14 1.4.3 Employment – Opportunities after Graduation .............................................14 1.4.3.1 Opportunities after B.S. in Mechanical Engineering ...............................14 1.4.3.1.1 Master’s Degree ...........................................................................14 1.4.3.1.2 PhD Engineering ME ..................................................................15 1.5 Conclusion ...........................................................................................................15 II. ANALYSIS OF GRADUATE MECHANICAL ENGINEERING PROGRAMS BY RANKING ......................................................................................................................17 2.1 Abstract ................................................................................................................17 2.2 Introduction .........................................................................................................17 2.3 Literature Review ................................................................................................19 v 2.4 Methodology ........................................................................................................21 2.4.1 Data collection and coding ............................................................................22 2.4.2 Data calculations ...........................................................................................23 2.5 Results .................................................................................................................24 2.5.1 Minor and Breadth of Program ......................................................................25 2.5.2 Trends based on U.S. News Ranking ............................................................25 2.6 Discussion ............................................................................................................27 2.6.1 What do they mean? ......................................................................................27 2.6.2 Implications and limitations/future research – recommended future research .......................................................................................................................28 2.7 Conclusion ...........................................................................................................29 III. A NEW QUESTIONNAIRE FOR ASSESSMENT OF A MECHANICAL ENGINEERING SENIOR DESIGN CLASS .................................................................30 3.1 Abstract ................................................................................................................30 3.2 Introduction .........................................................................................................30 3.3 Status of the course and current evaluation questionnaire ..................................33 3.4 Design of a new assessment instrument ..............................................................36 3.5 Assessment results ...............................................................................................39 3.5.1 Course Goals .................................................................................................39 3.5.2 Group dynamics .............................................................................................40 3.5.3 Industry importance .......................................................................................41 3.5.4 Student outcomes ...........................................................................................41 3.5.5 Student comments .........................................................................................41 3.6 Discussion ............................................................................................................42 3.6.1 Effectiveness on skill growth and knowledge development .........................42 3.6.2 Impact on ABET ............................................................................................44 3.7 Conclusion ...........................................................................................................44 IV. DEVELOPMENT, ASSESSMENT, AND EVALUATION OF LABORATORY EXPERIMENTATION FOR A MECHANICAL VIBRATIONS AND CONTROLS COURSE .........................................................................................................................46 4.1 Abstract ................................................................................................................46 4.2 Introduction .........................................................................................................46 4.3 Background ..........................................................................................................49 4.4 Description of team projects ................................................................................51 4.5 Selected project results ........................................................................................53 4.5.1 First order spring-damper system ..................................................................53 4.5.2 Second-order mass-spring-damper system ....................................................55 4.5.3 Thermocouple project ....................................................................................61 4.5.4 Electrical scale project ...................................................................................67 4.6 Student evaluation ...............................................................................................70 4.6.1 Course goals ..................................................................................................70 4.6.2 ABET student outcomes ................................................................................72 vi 4.6.3 Roles of textbook and open educational resources in this course .................72 4.6.4 Selected student comments ............................................................................73 4.7 Conclusion ...........................................................................................................74 V. GRADUATE SKILLS MASTERED UPON GRADUATION ......................................76 5.1 Abstract ................................................................................................................76 5.2 Introduction .........................................................................................................76 5.3 Relationship to student motivation ......................................................................79 5.4 Perceptions of what is important .........................................................................82 5.5 Conclusions .........................................................................................................90 VI. SOFT SKILLS FOR ENTRY-LEVEL ENGINEERS: WHAT EMPLOYERS WANT .91 6.1 Abstract ................................................................................................................91 6.2 Introduction .........................................................................................................92 6.2.1 Purpose and Problem Statement ....................................................................95 6.2.2 Research Questions .......................................................................................96 6.2.3 Conceptual Framework .................................................................................96 6.3 Review of Literature ............................................................................................97 6.3.1 What Are Soft Skills? ....................................................................................97 6.3.2 Research on Soft Skills ..................................................................................98 6.3.3 What Soft Skills Are Important in the Employment Context? ....................101 6.4 Method and Results ...........................................................................................104 6.4.1 Survey Design and Distribution ..................................................................105 6.4.1.2 Information about the Respondents and Their Organizations ...............107 6.4.2 Results of Paired Mean Difference Analysis ...............................................109 6.4.2.2 Size of the Organization ........................................................................114 6.4.2.3 Sector Type of Organization .................................................................114 6.4.2.4 Geographic Location of Headquarters and Branches, Offices, of Plants .... .........................................................................................................115 6.4.2.5 Primary Line of Business ......................................................................115 6.4.2.6 Role of Respondent in Organization .....................................................116 6.4.2.7 Supervision Role by Respondents in Organization ...............................117 6.4.3 Results of between Organization and Respondent Characteristics Analysis of Variance of Importance and Proficiency Ratings ........................................118 6.4.3.1 Results of Organizations’ Size Analysis of Variance ......................119 6.4.3.2 Results of Organizations’ Sector Analysis of Variance ........................120 6.4.3.3 Results of Organizations’ Locations Analysis of Variance ...................122 6.4.3.4 Results of Primary Line of Business Analysis of Variance ..................124 6.4.3.5 Results of Respondents Role in Organizations Analysis of Variance ...125 6.4.3.6 Results of Supervisory Roles in Organizations Analysis of Variance ..127 6.4.3.7 Review of Analysis of Variance Outcomes ...........................................129 6.4.4 Analysis of Participants’ Open-Ended Comments at the End of the Survey .....................................................................................................................131 6.4.4.1 Soft Skills Are Often the Final Deciding Factor ...................................132 vii 6.4.4.2 What Do Employers Look for Specifically during the Hiring Process? ..... .........................................................................................................133 6.4.4.3 Communication Skill .............................................................................135 6.4.4.4 Interpersonal Skills ................................................................................136 6.4.4.5 Personality Characteristics ....................................................................137 6.4.4.6 Summary of Participants’ Comments ....................................................137 6.5 Discussion ..........................................................................................................138 6.5.1 Implications for Engineering Education ......................................................148 6.5.2 Implications for Engineering during Industry 4.0 .......................................150 6.6 Conclusion .........................................................................................................151 VII. REQUIREMENTS OF MECHANICAL ENGINEERING FACULTY: EVIDENCE FROM JOB AD QUALIFICATIONS AND RESPONSIBILITIES .............................153 7.1 Abstract ..............................................................................................................153 7.2 Introduction .......................................................................................................154 7.3 Background ........................................................................................................155 7.4 Methods .............................................................................................................157 7.5 Findings .............................................................................................................159 7.5.2 Required Qualifications ...............................................................................160 7.5.2.1 Degree and area of expertise .................................................................161 7.5.2.2 Accreditation requirements of degree granting institutions ..................163 7.5.2.3 Research expertise required ...................................................................164 7.5.2.4 Teaching experience required ................................................................165 7.5.2.5 Professional Engineering licensure requirements .................................167 7.5.2.6 Relevant industry experience required ..................................................167 7.5.2.7 Other qualities and skills required .........................................................168 7.5.3 Skills most frequently specified as preferred ..............................................171 7.5.3.1 Teaching ................................................................................................171 7.5.3.2 Research ................................................................................................173 7.5.3.3 Service ...................................................................................................173 7.5.3.4 Specific classification and language proficiency ..................................174 7.5.3.5 Specific knowledge ...............................................................................175 7.5.4 Skills listed within the responsibilities ........................................................177 7.6 Discussion ..........................................................................................................178 7.7 Conclusion .........................................................................................................182 VIII. CONCLUSION .............................................................................................................184 8.1 Discussion & Conclusion ..................................................................................184 8.2 Overall Limitations ............................................................................................186 8.3 Recommendations for Future Studies ...............................................................187 REFERENCES ............................................................................................................................188 viii LIST OF TABLES Table 1.1 Skill descriptions of engineering master’s graduates [Nevia, 2019] and connected ABET outcomes [ABET, 2021] ................................................................12 Table 1.2 European Qualification Framework [Nair, Patil & Mertova, 2009] ..........................13 Table 3.1 Evaluation questions in the currently used evaluation form and student feedbacks ....................................................................................................................35 Table 3.2 Assessment and results on course goals. ....................................................................37 Table 3.3 Assessment and results on industry importance. ........................................................37 Table 3.4 Assessment results of the course’s impact on ABET outcomes. ................................38 Table 3.5 Ranking of student perceptions on industry importance of skills and knowledge and their corresponding growths. .............................................................43 Table 4.1 Calibration points showing the displacement–voltage relationship. ..........................53 Table 4.2 Bill of materials for project 1. ....................................................................................55 Table 4.3 Bill of materials for project 2. ....................................................................................61 Table 4.4 Bill of materials for project 3. ....................................................................................63 Table 4.5 Gains of the op-amps used in the thermocouple system. ...........................................63 Table 4.6 Bill of materials for project 4. ....................................................................................69 Table 4.7 Assessment and results on course goals. ....................................................................69 Table 4.8 Assessment results of the course’s impact on ABET outcomes. ................................71 Table 5.1 Aggregate student and faculty rating of the ABET student outcomes .......................84 Table 5.2 Comparison by student respondent of the 3 most important skills for master’s degree and for doctoral students exiting the mechanical engineering program. ........86 Table 5.3 Comparison by faculty respondent of the 3 most important skills for master’s degree and for doctoral students exiting the mechanical engineering program. ........87 ix Table 5.4 Enrollment Status by Graduate Student .....................................................................89 Table 6.1 Lists of Soft Skills Required for Entry and Success in the Workplace. ...................102 Table 6.2 Survey Format. .........................................................................................................106 Table 6.3 Profile of the Respondents and their Organizations .................................................108 Table 6.4 Soft skills rating of Importance and Proficiency and pair differences means, ranked by Proficiency rating from least to greatest ..................................................113 Table 6.5 Primary Line of Business Recode Between Variable Tukey Pairwise Results ........116 Table 6.6 Role of Respondent in Organization Recode Between Variable Tukey Pairwise Results........................................................................................................117 Table 6.7 Primary Line of Business Analysis of Variance results for Importance Ratings of Soft Skills ................................................................................................124 Table 6.8 Respondent’s Role in Organization Analysis of Variance results for Importance and Proficiency Ratings of Soft Skills ..................................................126 Table 6.9 Respondent’s Supervisory Role of Entry Level Engineers Analysis of Variance results for Importance and Proficiency Ratings of Soft Skills ..................128 Table 7.1 Top Ten Text Matches in Academic Job Advertisements Analyzed .......................158 Table 7.2 Counts of Position Types and Selected Requirements .............................................160 x LIST OF FIGURES Figure 2.1 Average percent of research dollars, applications, and graduation by rank group; percentage is calculated as mechanical engineering program values compared to engineering program values. ..................................................................26 Figure 2.2 Comparison of average mechanical engineering programs’ ranking and average engineering programs’ ranking by group to the ranking by U.S. News ...........................................................................................................................27 Figure 3.1 Examples of student outcomes from the design course..............................................34 Figure 4.1 Developed first-order vibration system: (a) CAD model; (b) prototype. ...................53 Figure 4.2 LabView block diagram. ............................................................................................55 Figure 4.3 Prototype of second-order vibration system. ..............................................................57 Figure 4.4 Mass-spring system with mass carriage and machined steel frame ...........................58 Figure 4.5 Damper and its connection with the mass. .................................................................58 Figure 4.6 Placement of LVDT system .......................................................................................59 Figure 4.7 Attaching a ruler to the frame. ....................................................................................60 Figure 4.8 Thermocouple design. ................................................................................................62 Figure 4.9 Circuit diagram of the thermocouple design. .............................................................63 Figure 4.10 The block diagram of the system in Simulink. ...........................................................64 Figure 4.11 Theoretical method to determine Km and τm. .............................................................65 Figure 4.12 The response voltage when the temperature is 273K. ................................................65 Figure 4.13 Theoretical calculations to determine the voltages. ...................................................66 Figure 4.14 Mathcad codes for calculating time constant, damping ratio, and natural frequency based on established transfer function Y/X. ..............................................67 Figure 4.15 Electrical scale using a bar strain gage load cell. .......................................................68 xi Figure 4.16 Complete circuit diagram. ..........................................................................................68 Figure 6.1 Importance vs. Perceived Proficiency ......................................................................112 1 CHAPTER I INTRODUCTION 1.1 Summary The programs and professors providing the students with a quality education have the potential to increase the attraction of highly skilled students to apply for their mechanical engineering programs. Consequently, the reinforcement of required technical, professional, and academic knowledge, skills, and abilities within the program of study and enrollment of highly skilled students increases the likelihood of a higher level of employability of program graduates. Subsequently, faculty and students would expect to have increased competitiveness to secure extramural funding from federal, state, and private industry sources. This positive spiral of improved quality of program elements to meet the global workforce requirements of mechanical engineers, highly skilled students, and funding can also lead to program and physical facility growth with increased enrollment and financial resources to expand professional grade research equipment capacity and capability. 1.2 Research Questions The manuscripts in this dissertation are being applied to find the answers to the following questions. 1. What skills do Master’s and PhD students in Mechanical Engineering need to develop to ensure they have highly sought after technical and professional skills required to improve the likelihood of employability? 2 2. What additional skills are needed within the Master’s and Ph.D. Mechanical engineering programs to ensure that the students are prepared for global workforce requirements? The first manuscript, “Analysis of graduate mechanical engineering programs by ranking” documents the current programmatic design decisions in graduate level mechanical engineering programs. The trends in programs based on ranking by U.S. News are used to compare graduate mechanical engineering programs and determine trends that exist between the programs. The second manuscript, “A new questionnaire for assessment of a mechanical engineering design class” was published in the International Journal of Mechanical Engineering Education in 2018. Yucheng Liu and Francie Baker co-authored the paper. The paper was also presented at the 2018 ASEE Southeastern Section Conference. The paper discusses a new questionnaire that is designed to assess programmatic design decisions related to professional skills developed in the classroom. Courses are redesigned in order to teach students to more effectively meet the skills needed in their careers. This paper discusses the improvement in student’s skills in problem solving and multidisciplinary teams in the redesigned course. The third manuscript, “Development, assessment, and evaluation of laboratory experimentation for a mechanical vibrations and controls course” was published in the International Journal of Mechanical Engineering Education in 2019. Yucheng Liu, Francie Baker, Wenpei He. and Wei Lai co-authored the paper. The paper was also presented at the 2019 ASEE Southeastern Section Conference. This paper builds on the prior research with the survey instrument and serves as a tool to assess programmatic design decisions related to course materials and projects. Once again 3 confirming a renovated course design is meeting the needs of the students and an assessment if course materials met the learning needs of the students. The fourth manuscript, “Graduate skills mastered upon graduation” is expected to be presented at a conference. This paper touches on how perceived importance of graduate level student outcomes differ by graduate student and faculty status. People will be motivated by what they perceive as most important – determination of congruence and divergence in motivations of graduate students and faculty. Understanding of where students and faculty match and differ can help increase communication within the courses and program design. The fifth manuscript, “Soft skills for entry-level engineers: what employers want” is a co-authorship of Malar Hirudayaraj, Rose Baker, Francie Baker, and Mike Eastman and was published in Education Sciences in 2021. The paper informs programmatic decisions to prioritize curriculum content and resource allocation to maximize proficiency to meet the industry requirements for professional skills in this time of Industry 4.0. The paper identified industry requirements for professional skills and which professional skills are not currently being met within programs. The sixth manuscript, “Requirements of mechanical engineering faculty: evidence from job ad qualifications and responsibilities”, is intended for publication. The paper identifies the academia criteria that will inform programmatic design decisions. Identifying academia requirements for professional skills in job advertisements. The skills that are referenced by various academia for jobs seeking candidates who have obtained graduate level mechanical engineering degrees. 4 1.3 Introduction Students who study mechanical engineering with the desire to become professional engineers (P.E.) are required to either graduate from an ABET (Accreditation Board for Engineering and Technology) accredited undergraduate engineering degree program or couple a related bachelor’s degree (Non-ABET, Engineering Technology, or related science) with an advanced engineering degree from a school with an accredited undergraduate program. ABET accredited undergraduate and master’s level degree programs require students to meet a set of qualifications that the programs have to document that the students are attaining. These ABET accreditation requirements define the integrated, organized experience for the program’s educational objectives, student outcomes, curriculum, faculty, and facilities. Few master’s degree programs and no Doctoral programs are accredited by ABET. Although ABET accredited program graduation is a benefit for students seeking certification and work as a P.E., not all graduate level engineering students have an undergraduate degree from an ABET accredited program or from an engineering program. Specifically, accepted master’s and doctoral (Ph.D.) students in mechanical engineering may not have an ABET accredited undergraduate degree upon entry to their graduate program. Because ABET accredited programs have the requirements necessary to meet the skills expected by a global workforce, master’s and doctoral programs might find it beneficial to reinforce the ABET accreditation knowledge, skills, and abilities for their students. The goal of this Dissertation is to inform programs and professors about the knowledge, skills, and abilities the global workforce requires for mechanical engineering graduates. This information for how the programs and professors can provide the students with a quality education has the potential to increase the attraction of highly skilled students to apply for the 5 mechanical engineering programs. Consequently, the combination of the reinforcement of expected knowledge, skills, and abilities within the program and the further development of highly skilled students has the likelihood of a higher level of employability of program graduates. Subsequently, faculty and students would expect to have increased competitiveness to secure extramural funding from federal, state, and private industry sources. 1.4 Mechanical Engineering Skills and Programmatic Outcomes Mechanical engineering education has shown significant increase in attention since the late 1990s with a worldwide movement towards outcomes-based quality assurance in engineering education (American Society for Engineering Education, 1994; Crawley, Malmqvist & Ostlund, 2007; Cupp, Moore & Fortenberry 2004; De Graaff & Ravesteijn 2001; McMasters & Komerath 2005; National Research Council, 1995; Passow, 2012). With the creation of Engineering Criteria 2000 (EC2000), ABET focus shifted more towards the non-technical or professional skills that graduates need to succeed in the global workforce (Whiteman, 2003). There is an increase in research within engineering programs focused on refining teaching strategies, updating labs, and advancing student experiences (Liu & Baker 2018; Liu, Baker, He & Lai, 2019). The majority of this research has been focused on the undergraduate level and the implications of senior capstone projects. 1.4.1 Systematic Evaluation Techniques Assessing skills and determining causal relationships of program design decisions and outcomes requires systematic evaluation techniques. Using systematic evaluation techniques, the outcomes of the identification of the learning activities, levels of engagement, and attainment of 6 course objectives will outline the process to assess the skills needed and quantify the skills learned by students. 1.4.1.1 Systematically Assess Skills The assessment of skills, both technical and professional, is important to determine if students are learning what they need to be competitive in the global labor market. Student and employers “expect a high degree of synergy” between what is learned in school and what is needed in the field of practice [The Steering Committee of the National Engineering Research Colloquies, 2006]. In order to become a professional engineer after a bachelor’s degree, students are required to have an ABET accredited degree [Requirements, 2021]. As part of the ABET accreditation, engineering students by the time they graduate must have documented attainment of a set of professional and technical skills. These skills include teamwork, oral and written communication, impact of engineering solutions, life-long learning, and knowledge of contemporary issues [ABET, 2021]. When a student graduates with an ABET accredited degree, their school is certifying that the student has met or exceeded a specific set of skills that are valuable to being mechanical engineers in the workforce. These skills include both technical and professional skills. Being able to assess these skills while students are earning their degree is important to maintain this accreditation at the time of each program review [ABET, 2021]. There has been a significant increase in the last two decades in studies related to the assessment of skills of undergraduate engineers and undergraduate engineering programs. The teaching and assessment of ABET skills remains problematic [Al-Bahi, Taha & Turkmen, 2013]. 7 Due to the broad scope of application and knowledge, it can be difficult to assess the necessary skills of mechanical engineers. Documentation of students’ learning and their improvements is vital to demonstrating that a program is meeting or exceeding accreditation standards at the undergraduate level and fostering strong graduate level students upon entrance into the workforce. Methods to assess improvement in students are closely tied to assessment of the skills themselves. One method to assess skills is through a student questionnaire. Student course evaluation questionnaires are widely used in colleges and universities as an instrument to evaluate teaching performance [Liu & Baker, 2018]. The validity of using such a questionnaire has been confirmed in several studies [Wilson, Lisso & Ramsden, 2006; Coffey & Gibbs, 2001]. Researchers develop specialized questionnaires to measure teaching methods or expected student outcomes [Spencer & Aleamoni, 1970; Cassel, 1971; Ramsden, 1991; Lyon & Hendry, 2002]. Students completing self-assessment questionnaires can help researchers determine how students are perceiving learning ABET criteria. Liu and Baker [2018] developed a course questionnaire to assess a new course design for a senior level design class. This instrument covered the key technical skills associated with the course, industry soft skills, and the ABET criteria. The professional/soft skills assessed included teamwork, communication, management, problem solving, organization, and leadership. In addition to ranking these skills, the students also ranked on a Likert scale how much they agreed that the course provided the students with each of the ABET criteria outcomes a through k. The instrument used in this study was adapted and utilized to assess a senior level introduction to vibrations and controls course [Liu, Baker, He & Lai, 2019]. Even though the assessment initially focused on a different set of technical skills for a different course, the students in the senior level course were asked the same questions about 8 rating the course’s impact on ABET outcomes. Both of these applications of the instrument demonstrate that the skill students need, technical and professional, can be assessed and compared with ABET outcomes to get a full picture of student learning outcomes. 1.4.2 Professional and Technical Skills of Engineers Since the Space race of the 1950s, there has been an increase in desire to have more engineers in the workforce with critical thinking and engineering skills. Approaching the 21st century, the focus and importance of these skills had shifted from not just technical engineering skills, but shifted to include non-technical skills, often referred to as “soft-skills”. As time has marched forward in the 21st Century, in order to succeed in the workforce, Engineers are expected to have both professional and technical skills [Shuman, Besterfield-Sacre & McGourty, 2005]. 1.4.2.1 Professional Skills/ Soft Skills of Engineers Professional skills, also commonly referred to as Soft Skills, are the non-technical skills engineers need to be employable. Evidenced by research and publication, over the last 20 years there has been a worldwide movement to not only educate engineers in technical skills but also what are generally referred to as soft skills. [Cruz, Saunders-Smith & Goen, 2020]. Within this window of increased expectations, research indicated that mechanical engineers were not developing the critical “skills needed in the workplace” [Nair, Patil & Mertova, 2009]. According to Adecco [Adecco, 2021], 44% of Americans lack soft skills including communication, creativity, critical thinking, and collaboration. A survey of 1372 engineers with bachelor, master or diploma degrees showed large gaps in communication skills, leadership skills and social skills [Bodmer, Leu, Mira & Rutter, 2002]. 9 1.4.2.2 Graduation Skills of Mechanical Engineers Graduates of a mechanical engineering undergraduate program should be able to succeed in a diverse mix of career paths. These include traditional engineering positions such as working in manufacturing and service fields (e.g., automotive, HVAC, etc.,) STEM fields, or other fields that draw upon specialized engineering knowledge (e.g., consulting and finance). The results of a 2009 study in Australia indicated the most critical skills required by graduating engineers out of both technical and non-technical programs were communication, teamwork, self-management, and problem solving [26]. These are consistent with skills identified by the U.S. engineering community: communication, business, teamwork, creativity, lifelong learning, and problem solving [ABET, 2021; McMasters & Komerath, 2005; National Academy of Engineering, 2004]. 1.4.2.2.1 Requirements of Mechanical Engineering Degrees Students who earn an undergraduate degree in mechanical engineering are expected to be able to work in a diverse set of industries. ABET works to prepare students in mechanical engineering for this diverse career set. 1.4.2.2.2 Undergraduate ABET Criteria as it applies to ME As on 8/30/2021 that are 386 bachelor level programs in mechanical engineering in the United States and 481 world-wide [ABET, 2021]. Each program must satisfy applicable Program Criteria (if any). Program Criteria provide the specificity needed for interpretation of the general criteria as applicable to a given discipline. Requirements stipulated in the Program Criteria are limited to the areas of curricular topics and faculty qualifications. If a program, by virtue of its title, becomes subject to two or more sets of Program Criteria, then that program must satisfy 10 each set of Program Criteria; however, overlapping requirements need to be satisfied only once. The curriculum must require students to apply principles of engineering, basic science, and mathematics (including multivariate calculus and differential equations); to model, analyze, design, and realize physical systems, components, or processes; and prepare students to work professionally in either thermal or mechanical systems while requiring topics in each area [ABET, 2021]. Students will be able to demonstrate all of the Student Outcomes in Criterion 3. According to ABET criteria requirements, the curriculum must include all of the following specific areas [ABET, 2021]: a. a minimum of 30 semester credit hours (or equivalent) of a combination of college-level mathematics and basic sciences with experimental experience appropriate to the program. b. a minimum of 45 semester credit hours (or equivalent) of engineering topics appropriate to the program, consisting of engineering and computer sciences and engineering design, and utilizing modern engineering tools. c. a broad education component that complements the technical content of the curriculum and is consistent with the program educational objectives. d. a culminating major engineering design experience that 1) incorporates appropriate engineering standards and multiple constraints, and 2) is based on the knowledge and skills acquired in earlier course work. 1.4.2.2.2.1 Graduate-level ABET Criteria as it applies to Mechanical Engineering An option at many universities for students is to complete an integrated Baccalaureate-Master’s degree program. These programs generally have specific requirements for student 11 enrollment. ABET requires these programs to meet all of the General Criteria for baccalaureate programs plus additional criteria below [ABET, 2021]: a. Supports the attainment of student outcomes of Criterion 3 of the general criteria for baccalaureate level engineering programs, and b. Includes at least 30 semester credit hours (or equivalent) of math and basic science (basic science includes the biological, chemical, and physical sciences), as well as at least 45 semester credit hours (or equivalent) of engineering topics and a major design experience that meets the requirements of Criterion 5 of the general criteria for baccalaureate level engineering programs. By attending a school with an accredited undergraduate engineering program, mechanical engineering graduate students who do not have an ABET accredited B.S. engineering degree can couple their undergraduate degree with the graduate degree to satisfy the academic requirements for PE certification [Requirements, 2021]. 1.4.2.2.2.2 International Criteria of Mechanical Engineering Foreign nationals account for 58% of full-time mechanical engineering graduate students at U.S. universities [Cruz, Saunders-Smith & Groen, 2020]. Without international students it would be difficult to maintain these graduate programs. These graduate students need to be prepared for the global workforce. There are different accreditation frameworks around the globe. Many countries outside of the U.S. use ABET criteria, but most do not. A comparison of the skill descriptors between European master’s graduates and ABET outcomes is given in Table 1.1. 12 Table 1.1 Skill descriptions of engineering master’s graduates [Nevia, 2019] and connected ABET outcomes [ABET, 2021] Skill Skill description for engineering master’s graduates ABET Criterion 3: Student Outcomes (1-7) Communication Outline a communication strategy, cite sources and organise thoughts logically and with correct grammar. Deliver the message in written and oral form, show knowledge on the topic, ideas, problems, solutions, processes and outcomes. Adapt content to skilled engineers and the general public, both national and international 3 - an ability to communicate effectively with a range of audiences Teamwork Work effectively as a member in a team, nationally or internationally, with different cultures and beliefs, and with multiple disciplines. Meet deliverable deadlines, schedule and budget requirements, while following the working methods previously defined. Work effectively as a leader in a team, nationally or internationally, with different cultures and beliefs, and with multiple disciplines. Guide the team members through their tasks and deadlines defined previously. 5- an ability to function effectively on a team whose members together provide leadership, create a collaborative and inclusive environment, establish goals, plan tasks, and meet objectives Conflict Solving Take a discussion from the beginning and help participants reach a conclusion, while keeping neutrality Understand someone’s needs and feelings by analysing their body language. Paraphrase to make the other person feel heard. 4-an ability to recognize ethical and professional responsibilities in engineering situations and make informed judgments, which must consider the impact of engineering solutions in global, economic, environmental, and societal contexts 2-an ability to apply engineering design to produce solutions that meet specified needs with consideration of public health, safety, and welfare, as well as global, cultural, social, environmental, and economic factors Critical thinking Find useful information, interpret evidence, examine beliefs, justify opinions, explain assumptions and reasons. 6-an ability to develop and conduct appropriate experimentation, analyze and interpret data, and use engineering judgment to draw conclusions Problem solving and creativity Apply models or methodologies to a problem, try different and innovative approaches and solve the complex questions that emerge from it. 1 -an ability to identify, formulate, and solve complex engineering problems by applying principles of engineering, science, and mathematics 7 - an ability to acquire and apply new knowledge as needed, using appropriate learning strategies. 13 In Table 1.1 there is general agreement between the outcomes of the 5 important skills of European engineering master’s graduates and ABET criterion 3 Student Outcomes. The Criterion 3 outcomes are specifically designed to prepare graduates to enter the professional practice of engineering [ABET, 2021]. Europe has the European Qualification Framework which defines the knowledge and skills engineers should possess at difference levels. These levels (6, 7, and 8) are roughly equivalent to a B.S., M.S., and Ph.D. respectively. A definition of these is summarized in Table 1.2. Table 1.2 European Qualification Framework [Nair, Patil & Mertova, 2009] Level Knowledge Skills Responsibility and Autonomy Correlated U.S. Degree level 6 Advanced knowledge of a field of work or study, involving a critical understanding of theories and principles advanced skills, demonstrating mastery and innovation, required to solve complex and unpredictable problems in a specialised field of work or study manage complex technical or professional activities or projects, taking responsibility for decision-making in unpredictable work or study contexts; take responsibility for managing professional development of individuals and groups bachelors 7 Highly specialised knowledge, some of which is at the forefront of knowledge in a field of work or study, as the basis for original thinking and/or research Critical awareness of knowledge issues in a field and at the interface between different fields specialised problem-solving skills required in research and/or innovation in order to develop new knowledge and procedures and to integrate knowledge from different fields manage and transform work or study contexts that are complex, unpredictable and require new strategic approaches; take responsibility for contributing to professional knowledge and practice and/or for reviewing the strategic performance of teams Masters 8 Knowledge at the most advanced frontier of a field of work or study and at the interface between fields the most advanced and specialised skills and techniques, including synthesis and evaluation, required to solve critical problems in research and/or innovation and to extend and redefine existing knowledge or professional practice demonstrate substantial authority, innovation, autonomy, scholarly and professional integrity and sustained commitment to the development of new ideas or processes at the forefront of work or study contexts including research PhD 14 These international accreditation and criteria are comparable to ABET criteria and extend into the graduate level. 1.4.2.3 Core Skills for Employment of Engineers To be successful in the global workforce, mechanical engineers must possess the necessary skills for employment. Analyzing job postings is a common methodology to determine the current requirements of an industry or the demand of skill sets. Content analysis of job postings has been used in many fields [Bodmer, Leu, Mira & Rutter, 2002] including engineering [Male, Bush & Chapman, 2009; National Academy of Engineering, 2004]. 1.4.3 Employment – Opportunities after Graduation Getting a job is the next logical step after obtaining a degree. Students who are about to complete or have recently completed their degree need jobs. While not all engineers will remain in their field of study, those that do will seek opportunities after graduation to earn a living. On August 30, 2021, there are over 130,000 jobs in the National Labor Exchange for Mechanical Engineers in the United Stated [National Foundation for American Policy, 2021]. Helping students obtain the skills necessary for the global market makes them competitive for these jobs. 1.4.3.1 Opportunities after B.S. in Mechanical Engineering 1.4.3.1.1 Master’s Degree Students and professionals can choose to pursue a master’s degree for a variety of reasons. Those reasons include wanting to expand their knowledge in the field related to their current professional specialization or develop knowledge for a new professional career field. Students with an undergraduate in mechanical engineering might also choose to get a masters in a different field, such as business, to develop the skills necessary to success in other career paths 15 or opportunities. The number of college graduates who have earned master’s degrees in the last two decades alone has more than doubled with 13.1% of Americans having a master’s, professional degree or doctorate [Nevia, 2019]. According to the Bureau of Labor Statistics [European Network for Accreditation of Engineering Education, 2021], Engineers with master's degrees earned 9-13% more than workers with a bachelor's degree. Pursuing a master’s degree in the field of mechanical engineering opens additional job opportunities. The master’s degree may also just be a stop on the way to the doctoral level. 1.4.3.1.2 PhD Engineering ME A Doctor of Philosophy (Ph.D.) in mechanical engineering prepares students for careers in research and academia. A Ph.D. is an essential requirement for mechanical engineers who seek faculty positions in higher education. 1.5 Conclusion Existing literature denotes gaps between skills learned in mechanical engineering programs and the skills needed by industry. Systematically assessing the skills learned in programs and the skills needed by industry and academia can support a model for administrators to make programmatic design decisions for improvement of their programs. The goal of this dissertation is to inform programs and professors about the knowledge, skills, and abilities the global workforce requires for mechanical engineering graduates. This information for how the programs and professors can provide the students with a quality education has the potential to increase the attraction of highly-skilled students to apply for the mechanical engineering programs. Consequently, the combination of the reinforcement of expected knowledge, skills, 16 and abilities within the program and the further development of highly-skilled students has the likelihood of a higher level of employability of program graduates. Subsequently, faculty and students would expect to have increased competitiveness to secure extramural funding from federal, state, and private industry sources. 17 CHAPTER II ANALYSIS OF GRADUATE MECHANICAL ENGINEERING PROGRAMS BY RANKING 2.1 Abstract Annually, U.S. News releases rankings of academic programs to inform consumer decisions. This study sought to determine what relationships could inform actions for programs to make program design decisions to help improve their ranking and to determine what top ranked programs include to better prepare their students for the global market. U.S. News ranked 182 mechanical engineering programs using their specialty rating process. Analysis indicated that nearly 21% of PhD students and 14% of master’s students are in the top 9 programs. It also indicated 40% of PhD graduates in mechanical engineering are from the top 25 out of 182 programs. Average percent of research dollars, applications, and graduates declined as the ranking value increased. Top rated programs include minors and other program design decisions to enhance the breadth of their programs and prepare students for the global market. 2.2 Introduction Mechanical engineers must be well trained and highly skilled with the adoption of Industry 4.0 practices to integrate people, machines, and products (Fernández-Miranda, Marcos, Peralta, & Aguayo, 2017). This increasing need for highly skilled workers to develop processes to integrate data exchange, customer contact, and service corresponds to an increased demand for graduate degrees and an increase in doctorate-holding nonfaculty researchers in mechanical engineering (Arbeit & Yamaner, 2021). Over the past two decades, mechanical engineering 18 remains one of the most popular engineering disciplines with one of the highest counts of doctoral degrees and master’s degrees awarded (Arbeit & Yamaner, 2021; NCES, 2022: NSF, 2022). Future students will look to find a program that meets their needs and abilities and will likely choose the most highly ranked university to which they can be accepted. Competition among colleges and universities for the best graduate students is often focused on the school’s ranking (Dill & Soo, 2005; Ghiasi, 2019; Williams & Van Dyke, 2008). University administrators utilize these rankings not only to attract the best students and faculty members, but also to increase donations from their alumni (Grewal et al., 2008). A significant number of studies have shown that U.S. News and World Report (U.S. News) rankings are influential to university admissions, donations, and other nuances leading to important effects on university policies (Bougnol & Dula, 2015; Bowman & Bostedo, 2009; Dichev, 2001; Hansmann, 1999; Machung, 1998; Merideth, 2004; Pike, 2004; Sweitzer & Volkwein, 2009; Yeung et al., 2019). In U.S. News graduate engineering programs, peer assessment scores account for a quarter of the total score. The peer assessment ranking is tied to the perception and reputation of the university (Ghiasi, 2019). Globally, top U.S. colleges tend to remain at the top due to their large research expenditures with many of these top schools being those with strong reputations (Wong, 2016). Governmental and private funding for universities can also be related to ranking results (Hazelkorn, 2008). In order to benefit from a higher ranking, graduate programs must improve the attributes that the rankings are based on in order to increase their ranking. The National Research Council benchmarked 5,004-doctoral programs at 212 universities, covering 62 fields of study. This assessment was designed to help universities determine where they are in the rankings relative to other universities and how they could 19 improve the quality of their programs (National Research Council, 2011). Graduate mechanical engineering programs must continually adapt their programmatic design decisions to improve their programs, attract students, and receive funding. 2.3 Literature Review With the rise of China, India, and other emerging economies, there is growing concern the U.S. may be losing its competitive edge for graduate education (Han et al., 2015). Previously, first time graduate enrollment of foreign students (MS and PhD) decreased in 2001 and 2004 (Oliver, 2006). In Fall 2020, the Institute of International Education marked a 17 percent decrease in total international students’ enrollment; this decrease rebounded by 8 percent in Fall 2021; however, the number of international students enrolled is less than Fall 2019 (Martel, 2021). The U.S. cannot rely on international students to provide talent (Bowen, Chingos, & McPherson, 2009). If there is a continual decline in student populations in graduate studies, mechanical engineering programs will have to be more competitive in preparing students for a global workforce. There is an increasing need for cross-functional work organization and cross-company partner networks (Bonekamp & Sure, 2015). A significant call remains a priority for mechanical engineering departments to update curriculum to prepare students to operate in a global environment, thus preparing student to work in virtual global teams across time zones, cultures, and languages (Zappe, Litzger, & Nguyen, 2010). Industry-academia partnerships have demonstrated to enhance quality of both graduate and doctoral programs in engineering through increasing skill exchange, teaching results, and increasing student motivation (Bosi, et al, 2013). Mechanical engineering programs are among the highest of the engineering program disciplines to adopt innovation in engineering education. Using the Carnegie classification of the 20 institution to compare adoptions rates, master’s institutions showed the highest adoption of innovations followed by doctoral/research institutions with baccalaureate lowest (Borrego, 2010). The same factors of globalization and rapid changing technology, which are key to updating and improving undergraduate programs, are also key in graduate education. The Conceive-Design-Implement-Operate (CDIO) initiative has globally been used to improve undergraduate engineering programs, with over 140 universities around the world utilizing this framework. Chuchalin, et al. (2016) showed that analytical reasoning and problem solving, experimentation and knowledge discovery, and system thinking areas of CDIO were more aligned within postgraduate than undergraduate programs. Bachelor’s degree programs were involved in implementing and operating products and systems, and Master of Science (MSc) programs selected to implement the design of new engineering products or systems (Chuchalin, 2018). A traditional PhD graduate in engineering has experience in his/her own field but not in wider social, economic, and cultural considerations (Alpine, Skakni, & Inouye, 2021). Increased breath of knowledge and expertise is gained through exposure to other departments and disciplines on campus (Akay, 2008). This kind of “minor” or breadth of study is observed in top programs such as the Massachusetts Institute of Technology (MIT) engineering programs, which require engineering students to study in an area outside their main technical topic. (MIT program bulletin). Science, Technology, Engineering, and Mathematics (STEM) doctoral degree plans need to include more flexibility to equip students to handle varied cultural, social, and economic situations (Hancock & Walsh, 2016). Documentation and analysis of program decisions in the United Kingdom (UK; Park, 2005), U.S. (Taylor 2011), and Australia (Gilbert 2004) 21 demonstrate outcomes of the debates on the best practices to be incorporated within the current PhD education model. Analysis of graduate mechanical engineering program rankings and benchmarks set by high-performing programs provide a guide to identify quality education. This information has the potential to increase the attraction of highly skilled students to apply for and enroll in the high-performing mechanical engineering programs. Consequently, the combination of the reinforcement of expected knowledge, skills, and abilities within the program and the further development of highly skilled students has the likelihood of a higher level of employability of program graduates. Subsequently, faculty and students would expect to have increased competitiveness to secure extramural funding from federal, state, and private industry sources. To guide this analysis of engineering program ranking and qualities of high performing programs, the following research questions were asked: 1. Which, if any, schools have built an increased breadth of knowledge into their graduate programs that serve as a benchmark for other programs? 2. What trends exist between programs and rankings that can inform the design of mechanical engineering programs? 2.4 Methodology Using ranking indicators to assess each program across the categories of engagement, faculty credential and training, expert opinion, services and technologies, and student excellence, U.S. News calculate a program score for each program in a selected category (U.S. News). Content analysis was used to examine the reported scores and data elements for universities and colleges with the top 182 mechanical engineering programs. Content analysis is a research methodology that is often used to analyze verbal and visual messages in data and statements 22 (Cole, 1988). A structured and directed approach (Hsieh & Shannon, 2005) was used to explore the content of each university or college’s report to cull out trends in rankings of mechanical engineering programs. Schools that are tied are listed alphabetically at that rank. 2.4.1 Data collection and coding The first step of the data was to secure an account with U.S. News to access the data in October 2021 and February 2022. Inclusion criteria were determined to be mechanical engineering programs that award graduate level degrees and have an ABET accredited undergraduate program. The search terms were entered. The resulting data set identified 182 schools in the U.S. that have graduate level mechanical engineering programs. In October 2021, a pilot set of data was selected for the top 50 ranked graduate mechanical engineering programs. After export of the 50 records, the data were transferred to Microsoft Excel for organization and content analysis. These initial 50 reports accessed in October 2021 were used as pilot data to establish what data were necessary to be obtained for all the mechanical engineering programs that award graduate degrees. In February 2022, the data for the 182 schools were accessed, exported, and transferred to Microsoft Excel. Although the top ranked schools’ data sets were complete, many of the lowest ranked schools were missing data in their reports. To supplement the data drawn from U.S. News, program data were collected from the mechanical engineering programs’ websites for selected schools. These criteria included the reporting of a minor field of study that accompanied the course requirements for the graduate level mechanical engineering program, a top-25 ranking by U.S. News, and identification as an Ivy League school. This data was used to supplement and explain what was noted in the U.S. News data and observed trends. 23 2.4.2 Data calculations The top programs were determined based on the U.S. News ranking of graduate mechanical engineering programs. The top nine programs were explored since three schools were ranked tied at ten. For each of the top nine programs a search was conducted on each universities mechanical engineering website and bulletin for the general requirements and program outcomes. All the schools with clearly listed program outcomes had a phrase such as high attainment or depth of knowledge in a “particular field”. This choice of phrasing of program outcomes continued throughout the rankings as a common base of all graduate mechanical engineering programs. A deep knowledge of a particular field is the classical program for a doctorate, but there is an increasing shift towards Industry 4.0 and creating engineering that had a broader range of skills. Websites and bulletins were scanned for phrases or requirements that demonstrate this shift. Phrases such as “provide a breadth of knowledge in a minor field of study that fosters an awareness of and skill in interdisciplinary approaches to problem solving” and the requirement of a minor study outside of the major field demonstrate a movement towards a broader knowledge base for graduates of these programs. Overall engineering program rankings (not mechanical engineering discipline specific) take into account quality assessment, faculty resources, student-faculty ratios, research activity, and student selectivity in a weighted system. Specialty rankings of mechanical engineering are based on a 5-point peer assessment score by department heads in mechanical engineering. Of the 182 schools identified as having doctoral degrees in mechanical engineering, 58% of department heads responded to the survey (U.S. News). There is general agreement between the overall engineering program rank and the graduate mechanical engineering program rank with a root-mean-square deviation of 17 for the 179 schools that also have overall engineering program 24 rankings. The survey results are likely due to perception of the program; schools that are generally ranked higher tend to be thought of as better. Increasing perception of a program by increasing general engineering rank could impact mechanical engineering program rankings. Similar numbers of schools tied in ranking were evaluated for five groups based upon analysis of similarities in reporting. These groups are near the top, top-middle middle, and bottom of the rankings to help present the trends in the data. Initial data analysis noted values were clustered more towards the bottom of the rankings with larger changes occurring in the first quartile. An additional group of schools was examined between the top nine and the middle group to help extract the rate of these changes. These groups were comprised of a group of 14 schools ranked 159th, a group of 10 schools ranked 91st, a group of 10 schools ranked 49th, a group of 8 schools ranked 29th, and 9 schools ranked 1st through 8th. The averages across these groups were taken for the comparisons across the rankings. 2.5 Results U.S. News ranked 182 schools that had graduate mechanical engineering programs in the United States (U.S.). To answer the first research questions, Which, if any, schools have built an increased breadth of knowledge into their graduate programs that serve as a benchmark for other programs?, data from selected websites was analyzed for minors and breadth of the program. To answer the second research question, What trends exist between programs and rankings that can inform the design of mechanical engineering programs?, research dollars and acceptance rate data were analyzed and compared to the mechanical engineering program rank. The study identified the following trends to be the most actionable differences between the ranked programs. 25 2.5.1 Minor and Breadth of Program Three out of the top four ranked doctoral mechanical engineering programs require a minor field of study outside of the major field (mechanical engineering). Of the eight Ivy league schools, two had a minor requirement and four had specifically built “breadth” into their degree program requirements. Only six other schools, with an average rank of 62nd were found to require a minor field of study. When compared on an internationally ranked list of mechanical engineering programs (topuniversities.com), eight out the top ten doctoral programs required a breadth of skills including required minors, seminars for communication skills, or professional skills courses built into the program requirements. These skills demonstrate the top programs are already preparing students for the future skills and capabilities needed to be most successful. 2.5.2 Trends based on U.S. News Ranking The top ranked programs by U.S. News contain a disproportionate number of graduate students and research dollars. U.S. News data indicates nearly 21% of PhD students and 14% of master’s students are in the top 9 programs. This 2020 data indicates 40% of PhD students are from the top 25 out of 182 programs, which is comparable to the National Research Council data in 2005-2006, which showed 48% of PhD students were in the top 25 out of 122 programs. Figure 1 depicts the average percentage for the colleges and universities in each group for each of the categories presented. Data values are depicted for the top 9 schools, the group of schools ranked 29, the group of schools ranked 49, the group of schools ranked 91, and the group of schools ranked 159. Percentages for MS and PhD mechanical engineering applications were determined as the percent of the total number of MS or PhD applicants or graduates in all MS or PhD graduate programs, respectively. 26 When examining the enrollment of graduate students’ data in Figure 1, there is a clear decline in both applications and enrollment that corresponds to the decline in ranking. This decline is especially pronounced in doctorate students from the top 9 schools to the schools ranked 29th, where the rate begins to decline at the same rate as master’s students’ application and enrollment rates. Doctorate student applications and enrollment closely resemble research dollars. Figure 2.1 Average percent of research dollars, applications, and graduation by rank group; percentage is calculated as mechanical engineering program values compared to engineering program values. 27 Figure 2.2 Comparison of average mechanical engineering programs’ ranking and average engineering programs’ ranking by group to the ranking by U.S. News Of the 182 schools ranked by Mechanical Engineering program, 179 have an overall engineering program ranking. 32 of those schools are ranked in the bottom quartile of engineering programs, which means they are given a range of ranking from 154-202. The root-mean-square deviation between the mechanical engineering program and engineering program ranking including these schools as all being ranked as tied for 154 and excluding these schools are 17.1 and 16.9 respectively. Of the top 9 mechanical engineering programs, only one school’s mechanical engineering program is ranked higher in the overall engineering program ranking. Figure 2 depicts the average mechanical engineering program ranking and the average engineering program ranking compared to the U.S. News average ranking for the group. 2.6 Discussion 2.6.1 What do they mean? Previous literature has already linked program funding, student applications, and other measures to program rankings. The data presented in this study are reinforcing that U.S. News ranking data can be used for program improvement planning and inform design decisions for mechanical engineering programs. The outcomes of the comparisons made between the groups in Figures 1 and 2, demonstrates some of the possible benchmarks that programs can use 28 to improve their ranking. Top programs are already incorporating design decisions to prepare students for a global workforce with the inclusion of additional coursework outside of their major area. Where other programs are more flexible in the choice students must take for coursework, programs have an opportunity to suggest or mandate that students seek to broaden their knowledge with key skills. Although the specialty rankings for mechanical engineering programs are not based on the same factors that are considered for the overall engineering programs’ ranking, there is a strong correlation between these two sets of data. The perception of the overall engineering school ranking is likely to play a part in the peer assessment. Excluding those schools ranked in the bottom quartile of all engineering programs, there are 88 schools for which the rank of their mechanical engineering program is higher than their engineering program. The 59 programs which have lower mechanical engineering ranking are schools that can show improvement of their specialty ranking through the perception of their peers. Recommendations for mechanical engineering programs to plan improvements are for programs to benchmark against their peers and against the top 9 ranked programs’ curriculum content, practices, and faculty. 2.6.2 Implications and limitations/future research – recommended future research Within the rankings of the top ranked schools there is a significant drop in scores that inform the ranking value. These score drops are reflected in the number of graduate student applications, funding, and faculty. This has led to a historically disproportionate number of students attending a small portion of the schools. Future research is recommended to be conducted to determine what factors deans or other administrators consider when ranking their peers. What are their perceptions of the other 29 programs based upon that they assign a particular score? Is their knowledge of the other programs dependent upon interactions in professional societies, during conference presentations and invited talks, comments from colleagues, or other reputation factors? 2.7 Conclusion Top mechanical engineering graduate programs are already implementing requirements for doctoral students to have wider ranges of skills outside of their specialty discipline. Including minors or requiring coursework to improve the breadth of knowledge of graduate students will prepare them for a global workforce. Programs in which minors and course requirements outside of the engineering core are already professionally developing students who are meeting the needs of the global workforce. Although master’s degrees applications and graduation counts decrease nearly linearly in relation to the increase in the program rankings, PhD applications and graduations are significantly higher in the top programs before a sharp decline to the similar proportional relationship observed with master’s degree enrollments. Improvements in program ranking increases the likelihood that mechanical engineering programs would attract more students and potentially more funding to their graduate programs. 30 CHAPTER III A NEW QUESTIONNAIRE FOR ASSESSMENT OF A MECHANICAL ENGINEERING SENIOR DESIGN CLASS 3.1 Abstract An improved course assessment questionnaire was designed and used as an assessment tool for evaluation of a design-based and team-oriented mechanical engineering senior design course. The student feedback to the evaluation questionnaire was collected and analyzed to gain a better understanding of how well this course met the learning needs of students and addressed the goal of developing their career skills, as well as its impact on Accreditation Board for Engineering Technology educational objectives, upon which a plan to improve this senior design course would be formulated. The designed assessment questionnaire is a good supplement tool to the regular student evaluation form as a means to gather more insightful and valuable information from students for this specially designed course, through which the additive value of the unique industry-tied and team-oriented education mode implemented in that course can be correctly evaluated. 3.2 Introduction An industry-tied and team-oriented mechanical systems design course had been previously developed and offered to senior students at Mississippi State University (MSU) [Liu & Dou, 2015; Liu, 2017]. In that course, design projects provided and sponsored by industrial partners, research centers, and state agencies were assigned to student teams and used as an 31 effective device to improve student capacity of solving real-world engineering problems and develop their career skills in a multidisciplinary environment. In order to assess and improve teaching approaches, learning materials, and education model implemented in that course, an effective student evaluation instrument was needed. However, the currently used course evaluation questionnaire only includes four formative and summative questions, which is too simple to allow the instructor to collect enough useful information from the students to evaluate if the specific aims of this course have been achieved and to determine what specific modifications need to be made to improve the effectiveness of that course. A powerful evaluation questionnaire which enables the instructor to obtain a comprehensive understanding of advantages and shortcomings of the renovated design course needs to be constructed. In particular, the evaluation questionnaire should be able to effectively assess the unique industry-tied and team-oriented education mode implemented in that course. The student course evaluation questionnaire has long been developed and employed as an effective instrument to measure the teaching performance of aca- demic organizational units. Its validity and usefulness as a performance indicator of quality has been confirmed in several investigations [Wilson, Lizzio & Ramsden, 2006; Wachtel, 1998; Coffrey & Gibbs, 2001]. In the 1970s, Spencer and Aleamoni [1970] had designed a student course evaluation questionnaire based on 50 items and used it at 13 different institutions. A preliminary evaluation of that questionnaire was reported by Cassel [1971] to edit or eliminate its weak or inadequate items. Aleamoni [1978], based on over 15 years of research and experience in the area of instructional evaluation, developed the Arizona Course/Instructor Evaluation Questionnaire and demonstrated its reliability and validity. Recently, Ramsden [1991] described the development of a Course Experience Questionnaire (CEQ) to measure the perceived quality of teaching in degree 32 programs. As a general tool the CEQ data were intended for use in making comparisons within fields of study over time and/or across institutions. Those general evaluation tools can be broadly applied to evaluate many different courses but considering the breadth and diversity of the courses, especially those courses in which an innovative teaching method is implemented, the general questionnaire may not be able to measure the efficiency and effectiveness of the unique teaching method or education model. For example, Lyon and Hendry [2002] had used the CEQ as an instrument to monitor a problem- based medical program at the University and Sydney but after review of the results, the authors argued that particular items in the CEQ did not reflect the educational philosophy or the instructional processes of the problem-based learning programs. Because of that reason, many specialized questionnaires have been designed to measure either a particular program, or a specific teaching method, or expected student outcomes. Kember et al. [2000] reported the development and testing of an instrument to determine whether students engage in reflective thinking in those courses aiming to promote reflective thinking or reflection upon practice. Byrne and Flood [2010], however, modified the CEQ and used the modified CEQ to assess the teaching quality of accounting programs. Following the previous work, one objective of this study is to design and construct an evaluation questionnaire to effectively evaluate the quality of the mechanical systems design course. Especially, the developed questionnaire should be an effective instrument for measuring the industry-tied and team-oriented education mode. By using this questionnaire for teaching assessment, the effectiveness and efficiency of the group design project in improving students’ skills in problem solving and multidisciplinary team working can be confirmed. The presented questionnaire can also be incorporated into the project-based learning model [Foss & Liu, 2020; Foss & Liu, 2021a; Foss & Liu, 2021b; Liu et al., 2022] in engineering education to better 33 evaluate the effectiveness of the project-based engineering courses The authors could not find another questionnaire for a design-based course from published literature. 3.3 Status of the course and current evaluation questionnaire One unique feature of this design course is that many design projects provided from industry partners, research centers, and stage agencies were introduced and assigned to student teams. Typical projects include: (1) design a chip reading tool for forensic criminal investigations with much reduced cost (support from Mississippi State Office of the Attorney General); (2) design of an in situ and real-time clean system that effectively removes the stains and metal swarf on the conveyor rollers (sponsored by PACCAR, Inc.); (3) design of an in situ and real- time clean system that removes and collects the metal debris accumulated in the gaps of the heavy duty diesel engine conveying line (sponsored by PACCAR, Inc.); (4) case study of advanced processes, materials, and structural designs to improve heat resistance of helicopter engine cowlings (sponsored by Airbus Helicopters, Inc.); (5) design of a reliable robotic equipment to assist workers to lift and move car seats from the assembly line to the conveying line (sponsored by Systems Automotive Interiors); (6) rear sub-frame design for Subaru BRZ (sponsored by Center of Advanced Vehicular Systems (CAVS) at MSU); (7) innovative design of a plug-in vehicle charging door using an iris diaphragm (sponsored by CAVS); (8) enhanced design and characterization of a steel tensile test grip (sponsored by CAVS); (9) improved design of front upright, front hub and spindle assembly, and pedal tray for SAE formula car (support from CAVS); (10) redesign a boat seat joint to improve its dynamic impact resistance (sponsored by Wise Seat Company); (11) design of casings for housing different accelerometers to monitor behaviors of wild animals, including marine and egg-born animals (support from a faculty of Department of Wildlife, Fisheries, and Aquaculture at MSU), 34 and several other projects containing information that the sponsors did not want to disclose. Figure 3.1 displays prototypes, models, and experimental setups designed by the student teams. Figure 3.1 Examples of student outcomes from the design course. An evaluation form had been designed and used to evaluate the effectiveness of this course along with a regular student evaluation form issued from the Provost’s Office for each class taught at MSU. The evaluation form was used because it was found that the regular student evaluation form alone could not reflect the student feedback on unique teaching methods specially designed for a variety of courses from the author’s previous research [Liu, et al., 2011; Liu, 2011a; Liu, 2011b; Liu, 2011c]. 35 Table 3.1 Evaluation questions in the currently used evaluation form and student feedbacks As displayed in Table 3.1, the evaluation form only includes four questions, which would guide both summative and formative evaluation to examine the effective- ness of this renovated design course in terms of student learning (awareness, knowledge, understanding, and skills), course validity (meeting industry needs), interest or engagement, and attitude. Although these questions are primarily summative in nature, they will also be assessed during formative evaluation to monitor and improve the course renovation process. A total of 121 students who took the course in fall 2014, spring 2015, and fall 2015 had participated in this evaluation. That questionnaire tried to use formative and summative questions to estimate the impact of the 36 course on student performance improvement and preparation for industry employment or further education. However, the results obtained from those questions can be very ambiguous. For example, in the first question “How do you think that the course will help you to meet industry needs”, the survey results did not clarify what type of the “industry needs” was met and to which extent that that “industry need” was met. In addition, this questionnaire did not reveal any information about the nature of the projects each student worked on. Also, how the student outcomes from that course match the Accreditation Board for Engineering Technology (ABET) educational objectives remained unclear from that survey. Moreover, the old questionnaire (Table 3.1) used “mean scores” to evaluate the course effectiveness, which is not appropriate because they were calculated based on the Likert scale scores. According to Sullivan and Artino [2013], the numbers developed from Likert scales represent ordinal responses and the calculated means are of very limited value and not helpful for enlightening to readers. 3.4 Design of a new assessment instrument An improved assessment instrument was designed, in which more questions were incorporated to gather more student views on this class. The enhanced student evaluation questionnaire includes four sections. The Course goals section (Table 3.2) is about the achievement of the course goals, including 10 closed-format questions and two open-format questions. In the section, the students are asked to evaluate their growths on following skills, organization, teamwork, communication, leadership, management, and problem solving as well as the knowledge development on topics of solid mechanics, fluid mechanics, manufacturing, and CAD/CAE. Group dynamics section) uses four open-format questions to obtain more information about the nature of the project that each student team worked on. The acquired 37 information can provide additional details related to their motivations, knowledge gains, and skill performances of this course. Industry importance section (Table 3.3) with its 10 closed-format questions on a six-point Likert scale aims at finding out student perception of industry importance on the skills and knowledge covered in this course. The collected results can be used to assess their possible motivation for mastering different skills and topics associated with employability and industry standards. Table 3.2 Assessment and results on course goals. Table 3.3 Assessment and results on industry importance. 38 Table 3.4 Assessment results of the course’s impact on ABET outcomes. 39 Student outcomes section (Table 3.4) discusses the impact of the renovated course on ABET educational goals. Student perceptions of course performance for ABET criteria would enhance the assessment of the course by expanding the prior formative and summative assessments to detail specific ABET measures. Thus, the ABET assessment part of this survey was designed to examine the rationale and motivation for learning gains, student perceptions of preparation, and awareness of the ABET criteria inclusion within this design course. The 11 closed-format questions on a five-point Likert scale were added to assess the student outcomes according to the 11 ABET (A–K) educational objectives. Finally, each student is asked to write down their additional comments on this course. In summary, the designed questionnaire includes five sections, with 31 closed- format questions made on five- and six-point Likert scales and seven open-format questions. This survey was conducted in the fall semester of 2016 and 44 senior students enrolled in that class participated in the survey. All the questions, student evaluation results for the closed-format questions, as well as some selected student comments are listed in the next section. 3.5 Assessment results 3.5.1 Course Goals In the “Before Course” column rank your level for each skill and knowledge of each topic before the course and on the “After Course” column rank how you think you are now that you have completed the course. The number 1 represents the lowest ranking and 5 represents the highest ranking for each skill and topic. The numbers in the cell represent the number of students who chose that point. For example, the “13” in the row of “Organization” means that 13 students selected “3” for that question. Mean scores were calculated based on the students’ feedback for each of the 10 closed-format questions in terms of “before the class” and “after the class”. The 40 column “Δ” lists the differences between the “After Course” mean values and the “Before Course” mean values. For example, in the row of “organization”, the mean value before the class is 3.86 and after class is 4.16, which means that the average “organization skill” point of the entire class had been 3.86 while it reached 4.16 after the class. Its “Δ” = 4.16 - 3.86 = 0.30 shows that that skill was increased by 0.30 points through this class. As shown from that column, all the “Δ” values are positive, which proves that this course enhanced students’ skills and knowledge in various degrees. Which, if any, skills or topics did you note an increase? What do you think lead to your increase in that area? Which, if any, skills or topics did you note a decrease? What do you think lead to your decrease in that area? 3.5.2 Group dynamics How many students were in your group? (each group should include four or five students). Which role were you assigned in your group? (For example: Project leader, Mechanical Design Leader, Computer Modelling Leader, Electronic Power design, etc.) Did you choose this role? Why were you assigned this role? How did your group communicate during the project? Student answers to those questions were collected and stored into our database for future analyses. 41 3.5.3 Industry importance Use Table 3 to rank the skills and topics in order of importance for industry according to your experiences and perceptions. The number 1 is the most important and number 6 is the least important. Use each number 1, 2, 3, 4, 5, 6 only once for each set. The numbers in parentheses represent the number of students who selected the scale indicated before the parentheses. For example, 1(6) means that there were six students choosing “1” for a particular question. 3.5.4 Student outcomes Please mark the cell that best describes your response to the following statements about how this course met each of the following ABET criteria. The mean scores were calculated following the same way as explained in Tables 3.1 and 3.2. Even though that the mean values calculated from the Likert scores do not provide much in-depth information, they were calculated and are displayed here for showing the overall satisfaction degree of the students in terms of each ABET outcome. 3.5.5 Student comments Please use the space below to write any additional comments you have for this course. I like how the projects were introduced and assigned. We were able to learn more about the skills necessary to succeed in an engineering career. I learned a great deal of knowledge from MSD class! This course taught me how to deal with people and how to communicate with different parties to solve a problem. If anything, I’m thankful that I improved those skills while in this class. Going forward, I believe that project management should be a topic of discussion. 42 Overall, I have enjoyed this course. I believe I have learned a lot through the lectures and homework. I also believe I improved many skills through the design project. I enjoyed the class as well as the professor. The most exciting portion of the course was the final design project. This allowed us to tackle a real world engineering problem before venturing out into our career fields. I think the course was great! Thank you for your enthusiasm and dedication to our success. I like the layout of the course where there is one big project that you work on all semester. This is what I have been working towards all through my undergraduate experience. 3.6 Discussion 3.6.1 Effectiveness on skill growth and knowledge development Based on Table 3.1 it can be found that all the listed skills and knowledge of the participating students were improved through this course. The students identified that they had achieved the largest improvements on their project management skill and their solid mechanics knowledge. This can be attributed to the implementation of the team-based design projects and the fact that this systems design course focused more on the solid mechanics, including mechanical components design and analysis. The least improvements they made in this class include the fluid mechanics knowledge and the teamwork skills. This is because that the course syllabus did not cover many fluid mechanics topics and few design projects include the design of fluid systems. In addition, the results also suggest that the organization of the group design projects needs to be improved to better develop the students’ teamwork skills. Table 3.3 reveals the student perceptions of the industry importance of the listed skills and topics. From that table it can be seen that the students highly valued the influence of 43 knowledge base of solid mechanics and manufacturing on their careers and ranked the leadership skill and CAD/CAE experience with the least industry importance. These results will be brought to our industry partners to find out the most wanted employability skills, according to which the course structure will be further modified. Table 3.5 Ranking of student perceptions on industry importance of skills and knowledge and their corresponding growths. Table 3.5 links the student evaluation results on the course goals (Table 1) with the industry importance (Table 3) to measure student satisfaction in this design course, in which the topics and skills are reordered according to their ranks in the industry importance survey. From that table it can be seen that most skills and knowledge of topics that the students considered important were evidently improved through this course. The only exception is the teamwork skills. The students considered that skill the third most important in industry but the growth of that skill only ranked 9th after completing the course. It is once again suggested that further measures need to be taken to fully develop the students’ teamwork skills. The following approaches will be employed in the future to provide a learning environment to develop critical teamwork skills on students. At first, each participant will be 44 asked to complete a peer evaluation form to assess every team member (including him/herself) for the contribution to the project in terms of different categories (participation, technical competence, interaction with other team members, etc.). The peer evaluations will be used to measure the contribution of each team member and will be used, together with the team grade, to determine the final grade for each student in a team. Second, every team needs to prepare a meeting report after each group meeting. This report should include the time and location of the meeting, members present and absent, topics discussed, decisions made, tasks assigned, as well as plan for the next meeting. All meeting reports will be collected at the end of the project period and will be used as a measuring tool in grading the students’ work. 3.6.2 Impact on ABET This course has a broad impact on ABET educational objectives, which has also been verified through this survey. As can be seen from Table 4, the students agreed that this design course helped them to achieve 10 out of the 11 ABET outcomes (with an overall score above 4 out of 5). The only ABET outcome that received a score below to 4 is the criteria J): a knowledge of contemporary issues. This fact that the students did not feel much improvement on their knowledge of contemporary issues suggests the teacher should introduce more contemporary issues in engineering and design into the class to fill this theory–practice gap. 3.7 Conclusion An enhanced course assessment questionnaire was designed and used for assessing teaching and course quality of the Mechanical Systems Design course at MSU, in which a unique industry-tied and team-oriented education mode was implemented. The presented questionnaire 45 comprehensively investigated the student perceptions on achievement of course goals, student outcomes, and impact on the ABET out- comes, based on which the effectiveness and efficiency of the teaching and education approach and the satisfaction level of the students on this course can be deduced. As verified by the positive D values listed in Table 2, the students felt that their skills and knowledge on related topics were enhanced through this class. Means scores displayed in Table 4 present another proof of the overall satisfaction degree of students in this class with respect to the fulfillment of the ABET out- comes. Student feedback was collected and studied. The results showed that most course goals were achieved and overall the students were satisfied with the renovated course and recognized the effectiveness of the team design projects in growing their knowledge bases and developing their employability skills. However, the improvement of the students’ employability skills need to be confirmed with an “employer satisfaction survey” and those survey results will show how the employers are satisfied with the MSU mechanical engineering (ME) graduates. Adoption of this new survey design also advanced the course assessment to ascertain motivation, experience, and understanding of ABET outcomes. From the results, it is also suggested that the organization of the design projects should be improved to enable the students to function more effectively in their teams. More contemporary issues in engineering design should also be brought into the course syllabus. 46 CHAPTER IV DEVELOPMENT, ASSESSMENT, AND EVALUATION OF LABORATORY EXPERIMENTATION FOR A MECHANICAL VIBRATIONS AND CONTROLS COURSE 4.1 Abstract A vibrations and controls course in the Department of Mechanical Engineering at Mississippi State University was reorganized by implementing substantial laboratory experimentation. Team projects were designed and assigned to students asking them to develop vibration and control systems using knowledge and theories learned from lectures. Through those projects, students’ problem-solving capacity, hands-on experience, and teamwork skills were fully developed. The developed vibration and control systems will be permanently integrated into the curriculum, based on which a series of lab sessions can be designed to reinforce the concepts and theories covered in lectures and gain practical experience to characterize vibration and control behavior of dynamic systems. Student feedback to a course evaluation questionnaire showed that the renovated course met the learning needs of students by addressing most course goals with respect to ABET learning outcomes. Dependence on costly textbook and role of open educational resources in this class were also discussed. 4.2 Introduction Vibrations and controls are highly multidisciplinary subjects, which encompass almost all engineering disciplines. A variety of vibrations and controls courses, including laboratories, are 47 offered through different engineering departments in four-year colleges and universities. The Department of Mechanical Engineering at Mississippi State University (MSU) offers Introduction to Vibrations and Controls to all its senior students and the goals of this course are to provide students with conceptual and analytical skills required for modeling and analyzing vibrating mechanical systems for design, maintenance, and testing purposes. This course used to be purely lecture-based and emphasized too much on solving equations and theoretical concepts. Previous student questionnaires and assessment data reflected that since this course was very theoretical, many concepts and phenomena about system dynamics, vibrations, and controls are too abstract for the students to understand. Therefore, this course had to be restructured by implementing laboratory experimentation to reinforce the concepts and knowledge learned from class lectures through hands-on experiments and help the students to better understand the vibration and control theories from the observed behavior of practical dynamic systems. Educational laboratory equipment for demonstration of vibration and control phenomena are available but are very expensive. For example, a mass-spring-damping system with two degrees of freedom costs $18K and a complete free and forced vibration apparatus costs more than $25K. Recognizing the need of the laboratory equipment for the vibrations and controls course and concerning the high cost of commercial vibration and control apparatus, we designed a number of team projects for the students to build up such apparatus at much lower cost. Implementation of these projects into the curriculum led to a reorganization of the course materials, which were also accompanied with an effort of replacing traditional textbooks with open materials available at internet resources in engineering education. Most textbooks for a combined vibrations and controls course cost above $250 for new books and $100–150 for used ones. For college students come from low- or median-income 48 families, the high cost of textbooks can be a burden for them. It is concerning that the mounting textbook cost will not only prevent those students from purchasing them, which will result in poor academic performance, but also affect the students’ willingness to take that course. In addition to the high price, efficiency of using textbooks for the combined vibrations and controls course is relatively low. Due to the limited lecture time of a one-semester course, only less than 40% contents of a regular textbook (800–1000 pages) can be covered in a single semester. Moreover, there is few textbook that inclusively cover two categories: vibration analysis in mechanical systems and feedback control systems and designs. Therefore, students usually need to buy two books to fully cover the materials of that class, which adds financial burden on the students. Another fact is that student enrollment in mechanical engineering undergraduate programs in United States has grown dramatically in the last 10 years. As an example, since 2008 the undergraduate enrollment in the Department of Mechanical Engineering at MSU has increased by 10% each year and it is expected that this trend will continue in the next 10–15 years. At MSU, the Introduction to Vibrations and Controls is a core course which all mechanical engineering under- graduate students are required to take. At the current rate of enrolment increases in the department, it is anticipated that the class size will exceed 100 each semester over the next 3 to 4 years (the current typical enrollment is 70 students per semester). The fast growing student population in mechanical engineering programs, along with the limitations of the textbooks currently in use, urges the teachers to resort to the open educational resources to create more affordable, flexible, and efficiently courseware to reduce the students’ dependence on traditional textbooks. 49 Considering this, the designed course projects are independent of textbooks and students are encouraged to refer to the free course materials available online to build their vibration and control systems and develop associated lab notes. 4.3 Background Significant efforts have been undertaken at other institutions to promote teaching of combined vibrations and controls courses by bridging the gap of vibration and control theories and practice. Horacek [2000] discussed the need of building a control laboratory supporting controls courses, displayed required equipment, scale models, and software environment, and introduced classes of laboratory models to help engineering educators to build a control laboratory with practical experiments at saved time and cost. Kiritsis et al.[2003] introduced an experiment to use a strain gage, a linear variable differential transformer and an accelerometer to measure the response of an aluminum cantilever beam under harmonic excitation and compare the measurements to the theoretical response. This vibration experiment was used at McNeese State University in many different ways throughout the mechanical engineering curriculum. Lenoir [2005] developed and implemented a 3-credit combined mechanical vibrations and controls course at senior level at Western Kentucky University. In addition, an integrated 1-hour laboratory section was added to support the lecture sessions. Unfortunately, due to the constraint of the limit of total program credits set by Accreditation Board for Engineering and Technology (ABET), the 1-hour laboratory section cannot be allocated at MSU and both lecture and laboratory sections have to be integrated into the 3-hour senior Introduction to Vibrations and Controls and balanced there. Rezaei and Davari [2005] described teaching vibration and automatic control courses in the Mechanical and Electrical Engineering departments at the West Virginia University Institute of Technology. They designed experiments to give student thorough 50 understanding of basic concepts in vibration and control theories using animation, simulation, and experimentation. A series of lab sessions based on the designed experiments were introduced to the class to complement the lecture materials. Ruhala [2010] designed four free-vibration experiments for a 3-credit engineering elective course in vibrations at the University of Southern Indiana. Sridhara and White [2012] realized a similar problem in the Engineering Technology program at Middle Tennessee State University that its lecture/lab vibration course had failed to provide enough lab experience to students. Therefore, the authors developed a lab portion for that course with several donated vibration instruments. Five experiments were developed for that course, which could be run in a class- room or lab. Most recently, Peters et al. [2016] modified a two-course sequence in Mechanical Engineering Department at Kettering University, the first course is Dynamic Systems with Vibrations, and the second is Dynamic Systems with Controls. Lab was redesigned for the Dynamic Systems with Controls and a lab component involving Matlab/Simulink modeling and simulations was added to Dynamic Systems with Vibrations. As mentioned above, the major challenge at MSU is how to combine both vibrations and controls in one 3-credit class, in which the lecture and lab component are well balanced. Compared to previous work, uniqueness of the present study is that the laboratory experimentation is designed for the combined vibrations and controls course and the required laboratory apparatus are designed and built by students through team projects to enhance their skills for interpersonal relationship and teamwork [Liu, 2020a; Liu, 2020b; He & Liu, 2022; Liu et al., 2022]. The vibration and control systems built by student teams will be given to upcoming students to conduct vibration and control experiments. A brief course description is presented in this section to provide readers more information about this 3-credit senior class. This course provides a foundation in vibration analysis, control 51 systems, system modeling and dynamics analysis. Free body diagrams and energy methods will be shown. Solution of free and forced response will be investigated. Basic vibration analysis will be used to apply vibration isolation methods. The course will enable students to design effective feedback control using a broad range of control design tools including mathematical modeling of system components, block diagram manipulation, linearization, and Laplace transform. Eigenvalue problems and modal analysis are also covered. A junior level course, System Dynamics, is set as the prerequisite of this course, which prepares the students a mathematical background for system dynamic behavior, accuracy, and stability and forms the knowledge base of this course. 4.4 Description of team projects Four projects were designed and assigned to the students in fall 2017 class. In those projects, students worked in teams to design and build vibration and control systems based on specified requirements applying the knowledge they learned from the class. Deliverables include an oral presentation and demonstration, a final report, and an optional peer evaluation to help the teacher to appropriately assign grade to individual team members based on their contribution and performance in the team. The semester long team project is the most important work product in the class and weighs 30% in the final grade. A brief description of these four projects is given in following sections. Project 1: Build a first-order spring-damper system: Students are required to design and build a first-order system, which consists of a spring and a damping element. A team for such project should have five members. This project is related to the topics mass-spring systems modeling and frequency response of first-order systems. 52 Project 2: Build a second-order spring-damper system: Students are required to design and build a second-order vibration system, which consists of a mass, an adjustable spring, a damper, and a linear variable differential transducer (LVDT) sensor. The project team should have eight members. This project is related to the topics mass-spring-damper systems modeling and frequency response of higher order systems. The first and second vibration systems must be reliable, easy to assemble/ disassemble, easy for any operation and maintenance, and cost effective. Project 3: Thermocouple project: Given potentiometers, resistors, op-amps, batteries, breadboard, thermocouple, and wiring to: (i) construct a system and determine the relationship between temperature and output voltage; (ii) determine the time constant and gain of the motor/potentiometer assembly; (iii) construct a feedback control system. A team for such project should have four members. Project 4: Electrical scale project: The purpose of this project is to build an electrical scale that will weigh up to 40 pennies. The circuit for the scale will be constructed using an assortment of operational amplifiers (op-amps), resistors, capacitors, a potentiometer, an electric motor, and a power source. A team for such project should have four members. Projects 3 and 4 are related to the topics feedback control systems, PID control algorithm, and block diagrams. In the oral presentation and demonstration, each team should: (i) demonstrate the system they developed and show its functions; (ii) play a video to explain how the system was designed and show a step-by-step building process; (iii) explain roles and responsibilities of each team member in this project. Most of the data, results, images, and drawings presented in the slides should also be included in the final report. Moreover, it is required that by only reading the 53 report, the readers should understand the theories, principles, and concepts behind the vibration or control behavior of the developed systems. Deliverables of those projects include final report, presentation slides, videos, the built vibration or control system, and all other metadata. Along with the implementation of those projects, the curriculum of Introduction to Vibrations and Controls has been restructured to reduce its dependence on traditional textbooks but promote the using of online open educational resources, such as the MIT OpenCourseWare (http://ocw.mit.edu). Educational approaches demonstrated in Liu et al. [2017, 2011, 2015] were employed in this study for project implementation and syllabus renovation. 4.5 Selected project results 4.5.1 First order spring-damper system Figure 4.1 Developed first-order vibration system: (a) CAD model; (b) prototype. Table 4.1 Calibration points showing the displacement–voltage relationship. 54 Figure 4.1 displays a developed first-order system, which consists of an aluminum arm with a spring attached to one end and a damper attached to the other. The pivoted arm, spring, and damper are installed on a plywood board. The spring constant is 4.18 lbf/in (732 N/m) and the damper is adjustable so that the damping coefficient ranges from 0 to 40 lbf-s/in (7 kN-s/m). The spring constant and damping coefficient were chosen such that the mass of the entire system can be ignored. A data acquisition (DAQ) system was designed and installed to measure the time response of the first-order system. The DAQ system consists of a Hall effect sensor (DRV5053RAQLPG) and a multifunction I/O device that is compatible with LabView. The sensor outputs a variable voltage based on the magnitude of magnetic flux density it senses; the I/O device allows for the voltage to be recorded by a computer. The sensor was placed along the bottom of the dashpot facing the bottom corner of the rotating arm. A magnet was attached to the bottom of the arm close to the sensor to generate the magnetic flux density. The arm was moved to nine different positions and the output voltage was recorded with an oscilloscope to obtain a relationship between the displacement of the arm and the output voltage. The calibration points are listed in Table 4.1. The displacement then can be easily converted to rotating angle of the pivoted arm using trigonometric relations. Finally, a LabView program (Figure 4.2) was developed to collect the data. A sampling frequency of 200 Hz was used so the voltage would be measured every 5 ms. Total cost for building such a system is $266.41. Bill of materials for this project is presented in Table 4.2. With the implementation of the developed first-order system, lab sections can be designed to measure its time constant, estimate its damping ratio, and predict its time and frequency response. 55 Figure 4.2 LabView block diagram. Table 4.2 Bill of materials for project 1. 4.5.2 Second-order mass-spring-damper system The developed second-order vibration system is shown in Figure 4.3. This system reflects a vertical design and its core component is a mass-spring-damper system. One uniqueness of this design is that the mass, spring, and damper are either interchangeable or adjustable. Coil springs with the same length but different spring constants can be easily installed/uninstalled, which directly connect to the mass element. The amount of mass can be changed by adding or removing weights (Figure 4.4). The damper is essentially a piston system that consists of a disk 56 and container. Damping effect is provided through viscous fluid in that container, which is coconut oil in this system. The viscosity of the coconut oil is about 0.025 lbf-s/in (4.38 N-s/m). The piston used in the oil container has a certain amount of drag that is correlated with the surface area of the piston. The disk is also changeable, and disks with different surface areas will lead to different amount of drag therefore yielding different damping coefficients. In summary, the damping coefficient of the proposed damper can be controlled in terms of the surface area of the disk inside the container and the viscosity of the fluid in the container. A steel frame was machined to hold the mass-spring-damping system and a carriage was designed to transport the mass up and down along the frame (Figure 4.4). Figure 4.5 illustrates the damping element as well as how it connects with the mass through the mass carriage. As shown in Figure 3, the steel frame, along with the mass-spring-damping system are housed in a wooden base. 57 Figure 4.3 Prototype of second-order vibration system. 58 Figure 4.4 Mass-spring system with mass carriage and machined steel frame Figure 4.5 Damper and its connection with the mass. An LVDT (Schaevitz HR 2000 LVDT) was attached to the system to detect the displacement of the mass and translate that into electrical signal. The generated electrical signal 59 was then translated into readable data through a signal condition- er. As shown in Figure 4.6, the inserting rod of the LVDT was attached to the mass carriage system and the cylinder of the LVDT was attached to the bottom of the steel frame. A signal generator was connected to the LVDT and grounded to the signal conditioner, a National Instruments myDAQ device, to create a differential input signal for LabView to display the waveform and append the received data to a text file. A ruler was attached to the frame so that the displacement and equilibrium position of the mass can be easily read (Figure 4.7). Figure 4.6 Placement of LVDT system 60 Figure 4.7 Attaching a ruler to the frame. By manipulating the viscosity of the fluid in the oil container, the surface area of the disk inside of it, and the spring constant, underdamped and overdamped responses can be observed from the second-order system. Lab sessions will be developed based on this second-order vibration system for students to determine its natural and damping frequencies, measure its transient and steady state responses, study the over-, critically, and underdamped cases. Total cost for building this system is $1,122.36, as listed in Table 4.3. 61 Table 4.3 Bill of materials for project 2. LVDT: linear variable differential transducer 4.5.3 Thermocouple project Figure 4.8 shows a thermocouple designed by a student team, which is able to con- vert temperature into a voltage that could then power a motor. A circuit diagram of the design and a block diagram of the feedback control system are displayed in Figures 9 and 10, respectively. The circuit consists of several voltage followers, inverting op-amps, resistors, a high-voltage-high-current (HVHC) op-amp, motor- potentiometer assembly, a breadboard, circuit wiring and a Type-K thermocouple. The op-amps and the rotary potentiometer are powered by two 6V batteries connected in series. The total cost for building this system is $75.22, as detailed in Table 4.4. According to the approximately identical correlation between temperature and voltage of thermocouple, it is easy for us to only measure input and output voltages rather than temperatures. In this control system, the input is a voltage of the thermocouple which is 62 converted from temperature while the output is the voltage measured by the potentiometer. The voltage difference (input voltage– output voltage) is then multiplied by power amplifier gain KA and is converted to rotation speed of the motor (rad/s). After integration, the angular position can be translated to output voltage through the potentiometer. A complete feedback control system was created by combining the circuit with thermocouple wiring and the motor–potentiometer assembly. Specifications of the op-amps are listed in Table 5. The gains of op-amp 1 and op-amp 2 are –20 and –13.5, respectively. The total gain KT = (– 20) x (– 13.5) = 270. The gain of the HVHC op-amp is KA = R7/R5 = 15.3. The gain of the linear rotary potentiometer Kpot = 0.1911. Figure 4.8 Thermocouple design. 63 Figure 4.9 Circuit diagram of the thermocouple design. Table 4.4 Bill of materials for project 3. Table 4.5 Gains of the op-amps used in the thermocouple system. HVHC: high volage high current 64 Figure 4.10 The block diagram of the system in Simulink. A first-order motor was chosen for this system, whose function is shown in the block diagram (Figure 4.10). Figure 4.11 shows the process of finding optimal gain (Km) and time constant (τm) for the motor, the final values for Km and τm were found to be 1.8 and 0.001198, respectively. The block diagram was implemented into a Simulink model, after running that model, the response voltage was plotted by MATLAB, as shown in Figure 4.12. From that figure, it can be seen that the developed thermocouple system is an overdamped second-order system and the steady state is reached within about 1 s. 65 Figure 4.11 Theoretical method to determine Km and τm. Figure 4.12 The response voltage when the temperature is 273K. 66 To validate the designed thermocouple, the thermocouple was tested under three temperatures: 273 K, 293 K, and 373 K. Parameters such as the values for the K-type thermocouple coefficients, gain of the circuit system, and other equation constants were calibrate. It was found that the output voltages under those three temperatures were 50.592 mV, 295.98 mV, and 1375.75 mV, which agreed very well with the calculated (theoretical) voltage values 52.272 mV, 299.43 mV, and 1380 mV (Figure 4.13). The percentage errors between the measured voltages and the theoretical calculations were 3.21%, 1.29%, and 0.31%, respectively. Figure 4.13 Theoretical calculations to determine the voltages. 67 Figure 4.14 Mathcad codes for calculating time constant, damping ratio, and natural frequency based on established transfer function Y/X. Finally, a transfer function was established for the feedback control system and its time constant (τs), damping ratio (ξ), and natural frequency (ωn) were calculated using equations taught in the class. Following the approach shown in Figure 4.14, we obtained τs = 0.4 s, ξ = 0.327, and ωn = 7.645 rad/s. Based on those values the rise time, settling time, and overshoot (M) can be determined as: τrise = 1.8/ ξn = 0.235 s, τsettling = 4.6/ξωn ¼ 1.84 s, M = 1 – ξ/0.6 = 0.455. 4.5.4 Electrical scale project An electrical scale designed by one student team is presented at last, which can weigh up to 40 pennies and display the weight of the pennies (Figure 4.15). In this design, a bar strain gage load cell was used to weigh the pennies. In the load cell, strain gages are attached on each end of the bar to measure the tension applied on the bar as well as compression resulting from bending distortion. The strain gates convert the measured strain to a change in resistance. The change in resistance is then amplified through an HX711 load cell amplifier, which works as a Wheatstone bridge circuit to generate an amplified voltage 68 signal. Finally, the voltage signal is converted into weight through an Arduino and displayed on a LCD screen. Figure 4.15 Electrical scale using a bar strain gage load cell. Figure 4.16 Complete circuit diagram. 69 The Arduino platform consists of a microcontroller circuit board and an integrated development environment (IDE) software. The microcontroller is attached to the circuit while IDE runs a code to control the circuit and the display on the LCD screen. The circuit board is connected to a computer that is running the IDE software. The Arduino circuit board and the LCD screen are wired onto a bread- board. Figure 4.16 displays an assembly of the load cell, HX711 amplifier, LCD screen, and the Arduino, which are wired together. The designed electrical scale was then used to weigh 40 pennies and the displayed weight was 102.07 g, com- pared to their standard weight (2.5 g 40 100 g), the error is only 2%. Total cost for building such a system is $55.12 (Table 4.6). Table 4.6 Bill of materials for project 4. Table 4.7 Assessment and results on course goals. 70 4.6 Student evaluation A course assessment questionnaire was designed following the approach presented in [Liu & Baker, 2018; Liu & Baker, 2019] for assessing teaching quality and course effectiveness of this renovated vibrations and controls course. Student perceptions on achievement of course goals, student outcomes, impact on the ABET outcomes, and the role of textbook and open resources were collected and analyzed through this questionnaire. 4.6.1 Course goals Table 4.7 shows how students compared their level of knowledge for related topics before and after this course. In that table, “1” represents the lowest ranking and “5” represents the highest ranking for each skill and topic. The numbers in the cell represent the number of students who chose that particular point. For instance, the number “20” in the row of “Laplace transform” means that 20 students selected “3” for that question. Mean scores were calculated based on the students’ feedback for each of the 6 closed-format questions in terms of “before the class” and “after the class”. The column “Δ” lists the differences between the “After Course” mean values and the “Before Course” mean values. For example, in the row of “Laplace transform”, the mean value before the class is 2.95 and after class is 3.71, which means that the average “organization skill” point of the entire class had been 2.95 while it reached 3.71 after the class. Its “Δ” = 3.71 – 2.95 ¼ 0.76 shows that that skill was increased by 0.76 points through this class. As shown from that column, the “Δ” values range from 0.76 to 1.55 with a perfect score of 5, which proves that this course significantly enhanced students’ skills and knowledge. 71 Table 4.8 Assessment results of the course’s impact on ABET outcomes. 72 4.6.2 ABET student outcomes Student learning outcomes and the impact of the renovated curriculum on related ABET criteria are elucidated in Table 8. The mean scores in that table were calculated following the same way as explained before, where “Strongly Agree” = 5 points and “Strongly Disagree” = 1 point. Even though that the mean values calculated from the Likert scores do not provide much in-depth information, they were calculated and are displayed here for showing the overall satisfaction degree of the students in terms of each ABET outcome. As can be seen from Table 7, the students agreed that the enhanced curriculum, with laboratory experimentation implemented, helped them to achieve 8 out of the 11 ABET outcomes related to the vibrations and controls course (with an overall score above 4 out of 5). The only ABET outcome that received a score below to 4 is the criteria H): The broad education necessary to understand the impact of engineering solutions in a global, economic, environmental, and societal context. This deficiency suggests the teacher should include more examples to demonstrate the very wide application of vibration and control systems and theories in industry and our daily lives. 4.6.3 Roles of textbook and open educational resources in this course Student perceptions on the roles of traditional textbook and open educational resources are also reflected in this survey. Even most students are concerned with the costs of the textbook, and the majority of them still think that a textbook is necessary in this class. Twenty eight out of 42 students can only afford a used book of less than $100 and 18 of them would spend up to $50 to buy a textbook. However, out of 42 students, 27 of them would prefer to have at textbook for this course and 37 students agree that to have a physical textbook is important for them to earn a good grade. Weighing the high cost of the textbook and its importance on student learning, only 73 20 students bought new textbook in this semester, and other students either bought a used or older version, or used a digital copy, or rented a book. There is only one student did not use a book for this class. Moreover, majority of the students (37 out of 42) used the textbook quite often in fall semester of 2017. On the other side, the implementation of the system design and development projects forced more students to switch to open educational resources for help. Twenty-nine students used search engines to look up information for this course more than 2–3 times a week. Thirty-four students used the open course materials as a supplement of the textbook for knowledge that was not covered in it. Thirty-nine students considered the open resources outside the textbook an important tool for them to succeed in this class. In summary, the addition of the laboratory component and the accompanied course reorganization changed the teaching approach from a purely lecture and textbook-dependent approach to an integrated lecture- lab approach with combined use of textbook and open educational resources. 4.6.4 Selected student comments “I like the emphasis on the final project for this class in place of the final exam.” “The changes made to this course really helped.” “Thank you for a great semester, you are a very enthusiastic teacher who cares deeply about his students.” “It was a very tough class, but has made me a better engineer.” “I like having a project.” “I enjoyed the class and learned a lot throughout the semester.” “The course is highly refined, but at the same time it covers the minutiae details. The method of using power point presentation is more efficient.” 74 “The course content really helped me to connect with other current courses.” “I have learned a lot in this class. Thank you for the semester!” “As far as our professor, I think he was friendly and always made sure to be open for questions and extra help.” 4.7 Conclusion In this study, the Introduction of Vibrations and Controls was substantially restruc- tured from a purely lecture and textbook-dependent course to an integrated lecture-lab course with the combined use of textbook and open learning materials. Projects were assigned in the beginning of the semester and students worked in teams to design and build vibration and control systems using theories and knowledge learned from the lectures. The implementation of those team projects provided students with excellent training to work in a group and interact with others to elucidate complicated vibration and control behavior of dynamic systems thereby greatly advanced their understanding on this subject. The develop vibration and control systems will be permanently integrated into the curriculum, based which a series of lab sessions can be designed to enable future students to reinforce their understanding on vibration and control theories and principles through hands-on demonstration and experimentation. For example, the developed first- and second- order systems will allow students to study their time and frequency response under various damping scenarios and measure important parameters such as time constant and damping ratio. The developed thermocouple and electrical scale will allow the students to better understand the components in a feedback control system and how they interact with each other, how to determine parameter values such as gain factors, time constants, frequencies, and damping ratios, as well as how to characterize the behavior of such a system through its rise time, settling time, and overshoot. Furthermore, in the future, more vibration and control systems 75 will be developed through the same channel at low cost to accommodate more engineering students. Course assessment results showed that most goals of this course were achieved and overall the students were very satisfied with the renovated course and recognized the effectiveness of the projects in growing their knowledge bases and developing their problem solving capacity, hands-on experience, and teamwork skills. Overall satisfaction degree of the involved student with respect to the fulfillment of the ABET outcomes was also confirmed. The renovated course requires students to absorb knowledge and useful information from both textbook and online learning materials. 76 CHAPTER V GRADUATE SKILLS MASTERED UPON GRADUATION 5.1 Abstract Instructors organize the design, development, and implementation of their course work based on the necessary learning outcomes and the needs of their students and students will be motivated but what they perceive as most important. The seven outcomes in ABET criteria for mechanical engineering programs can be examined for what students determine as most important. Students would provide attention to these categories, find their content relevant to achieving their goals, work through their challenges with confidence, and have a feeling of satisfaction for achieving the outcomes. The purpose of the study was to determine the ratings of students and faculty for what each perceived to be the most important student outcomes. The outcomes presented were the ABET criteria for a southern United States (U.S.) university’s mechanical engineering program. 5.2 Introduction The standards set by the Accreditation Board for Engineering and Technology [ABET] guarantee a level of quality and inspire confidence for a safer, more efficient, more comfortable, and more sustainable world (ABET, 2022a). The program evaluators are leaders from industry, academia, and government agencies. They evaluate program materials for evidence of what students learned rather than what the students have been taught. Criterion 3, Student outcomes, 77 requires documentation of outcomes that are meant to prepare graduates to enter the professional practice in the field of study represented by the program being evaluated (ABET, 2022b). These student outcomes focus on core knowledge and skill that is systematically presented and practiced within the program’s courses and activities. These seven outcomes can be supplemented by additional program outcomes. Criterion 3 of the ABET standards for student outcomes are (ABET, 2022b): 1. an ability to identify, formulate, and solve complex engineering problems by applying principles of engineering, science, and mathematics. 2. an ability to apply engineering design to produce solutions that meet specified needs with consideration of public health, safety, and welfare, as well as global, cultural, social, environmental, and economic factors. 3. an ability to communicate effectively with a range of audiences. 4. an ability to recognize ethical and professional responsibilities in engineering situations and make informed judgments, which must consider the impact of engineering solutions in global, economic, environmental, and societal contexts. 5. an ability to function effectively on a team whose members together provide leadership, create a collaborative and inclusive environment, establish goals, plan tasks, and meet objectives. 6. an ability to develop and conduct appropriate experimentation, analyze and interpret data, and use engineering judgment to draw conclusions. 7. an ability to acquire and apply new knowledge as needed, using appropriate learning strategies. 78 Integrated baccalaureate-master’s programs have similar ABET criteria for student outcomes. These outcomes can be supplemented with additional outcomes articulated by the program. The integrated baccalaureate and master’s programs student outcomes from Criterion MI3 are (ABET, 2022b): 1. an ability to identify, formulate, and solve complex engineering problems by applying principles of engineering, science, and mathematics. 2. an ability to apply engineering design to produce solutions that meet specified needs with consideration of public health, safety, and welfare, as well as global, cultural, social, environmental, and economic factors. 3. an ability to communicate effectively with a range of audiences. 4. an ability to recognize ethical and professional responsibilities in engineering situations and make informed judgments, which must consider the impact of engineering solutions in global, economic, environmental, and societal contexts. 5. an ability to function effectively on a team whose members together provide leadership, create a collaborative and inclusive environment, establish goals, plan tasks, and meet objectives. 6. an ability to develop and conduct appropriate experimentation, analyze and interpret data, and use engineering judgment to draw conclusions. 7. an ability to acquire and apply new knowledge as needed, using appropriate learning strategies. The master’s level components must have outcomes that prepare students for the mastery of the program being evaluated. Standalone master’s programs have Criterion MS3, Student Outcomes, that state a requirement for programs to have documented student outcomes to 79 support the stated educational objectives of the program and to support mastery of the educational objectives. This standard does not list the seven outcomes common to the other two programs. It is important to note that the seven outcomes within the respective criterion have the same wording. The differences are related to supplemental program outcomes and those outcomes necessary for master’s program students to attain mastery that is consistent with professional practice. 5.3 Relationship to student motivation The publication of the outcomes that meet the ABET criteria have a potential to increase the perceptual arousal, inquiry arousal, and variation (Keller, 1987) of the students in the educational program. These strategies are part of the attention getting strategies that activate a learner’s orienting reflex, curiosity, and sensation seeking. The implementation of change in the environment can serve as an arousal for perception. Problem situations that engage the learner stimulate the inquiry arousal. Changes in presentation, educational media, use of educational technologies, or engaging in problem-based learning (Warnock & Mohammadi-Aragh, 2016) can serve to provide variation in the presentation. Together, perception arousal, inquiry arousal, and variation attract and hold the attention of the learner. These seven outcomes within the criterion offer the learner a sense of relevance. Items that are perceived as relevant are considered to be instrumental for helping the learner achieve a need that is satisfying and helps the learner attain personal goals (Keller, 1983). Interdisciplinary and transdisciplinary education offer learners insight into how their field of learning is relevant to solving problems and interacting with other disciplines (Carey, Knizley, & Howard, 2018; Klaassen, 2018). Other strategies for gaining a sense of relevance are goal orientation, motive 80 matching, and familiarity (Keller, 1987). The integration of the seven outcomes within an engineering program could provide the level of goal achievement necessary for students to see how the outcomes are related to future employment, potential success for graduate school acceptance or being hired for a job. Achievement of outcome 2, “apply engineering design to produce a solution” (ABET, 2022b), could be appealing to a learner’s motives (Knizley & Spayde, 2020). Confidence building strategies are used by instructors to help their learners counter a fear of failure and to gain a sense of accomplishment and perform the skills within the instruction (Knizley, Spayde, & Brocato, 2019). The learning requirements are a simple way for learners to excel at what is expected of them and is a means to counter feelings of failure (Keller, 1987). Personal gains by students in the face of a challenge promotes a sense of accomplishment that helps to overcome feelings of anxiety and self-doubt (Carey, Knizley, & Howard, 2018). The success opportunities encourage learners to succeed at challenging tasks. As learners make incremental changes in their performance, they experience a change such that their environment and their personal control influence their behavior and performance (Gilbert, 1978; Turner & Baker, 2016). As confidence grows, the feeling of personal control also increases. Corrective feedback offers learners a chance to see their mistakes and what corrective actions are necessary to take to improve their performance. Satisfaction is dependent upon the perspective of the learner. The types and frequencies of rewards can influence behaviors in such a way as to reinforce the desired behavior and help to promote a feeling of satisfaction. The strategies to use are dependent upon the outcome. For example, for outcome 4, “an ability to recognize ethical and professional responsibilities in engineering situations and make informed judgments, which must consider the impact of 81 engineering solutions in global, economic, environmental, and societal contexts,” the learner must have the confidence and attention to see the relevant information in a problem related to ethical and professional responsibilities. The informed judgment that includes consideration of the impacts of the engineering solution on the variety of contexts would serve as a natural consequence to an event; natural consequences that are positive are one of the most rewarding results (Keller, 1987). Although new knowledge presented to learners is not always applied to situations immediately. After a number of learning experiences, the likelihood of the learner realizing the many lessons have resulted in a capability or capacity that the learner did not have prior increases. At this time, the learner would experience a series of positive consequences as a result of the new knowledge and may be rewarded intrinsically (self-satisfaction) or extrinsically (payment or other reward for services). A final component of satisfaction is equity. Instructors are encouraged when managing performance to determine the exemplar performance and maintain consistent standards and consequences for task performance. Together, Attention, Relevance, Confidence, and Satisfaction are the elements of the Keller’s ARCS model of motivation. This typology helps instructors organize the design, development, and implementation of their course work. The seven outcomes in ABET criteria for mechanical engineering programs can be examined for what students determine as most important. Students would provide attention to these categories, find their content relevant to achieving their goals, work through their challenges with confidence, and have a feeling of satisfaction for achieving the outcomes. The purpose of the study was to determine the ratings of students and faculty for what each perceived to be the most important student outcomes. The outcomes presented were the ABET criteria for a southern United States (U.S.) university’s mechanical engineering program. 82 5.4 Perceptions of what is important The criterion 3 outcomes for a southern U.S. university were presented to active graduate students and active faculty in the program studied. The University’s Institutional Review board reviewed and approved the protocol. No personal data was collected within the study. All responses were anonymous. The survey was shared with active mechanical engineering master’s degree and doctoral students and faculty assigned to teach courses within the mechanical engineering program. Results were obtained from six graduate students and from eight faculty members. Each group was asked to review a list of 11 ABET criteria for the mechanical engineering program and consider those outcomes for master’s students and doctoral students upon their exit of the mechanical engineering program. Table 1 provides an aggregate for each of the four categories of ratings that were completed. Tables 2 and 3 are organized by respondent and each of the skills is numbered with the assigned number from Table 1. Comparisons of the counts and percentages in Table 1 can be attributed to life experiences. All four groups ratings were 50 percent to 75 percent of the respondents considering that the ability to apply knowledge of mathematics, science, and engineering was one of the three most important outcomes a master’s or doctoral student exiting the program should have mastered while in the program. Although the faculty and students were similar in thinking about the ability to identify, formulate, and solve engineering problems with 40 percent student rating for one of the three most important and 50 percent of the faculty identifying the same for master’s degree students, the percentage rating by the faculty is much more than the percentage of students when considering the outcome as one of the most important for doctoral students. 83 More than half of the faculty considered ability to identify, formulate, and solve engineering problems as one of the three most important. The outcomes rated by graduate students for master’s degree mechanical engineering students had a tie at 60 percent for the first two and a tie at 40 percent for four other categories: • an ability to apply knowledge of mathematics, science, and engineering • an ability to communicate effectively • an ability to design a system, component, or process to meet desired needs within realistic constraints such as economic, environmental, social, political, ethical, health and safety, manufacturability, and sustainability • an ability to function on multidisciplinary teams • an ability to identify, formulate, and solve engineering problems • an ability to use the techniques, skills, and modern engineering tools necessary for engineering practice The outcomes rated by faculty as the most important for a master’s degree mechanical engineering graduate to master were: • an ability to apply knowledge of mathematics, science, and engineering • an ability to identify, formulate, and solve engineering problems • an ability to communicate effectively • an ability to use the techniques, skills, and modern engineering tools necessary for engineering practice The outcomes rated by graduate students as the most important for a doctoral student exiting the program to have mastered were: • an ability to apply knowledge of mathematics, science, and engineering 84 • an ability to design and conduct experiments, as well as to analyze and interpret data • an ability to communicate effectively The outcomes rated by faculty as the most important for a doctoral student exiting the program to have mastered were: • an ability to identify, formulate, and solve engineering problems • an ability to apply knowledge of mathematics, science, and engineering • an ability to design a system, component, or process to meet desired needs within realistic constraints such as economic, environmental, social, political, ethical, health and safety, manufacturability, and sustainability Table 5.1 Aggregate student and faculty rating of the ABET student outcomes # Skills Student Rating Faculty Rating Student Rating Faculty Rating MS (n=5) MS (n=8) PhD (n=6) PhD (n=8) 1 an ability to apply knowledge of mathematics, science, and engineering 3 60% 6 75% 4 66.7% 4 50% 2 an ability to design and conduct experiments, as well as to analyze and interpret data 0 2 25% 3 50% 1 12.5% 3 an ability to design a system, component, or process to meet desired needs within realistic constraints such as economic, environmental, social, political, ethical, health and safety, manufacturability, and sustainability 2 40% 2 25% 1 16.7% 4 50% 4 an ability to function on multidisciplinary teams 2 40% 1 12.5% 1 16.7% 0 5 an ability to identify, formulate, and solve engineering problems 2 40% 4 50% 2 33.3% 5 62.5% 6 an understanding of professional and ethical responsibility 0 0 1 16.7% 0 7 an ability to communicate effectively 3 60% 3 37.5 3 50% 3 37.5% 8 the broad education necessary to understand the impact of engineering solutions in a global, economic, environmental, and societal context 0 1 12.5% 1 16.7% 1 12.5% 9 a recognition of the need for, and an ability to engage in life-long learning 1 20% 0 0 3 37.5% 10 a knowledge of contemporary issues 0 0 0 0 11 an ability to use the techniques, skills, and modern engineering tools necessary for engineering practice 2 40% 5 37.5% 2 33.3% 3 37.5% 85 The ratings were organized in Tables 2 and 3 to provide insight into how the respondents had responded to each of the levels. Only one student rated the three most important outcomes to have mastered by the time a student completed the program; this was student 6 in Table 2. Each of the others had at least one and sometimes two of the same outcomes in their ratings. No student who responded had the ratings completely different for master’s and doctoral students. 86 Table 5.2 Comparison by student respondent of the 3 most important skills for master’s degree and for doctoral students exiting the mechanical engineering program. # For Master’s students For PhD students 1 1. an ability to apply knowledge of mathematics, science, and engineering, 7. an ability to communicate effectively, 11. an ability to use the techniques, skills, and modern engineering tools necessary for engineering practice 1. an ability to apply knowledge of mathematics, science, and engineering, 2. an ability to design and conduct experiments, as well as to analyze and interpret data, an ability to communicate effectively, 11. an ability to use the techniques, skills, and modern engineering tools necessary for engineering practice 2 3. an ability to design a system, component, or process to meet desired needs within realistic constraints such as economic, environmental, social, political, ethical, health and safety, manufacturability, and sustainability, 4. an ability to function on multidisciplinary teams, 5. an ability to identify, formulate, and solve engineering problems 1. an ability to apply knowledge of mathematics, science, and engineering, 5. an ability to identify, formulate, and solve engineering problems, 7. an ability to communicate effectively 3 No response received 2. an ability to design and conduct experiments, as well as to analyze and interpret data, 6. an understanding of professional and ethical responsibility, 8. the broad education necessary to understand the impact of engineering solutions in a global, economic, environmental, and societal context 4 1. an ability to apply knowledge of mathematics, science, and engineering, 4. an ability to function on multidisciplinary teams, 7. an ability to communicate effectively 1. an ability to apply knowledge of mathematics, science, and engineering, 2. an ability to design and conduct experiments, as well as to analyze and interpret data, 7. an ability to communicate effectively 5 5. an ability to identify, formulate, and solve engineering problems, 7. an ability to communicate effectively, 9. a recognition of the need for, and an ability to engage in life-long learning 4. an ability to function on multidisciplinary teams, 5. an ability to identify, formulate, and solve engineering problems, 7. an ability to communicate effectively 6 1. an ability to apply knowledge of mathematics, science, and engineering, 3. an ability to design a system, component, or process to meet desired needs within realistic constraints such as economic, environmental, social, political, ethical, health and safety, manufacturability, and sustainability, 11. an ability to use the techniques, skills, and modern engineering tools necessary for engineering practice 1. an ability to apply knowledge of mathematics, science, and engineering, 3. an ability to design a system, component, or process to meet desired needs within realistic constraints such as economic, environmental, social, political, ethical, health and safety, manufacturability, and sustainability, 11. an ability to use the techniques, skills, and modern engineering tools necessary for engineering practice Similarly to the student ratings, only one faculty member rated the same three outcomes as most important; this was faculty 1 in Table 3. All the other faculty as one or two rated the same for master’s as for doctoral students. 87 Table 5.3 Comparison by faculty respondent of the 3 most important skills for master’s degree and for doctoral students exiting the mechanical engineering program. # For Master’s students For PhD students 1 1. an ability to apply knowledge of mathematics, science, and engineering, 2. an ability to design and conduct experiments, as well as to analyze and interpret data, 7. an ability to communicate effectively 1. an ability to apply knowledge of mathematics, science, and engineering, 2. an ability to design and conduct experiments, as well as to analyze and interpret data, 7. an ability to communicate effectively 2 1. an ability to apply knowledge of mathematics, science, and engineering, 7. an ability to communicate effectively, 11. an ability to use the techniques, skills, and modern engineering tools necessary for engineering practice 1. an ability to apply knowledge of mathematics, science, and engineering, 5. an ability to identify, formulate, and solve engineering problems, 7. an ability to communicate effectively 3 1. an ability to apply knowledge of mathematics, science, and engineering, 4. an ability to function on multidisciplinary teams, 5. an ability to identify, formulate, and solve engineering problems 1. an ability to apply knowledge of mathematics, science, and engineering, 5. an ability to identify, formulate, and solve engineering problems, 9. a recognition of the need for, and an ability to engage in life-long learning 4 3. an ability to design a system, component, or process to meet desired needs within realistic constraints such as economic, environmental, social, political, ethical, health and safety, manufacturability, and sustainability, 5. an ability to identify, formulate, and solve engineering problems, 11. an ability to use the techniques, skills, and modern engineering tools necessary for engineering practice 3. an ability to design a system, component, or process to meet desired needs within realistic constraints such as economic, environmental, social, political, ethical, health and safety, manufacturability, and sustainability, 5. an ability to identify, formulate, and solve engineering problems, 11. an ability to use the techniques, skills, and modern engineering tools necessary for engineering practice 5 1. an ability to apply knowledge of mathematics, science, and engineering, 2. an ability to design and conduct experiments, as well as to analyze and interpret data, 11. an ability to use the techniques, skills, and modern engineering tools necessary for engineering practice 3. an ability to design a system, component, or process to meet desired needs within realistic constraints such as economic, environmental, social, political, ethical, health and safety, manufacturability, and sustainability, 5. an ability to identify, formulate, and solve engineering problems, 11. an ability to use the techniques, skills, and modern engineering tools necessary for engineering practice 6 1. an ability to apply knowledge of mathematics, science, and engineering, 7. an ability to communicate effectively, 11. an ability to use the techniques, skills, and modern engineering tools necessary for engineering practice 5. an ability to identify, formulate, and solve engineering problems, 7. an ability to communicate effectively, 9. a recognition of the need for, and an ability to engage in life-long learning 7 1. an ability to apply knowledge of mathematics, science, and engineering, 5. an ability to identify, formulate, and solve engineering problems, 11. an ability to use the techniques, skills, and modern engineering tools necessary for engineering practice 1. an ability to apply knowledge of mathematics, science, and engineering, 3. an ability to design a system, component, or process to meet desired needs within realistic constraints such as economic, environmental, social, political, ethical, health and safety, manufacturability, and sustainability, 11. an ability to use the techniques, skills, and modern engineering tools necessary for engineering practice 88 Table 5.3 (continued) # For Master’s students For PhD students 8 3. an ability to design a system, component, or process to meet desired needs within realistic constraints such as economic, environmental, social, political, ethical, health and safety, manufacturability, and sustainability, 5. an ability to identify, formulate, and solve engineering problems, 8. the broad education necessary to understand the impact of engineering solutions in a global, economic, environmental, and societal context 3. an ability to design a system, component, or process to meet desired needs within realistic constraints such as economic, environmental, social, political, ethical, health and safety, manufacturability, and sustainability, 8. the broad education necessary to understand the impact of engineering solutions in a global, economic, environmental, and societal context, 9. a recognition of the need for, and an ability to engage in life-long learning To provide additional context to the ratings, students were asked to mark which of the southern U.S. university mechanical engineering courses they had taken, were currently taking, or were planning to take. This direct student measure requires more data for confident conclusions to be drawn. 89 Table 5.4 Enrollment Status by Graduate Student Course Name 1 2 3 4 5 6 ME 6193 Automotive Engineering] ME 6333 Energy Systems Design] Taken Taken ME 6343 Intermediate Heat Transfer] Taken ME 6353 Alternate Energy Sources] Taken ME 6373 Air Conditioning] Taken Taken ME 6393 Power Generation Systems] ME 6413 Casting and Joining] ME 6443 Mechanical Systems Design] Taken Taken ME 6543 Combustion Engines] ME 6624 Experimental Methods in Materials Research] ME 6643 Introduction to Vibrations and Controls] Taken Taken ME 6823 Compressible Flow and Turbomachinery] ME 6833 Intermediate Fluid Mechanics] Taken Taken ME 8011 Graduate Seminar] Taken Taken, Plan to Take Taken Taken Taken Plan to Take ME 8144 Transmission Electro Microscopy] ME 8213 Engineering Analysis] Taken Taken Taken ME 8223 Inelasticity] Taken Taken ME 8243 Finite Elements in Mechanical Engineering] Plan to Take ME 8253 Fatigue in Engineering Design] Taken ME 8313 Conductive Heat Transfer] Currently Enrolled ME 8333 Convective Heat Transfer] ME 8373 Integrated Computational Materials Engineering] Taken ME 8513 Classical Thermodynamics] Plan to Take ME 8613 Dynamical Systems] ME 8733 Experimental Procedures] ME 8813 Viscous Flow I] Taken Plan to Take Taken ME 8823 Viscous Flow II] Taken Plan to Take Taken 90 5.5 Conclusions The environment and personal repertoire of the students and the faculty are influential in what they each believe to be most important. When comparing the responses, there was agreement for the most important outcome for master’s degree students. For doctoral students, this skill, an ability to apply knowledge of mathematics, science, and engineering, was rated the highest by master’s degree students and was tied for second/third in the rating by the faculty. Communication skills were rated as one of the most important by the students and the faculty for master’s degree graduates; however, the outcome – an ability to design a system, component, or process to meet desired needs within realistic constraints such as economic, environmental, social, political, ethical, health and safety, manufacturability, and sustainability—was one of the top three for doctoral student graduates as rated by the faculty to be one of the most important outcomes. 91 CHAPTER VI SOFT SKILLS FOR ENTRY-LEVEL ENGINEERS: WHAT EMPLOYERS WANT 6.1 Abstract Among the requirements for engineering programs, the Accreditation Board of Engineering and Technology (ABET) criteria for student outcomes require students to have the ability to communicate effectively with a range of audiences, recognize ethical and professional responsibilities, function effectively on a team, and apply new knowledge. A review of literature for skills comprised within these ABET criteria determined 26 topics necessary for the entry-level and continued success of engineers. Nearly 500 companies and organizations rated the importance and proficiency of their recent entry-level engineers for these 26 identified soft (professional) skills. The findings suggest that although entry-level engineers have proficiency in all of these ABET required skills, the entry-level engineers were not meeting the level of importance expressed by the organization for 24 of these 26 skills. A specific ABET required skill, the ability to communicate effectively with diverse groups of people, has the greatest difference between the level of proficiency and the level of importance. Analysis of variance was conducted using each of the demographic variables to determine the effect sizes in the ratings of importance, proficiency, and the differences between importance and proficiency. These results were shared with industry members to confirm the relevance of the survey findings during the pandemic. This survey research has implications for any university engineering department where students are seeking entry-level engineering positions after graduation. 92 6.2 Introduction The Accreditation Board of Engineering and Technology [ABET, 2021a] identifies preparing students for engineering practice as one of the critical criteria for evaluating engineering education. The expected student outcomes outlined by ABET include non-technical or soft skills such as ability to communicate effectively, function in teams, and the knowledge of the social, political, economic, and global context of their work and the impact of their work in these contexts [ABET, 2021b]. Even though ABET articulates the need for engineering education to also support the acquisition of non-technical skills and knowledge, it does not identify a specific set of soft skills on which engineering programs should focus. Because the primary goal of engineering education is to prepare engineers for professional practice, university engineering departments need to turn to industry to understand what soft skills employers want their entry-level engineers (newly hired engineers) to possess and if employers are satisfied with the soft skills these new-hires demonstrate. This study identifies and reports industry assessment of specific soft skills necessary to meet the ABET criteria. The outcomes of the research enable engineering education programs to be responsive to industry needs for non-technical entry-level skill proficiency. In order to foster the development of program specific skills, engineering curricula place primacy on hard skills (technical skills) over soft skills [Miller, 2017]. The soft skills are not skills or abilities in a traditional sense, but rather they constitute a combination of interpersonal skills and personal attributes [Robles &Srour, 2016] that augment the technical skills traditionally seen as paramount to engineering success. There is growing evidence and impetus for focusing intentionally on soft skills within technical and professional curricula [Autor, 2015]. Changes in technology, increasing reliance on automation, transnational production processes, 93 and the sheer complexity of work in the 21st century demand that employees demonstrate skills sets that machines cannot master [Autor, 2015; Deming, 2017]. Workplace situations and interactions that require social and interpersonal skills cannot be automated easily [Autor, 2015]. There are increasing expectations, therefore, for people in technical work places to focus on supplementing and complementing the growing capabilities of machines [Miller, 2017]. Qualities, such as the potential for non-routine interaction, ability to understand people’s intentions, actions to successfully collaborate, decision making, leading, and adaptation to a changing environment, give human beings an edge over machines and enable employees to leverage human capabilities that machines cannot successfully master [Autor, 2015; Deming, 2017; Autor, 2003]. Moreover, there is additional evidence within labor economics, which underscores the need for social, interpersonal, and non- cognitive skills even within professions traditionally deemed technical. Labor economists have established that jobs demanding higher levels of social skills grew more between 1980 and 2012 in contrast to jobs requiring higher math but lower social skills [Deming, 2017]. Furthermore, jobs that will be available for the human workforce in the 21st century and those that will grow and flourish, even within technical fields, demand higher levels of interpersonal and social skills [Miller, 2017]. Concerns related to a lack of soft skills among engineers and engineering graduates have come to the forefront over the last decade. Recognizing the needs of the rapidly evolving and globally dispersed work contexts, IBM (International Business Machines Corporation) recommended that technical education in the 21st century should focus on preparing “T” shaped individuals who are not only steeped in field specific technical knowledge but also are able to demonstrate knowledge across disciplines and the ability to work with others [9]. More recently, in its exploration of the future direction of science, technology, engineering, and mathematics 94 (STEM) education, the STEM connector’s Innovation Task Force (SITF) emphasized that the next stage of STEM education should enable students to master the context, which demands the ability to function in teams, to demonstrate business acumen and leadership skills, and to be able to “navigate across global organizations” [SITF, 2014 p. 13]. However, of concern to engineering educators, Busteed [2021] reported that employers expressed deep concerns about the preparation of college graduates and revealed a great disconnect between what employers expect and the level higher education considered as prepared for work. Another study reported that 58% of managers responding believed that the productivity of their company was limited because of the lack of soft skills among their potential employees, especially among high growth industries and start-up enterprises [Berger, 2021]. Additionally, 59% of these managers specified that employees who demonstrated competence with soft skills were harder to find than those with technical skills [Berger, 2021]. Heckman and Kautz [2012] argued that, at an individual level, soft skills such as conscientiousness predicted success in life, academic attainment, health, and higher labor market outcomes as much as cognitive ability. What is more, in a 21st century workplace, lack of soft skills can undermine the technical ability of individuals and can cost them their job and/or potential career growth [Laus, 2010]. Consequently, there is a noteworthy shift in the importance given to soft skills within technical fields. Accrediting bodies, such as ABET, have reiterated the need for engineering education programs to provide students opportunities to acquire a broader set of skills to improve their ability to collaborate, work in teams, and thrive in a globalized work environment [ABET, 2021a]. Soft skills that were considered ‘nice to have’ within technical fields in the last century are moving to the ‘need to have’ category in the current century [Fernandes, Jardim & Lopes, 2021; Schulz, 2008; Touloumakos, 2007]. 95 6.2.1 Purpose and Problem Statement Soft skills, however, are not a finite set of skills or abilities. They constitute a wide range and disparate set of social and people skills, personal attributes, and self-management skills [Matteson, Anderson & Boyden, 2016]. Soft skills required by engineers may vary at different levels of their careers [Riley, Horman & Messner, 2008]. Fundamentally, the set of soft skills required in entry-level occupations are not the same as those necessary for senior management level positions [Kappelman et al. 2016]. Recent studies have been conducted to analyze future skills needed and to identify which soft skills employers consider important for new or entry-level engineers [Cruz, Saunders-Smith, Groen, 2020; Adecco, 2016; Akyazi et al., 2020a, Akyazi et al., 2020b; Arcelay et al., 2021; Maisiri & Van Dyke, 2021]. The purpose of this study, therefore, was to provide documentation for university engineering programs related to expected soft skills by determining what soft skills employers perceive as being important for entry-level engineers to possess and demonstrate and by assessing the perception of proficiency of recent new hires in engineering. The study also sought to further understand the difference in employers’ perceptions about importance and proficiency of soft skills for entry-level engineers within to their performance. A qualitative evaluation of open-ended responses answered the question of what employers look for in applicants and new hires. Snowball unstructured interviews reinforced the outcomes of the quantitative analysis of the survey data and the qualitative evaluation of open-ended responses. The objective was to inform engineering educators about the need to focus on non-technical skills within the curriculum [ABET, 2021a; Pocsova et al., 2020] and help to prioritize which soft skills are reported as most important for entry-level engineering roles. 96 6.2.2 Research Questions This study addressed the following research questions: • What soft skills do employers expect entry-level engineers to demonstrate, which soft skills are most important? • What is the perception of employers regarding the general level of soft skills proficiency of entry-level engineers? • What is the difference between expectations of employers and their perceptions of proficiency demonstrated by entry-level engineers across the measured set of soft skills? • What are the qualities that employers look for in applicants and new hires as entry- level engineers? 6.2.3 Conceptual Framework ABET expects engineering programs to reflect current and future aspects of the technical fields and prepare students for a career in the discipline. Engineering programs are required to watch the trends in technical fields and the changes in knowledge and skill requirements these changes might augur. Environmental scanning is an established process used by organizations and higher educational institutions to gather information on the current and future trends in the macroenvironment in which they operate [Morrison, 1993]. Aguilar (as cited in [Morrison, 1993]) identified four methods of scanning the macroenvironment, including formal searching that refers to proactive seeking of information for specific purposes. The goal of environmental scanning is to alert decision makers to changes in the environment that lead to, or might lead to, changes in expectations [Morrison, 1993]. In this study we use environmental scanning as the conceptual framework to assess the expectations of employers that recruit engineering graduates 97 with the purpose of using the outcomes to inform engineering education programs. We specifically used an active, formal search approach to gather data on what soft skills employers expected engineering graduates to possess. 6.3 Review of Literature 6.3.1 What Are Soft Skills? Skills generally refer to abilities people have acquired over time with effort or training and always involve an element of execution or performance [Touloumakos, 2020; Matterson, Anderson & Boyden, 2016]. Hard skills in an engineering context refer to technical skills or abilities that are required to perform work related tasks. Soft skills on the other hand are less tangible, hard to quantify, and rather challenging to define. In contrast to technical knowledge or abilities, the term ‘soft skills’ is used loosely in literature to denote a disparate set of personal attributes, traits, attitudes, and behaviors [Robles, 2012; Touloumakos, 2020]. Research on soft skills exists across different fields such as labor economics [Deming, 2017]; employability, workforce development, and human resource development [Autor, 2015; Autor, Levy & Murnane, 2003]; management and communication [Robles, 2012; Jones et al., 2016]; and in industry or subject specific literature such as information technology [Kappelman et al., 2016; Aasheim, Li & Williams, 2009]; STEM [John & Chen, 2017]; education [Fernandes, Jardim & Lopes, 2021], or library and information science [Matteson, Anderson & Boyden, 2016]. In addition, not for profit agencies and government funded or public sector projects also conduct country, region, or industry specific research on soft skills [Crawford et al., 2011; Hannover Research, 2021; Washington State Human Resource Council, 2014]. Private consulting agencies involved in studying the pulse of specific industries and evolving skill requirements within these industries investigate non-technical skills alongside technical skills 98 requirements [Busteed, 2014]. Given the multiplicity of fields in which research on soft skills is situated, it is not surprising that the taxonomy of soft skills is varied or that the definition of the term is rather fuzzy. There is no universally accepted classification of what constitutes a soft skill [Touloumakos, 2020; Matteson, Anderson & Boyden, 2016]. Researchers use terms such as non-cognitive, non-technical skills; people skills; transferable skills; employability skills; and interpersonal skills to refer to soft skills [Touloumakos, 2020; Matteson, Anderson & Boyden, 2016; Pocsova et al., 2020]. Most research equates soft skills with people skills or the ability to get along with or work effectively with others [Robles, 2012]. However, soft skills are more than people skills or interpersonal skills (such as effective communication, collaboration, and co-operation) required to relate to other people [Robles, 2012; Touloumakos, 2020; Matteson, Anderson & Boyden, 2016]. The term soft skills also encompasses intrapersonal elements (abilities such as adaptability and self-regulation that reside within the individual), personality traits (example: agreeableness, conscientiousness), attributes (example: confidence, resilience); and straddles both the cognitive (examples: analytical ability, decision-making) and affective (example: active listening, empathy) domains [Touloumakos, 2020; Matteson, Anderson & Boyden, 2016]. Since soft skills are non-technical and not industry specific, these are highly transferable across contexts and are broadly applicable [Prett, 2019]. 6.3.2 Research on Soft Skills Research on soft skills generally tends to focus on: (a) examining the importance of soft skills in academic and work contexts; (b) compiling a list of soft skills that employers consider important in a specific field; (c) comparing perceptions of different stake- holders on the importance of a specific set of soft skills within a given field or industry; (d) assessing soft skills 99 requirements for different levels of employment; and (e) developing tools to measure soft skills or assess their demonstration. For instance, Heckman and Kautz [2006] demonstrated that personality traits such as conscientiousness, perseverance, sociability, and curiosity played a significant role in predicting and determining success in academic, social, and work lives. Exploring the importance of soft skills from the demand perspective, Deming [2017] found that jobs requiring high social interactions experienced significant growth in the United States between 1980 and 2012. Several studies have also emphasized a demand for social and interpersonal skills in the labor market in the coming years [Autor, 2015, Heckman, Stixford & Urzua, 2006; Borghans, Ter Weel & Weinberg, 2014; Lindqvist & Vesman, 2011; Kuhn & Weinberger, 2005]. There exists a robust portfolio of research on the soft skills required in specific industries. Robles [Robles, 2012] asked business executives to identify ten soft skills they considered most important for new employees to possess and collected a list of 517 soft skills. Robles [2012] then identified the top ten most frequently listed soft skills and created a questionnaire asking the executives to rank these skills in order of importance. Adopting a quasi-ethnographic approach Windels, Mallia, and Broyles [2013] explored specific soft skills that were most useful in the advertising industry. Research on skills requirements in the field of library and information science also explored soft skills essential to succeed in the evolving field [Hall-Ellis, 2008; Stephens, 2013]. Comparing perceptions of various stakeholders such as students (for example: [Itani & Srour, 2016]), faculty, and employers on soft skills requirements is another area of emphasis within soft skills research. Rainsbury, Hodges, Burchell, and Lay [2002] studied the perceptions of students and graduates on workplace competencies. More recently, using a qualitative approach John and Chen [2017] investigated the importance placed by students and 100 industry practitioners on the skills (both technical and non-technical) necessary for success in STEM. In their study of knowledge and skill requirements (including interpersonal skills and personal traits) for entry-level information technology workers, Aasheim et al., [2009] compared the perspectives of industry personnel and faculty. Determining soft skills requirements for different categories of employees such as entry-level performers, middle management, and senior management or leadership is also gaining traction in different fields. For instance, Weber, Finley, Crawford, and Rivera [2009] studied soft skills required for entry-level managers in the hospitality and tourism industry. Another study used the Delphi method to identify skills for success at various stages of careers within the information technology (IT) industry [Riley, Horman & Messner, 2008]. The study developed a list of skills including non-technical, interpersonal, and intrapersonal skills IT professionals considered most important for success at entry-level, mid-managerial level, and senior managerial level within their industry [Kappelman et al., 2016]. Assessment of these intangible skills is another challenge explored in soft skills re- search. Klein, DeRouin, and Salas [2006] provided a taxonomy of interpersonal skills and suggested a variety of means to categorize and assess interpersonal skills. Loughry, Oh- land, and Moore [2007] focused specifically on individuals’ ability to work in teams and demonstrated means to assess capacity for working effectively in teams. Some researchers have developed scales or tools to measure specific soft skills. For instance, Taggar and Brown [2001] created scales to measure conflict resolution, communication, and group problem solving. Heckman and Kautz [2012] not only argued that personality traits played a significant role in predicting and determining success in academic, social, and work lives beyond standardized achievement tests, but also demonstrated how personality traits can be measured. 101 6.3.3 What Soft Skills Are Important in the Employment Context? In an attempt to understand the demand side of conditions, researchers and research groups often compile a list of soft skills based on employer expectations or requirements. They collect data from employers through surveys and interviews on soft skills they want their employees to possess or demonstrate. Table 6.1 presents lists of soft skills required for entry and success in the workplace. The references presented are organized by date. The citation counts provided offer support for the continued relevance of the lists of soft skills. 102 Table 6.1 Lists of Soft Skills Required for Entry and Success in the Workplace. Author/Source Area of focus Source of data List of Soft Skills considered important Andrews & Higson, 2008 (over 1200 citations) Graduate employment Literature review Professionalism, reliability, ability to cope with uncertainty, ability to work under pressure, ability to plan and think strategically, capability to communicate and interact with others either in team or through networking, good written and verbal communication skills, creativity and self-confidence, good self-management and time management skills, willingness to learn and accept responsibility, Aasheim, Li, & Williams, 2009 (over 140 citations) Information Technology (Entry-level) Senior & Middle management Communication, ability to work in teams, interpersonal skills, personal skills or traits, honesty/integrity, analytical skills, flexibility/adaptability, motivation, creative thinking, organizational skills, entrepreneurial skills/risk-taking Mitchell, Skinner, & White, 2010 (over 350 citations) Business graduates Recruiters Positive attitude, being respectful, trustworthy, honest and ethical, taking initiative and responsibility, being co-operative and a team player, possessing good communication and interpersonal skills, being ambitious and self-confident, and ability to think critically Crawford, Lang, Fink, Dalton, & Fielitz, 2011 Students graduating from Agriculture & natural resources related programs Employers Alum, Faculty, Students Seven soft skills clusters: Communication, decision-making/problem-solving, self-management, team work, professionalism 21st century skills for engineers (Hanover, 2011) Engineers Team work, consensus building, entrepreneurial mindset, creative design, empathy and social responsibility, global awareness and perspective, ethical behavior and trustworthiness, broad systems thinking, multidisciplinary thinking 103 Table 6.1 (continued) Author/Source Area of focus Source of data List of Soft Skills considered important Robles, 2012 (over 1600 citations) Business graduates Business Executives Communication, courtesy, flexibility, integrity, interpersonal skills, positive attitude, professionalism, responsibility, team work, work ethic Lippman, Ryberg, Carney, & Moore, 2015 (over 200 citations) Youth Literature review Social skills, communication skills, higher order thinking skills, self-control, positive self-concept Wikle & Fagin, 2015 (over 50 citations) Geographic Information Science Employer Problem solving/trouble shooting, critical thinking, flexibility/adaptability, working in a team environment/ability to work independently, time management/multi-tasking, creativity/verbal presentation, writing, project management/leadership Berger, 2016 (over 5 citations) Entry-level contributors LinkedIn profiles Communication, organization, team work, creativity, social skills, critical thinking, interpersonal communication, adaptability, punctuality, friendly personality John & Chen, 2017 (over 2 citations) STEM Employer Team work, communication, empathy, analytical skills, self-control, positive self-concept Pócsová, Bednárová, Bogdanovská, & Mojžišová, 2020 (over 2 citations) Engineers Social and emotional learning competencies Critical thinking/problem solving, creativity, communication skills, collaboration Fernandes, Jardim, & Lopes, 2021 (over 5 citations) Special education teachers Literature review Personal and social skills, personal attributes management, performance improvement, sustaining interpersonal relationships Close analysis of the soft skills required across different studies (Table 6.1) establishes a lack of uniformity in the set of soft skills required within different disciplines or industries. Moreover, very few studies specifically focus on soft skills requirements for employees at one or 104 different levels of employment. Soft skills required at entry-level employment may be different from those that are required at middle managerial or senior management levels [Matteson, Anderson & Boyden, 2016; Kappleman et al., 2016; Aasheim, et al., 2009]. In addition, soft skills required to survive, grow, and contribute effectively in technical professions differ from those that apply to generic college level employment. Whatever literature that is available on soft skills requirements for engineers is either broad-based and not employment level specific or it is a compilation of expert opinion. There is a dearth of evidence-based studies that attempt to identify soft skills required by entry-level engineers specifically [Toor & Ofori, 2008]. This study endeavors to address this gap in literature by compiling a set of soft skills for employers to evaluate for the level of importance for engineers who are recently out of college to possess. Second, the study documents perceptions of employers about the level of proficiency newly hired engineers demonstrate in these important soft skills. Documenting the soft skills employers expect can help engineering educators target specific skills and strategies when preparing the engineering workforce. Understanding employers’ perceptions about general proficiency levels of engineering graduates in terms of soft skills enables prioritization of areas that engineering educators need to concentrate on within their mainstream curriculum and through supplemental activities. 6.4 Method and Results The study employed a survey to collect data from employers who hired newly graduated engineers. The study sought to find: (a) the set of soft skills employers expect from their entry-level/new hire engineers; and (b) employers’ rating of the proficiency levels of entry-level engineers in terms of soft skills. The survey was conducted prior to the pandemic. The results of the analysis of variance were shared using a snowball interview technique with engineers, 105 educators, and managers in industries identified as having statistically significant results. These follow-up interviews to confirm or refute the findings of the analysis were conducted in summer and fall 2021. The comparison of importance and proficiency is a job analysis type method where the use of the two indicators, importance and proficiency, relate to research to assess functions and effectiveness of characteristics of employees [Flanders & Utterback, 1985]. Importance and proficiency are used to measure the scope and range of responsibilities for positions. The measure of importance provides an indicator of the job requirements and the differences, importance minus proficiency, provide the strengths and development needs of those being rated. Responses about the importance of skills and the perception of performance clarify the engineer’s roles and job requirements, identify individual engineer’s strengths and development needs, inform education planning needs, support decisions about engineering programs, confirm training and development priorities and resource allocation, identify content and design of engineering training and development programs, and supply evaluation data for engineering training and development programs. 6.4.1 Survey Design and Distribution The survey was created based on extensive review of soft skills literature that reported employer expectations in the following categories: (a) graduate employment; (b) STEM and technical professions; (c) future skills requirements in STEM; (d) entry-level employees; and (e) youth employability. Initially the researchers combed literature on soft skills to arrive at the taxonomy of soft skills and the different terms used to refer to soft skills across disciplines. Then we identified literature that reported employer expectations or requirements or perceptions of soft skills (or terms used interchangeably such as transferable skills, employability skills, 106 interpersonal skills, non-technical or non-cognitive skills) in each of the categories. We then compiled a set of soft skills across the literature collected, and, lastly, assembled a set of 26 soft skills that appeared most frequently across these categories. The list of 26 soft skills compiled from literature formed the crux of the survey created. The survey itself consisted of four sections of questions (see Table 6.2) followed by space at the end for participants to add their comments and inputs regarding soft skills requirements for entry-level engineers. Career service professionals who work closely with engineering employers and senior academicians vetted the survey for content and language and then the survey was pilot tested with 10 engineering employers. The researchers then incorporated the suggestions collected in the process and finalized the survey for distribution. The survey was distributed to 1200 employers who were known to employ engineers through Qualtrics and over a period of 30 days in 2018; we received 489 responses (40.75%). Table 6.2 Survey Format. Survey Sections Focus Section A Profile details of respondents and the organization represented (job title, supervisory responsibilities over entry-level engineers, organization details: size, sector, headquarters, nature of business) Section B List of 26 soft skills (level of importance of each of these skills) Section C List of 26 soft skills (rating of proficiency levels of entry-level engineers in their organization on each of these skills) Section D Types of engineers employed in their organization (Example: Mechanical engineer; software engineers; process engineers) Section E Space to add inputs and comments on soft skills requirements for entry-level engineers 107 6.4.1.2 Information about the Respondents and Their Organizations Respondents to the survey were asked questions about their organization. A summary of these questions and frequencies are presented in Table 6.3. Firm size was reported in categories of less than 100, 100 to 500, and more than 500. Categorization of the organizations were to indicate if the organization was in the private sector, public sector, or other. Open ended responses for the other types of organizations included education, government contract, military contract, non-profit, research, and utility. To assess the geographical boundaries of the organizations, respondents indicated if their organization was head- quartered in or outside the United States and if the organization had branches, offices, or plants outside the United States. Respondents were asked an open-ended question to state the primary line of business for their organization. The result was over 240 individual responses. A recode of these responses reduced the number of primary lines of business to 20 industries and a category of not declared. Over 300 different titles were entered by the respondents in response to the open-ended question prompt asking for the respondent’s current title. These titles were recoded into six position titles: administrator, director, engineer, HR, manager, and recruiter. Those without an entry were coded as not declared. The last profile question asked if the respondent supervised entry-level engineers directly. 108 Table 6.3 Profile of the Respondents and their Organizations Category Response Options Frequency Valid Percent (%) Number of people employed in organization Less than 100 96 22.0 100 - 500 95 21.7 More than 500 246 56.3 Categorization of the organization Private Sector 317 72.5 Public Sector 105 24.0 Other 15 3.4 Headquarters in the United States Yes 388 88.8 No 49 11.2 Organization has branches, offices, or plants outside the United States Yes 304 69.6 No 133 30.4 Primary line of business Aerospace 20 4.1 Automotive 16 3.3 Chemical 6 1.2 Civil Engineering 11 2.3 Consumer Products 32 6.6 Defense 11 2.3 Education 6 1.2 Electronics 7 1.4 Energy 5 1.0 Engineering 31 6.4 Financial 6 1.2 Healthcare 4 0.8 Industrial Engineering 7 1.4 Manufacturing 131 26.9 Medical 24 4.9 Not declared 53 10.9 R&D 8 1.6 Semiconductor 14 2.9 Technology 79 16.2 Transportation 4 0.8 Utilities 12 2.5 Current title of respondent within organization Administrator 16 3.3 Director 87 17.9 Engineer 120 24.6 HR 55 11.3 Manager 113 23.2 Not declared 52 10.7 109 Table 6.3 (continued) Category Response Options Frequency Valid Percent (%) Recruiter 44 9.0 Respondent directly supervises entry-level engineers Yes 217 49.8 No 219 50.2 Note: N=487. Missing values are not included in the table. 6.4.2 Results of Paired Mean Difference Analysis The 26 soft skills were evaluated using a Likert scale of 0 as not important or not proficient to 4 as absolutely essential or absolutely proficient. A paired t-test was conducted to examine the mean of paired differences between each respondent’s rating of importance and proficiency because it was determined that the responses were not independent of each other [Ross & Willson, 2017]. The mean of the paired differences resulted in 24 of the 26 soft skills assessed as having a statistically significant difference of the two ratings. The level of importance exceeded the level of proficiency for these 24 soft skills. Figure 1 depicts the comparison of the levels of importance and the levels of proficiency for each of the soft skills; the entries are presented in rank order from greatest to least of the means of the paired difference values. Table 4 is presented based upon the ranking for the level of proficiency and depicts the mean value for each of the soft skills and the mean of the paired differences. The five soft skills rated as most important for an entry-level engineer were: (1) reliability, (2) ability to work in teams, (3) responsibility, (4) self-motivation, and (5) positive attitude. The five soft skills rated to have the greatest differences between the paired ratings of importance and proficiency were: (1) the ability to communicate with diverse groups of people, (2) time management, (3) ability to write effectively, (4) the ability to deal with 110 uncertainty when relating to people and situations, and (5) the ability to communicate across age groups. The five skills with the least proficiency and with a statistically significant difference for the paired t-test were: (1) leadership, (2) the ability to deliver effective presentations, (3) the ability to plan and think strategically, (4) the ability to write effectively, and (5) the ability to deal with uncertainty when relating to people and situations. Results of Analysis of Variance of Differences by Profile Characteristic A new variable was calculated within the data set to have a difference in ratings value for each of the 26 soft skills rated by the respondents for their importance within their organization and proficiency displayed by the organization’s newly hired engineers. This difference rating was calculated with the importance minus the proficiency. Outcomes of this calculation for individuals in similar assessment are used in job analyses to determine needs for training, coaching, or other professional development. Analyzed using analysis of variance for each of the profile variables, the outcomes can be used to identify where there is a need for additional development of engineers prior to being hired, and where educational programs could further assess their curricula to support development of the soft skills identified. A large positive difference indicates the ratings for importance were greater than the ratings of proficiency of the newly hired engineers. Differences at or near zero indicate the ratings for importance and for proficiency were the same or close to each other, respectively, and it is likely the educational preparation of the newly hired engineers is sufficient to meet the organizations needs and requirements. Analysis of variance was conducted to determine if any of the profile characteristics resulted in between group differences for the new variable calculated using importance rating minus proficiency rating. Results of the ANOVAs are presented with the partial eta squared 111 effect size and Cohen’s F effect size [Cohen, 1992] for comparisons that were statistically significant between the organization or respondent profile attributes; Partial eta squared effect sizes are considered small 0.01, medium 0.06, large 0.14, and Cohen’s F effect sizes are considered small 0.1, medium 0.25, large 0.4. 112 Figure 6.1 Importance vs. Perceived Proficiency 113 Table 6.4 Soft skills rating of Importance and Proficiency and pair differences means, ranked by Proficiency rating from least to greatest Soft Skills Importance Proficiency Paired Differences Mean Leadership 2.77 2.35 0.41 *** The ability to deliver effective presentations 3.10 2.62 0.50 *** Global and cultural awareness 2.65 2.68 -0.03 The ability to plan and think strategically 3.33 2.70 0.62 *** The ability to write effectively 3.51 2.73 0.80 *** The ability to deal with uncertainty in relating to people and situations 3.50 2.75 0.79 *** Social responsibility 2.70 2.83 -0.10 The ability to communicate across age groups 3.58 2.86 0.73 *** Creativity: Coming up with ‘out-of-the-box’ ideas and solutions 3.35 2.86 0.49 *** The ability to communicate effectively with diverse groups of people 3.78 2.89 0.90 *** Time-management 3.76 2.95 0.82 *** Ability to handle multiple priorities 3.66 3.01 0.65 *** Critical thinking (ability to identify, construct, and evaluate arguments; detect inconsistencies and errors in reasoning; solve problems systematically; reflect on underlying values and beliefs) 3.73 3.04 0.70 *** The ability to understand, articulate, and solve complex problems and make sensible decisions based on available information 3.66 3.04 0.62 *** The ability to work under pressure 3.55 3.04 0.52 *** Focused: the ability to stay focused on a task 3.76 3.06 0.71 *** Willingness to take initiative 3.77 3.09 0.70 *** Staying/ being organized 3.64 3.12 0.54 *** Self-efficacy: belief in one’s capabilities to achieve a goal or outcome 3.53 3.21 0.36 *** Flexibility and adaptability 3.75 3.29 0.48 *** Curiosity 3.44 3.30 0.13 * Self-motivation 3.85 3.30 0.55 *** Responsibility 3.86 3.32 0.52 *** Reliability 3.93 3.35 0.57 *** The ability to work in teams 3.86 3.38 0.48 *** Positive attitude 3.82 3.55 0.28 *** 114 6.4.2.2 Size of the Organization When considering the size of the organization (less than 100, 100–500, more than 500), statistically significant differences were determined for the difference in ratings of the ability to communicate across age groups (x<100 = 0.57, sd = 1.23; x100 500 = 0.56, sd = 0.79, x>500 = 0.87, sd = 0.92, F = 4.25, p = 0.015, η2 = 0.025, Cohen’s F = 0.16) and the ability to deliver effective presentations (x<100 = 0.32, sd = 1.12; x100 500 = 0.29, sd = 0.96, x>500 = 0.66, sd = 1.09, F = 4.59, p = 0.011, η2 = 0.027, Cohen’s F = 0.17). The Tukey pairwise comparison indicated for the difference in ratings of the ability to communicate across groups, the ratings for respondents in companies with more than 500 employees were higher than the ratings by respondents in companies with 100–500 employees (mean difference = 0.31, Std Error = 0.13, p = 0.046). The Tukey pairwise comparison for the ability to deliver effective presentations indicated that the ratings for respondents in companies with more than 500 employees were higher than the ratings for respondents in companies with 100–500 employees (mean difference = 0.37, std error = 0.14, p = 0.028). The effect size for each of these questions is a small to medium effect as indicated by the eta squared effect size and the Cohen’s F effect size. 6.4.2.3 Sector Type of Organization Respondents identified their organization as being categorized as public sector, private sector, or other. Statistically significant differences in the ratings between these three groups were found for only one of the differences in soft skills ratings. Tukey pairwise comparisons of the ratings for willingness to take initiative (xprivate = 0.67, sd = 0.90; xpublic = 0.91, sd = 1.10, xother = 0.07, sd = 0.92, F = 5.04, p = 0.007, η2 = 0.029, Cohen’s F = 0.17) indicated differences 115 between the public sector and those who indicated other (mean difference = 0.84, std error = 0.28 p = 0.007). The effect sizes for this difference between public sector organizations and other types of organizations is a small to medium effect. 6.4.2.4 Geographic Location of Headquarters and Branches, Offices, of Plants Ratings for differences of importance and proficiency of newly hired engineers for organizations that reported headquarters in the United States did not differ statistically when compared to those with headquarters in other countries. Statistically significant differences were found when conducting an ANOVA of differences in the ratings of importance and profi- ciency categorized by respondents’ indication if the organization had branches, offices, or plants outside the United States. Between group statistically significant differences were found for the ability to communicate across age groups (xyes = 0.81, sd = 0.91; xno = 0.55, sd = 1.09, F = 5.10, p = 0.025, η2 = 0.015, Cohen’s F = 0.12), the ability to deliver effective presentations (xyes = 0.59, sd = 1.09; xno = 0.29, sd = 1.02, F = 5.62, p = 0.018, η2 = 0.016, Cohen’s F = 0.13), and global and cultural awareness (xyes = 0.07, sd = 1.14; xno = 0.27, sd = 1.27, F = 6.04, p = 0.015, η2 = 0.018, Cohen’s F = 0.14). Each of these effect sizes are small. 6.4.2.5 Primary Line of Business After recoding the open-ended responses for the primary line of business indicated by the respondent, the ANOVA to examine between industry differences of the differences in ratings for importance and proficiency of newly hired engineers resulted in one of the differences to be statistically significant (F = 2.16, p = 0.004, η2 = 0.11, Cohen’s F = 0.36). Tukey pairwise comparisons were conducted to identify for which industry type differences were statistically 116 significant for the ability to write effectively for five of the between group comparisons. These outcomes are presented in Table 5. The negative value for the mean of the differences of the ratings the respondents who identified as being in an organization whose primary line of business was healthcare indicates that these respondents on average rated the level of proficiency of their newly hired engineers higher than the importance of the ability to write effectively. The effect sizes for this statistically significant difference in ratings is medium to large. Table 6.5 Primary Line of Business Recode Between Variable Tukey Pairwise Results Business Recode (I) N (I) ?̅? (I) sd (I) Business Recode (J) N (J) ?̅? (J) sd (j) MD (I-J) SE Sig Defense 9 1.33 1.12 Healthcare 4 -1.0 2.0 2.33 0.64 .043 Energy 5 1.60 0.55 Healthcare 4 -1.0 2.0 2.60 0.71 .035 Engineering 23 1.22 1.13 Healthcare 4 -1.0 2.0 2.22 0.55 .029 Medical 16 1.31 0.87 Healthcare 4 -1.0 2.0 2.31 0.61 .023 R&D 4 1.75 1.26 Healthcare 4 -1.0 2.0 2.75 0.73 .030 Note: MD: mean difference; SE: standard error, Sig.: significance p= 6.4.2.6 Role of Respondent in Organization The open-ended response for respondents to enter their current title in their organization was recoded from over 300 entries to 6 titles and a not declared category. The not declared entries included missing data in the ratings of importance or proficiency and were all removed from the analysis through pairwise deletion of the entry during analysis. An ANOVA was conducted for the remaining 338 entries. Statistically significant differences were noted for four of the ratings’ differences calculated by subtracting the proficiency rating of newly hired engineers from the rating of importance. The four soft skills were ability to communicate effectively with diverse groups of people (F = 2.56, p = 0.027, η2 = 0.037, Cohen’s F = 0.19), critical thinking (ability to identify, construct, and evaluate arguments; detect inconsistencies and 117 errors in reasoning; solve problems systematically; reflect on underlying values and beliefs) (F = 2.35, p = 0.041, η2 = 0.034, Cohen’s F = 0.19), time-management (F = 2.46, p = 0.033, η2 = 0.036, Cohen’s F = 0.19), and self-motivation (F = 3.08, p = 0.010, η2 = 0.044, Cohen’s F = 0.21). The effect sizes for these differences are small to medium effects. The means, standard deviations, mean differences, standard errors, and significance levels are presented in Table 6.6. Table 6.6 Role of Respondent in Organization Recode Between Variable Tukey Pairwise Results Soft Skill Position Recode (I) N (I) ?̅? (I) sd (I) Position Recode (J) N (J) ?̅? (J) sd (j) MD (I-J) SE Sig Ability to communicate effectively with diverse groups of people Engineer 95 1.06 0.98 Recruiter 27 0.41 0.50 0.66 0.20 .012 Critical thinking (ability to identify, construct, and evaluate arguments; detect inconsistencies and errors in reasoning; solve problems systematically; reflect on underlying values and beliefs) Engineer 95 0.86 0.92 Recruiter 27 0.22 0.58 0.64 0.20 .018 Time-management Engineer 95 0.93 1.00 Recruiter 27 0.26 0.66 0.67 0.20 .014 Manager 93 0.91 0.89 Recruiter 27 0.26 0.66 0.65 0.20 .018 Self-motivation Director 70 0.74 0.81 Recruiter 27 0.04 0.59 0.71 0.19 .004 Manager 93 0.61 0.88 Recruiter 27 0.04 0.59 0.58 0.19 .025 Note: MD: mean difference; SE: standard error, Sig.: significance p= 6.4.2.7 Supervision Role by Respondents in Organization Respondents indicated in the profile questions if they had direct supervision requirements for newly hired engineers. Analysis of this response on the differences of the ratings indicated that 11 of the 26 soft skills had statistically significant differences when comparing those who had direct supervision of newly hired engineers (N = 180) and those who did not (N = 158). The differences were found for ability to communicate effectively with diverse groups of people (xyes = 1.01, sd = 0.96; xno = 0.78, sd = 0.84, F = 5.56, p = 0.019, η2 = 0.016, Cohen’s F = 118 0.13), ability to deliver effective presentations (xyes = 0.64, sd = 1.08; xno = 0.34, sd = 1.06, F = 6.48, p = 0.011, η2 = 0.019, Cohen’s F = 0.14), ability to write effectively (xyes = 0.93, sd = 1.00; xno = 0.55, sd = 0.97, F = 6.86, p = 0.009 η2 = 0.020, Cohen’s F = 0.14), ability to understand, articulate, and solve complex problems and make sen- sible decisions based on available information (xyes = 0.79, sd = 1.01; xno = 0.42, sd = 0.80, F = 13.85, p < 0.001, η2 = 0.040, Cohen’s F = 0.20), critical thinking (xyes = 0.83, sd = 1.01; xno = 0.56, sd = 0.79 F = 7.05 p = 0.008, η2 = 0.021, Cohen’s F = 0.15), self-efficacy: belief in one’s capabilities to achieve a goal or outcome (xyes = 0.49, sd = 1.05; xno = 0.21, sd = 0.96, F = 6.68, p = 0.010, η2 = 0.019, Cohen’s F = 0.14), staying/ being organized (xyes = 0.65, sd = 1.01; xno = 0.41, sd = 0.84, F = 5.75, p = 0.017, η2 = 0.017, Cohen’s F = 0.13), time-management (xyes = 0.96, sd = 0.94; xno = 0.66, sd = 0.92, F = 8.94, p = 0.003, η2 = 0.026, Cohen’s F = 0.16), self-motivation— (xyes = 0.68, sd = 0.95; xno = 0.40, sd = 0.72, F = 9.05, p = 0.003, η2 = 0.026, Cohen’s F = 0.16), responsibility—(xyes = 0.86, sd = 0.93; xno = 0.42, sd = 0.76, F = 4.03, p = 0.045, η2 = 0.012, Cohen’s F = 0.11), and ability to handle multi- ple priorities (xyes = 0.79, sd = 1.04; xno = 0.49, sd = 0.87, F = 8.31, p = 0.004, η2 = 0.024, Cohen’s F = 0.16). The effect sizes for each of these differences are small to medium effects. 6.4.3 Results of between Organization and Respondent Characteristics Analysis of Variance of Importance and Proficiency Ratings The ratings were further analyzed to determine if there were differences in ratings of importance and proficiency related to the profiles of the organization and the respondents. The analysis was motivated by several of the analyses of the differences in the ratings such as the role of the respondent where the respondents identified as recruiters has ratings that were closer to 119 each other than three of the other coded roles in the organization. The differences noted in this section for the level of importance will reinforce the topics that should be included within the engineering curriculum as needed for preparation for specific industries. The differences identified for proficiency can be used to inform where engineer programs would consider additional opportunities to practice the soft skills reported to be areas where prior newly hired engineers were not as proficient as others hired in different categories of organizations. 6.4.3.1 Results of Organizations’ Size Analysis of Variance Respondents indicated the size of their organization as either less than 100, 100 to 500, or more than 500 employees. Between group comparisons were completed for the ratings of importance and the ratings of proficiency of newly hired engineers for the organization size. Tukey pairwise comparisons were determined for any statistically significant between group differences. The analysis of variance to examine the between group differences for importance rat- ings noted three soft skills with statistically different differences: the ability to deliver effective presentations (x<100 = 2.71, sd = 1.00; x100 500 = 3.06, sd = 1.02, x>500 = 3.25, sd = 0.87, F = 10.16, p < 0.001, η2 = 0.048, Cohen’s F = 0.22) ability to work in teams (x<100 = 3.74, sd = 0.66; x100 500 = 3.88, sd = 0.39, x>500 = 3.90, sd = 0.34, F = 4.21, p = 0.013, η2 = 0.021, Cohen’s F = 0.15), and leadership (x<100 = 2.51, sd = 1.00; x100 500 = 2.81, sd = 1.08, x>500 = 2.85, sd = 0.95, F = 4.42, p = 0.013, η2 = 0.021, Cohen’s F = 0.15). Tukey pairwise com- parisons noted that for ratings of the importance of ability to deliver effective presentations, organizations with 100–500 employees were rated higher than organizations with less than 100 employees (mean difference = 0.34, std error = 0.14, p = 0.044) and organizations with more 120 than 500 employees were rated higher than organizations with less than 100 employees (mean difference = 0.53, std error = 0.12, p < 0.001). Tukey pairwise comparisons noted that for ratings of the importance of ability to work in teams, organizations with more than 500 employees were rated higher than organizations with less than 100 employees (mean difference = 0.16, std error = 0.06, p = 0.009). Tukey pairwise comparisons noted that for ratings of the importance of leadership, organizations with more than 500 employees were rated higher than organizations with less than 100 employees (mean difference = 0.33, std error = 0.13, p = 0.002). The effect sizes for each of these differences are small to medium effects. The analysis of variance to explore the responses for differences in the ratings for proficiency of newly hired engineers resulted in one statistically significant difference in proficiency ratings by respondents, leadership (x<100 = 2.11, sd = 0.90; x100 500 = 2.27, sd = 1.02, x>500 = 2.48, sd = 0.95, F = 4.23, p = 0.015, η2 = 0.025, Cohen’s F = 0.16), Tukey pairwise comparisons noted that for ratings of the proficiency of leadership by newly hired engineers, organizations with more than 500 employees were rated higher than organizations with less than 100 employees (mean difference = 0.37, std error = 0.13, p = 0.015). The effect size for this difference of proficiency rating is a small to medium effect. 6.4.3.2 Results of Organizations’ Sector Analysis of Variance Respondents identified their organization as being categorized as public sector, private sector, or other. Statistically significant differences in the importance ratings between these three groups were found for four of the between group comparisons. The between group comparisons for proficiency noted the presence of two significantly different comparisons. Difference in importance ratings were determined to have statistically significant differences between groups for ability to deliver effective presentations, ability to plan and think strategically, social 121 responsibility, and global and cultural awareness. Tukey pairwise compar- isons of the ratings of importance for ability to deliver effective presentations (xprivate = 2.97, sd = 1.01; xpublic = 3.45, sd = 0.70, xother = 3.29, sd = 0.83, F = 10.29, p < 0.001, η2 = 0.048, Cohen’s F = 0.23) indicated the public sector rated the importance higher than those who indicated they were in the private sector (mean difference = 0.48, std error = 0.11 p < 0.001). Tukey pairwise comparisons of the ratings for ability to plan and think strategically (xprivate = 3.27, sd = 0.88; xpublic = 3.50, sd = 0.77, xother = 3.43, sd = 0.65, F = 5.04, p = 0.007, η2 = 0.029, Cohen’s F = 0.17) indicated differences between the public sector and those who indicated private sector (mean difference = 0.23, std error = 0.10, p =0.047) such that the public sector ranked the importance higher than the private sec- tor. Tukey pairwise comparisons of the ratings for social responsibility (xprivate = 2.60, sd = 1.08; xpublic = 3.00, sd = 0.97, xother = 2.79, sd = 0.89, F = 5.04, p = 0.007, η2 = 0.029, Cohen’s F = 0.17) indicated the public sector rated the importance higher than the private sector (mean difference = 0.40, std error = 0.12 p = 0.003). Tukey pairwise comparisons of the importance ratings for global and cultural awareness (xprivate = 2.54, sd = 1.04; xpublic = 2.94, sd = 0.99, xother = 2.71, sd = 1.14, F = 5.55, p = 0.004, η2 = 0.027, Cohen’s F = 0.17) indicated the public sector rated the importance higher than the private sector (mean difference = 0.40, std error = 0.12, p = 0.003). The effect sizes for this difference between public sector organizations and other types of organizations is a small to medium effect. The between group comparisons for the proficiency of newly hired engineers indicated two statistically significant differences between the sector types, ability to deliver effective presentations and leadership. Tukey pairwise comparisons of the proficiency ratings for ability to 122 deliver effective presentations (xprivate = 2.53, sd = 0.96; xpublic = 2.88, sd = 9.97, xother = 2.86, sd = 0.86, F = 4.27, p = 0.015, η2 = 0.025, Cohen’s F = 0.16) in- dicated differences between the public sector and those who indicated private sector (mean difference = 0.35, std error = 0.26, p = 0.016) such that the public sector responses were higher than private sector responses. Tukey pairwise comparisons of the ratings for leader- ship (xprivate = 2.27, sd = 0.95; xpublic = 2.55, sd = 1.00, xother = 2.71, sd = 0.83, F = 3.66, p = 0.027, η2 = 0.021, Cohen’s F = 0.15) did not indicate differences that were statistically significant between any of the pairwise combinations of the three types of organizations at the specified threshold to control errors. At times a statistically significant difference does not result pairwise differences due to controls for family Type 1 errors or low power in the comparisons. The effect size for the differences between public sector organizations and private sector organizations is a small to medium effect. 6.4.3.3 Results of Organizations’ Locations Analysis of Variance Within the profiles of the organizations, the respondents indicated if the organizations were headquartered within the United States or other locations and if they had branches, offices, or plants in countries other than the United States. Of the 489 respondents, 438 were headquartered in the United States, 15 in Japan, 12 in German, 4 in Canada, and 4 in France; the frequency of the headquarters in other countries were either 1 or 2 per country indicated. Respondents indicated that 133 organizations had branches in other countries and 304 did not have branches outside of the United States. The analysis of variance outcomes for both the ratings of importance and for proficiency of newly hired engineers for the locations of headquarters revealed no statistically significant results for any of the comparisons between those organizations with headquarters within the United States and those headquartered within 123 another country. Similarly, no statistically significant differences were noted for the ratings of proficiency by the location of branches, offices, or plants for the organization. There were statistically significant results noted for the comparison of the ratings for importance by location of branches, offices, or plants for the organization. An analysis of variance was conducted to assess any differences for countries having branches outside the United States and those located only within the United States. The comparison was made for each of the ratings of importance for the performance of newly hired engineers. A statistically significant difference was determined for two ratings, the importance of the ability to deliver effective presentations and the importance of global and cultural awareness. Respondents in organizations with branches, offices, or plants outside the United States rated the importance of the ability for newly hired engineers to effectively present higher than the rating by respondents from organizations with operations only within the United States (x = 3.19, sd = 0.92; x = 2.87, sd = 1.01, F = 9.24, p = 0.003, η2 = 0.022, Cohen’s F = 0.15). Respondents in organizations with branches, offices, or plants outside the United States rated the importance of global and cultural awareness higher than those respondents from organizations that do not have facilities outside of the United States (x = 2.76, sd = 1.01; x = 2.35, sd = 1.09, F = 11.35, p = 0.001, η2 = 0.027, Cohen’s F = 0.17). All other ratings for importance were statistically equivalent for the two organization types, organizations with branches, offices, or plants outside the United States and those within operations only within the United States. The effect sizes for the two soft skills with differences are small to medium. 124 Table 6.7 Primary Line of Business Analysis of Variance results for Importance Ratings of Soft Skills Soft skill Partial Eta Sq Cohen’s F Position Recode (I) N (I) ?̅? (I) sd (I) Position Recode (J) N (J) ?̅? (J) sd (j) Mean Difference (I-J) Std Error Sig Ability to deliver effective presentations .132 0.39 Aerospace 19 3.42 0.77 Technology 70 2.57 1.02 0.85 0.24 .050 Defense 11 3.73 0.47 Technology 70 2.57 1.02 1.56 0.30 .018 Manufacturing 127 3.23 0.89 Technology 70 2.57 1.02 0.66 0.14 <.001 Medical 21 3.43 0.68 Technology 70 2.57 1.02 0.86 0.23 .028 Ability to write effectively .107 .35 Medical 21 3.86 0.36 Technology 70 3.19 0.98 0.67 0.18 .037 Ability to deal with uncertainty in relating to people and situations .076 .29 Engineering 29 2.97 1.09 Manufacturing 127 3.56 0.71 0.59 0.14 .013 Ability to work under pressure .095 .32 Aerospace 19 3.68 0.48 R&D 6 2.50 1.37 1.18 .032 .033 Civil Engineering 11 3.91 0.30 R&D 6 2.50 1.37 1.41 .34 .009 Consumer Products 29 3.72 0.53 R&D 6 2.50 1.37 1.22 .30 .011 Manufacturing 127 3.61 0.66 R&D 6 2.50 1.37 1.11 .28 .018 Semiconductors 13 3.85 0.38 R&D 6 2.50 1.37 1.35 .34 .012 Social responsibility .073 .28 Leadership .084 .30 Reliability .087 .31 Note: Partial Eta squared effects: small 0.01, medium 0.06, large 0.14; Cohen’s F effects: small 0.1, medium 0.25, large 0.4. R&D is Research and Development. MD: mean difference; SE: standard error, Sig.: significance p= 6.4.3.4 Results of Primary Line of Business Analysis of Variance Respondents were asked to describe the primary line of business for their organization. The open-ended responses were recoded into 20 industries. The industries coded are presented in Table 3. For those respondents who did not identify a primary industry, the response was recoded as not declared. Univariate analysis of variance with Tukey pairwise comparisons was conducted for the ratings of importance on each of the soft skills and the ratings of the perception of proficiency of the newly hired engineers in their organization. Partial eta squared values and 125 Cohen’s F values were calculated. Statistically significant differences were present for ratings of importance. No between group differences were statistically significant for the ratings of proficiency of newly hired engineers. Statistically significant differences between industry types were determined for seven of the ratings of importance. The Tukey pairwise comparisons identified between group differences in ratings for four of the measures of differences of means that were statistically significant ratings of importance. The statistical values, partial eta square values and Cohen’s F effect sizes, for the soft skills found to have statistically significant differences for their ratings of importance between industries are presented in Table 7. In addition, included in Table 7 are the between industry differences identified in the Tukey pairwise comparisons. The effect sizes for the differences between groups for importance are medium to large effects. 6.4.3.5 Results of Respondents Role in Organizations Analysis of Variance The respondents were asked to enter their current title within their organization. The more than 300 responses were coded to 6 position titles: administrator, director, engineer, human resources (HR), manager, and recruiter. Those with missing information were coded as not declared. Between group comparisons were made using analysis of variance for each of the ratings of importance and for each of the ratings of proficiency of the newly hired engineers. Statistically significant differences were found for two of the ratings for importance and for eleven of the ratings for proficiency. Pairwise comparisons of those ratings indicated pairwise differences for only one of the statistically significant between group comparisons for importance and for all of the comparisons for proficiency that were found to have statistically significant between group differences. The outcomes are presented within Table 8. The effect sizes for the differences between groups for importance are small to medium effects. 126 Table 6.8 Respondent’s Role in Organization Analysis of Variance results for Importance and Proficiency Ratings of Soft Skills Soft skill Partial Eta Sq Cohen’s F Position Recode (I) N (I) ?̅? (I) sd (I) Position Recode (J) N (J) ?̅? (J) sd (j) Mean Difference (I-J) Std Error Sig Importance of ability to plan and think strategically .038 0.20 Recruiter Director 0.54 0.17 .020 Proficiency of ability to communicate effectively with diverse groups of people .035 0.19 Recruiter 27 3.33 0.62 Engineer 95 2.75 0.89 0.59 0.18 .014 Proficiency of ability to work under pressure .037 0.20 Recruiter 27 3.56 0.64 Engineer 95 2.88 0.99 0.67 0.19 .008 Proficiency of ability to plan and think strategically .037 0.20 Recruiter 27 3.30 0.61 Director 70 2.53 0.99 0.77 0.22 .008 Recruiter 27 3.30 0.61 Engineer 95 2.68 1.03 0.61 0.21 .049 Recruiter 27 3.30 0.61 Manager 93 2.66 0.95 0.64 0.21 .034 Proficiency of ability to understand, articulate, and solve complex problems and make sensible decisions based on available information .039 0.20 Recruiter 27 3.48 0.51 Engineer 95 2.88 1.00 0.61 0.19 .019 Proficiency of Critical thinking (ability to identify, construct, and evaluate arguments; detect inconsistencies and errors in reasoning; solve problems systematically; reflect on underlying values and beliefs) 0.047 0.22 Recruiter 27 3.52 0.58 Director 70 2.84 0.93 0.68 0.20 .008 Recruiter 27 3.52 0.58 Engineer 95 2.89 0.90 0.62 0.19 .013 Proficiency of Staying/ being organized 0.49 0.23 HR 42 3.50 0.77 Director 70 3.01 0.83 0.49 0.16 .035 HR 42 3.50 0.77 Engineer 95 2.94 0.91 0.56 0.15 .004 Proficiency of Time-management 0.047 0.22 Recruiter 27 3.44 0.58 Engineer 95 2.76 0.93 0.69 0.19 .005 Proficiency of Reliability 0.45 0.22 Recruiter 27 3.78 0.42 Director 70 3.16 0.81 0.62 0.18 .011 Recruiter 27 3.78 0.42 Engineer 95 3.21 0.87 0.57 0.18 .019 Recruiter 27 3.78 0.42 Manager 93 3.26 0.91 0.52 0.18 .044 Proficiency of Curiosity 0.57 0.25 Recruiter 27 3.81 0.40 Administrator 11 2.91 1.22 0.91 0.30 .031 Recruiter 27 3.81 0.40 Director 70 3.20 0.91 0.61 0.19 .016 Recruiter 27 3.81 0.40 Engineer 95 3.21 0.87 0.60 0.18 .013 Recruiter 27 3.81 0.40 Manager 93 3.23 0.82 0.59 0.18 .017 Proficiency of willingness to take initiative 0.37 0.20 Recruiter 27 3.59 0.50 Engineer 95 2.91 0.98 0.69 0.20 .008 Proficiency of ability to handle multiple priorities 0.041 0.21 Recruiter 27 3.48 0.64 Director 70 2.84 1.04 0.64 0.21 .036 Note: Partial Eta squared effects: small 0.01, medium 0.06, large 0.14; Cohen’s F effects: small 0.1, medium 0.25, large 0.4. R&D is Research and Development. MD: mean difference; SE: standard error, Sig.: significance p= 127 6.4.3.6 Results of Supervisory Roles in Organizations Analysis of Variance Respondents were asked if they supervised entry-level engineers directly. Once missing data were accounted for through pairwise deletion, the number of respondents indicating yes were 180 and 158 respondents indicated no. Analysis of variance to examine the between group differences resulted in five of the importance ratings and eighteen of the proficiency ratings were statistically significant. Partial eta square effect sizes and Cohen’s F effect sizes were calculated for each of the between groups analyses. The outcomes are presented in Table 9. The effect sizes for the differences between groups with statistically significant differences are small to medium effects. An outcome of the between group comparison is that for all of the ratings of soft skills that were statistically significant, both for importance and for proficiency, the rating by the respondent with direct supervision responsibility that rated the newly hired engineers was lower than the rating by the respondent without direct supervision requirements. 128 Table 6.9 Respondent’s Supervisory Role of Entry Level Engineers Analysis of Variance results for Importance and Proficiency Ratings of Soft Skills Yes (N=180) No (N=158) Rating of Soft Skill ?̅? (Yes) sd (Yes) ?̅? (No) sd (No) F Sig Partial Eta Sq Cohen’s F Importance of ability to work under pressure 3.44 0.77 3.66 0.60 10.15 .002 0.025 0.16 Importance of ability to plan and think strategically 3.21 0.89 3.45 0.80 8.02 .005 0.019 0.14 Importance of Flexibility and adaptability 3.69 0.59 3.82 0.43 5.78 .017 0.014 0.11 Importance of Self-motivation 3.80 0.47 3.91 0.29 7.98 .005 0.019 0.14 Importance of ability to handle multiple priorities 3.59 0.72 3.74 0.53 6.14 .014 0.015 0.12 Proficiency of ability to communicate effectively with diverse groups of people 2.78 0.88 3.01 0.74 6.23 .013 0.018 0.14 Proficiency of Ability to deliver effective presentations 2.51 1.01 2.75 0.91 5.30 .022 0.016 0.13 Proficiency of ability to deal with uncertainty in relating to people and situations 2.61 0.90 2.90 0.89 9.10 .003 0.026 0.16 Proficiency of ability to work under pressure 2.92 0.91 3.18 0.86 7.59 .006 0.022 0.15 Proficiency of ability to plan and think strategically 2.58 0.98 2.84 0.98 5.85 .016 0017 0.13 Proficiency of ability to understand, articulate, and solve complex problems and make sensible decisions based on available information 2.84 0.95 3.26 0.74 19.64 >.001 0.055 0.24 Proficiency of Critical thinking (ability to identify, construct, and evaluate arguments; detect inconsistencies and errors in reasoning; solve problems systematically; reflect on underlying values and beliefs) 2.92 0.90 3.26 0.74 7.19 .008 0.021 0.15 Proficiency of Creativity: Coming up with ‘out-of-the-box’ ideas and solutions 2.76 1.01 2.99 0.87 5.04 .025 0.015 0.12 Proficiency of Focused: the ability to stay focused on a task 2.95 0.92 3.19 0.83 6.28 .013 0.018 0.14 Proficiency of Self-efficacy: belief in one’s capabilities to achieve a goal or outcome 3.07 0.89 3.37 0.81 10.38 .001 0.030 0.18 Proficiency of Staying/ being organized 2.98 0.89 3.28 0.76 10.49 .001 .030 0.18 Proficiency of Time-management 2.78 0.90 3.14 0.85 14.315 <.001 0.041 0.21 Proficiency of Reliability 3.27 0.85 3.45 0.79 4.17 .042 0.012 0.11 Proficiency of Self-motivation 3.13 0.90 3.50 0.69 17.84 <.001 0.050 0.23 Proficiency of Responsibility 3.21 0.86 3.46 0.75 8.02 .005 0.023 0.15 Proficiency of Curiosity 3.19 0.90 3.42 0.78 6.17 .013 0.018 0.14 Proficiency of willingness to take initiative 2.99 0.92 3.21 0.90 4.62 .032 0.014 0.12 Proficiency of handle multiple priorities 2.82 1.02 3.23 0.84 16.22 <.001 0.046 0.22 129 6.4.3.7 Review of Analysis of Variance Outcomes Because the survey was distributed prior to the pandemic, the outcomes of the ratings of the between group differences by each of the profile variables were shared during summer and early fall 2021 with engineers, managers, and educators through a snow- ball technique to identify possible reviewers who would offer feedback on the results. These were unstructured interviews with a goal to capture reactions to the between group differences. An engineer within an organization that primarily works with defense contracts commented, “Those differences where aerospace, defense, and manufacturing are rated higher than technology makes sense. We require all of our aerospace people and those working on the defense and manufacturing contracts to talk directly with the customer to find out what the customer needs and to report on the project. The tech team working on programming and coding pretty much keep to their team and the scrum master talks with the client” [Engineer 1]. This comment supported the outcomes presented in Table 6.7, the importance ratings for the soft skill, ability to deliver effective presentations. An educator in a four-year higher education role and familiar with interactions of recruiters with students reviewed the results presented in Table 6.8. The educator commented, “The recruiters I have worked with over the years work diligently to review candidates for internships and positions. They interview faculty and have lunch and dinner meetings with the students to determine which students would fit their organization. Several have told me that they can teach the engineering, but a person must come with the ability to think strategically, work under pressure, be reliable, have good time management, and on. The personal skills and soft skills to be able to work with others are skills they need to demonstrate the first day the start to work” {Educator 1]. The conversation with the educator reinforced that there would be an 130 expectation that the recruiter would rate a newly hired engineer higher than others in the organization because the recruiter would have spent time getting to know the new hire during the recruiting phase. An educator with past work experience with small business and with firms that have worked with plants and offices in other countries reviewed the results of the location analysis, which are presented in Section 3.3.3. Although the effect sizes were noted to be small to medium, the educator’s comments provided additional insight into the expectations. “Cultural awareness is so important that sometimes people forget. Some people want rewards and people to notice what they have completed and have their picture on the board as employee of the month. Others would consider that type of recognition as something very bad and think it could actually destroy the functionality of the team if one person is recognized. New hire engineers need to have global and cultural awareness as they take part in global teams and global team meetings” [Educator 2]. Global and cultural awareness were rated higher by respondents from organizations that have branches, offices, or plants outside of the United States. The experiences and comments made by Educator 2 supported the necessity of engineers preparing to work in an organization with a global reach should include additional study to learn more about the culture and traditions of other locations where the organization operates its business. During a meeting with a global talent acquisition director, the discussion moved from soft skills requirements for potential employees to the outcomes of the paired t-test results and the analysis to assess the between group differences identified in the analysis of variance of the calculated differences. The director commented, “My company has an expectation that employees will be able to communicate effectively with the members of their team, their clients within the organization and those outside of the organization” [Manager 1]. The director 131 described situations where the soft skills that were rated the highest for importance were essential to the success of the employee’s onboarding in the company. The comments included skills such as communication with diverse groups, reliability, time management, and ability to focus on a task. These were described as aspects of employees that were needed to be applied daily. With the pandemic, the team is now all remote and interacts with each other on teams throughout the day. The comments reinforced how necessary it is to further develop these skills after joining a company. Statements supported the finding that new employees do not know the routines and patterns for communication when they begin; however, as they learn about the work they are to do and how to contribute to the bottom line of the organization, the need to apply the soft skills to their work and their relationships in their teams. These interviews reinforced that the soft skills identified prior to the pandemic were still relevant even though some work has shifted from offices to remote locations. The engineer, educators, and the manager interviewed have been working from their organization offices and with their teams in face-to-face settings. 6.4.4 Analysis of Participants’ Open-Ended Comments at the End of the Survey The survey also contained space for participants to articulate their thought on areas related to soft skills for entry level engineers in two sections of the survey. The purpose was to allow participants to elaborate on their thoughts about the importance of soft skills and to create an opportunity for them to specify reasons for their responses or draw attention to areas not covered in the survey [O’Cathain & Thomas, 2004]. The first space was provided at the end of the list of the 26 soft skills that participants were required to rate to capture soft skills that the survey did not assess but employers considered important. The second space was provided at the end of the survey to gather the general thoughts of employers about the importance of soft skills 132 for entry-level engineers in their organizations or line of work. A total of 136 participants added their comments in the first section and 79 in the second. The number of responses (215) highlighted the intent and the seriousness of purpose of the participants and prompted us to consider and analyze their thoughts on the importance of soft skills for entry-level engineers [World Economic Forum, 2021]. In the next section, we present an analysis of the comments of the respondents with some actual quotes from participants (P). 6.4.4.1 Soft Skills Are Often the Final Deciding Factor Most employers who responded to the open-ended questions emphasized the im- portance of soft skills for engineering graduates: “Interesting you are focusing on soft skills. When I look at a college hire, it is the soft skills that often are more important than technical knowledge” (P18). Most respondents mentioned that engineers with a willingness to learn can acquire the technical knowledge of skills on the job, while soft skills were the key discriminators during the hiring process: “General skills sets, GPA, and projects/extra-curricular activities that are related to the job weed out 90% of the candi- dates. The final choice is all about the attitude” (P29). Explaining why soft skills become the deciding factor, the employers argued that, if the engineering graduates were from reputed programs, their technical skills were most often satisfactory. Moreover, “hard skills are typically solid or buildable from entry level engineers/interns from decent programs” (P124), therefore, what differentiates the one graduate who is selected from the others who were not despite more or less equal technical skills were the candidates’ soft skills. “Your resume gets you in the door and tells me you have the intellect to learn what I have to teach you . . . What I am looking to confirm in new hires is work ethic, commitment and flexibility” (P256). Employers found soft skills to be important for engineers to obtain a job or become hired, but they also found soft skills to be more important for them to 133 grow in their careers: “It is the proficiency in soft skills that allow engineers to become successful technical, programmatic and functional leaders in organizations” (P76). 6.4.4.2 What Do Employers Look for Specifically during the Hiring Process? The consensus was when reviewing short-listed resumes, employers were not swayed by GPA or technical prowess, but instead, they: ... look for experience/activities outside degree requirements and primary disciplines, and employment concurrent with scholastics. This shows a well-rounded person able to work their brain in different ways and manage their own time and responsibilities (P94). Moreover, employers admitted that “A successful new hire will not be the most technically proficient, instead it will be the one best able to learn and communicate” (P394). Others identified communication skills, critical thinking skills, cultural fit (initiative, curiosity, interpersonal skills), enthusiasm/passion, and related extracurricular interests. Even though some employers said they were happy with young engineering graduates from good programs, many complained that they generally lacked basic knowledge of workplace norms such as dress, hours of work, work ethics, and basic acceptable behaviors in a work environment: “The primary problem with co-ops and recent grads is their complete lack of understanding of basic norms and expected behaviors in the “real world” (P356). Others echoed similar observations: “they don’t see why it is necessary to be at your desk working at the start of the day and are out the door like a shot at quitting time or even a little before that” (P404). Employers also said, they are forced to: Spend a lot of time talking about simple things such as telling your supervi- sor/manager if you will be out or late, communicating when you are done with an assignment—or if 134 you need help. Essentially, we have to teach entry level folks to talk and communicate in most aspects of simply holding a job (P148). Clarifying that not all young engineers need to be schooled on basic work ethics, one participant specifically said: This is not universally true of all millennials, but I can tell you nobody ever had to tell me not to do the following, all of which I’ve seen entry-level students do: 1. Show up to a job interview in a shirt and tie—with the shirt untucked! 2. In my second week on the job, ask for Friday off so I could go to a soccer tournament. 3. Fall asleep at my desk, even after being spoken to about it. 4. Spend 75% of my time looking straight down at my phone, even though my work is done on the monitors in front of me (P412). Some of the same concerns about not being actively engaged at work were expressed by other participants who mentioned that engineering interns and graduates were “really . . . not mentally engaged when he came to work and there was a sense of entitlement with him” (P36). The employers also identified soft skills they thought were important for entry-level engineers in addition to the 26 that were identified in the survey and also emphasized the soft skills they thought were critical in engineering workplaces in current times. Engineers are no longer “just” engineers. They work in many cross-functional teams; are held accountable for project plans and schedules; communicating with diverse teams; leading teams; and being able to communicate effectively, both in writing and verbally (P65). The soft skills the employers highlighted could be categorized as: (a) communication skills; (b) interpersonal skills; and (c) personality characteristics. 135 6.4.4.3 Communication Skill Most participants identified that engineering graduates more often lacked the ability to communicate or have an interaction with human beings and that they chose to commu- nicate virtually rather than in person, “which creates a challenge for them when they are engaged in an active (real-time) debate with another human being, especially a boomer or x-er” (P9). In addition to causing inter-generational conflicts, the choice of medium of communication was identified as a problem at other levels too: Just because you ‘drop an email’ does not mean that the person you are exchang- ing information with is going to respond. And, for any real technical debate, it will be more than 140 characters. One of the comments I make more often than I would like to is, “go see him/her” (P182). The participants also identified what aspects of communication were critical to entry-level engineers and why. One aspect mentioned by many participants was listening skills. Associated with listening, participants stressed the significance of listening with empathy, being able to take feedback, and following instructions: I think the ability to listen to users, empathize with them and accept their criticism to create a better product is a very important skill to have (P294). Too often I see SW [software] engineers dismiss valuable user feedback because they don’t take the time to understand the user’s reasoning, assume the user knows less than the engineer, or because they cannot accept criticism (P52). It was not surprising that the participants expected new engineers to articulate clearly, and speak up when needed, ask for help, and ask the right questions. More importantly, the employers emphasized that: 136 The biggest challenge for young engineers is communicating effectively both orally and in writing to people (nontechnical and customers) that are not within their engineering team and/or do not have their level of technical savvy . . . whether they are explaining technology and capability and/or gathering requirements (P172). In addition, choice of medium to communicate also came up in many responses. The employers felt that new engineers preferred to text rather than talk in person or communicate through “effective and polite emails” (P91). 6.4.4.4 Interpersonal Skills Employers consider interpersonal skills very important for engineers. The employ- ers’ comments indicate that even though engineers consider themselves as working with machines, systems, and technology, ultimately, they are working with people and for people: “It’s about solving problems for people; not about machines—you can have a perfect design but if you do not get peoples’ buy in it will not work” (P107). Therefore, interpersonal skills such as respecting older people, being socially aware, and demonstrating emotional intelligence in their interactions are seen to be critical in engineering workplaces. Employers identify the ability to build and maintain professional relationships with colleagues, customers, and clients as being the key for survival and growth even in technical roles. However, there seems to be mixed reactions to the need for leadership skills. Some employers consider leadership skills not essential for entry-level engineers: “I think leadership is a meaningless red herring. Leadership requires many things that come with experience. In addition to teaching people to “lead”, we need to teach them to be humble and follow” (P410). 137 6.4.4.5 Personality Characteristics Among the list of soft skills that employers chose to write down, there were many personality characteristics. These included honesty, humility, commitment to tasks, persistence, confidence, not being stubborn, being an active learner, drive, and quality consciousness. In addition, employers also underscored the need to demonstrate: “engagement and passion to do a good/complete job vs. checking the box as quick as possible” (P21), and creativity in resolving problems, ability to think through complex problems. They said they preferred even-tempered self-starters who show potential to “work without resources” (P3); “dealing with hostile coworkers” (P190); and are able to “pick up work where others left off and easily hand-off for others to pick up” (P312). Additionally, the employers expected new engineers to have the skill of “outcome thinking” or the ability to foresee the response or consequence of their actions. This was one of the main reasons, employers said they preferred slightly mature older graduates: They need to be reliable, positive, and even keeled. We often prefer more ‘mature’ new hires who took 5–10 years off after college to pursue other interests. They are typically more even keeled than their freshly graduated counterparts (P244). 6.4.4.6 Summary of Participants’ Comments Employers clearly described soft skills as the determining factor in the hiring and promotion process. Even though most employers appeared satisfied with the technical skills of engineering graduates, most of them were concerned that they lacked basic knowledge of work ethics and work place norms. Ability to listen with empathy, speak with clarity and politeness, and write clearly and effectively seemed to be very important for employers. While a few employers believed that soft skills cannot be taught and one either has them or not, most others suggested that colleges create opportunities for engineering students to develop soft skills, to be 138 involved in extra-curricular team activities, and to add a class that gave them a glimpse of the real world of work. 6.5 Discussion The purpose for this study was to address the gap between what is stated in the literature as expected of more senior members of an organization and what soft skills employers perceive as being important for entry-level engineers to possess and demonstrate. The 26 soft skills rated for importance and proficiency provided a look into perceptions of engineering firms outcomes of recent graduate hires. The open-ended questions illuminated more brightly the need to provide opportunities in courses and within school activities to further develop communication skills, interpersonal skills, and personality characteristics. The soft skills that employers expect entry level engineers to demonstrate included all 26 of the soft skills on the list; all had a score of 2.65 or higher, out of a scale of 0 to 4, indicating that they are important skills. Most important was Reliability, which was rated as 3.93 out of a possible 4.0 by the respondents to the survey. The open-ended comments reinforced this need for reinforcing reliability. Being considered reliable and having reliability are good social skills; social skills are necessary for successful social interactions [Deming, 2017]. Other top important soft skills to be maintained and improved in engineering education are team work, demonstration of responsibility, self-motivation, and a positive attitude. These can be included within engineering education through a variety of interactive activities such as group projects, independent projects, and activities that require personal accountability. The perception of employers regarding the general level of proficiency of entry-level engineers when it comes to soft skills is that the entry level employees are moderately proficient on all of the skills. Only positive attitude was rated above 3.5 (3.55 out of 4.0). The others were 139 rated between 2.35 and 3.38 on the level of proficiency. These moderate levels reinforce that engineering education programs are doing good work in that none of the average ratings were below two. More can be conducted to improve the proficiency of the students. Additional opportunities to practice leading others, making presentations, planning and thinking strategically, writing reports and other communications, and dealing with uncertainty would address those soft skills rated as the least levels of proficiency and in need of improvement. Those soft skills with the greatest differences between expectations and perceptions of proficiency across the set of soft skills could be grouped into the same categories as the open-ended comments: communication skills, personality traits, and interpersonal skills. The ability to communicate effectively with diverse groups of people and the ability to communicate across age groups are necessary in the globalization of organizations and the age ranges of employees in departments and work teams. Engineering education programs would have the greatest effectiveness for closing the gap between importance and proficiency by focusing on these soft skills. Time management is something that many need to improve; however, new employees without an understanding of the expectations of the work environment would not have a good foundation for time management. It seems that good time management skills balancing work and study while in college might not be enough to develop this skill in the workplace. The open-ended responses alluded to a solution, better preparation in the engineering education preparation of what a work day and work expectations would be. Knowing how to dress and be on time are also part of the need for work expectation awareness. Between group differences were assessed using analysis of variance and the profile characteristics of organizations and respondents to determine if there were differences by soft skill and its level of importance or the level of proficiency of the newly hired engineers in the 140 organizations. Of the 26 soft skills included in the survey, 25 of the soft skills resulted in a statistically significant between group difference for at least one of the profile characteristics. Positive attitude had an average rating of importance of 3.82 out of 4 and an average proficiency rating of 3.55. In the ranking of proficiency, positive attitude was the highest ranked skill for the entry-level engineers whose proficiency was being considered in the study by the respondents. This list describes the statistically significant between group comparisons found within the analysis of variance to determine the effects of the organization and respondent profile characteristics. Size, global location, public or private, primary business line, role within the organization, and supervisory requirements had differential effects for the soft skills. Engineering education programs can plan interventions within courses or offer opportunities to practice a soft skill in order to better prepare their graduates for work as an engineer. For example, knowing a large organization has a higher rated level of importance for being able to communicate across age groups, an engineering education program could have students present their senior design projects to a local community center where members of all ages from the community would be present to interact with the students. Another example, engineering education programs can review recommendations for program activities for other engineering accrediting bodies such as the European Commission (ESCO), the European Centre for the Development of Vocational Training (Cedefop), or the Council of European Professional Informatics Societies (CEPIS). Evaluations of program content within these organizations has been reported in series of future program requirements [Akyazi et al., 2020a; Akyazi et al., 2020b; Arcelay et al., 2021; Maisiri & Van Dyke, 2021] that could serve as checklists for programs or for students. 141 Descriptions of where the differences occurred in the comparisons are provided to help engineering educational program consider modifications or enhancements. 1. Ability to communicate effectively with diverse groups of people a. The ratings by the recruiters for the level of importance and the level of proficiency of newly hired engineers were much closer to each other than were the ratings reported by respondents whose roles were coded as engineers, managers, or directors. b. Although the effect sizes were small, respondents with direct supervision of newly hired engineers indicated greater differences between their ratings for importance and the level of proficiency exhibited by the newly hired engineer than those respondents without direct supervision. 2. Ability to communicate across age groups a. Larger companies have a greater requirement for communication across age groups; >500 had higher ratings than 100–500 firms and differences indicated a small to medium effect size. b. Organizations with branches, offices, or plants outside the United States report greater differences between importance and proficiency indicating a need for preparation prior to joining global firms. 3. Ability to deliver effective presentations a. Larger companies have a greater expectation for presentation ability. b. Organizations with branches, offices, or plants outside the United States report greater differences between importance and proficiency. 142 c. Although the effect sizes were small, respondents with direct supervision of newly hired engineers indicated greater differences between their ratings for importance and the level of proficiency exhibited by the newly hired engineer than those respondents without direct supervision. d. Public sector organizations report higher importance and higher proficiency ratings than private sector organizations. The effect size for the differences between public sector organizations and private sector organizations is a small to medium effect. This could indicate more opportunity to practice in public sector firms or more opportunity to be observed in private sector firms. e. Organizations with facilities outside the United States reported more impor- tance for newly hired engineers to effectively present than in organizations with operations only within the United States. f. The type of firm differs in requirements. The level of importance is rated higher for aerospace, defense, manufacturing, and medical compared to technology primary line of business. 4. Ability to write effectively a. Medium to large effect size for differences between industry recode of the pri- mary line of business. Respondents who identified as healthcare had reported the newly hired engineers’ proficiency exceeded the respondents’ ratings for the level of importance for writing effectively. Respondents from organizations whose primary line of business was defense, energy, engineering, medical, or research and development (R&D) coded the level of importance higher than the proficiency of the newly hired engineers such that 143 the between group com- parison of each of these lines of business were determined to have statistically significant differences from those respondents in healthcare. b. Although the effect size is small, those with direct supervision of newly hired engineers responded with greater differences between their ratings for importance than the level of proficiency exhibited by the newly hired engineer. 5. Ability to work in teams a. Importance of ability to work in teams, organizations with more than 500 employees were rated higher than organizations with less than 100 employees. b. Importance rating higher for engineering compared to manufacturing primary line of business. 6. Ability to work under pressure a. Importance ratings were higher for aerospace, civil engineering, consumer products, manufacturing, and semiconductors compared to R&D primary line of business. 7. Ability to plan and think strategically a. The public sector ranked the importance higher than the private sector. 8. Ability to understand, articulate, and solve complex problems and make sensible decisions based on available information a. Although the effect size is small, those with direct supervision of newly hired engineers responded with greater differences between their ratings for 144 importance than the level of proficiency exhibited by the newly hired engineer. 9. Critical thinking (ability to identify, construct, and evaluate arguments; detect inconsistencies and errors in reasoning; solve problems systematically; reflect on underlying values and beliefs) a. The ratings by the recruiters for the level of importance and the level of proficiency of newly hired engineers were much closer to each other than were the ratings reported by respondents whose roles were coded as engineers, managers, or directors. b. Although the effect size is small, those with direct supervision of newly hired engineers responded with greater differences between their ratings for importance than the level of proficiency exhibited by the newly hired engineer. 10. Creativity: coming up with ‘out-of-the-box’ ideas and solutions a. Ratings are lower by those who supervise than by those who do not supervise entry level engineers. 11. Social responsibility a. The public sector rated the importance higher than the private sector. b. Statistical difference for importance not evident in pairwise comparison when consider primary line of business. 12. Global and cultural awareness a. Small effect size for differences for where have branches, offices, or plants outside United States, no outside branches had greater difference between 145 importance and proficiency than the differences in ratings for those with branches, offices, or plants outside of the United States. b. Small to medium effect for the rating of importance for organizations with branches, offices, or plants outside of the United States. c. The public sector rated the importance higher than the private sector. 13. Leadership a. Organizations with more than 500 employees were rated importance and proficiency higher than organizations with less than 100 employees. b. Statistical difference for importance not evident in pairwise comparison when consider primary line of business. 14. Focused: the ability to stay focused on a task a. Ratings are lower by those who supervise than by those who do not supervise entry level engineers. 15. Self-efficacy: belief in one’s capabilities to achieve a goal or outcome a. Although the effect size is small, those with direct supervision of newly hired engineers responded with greater differences between their ratings for importance than the level of proficiency exhibited by the newly hired engineer. 16. Staying/ being organized a. Although the effect size is small, those with direct supervision of newly hired engineers responded with greater differences between their ratings for importance than the level of proficiency exhibited by the newly hired engineer. 146 17. Time-management a. The ratings by the recruiters for the level of importance and the level of proficiency of newly hired engineers were much closer to each other than were the ratings reported by respondents whose roles were coded as engineers, managers, or directors. b. Although the effect size is small, those with direct supervision of newly hired engineers responded with greater differences between their ratings for importance than the level of proficiency exhibited by the newly hired engineer. 18. Reliability a. Statistical difference for importance not evident in pairwise comparison when consider primary line of business. 19. Flexibility and adaptability a. Ratings are lower by those who supervise than by those who do not supervise entry level engineers. 20. Self-motivation a. The ratings by the recruiters for the level of importance and the level of proficiency of newly hired engineers were much closer to each other than were the ratings reported by respondents whose roles were coded as engineers, managers, or directors. b. Although the effect size is small, those with direct supervision of newly hired engineers responded with greater differences between their ratings for 147 importance than the level of proficiency exhibited by the newly hired engineer. 21. Responsibility a. Although the effect size is small, those with direct supervision of newly hired engineers responded with greater differences between their ratings for importance than the level of proficiency exhibited by the newly hired engineer. 22. Curiosity a. Ratings are lower by those who supervise than by those who do not supervise entry level engineers. 23. Willingness to take initiative a. Organizations that identified as other types reported ratings for importance and proficiency that were about the same meaning the newly hired engineers were performing at a level that fulfilled the requirements of the organization. The differences in ratings of the other type organizations compared to public sector organizations were identified as a small to medium effect size. 24. Ability to handle multiple priorities a. Although the effect size is small, those with direct supervision of newly hired engineers responded with greater differences between their ratings for importance than the level of proficiency exhibited by the newly hired engineer. Supporting the findings of the importance of these soft skills, in 2020, chief human resources and strategy officers from leading global employers identified the top ten skills for 148 employment, skills, and recruitment. Applied across industries and geographies, these included complex problem solving, critical thinking, creativity, people management, coordinating with others, emotional intelligence, judgment and decision making, service orientation, negotiation, and cognitive flexibility. Members of this group and others released a report in 2021 aimed to build common language and skills at work [World Economic Forum, 2021]. Within this report, attitudes for development were delineated as learned behaviors, emotional intelligence traits, and beliefs individuals allow to influence their ideas, interactions with others, and responses to situations [World Economic Forum, 2021]. Elements of the attitude category of the World Economic Forum taxonomy include working with people, self-intelligence, and global citizenship and civic responsibility [World Economic Forum, 2021]. These three subcategories of attitudes reflect similar topics to those identified as ones newly hired engineers were in need of developing such as active listening, communication, information exchange, following instructions, assisting coworkers, time management, self-control, and meeting commitments. Even though interactions and communication with others were at the top of the lists for importance and need for improvement, social responsibility and global and cultural awareness had statistically equal ratings for importance and proficiency. It was determined that highlighted focus over the past decade must have resulted in sufficient efforts to have adequate proficiency within these two soft skills yet there is still a need to address communication with diverse groups and effective writing. 6.5.1 Implications for Engineering Education By targeting the soft skills identified as most important by employers of entry-level engineers, we hope our research can inform engineering educators where to focus their efforts in developing well-rounded, successful graduates. Curriculum developers could leverage this 149 research to enhance student outcomes by emphasizing the skills employers have identified as most important. Understanding what soft skills employers consider important will enable engineering educators to prioritize those skills within higher education. Prioritizing industry relevant soft skills in turn will enhance the employability of engineering graduates and prepare them better for a professional career. From a student perspective, knowledge of non-technical skills that are critical for them to enter and grow in their professional careers is crucial to enhancing their employability. Being aware of employer expectations would help students to prepare better for the recruitment process. Intentional focus on soft skills will encourage engineering graduates to attend to acquiring and mastering of soft skills in addition to technical skills taught in their curriculum. Additionally, we encourage engineering educators to administer soft skills surveys to those employers who hire their graduates. While we have aggregated a large data set, specific employers may value certain soft skills more than others and some institutions may find value in customizing soft skill development to cater to local employer needs. We are relatively early in our research of soft skills for entry-level engineers and see opportunity for additional research to augment our current findings. Two areas we have identified for continued education research include learning soft skills in context and developing structured assessment plans for soft skill acquisition. We believe both of these areas hold promise in refining and enhancing learning outcomes in engineering education. Finally, as this area of research develops, we anticipate that ABET may develop more fine- grained expectations for Engineering Accreditation Commission (EAC) and Engineering Technology Accreditation Commission (ETAC) graduates. 150 6.5.2 Implications for Engineering during Industry 4.0 Similar to the outcomes for the explanatory sequential design used in this study to complete confirmatory interviews of the findings, interviews with members of the manufacturing industry in South Africa revealed “soft skills alongside technical skills are even more important than technical skills alone in Industry 4.0” [Maisiri & Van Dyke, 2021 p. 5]. Thinking skills, social skills, and personal skills were identified as essential skills for engineers to meet the requirements of Industry 4.0. Required skills identified in South African firms include soft skills evaluated within this study, that is critical thinking, creativity and innovation, decision making, accountability, application of knowledge, cross-cultural communication and collaboration. During the last decade, potential new hire engineers of a traditional age (18–24- year-olds) in college have experienced two global crises, the economic downturn and the pandemic. A labor polarization has taken place with an increase in automation to replace routine jobs that formerly were completed by human labor and a change in the interactions expected within the world of work and global labor market [World Economic Forum, 2021b]. Prior to the pandemic were considerations of the fifth social revolution, a time for the development of new social systems for the continual growth, renewal, and development of the workforce driven by technological and economic forces [Cottam, 2019]. Industry 4.0 includes a changing digital culture that relies on collaboration, innovation, data-driven insights, and customer-centricity [World Economic Forum, 2021c]. Each of these four pillars draws upon professional skills such as intergenerational feedback, inclusive language and interactions, corporate citizenship, open discussions, communication with customers, deepened customer relationships, support for creative solutions and innovation, and development of knowledge hubs to encourage sharing of ideas and enabling 151 other people to participate. The attention on the development of behaviors, mind- sets, and practices is a shift in focus from products and outputs to changes in personal actions that are driven by mindsets. While organizations will still rely on key performance indicators and structural performance in the organization through Industry 4.0 and on, the development of people to create safe environments for people to try new things relies of an integration and reinforcement of professional skills. Organizational initiatives are underway to develop digital culture target actions where leaders acknowledge they are human, offer a sense of empowerment to their employees, support new mindsets through reverse mentoring and exchange circles, and establish approaches and levels of vulnerability [World Economic Forum, 2021d]. The compounded challenges faced during the pandemic and the uncertainty to the future fuels the imperative that people working together and understanding the lives of other people is necessary to equip leaders with the insights and foresight necessary to make decisions in business and education [World Economic Forum, 2021d]. 6.6 Conclusion In order to inform students of technical criteria for success, the ABET criteria has communicated the requirements. The success of engineering students in non-technical areas has been outlined yet lacks specificity. This study’s purpose was to provide empirical evidence for the establishment of non-technical skills for engineering education. The data within this study were compiled for all industries. The between group comparisons explore differences in the expectations for soft skills by industry. The snowball interviews confirmed the findings of the survey implemented prior to the start of the pandemic were still relevant. Future research is proposed to conduct additional interviews with engineers, managers, and educators to further the 152 explanatory sequential research design and gain greater understanding of the needs within industry and by engineering discipline. The coverage for this study was quite broad; however, even though nearly 500 respondents participated in the study, not all responded to all of the soft skills questions. Missing data resulted in the removal of the record for the paired differences analysis. This is a potential limitation in that it reduces the number of full data elements to 337. The comparison of the difference in the mean values of the soft skills to the paired differences means were not statistically significant; thus, the deletion of the elements from the paired mean differences did not statistically impact the overall outcome of the need for improvement for 24 of the 26 soft skills studied. 153 CHAPTER VII REQUIREMENTS OF MECHANICAL ENGINEERING FACULTY: EVIDENCE FROM JOB AD QUALIFICATIONS AND RESPONSIBILITIES 7.1 Abstract The purpose of this study was to examine academic position job advertisements to determine the skills required for candidates of mechanical engineering programs with graduate level programs. Using content analysis, 200 job advertisements for active searches in February 2022 were coded for position type, required qualifications, preferred qualifications, and responsibilities. Required qualification in the job advertisements were coded into degree and areas of expertise, degree program accreditation, research experience, teaching, Professional Engineer licensure, industry experience, and other qualities and skills. Preferred qualifications were organized into five themes: teaching, research, service, specific classification and language proficiency, and specific knowledge. Responsibilities reflected the required qualifications related to teaching, research, and service. The findings of this study can inform MS and PhD programs of skills to continue and skills to add to better prepare graduate students for academic roles. Keywords: mechanical engineering, academic positions, required qualifications, preferred qualifications, responsibilities, professional skills, technical skills 154 7.2 Introduction Higher education has experienced rapid growth expansion in from local and national markets to international contexts (Toakley, 2004; Toner, 2011). Further changes in higher education have occurred due to requirements for programs to use new methods of instruction and delivery for the massive expansion of engaged learners for around the world (Kuczera & Field, 2013). With increased knowledge requirements of multiple settings and methods of delivery, faculty are required to be creative in how they engage students in problem-solving and decision-making using new technologies (OECD, 2021). The globalization of higher education must meet these changing expectations of successful global practice by hiring faculty with the inherent qualities and practices necessary to support the learners and research goals. The primary mission of faculty within the university is to educate students; connecting students to real-life problems offers the advancement of knowledge and learning with improved understanding and relevance of scientific knowledge (Gregorutti, 2015). The development of faculty is key to the success of students as they equip students with the technical and professional skills necessary to succeed in their career choices (Lenci, 2018). In order to ensure their students are employable, faculty must develop professional skills including communications, autonomy, decision-making, priority management, team working, stress management, self-confidence, and creativity (Chaibate, Hadek, Ajana, Bakkali, & Faraj, 2019) in addition to the development of the students’ technical skills. Demonstration and documentation of the requisite knowledge, skills, and experience that are in demand by academic institutions increases the likelihood of making decisions within programs to ensure the employability of their graduates. Competencies, behaviors, attitudes, and personal qualities are the elements that help people to work well with others, effectively navigate their environment, perform well on 155 required competencies, and achieve their professional goals (Lippman, Ryberg, Carney & Moore, 2015). The study of job advertisements provides a means to identify how the learning and employability are matched. 7.3 Background The Accreditation Board for Engineering and Technology (ABET) works globally to promote career mobility by documenting the outcomes of what is learned instead of what is taught. The criteria for accreditation are designed for undergraduate (BS) degrees to prepare students for the skills, both technical and professional that they will need in the workplace. Faculty standards exist within the ABET accreditation criteria to ensure that faculty are part of the continuous improvement process for their program and engineering education. Prior initiatives have resulted from research to help identify ways to improve student experience and skills obtained at the undergraduate level. (Carey, Knizley, & Howard, 2018; Knizley, Spayde, & Brocato, 2019; Knizley & Spayde, 2020; Liu & Baker, 2017; Liu & Baker, 2018; Liu & Baker, 2019; Liu, Baker, He, & Lai, 2019; Warnock & Mohammadi-Aragh, 2016). Although there is much documentation of the standards for preparation of the students to meet employment needs, the required skills industry wants in their employees is still in need (Hirudayaraj, Baker, Baker, & Eastman, 2021). A content analysis study was conducted of 923 job postings in 2020 to determine prominent activity in mechanical engineering programs (Pollack, Sarrafian, & Grimm, 2021); communication, management, and design were found as the most prominent activity for mechanical engineers. A call for faculty to build an informed pedagogy was made to better prepare undergraduates for employment as mechanical engineers. Lacking similar oversight for accreditation by ABET, graduate level programs in mechanical engineering require similar study. As Industry 4.0 advances expectations for 156 performance, educational institutions are noted to lag in the development of programs to meet the new and emerging technologies (Pejic-Bach, Bertoncel, Meško, & Krstić, 2020). Industry 4.0 job analysis indicates that there is already a significant number of jobs that require skills in these technologies (Motyl, Baronio, Uberti, Speranza, & Filippi, 2017). Mechanical engineers will be expected to possess these new skills to meet the challenges posed by advances in Industry 4.0. Faculty and researchers in academic environments are expected to lead these efforts. New research outcomes can be determined in design courses and research projects led by faculty and their graduate students. Graduate programs can attract students through low costs, rankings, faculty to student ratios, etc. (Baker, et al., this document). A method to increase the attraction of students to a program has been the graduation and placement of students who have the skill set to fulfill the key job roles needed by industry and academia. As people, machines, and products communicate in new ways in Industry 4.0, mechanical engineers are challenged to determine how these new technologies can benefit the customer (Fernández-Miranda, Marcos, Peralta, & Aguayo, 2017). The exploration of these new and emerging technologies begins with efforts by faculty in their research and course designs. Job advertisement research has been used to gather real-time requirements of employment needs and fast insights into the changes in job profiles. The focus of this research was to examine academic position job advertisements to determine the skills required for candidates of mechanical engineering programs with undergraduate and graduate level programs. Through analysis of job advertisements in academia, this study’s outcomes can inform programs of the requirements, preferences, and responsibilities being sought for tenure track, non-tenure 157 track, and research positions in mechanical engineering programs in the United States and other countries. This study addressed the following research question: • What skills are referenced as required by academia seeking candidates who have obtained graduate level mechanical engineering degrees? 7.4 Methods A primary research tool in the analysis of job advertisements for more than four decades (Harper, 2012), content analysis was used to code the 200 academic Mechanical Engineering related positions that were active searches in February 2022 and listed in HigherEdjobs.com. The academic positions represented academic institutions in the United States and other countries. Used to analyze verbal and visual messages (Cole, 1988), content analysis as a research methodology is an accepted technique for the qualitative assessment of text. Inferences about the communication in the message is assessed by evaluating and asking questions about what has been produced and included in the message (Kerlinger, 1973; Krippendorff, 2004). Coding of the advertisements was conducted within NVivo 12. A word count was conducted of stemmed words within the full text of the 200 advertisements selected for this study. This text analysis provided guidance to the research team about the common content within the advertisements. The ten most frequent words and their stemmed words were engineers, mechanization, university, applications, research, teaching, positively, students’, department, and faculty. The word length, count of occurrence, weighted percentage, and similar words are presented in Table 1. 158 Table 7.1 Top Ten Text Matches in Academic Job Advertisements Analyzed Word Count Weighted Percentage (%) Similar Words* engineers 3876 2.64 engin, engine, engineer, engineered, engineering, engineers, engines mechanization 2514 1.71 mechanic, mechanical, mechanically, mechanics, mechanism, mechanisms, mechanization university 1914 1.30 universal, universities, university, universitys applications 1875 1.28 applicability, applicable, applicant, applicants, applicants’, application, applications research 1470 1.00 research, researcher, researchers, researching teaching 1339 0.91 teach, teaches, teaching positively 1332 0.91 position, positioned, positions, positive, positively, positivity students’ 1290 0.88 student, students, students’ department 1127 0.77 department, departments faculty 1118 0.76 faculties, faculty Note: *Similar words are defined by algorithms within NVivo to provide exact matches, words with the same stem, synonyms, specializations, and generalizations. Each of the 200 advertisements included a position title. Although all had an educational level and duties described, the educational level and duties were not always presented as required qualifications. Often, the advertisements included the phrases “required qualifications,” “minimum requirements,” or “basic qualifications” as a heading or statement. A search was conducted for the word, require, and its stemmed words (i.e., required, requirements, requires). Within the 200 advertisements in this study, 174 files contained 667 instances of require and its stemmed words. Similarly, a search was made for the word, prefer, and its stemmed words (i.e., preference, preferred, preferably). Prefer or its stemmed words were often presented next to qualifications, candidates, or will be given to. Of the 200 advertisements evaluated, 121 advertisements contained 199 uses of prefer or one of its stemmed words. A third search was conducted for responsibility and its stemmed words (i.e., responsibilities, responsible, response, 159 responsive). The result was 122 of the 200 advertisements contained 222 instances of responsibility or one of its stemmed words. These results were used to define three categories for coding the content of the job advertisements: required qualifications, preferred qualifications, and responsibilities. The purpose of the content analysis was to apply a standard framework to describe the characteristics of the content (Berelson, 1952). In this study, following a structured and directed approach (Hseih & Shannon, 2005), selected content within each advertisement was identified as a position type, required qualifications, preferred qualifications, and responsibilities. The position types were delineated as administrator-chair, instructor, postdoctoral scholar, professor-of-practice or non-tenure track open rank professor, research or academic support, or tenure track. Tenure track was further coded as assistant professor, associate professor, or professor. 7.5 Findings The findings of the structured and directed approach used to code the 200 job advertisements are organized by position type, required qualifications, preferred qualifications, and responsibilities. More than two-fifths of the positions were advertisements seeking tenure track faculty. Many of the tenure track positions were posted as open rank, thus, the total of assistant professor, associate professor and professor is greater than the count of tenure track at any rank as shown in Table 2. A summary level of required degree, preferred degree, frequent requirements, and other requirements are given in Table 2 as a quick reference of the qualities of the 200 job advertisements for Mechanical Engineering positions retrieved from HigherEdJobs.com and active in February 2022. 160 Table 7.2 Counts of Position Types and Selected Requirements Position Count Required Degree Preferred Degree Frequent Requirements Other requirements Administrative - Chair 6 PhD ME PhD** Leadership Funding record Instructor/Lecturer/Adjunct 60 BS & MS ME PhD ME Teaching experience Industry experience Post-Doctoral Scholar 34 PhD ME PhD** Computer language Specialized knowledge Professor of Practice, Non-Tenure Track of any rank 15 PhD ME PhD** Industry experience Research/ Research support 3 MS, PhD PhD** Industry experience Academic support 1 BS, MS Teaching experience Advising experience Tenure track of any rank 87 PhD ME PhD** ABET EAC* Licensed PE Assistant professor 79 Postdoctoral experience Industry experience Associate professor 32 Teaching experience Research record Professor 24 Leadership External funding Note: PhD ME is PhD in Mechanical Engineering. BS is Bachelor of Science. MS is Master of Science. *ABET EAC accredited program requirement for degree granting institution and knowledge of accreditation requirements to achieve or maintain ABET or EAC accredited status for the ME program. ** PhD in a closely related field or the second program in a department that was ME and another engineering program. 7.5.2 Required Qualifications The required qualification in the job advertisements include degree and areas of expertise, degree program accreditation, research experience, teaching, Professional Engineer licensure, industry experience, and other qualities and skills. Within each area are presented an overview of the requirement and examples from the job advertisements. 161 7.5.2.1 Degree and area of expertise The degree listed as required for the position types varied based upon the expectations for teaching, research, and service. Those with higher levels of research and service to the professional community had expectations for PhD degrees. The same relationship did not exist for teaching; however, those teaching graduate level students had a requirement for a PhD. The areas of expertise were based upon department content and expected research. For professor positions and post-doctoral scholars, the most common statement for degree requirements were “PhD in Mechanical Engineering, or a closely related field” (ad101). Specialization of other degrees were dependent upon the roles to be taken by the successful candidate. Other fields of study included applied physics, applied mathematics, aerospace engineering, biomedical engineering, chemical engineering, civil engineering, computer science, electrical engineering, electrical engineering technology, electromechanical engineering technology, electronic, engineering mechanics, engineering technology, industrial engineering, manufacturing technology, mechatronics engineering, metallurgical engineering, nuclear engineering, physics, software engineering, and systems engineering. Expectations for cross-disciplinary work were expected for faculty. “Candidates who transcend the traditional boundaries of Mechanical Engineering to incorporate insights from Electrical Engineering, Chemical Engineering, or related disciplines to address high impact societal problems related to areas described above are especially encouraged to apply” (ad181). Instructor and lecturer roles often listed “Bachelors degree or higher is required” (ad108), a master’s degree or equivalent, or master's degree or equivalent international degree at the time of application. For example, “Master's degree with a major in engineering or with 27 graduate quarter/18 semester credits in engineering which would apply to the major” (ad1). The discipline 162 for the degree requirements included a broader scope of topics such as preference for automated systems, electro-mechanical technology, industrial engineering, electrical engineering technology, robotics technology, or related field. Work experience could be substituted for degree attainment. Depth of knowledge was required, especially for those who would be teaching undergraduate students. The degree requirements were stated that if a candidate had earned a master’s degree in engineering or a closely related field, the expectation included an earned bachelor’s degree in mechanical engineering. Not all lecturer positions were at the master’s degree level of experience. Lecturers and professors-of-practice were listed as requiring a degree plus specific commercial or military experience. Requirements for lecturer candidates for a position were stated as “Ph.D. in Mechanical Engineering or a closely related field from an ABET accredited institution at time employment begins, and prior commercial or US Navy nuclear power plant experience” (ad48). Professor-of-practice candidates for this same position required more significant experience, “Applicants for Professor of Practice must have significant professional experience in operations, engineering, or training at a commercial or naval nuclear power plant” (ad48). Although many of the assistant professor and open rank positions included a specialization, all post-doctoral scholar and research positions required expertise in a selected area of study. These research-intensive positions included specific statements for the types of research to be conducted. For example, “Excellent command in transmission electron microscopy; defect analysis. Experience in x-ray based microscopy is helpful; mechanical testing Excellent written/oral communication skills. Must pass the Sandia National Lab Screening and receive approval to the National Lab” (ad10). 163 Inclusive of instructor and tenure track positions, the main focus was on the following areas of ME: Fluid Mechanics, Thermodynamics, Heat, Robotics, Control, Biomechanics, Mass Transfer, Solid Mechanics, Thermal, Fluids, Thermo-Fluids, Design, Mechanics, and Energy. A few positions requires a specialization in Design and Structural Mechanics. Regardless of the area for research or assignment for teaching for instructors, the most common requirement for faculty was a degree in Mechanical Engineering with a strong commitment to teaching undergraduates. 7.5.2.2 Accreditation requirements of degree granting institutions Although attainment of a terminal degree was required for faculty, additionally, accreditation of the degree program from which a successful candidate graduated was listed as a requirement. The candidate’s master’s degree was to have been earned form “a regionally accredited institution” (ad107). Another position required a “Ph.D. in mechanical engineering (or a closely related field) and an ABET/EAC accredited undergraduate degree in engineering, or equivalent” (ad196). “Minimum qualifications for a non-tenure track faculty position include a degree from an institution offering an ABET accredited BS in Mechanical Engineering and a MS in Mechanical Engineering, Manufacturing Engineering, or Industrial Engineering” (ad55). The inclusion of an accredited program within the degree granting institution for successful candidates was also a requirement for consideration. “Earned Ph.D. (or if ABD the degree must be awarded by …) in Mechanical Engineering or closely related field from an institution that offers ABET EAC accredited program(s)” (ad25) and “Earned Ph.D. (or if ABD the degree must be awarded by …) in Electrical Engineering or Mechanical Engineering or closely related field from an institution that offers ABET EAC accredited program(s)” (ad29) are 164 examples of requiring the graduate degree to be obtained from an institution with an ABET or EAC accredited program. If the successful candidate earned a degree internationally, the position required the international organization to be internationally recognized. “Ph.D. degree in Mechanical Engineering, or a related field from a college or university accredited by the US Department of Education or internationally recognized organization and have a record of outstanding academic and scholarly achievements” (ad116). A responsibility listed for many positions is the management of ABET accreditation. Several positions list experience with ABET accreditation as a quality of an ideal candidate. Expectations also exist for management of the ASME chapter for undergraduate and graduate students. 7.5.2.3 Research expertise required Successful tenure track, professor-of-practice, and postdoctoral scholar candidates were expected to have research expertise with an expectation to establish “an externally funded research program” (ad112) and “work with key industry partners” (ad105). Not all announcements included specific language for the research area. The requirements were more general with an expectation the candidate would have a preferred area of expertise and general knowledge to be able to teach successfully. For those that were specific, the statement was presented with sufficient detail to allow a variety of candidates apply for the position. For example, “The candidate must have research expertise in the area of new energy systems modelling and analytics, with a focus on techno-economic analysis of energy systems, energy life cycle assessment, energy systems management, energy systems optimization, green energy, hydrogen production and use, heat and power, 165 photovoltaic and solar thermal systems, wind energy, batteries, and power storage” (ad101). A second example of a detailed research area is “The successful candidate will have research expertise in the area of engineering management and industrial engineering, with a focus on operations management, production planning, project management, operations research and optimization, logistics and supply chain management, ergonomics and human factors, quality and standardization, facility layout, workplace design, lean manufacturing, safety and risk management, technology commercialization, systems engineering, production systems modelling, Internet of Things, information systems design, and reliability” (ad102). The type of research experience was presented such that the successful candidate would have the experience from which to draw when teaching, seeking funding, or conducting research or service. Some positions required postdoctoral research experience as a required qualification to be a successful candidate. “PhD in physics or related science. Experience with atomic force microscopy (AFM), and knowledge of AFM hardware. 3 years' experience in postdoctoral research position” (ad3). Professor-of-practice positions included statements such as “Experience with instrumentation and equipment relevant to area of expertise. Significant record of scientific publications in peer-reviewed journals is required” (ad56). Research is very important to the success of the candidate. The frequency of the word research and its stemmed words resulted in research as the fifth most used term in the job advertisements after engineering, mechanical, university, and application. This frequency reinforces the necessity of research in the professor, instructor, and postdoctoral scholar roles. 7.5.2.4 Teaching experience required The next most populous words in the job advertisements were teaching and its stemmed words. Of the 200 job advertisements studied, 60 were instructor or lecturer positions and 79 166 were assistant professors. As stated in an advertisement, successful candidates in these roles will have to “demonstrate both clear potential to develop an independent, internationally recognized research program aligned with and contributing to the … goals described above, as well as excellence in teaching” (ad109). An associate professor position advertisement reinforced the importance of teaching by requiring “Significant teaching experience and/or relevant professional work and industry experience” (ad111). An expectation was presented in multiple advertisements for successful candidates to have the “ability to teach introductory mechanics courses such as statics, dynamics, strength of materials, etc.” and “an ability to teach courses related to manufacturing, sustainability and/or thermal sciences” (ad117). Tenure track faculty at all ranks were expected to “pursue and sustain scholarly research and publication; recruit and advise students; supervise graduate students and laboratories; support tasks required to maintain ABET accreditation and contribute to the department, college, university, and profession through academic and professional service” (ad184). Accreditation management and leading undergraduate laboratory experiences were also expected for successful candidates for instructor, lecturer, and non-tenure track teaching positions. “Ideal candidates will have evidence of strong course management skills, and knowledge and/or experience with ABET accreditation and ready to prepare and lead undergraduate laboratory experiences” (ad130). One professor position required “Have a high spirit and strong passion for education; demonstrate distinction and/or strong potential in research; be agile to embrace changes and take on new challenges; be open-minded to new and different environments; be a team-player willing to contribute to organizational goals and initiatives” (ad44). This advertisement included specific expectations related to teaching that was not included in any of the others, “Have good experience in experiential learning methods such as TBL (Team-based Learning), PBL (Project- 167 based Learning), ABL (Action-based Learning) and can successfully employ them in all courses.” Examples of course titles were included in some of the advertisements. “Teaching experience and demonstrated excellence in undergraduate Electromechanical Engineering Technology. Courses include, but are not limited to: Electronic Devices, Mechatronics, Robotics and Industrial Controllers, Digital Electronics, Computer Interfacing, Application of Microprocessors o Assembly, and C++” (ad27). 7.5.2.5 Professional Engineering licensure requirements An outcome of graduating from an undergraduate program is the potential to be a licensed Professional Engineer. The job advertisements reinforced the necessity to have the credential the students would be working to obtain. For successful candidates, if licensure as a Professional Engineer was not already earned, licensure was expected to be obtained. If a successful candidate was not licensed at the time of hire, expectation was communicated with a given time frame for licensure to be obtained. For example, “Licensure must be obtained within five years from the date of hire” (ad101). 7.5.2.6 Relevant industry experience required In addition to requiring licensure, many positions included a statement of required experience such as a minimum of two years of relevant industrial experience in general area of mechanical engineering. Others were more specific about the type and extent of industry experience required. “Industry experience and working knowledge of programmable logic controls, sensors and instrumentation, mechanical systems, electronics, pneumatics and hydraulics, and robotics” (ad60) identified the topics for experience. Time required for industry 168 experience was coupled with a preferred amount of experience, “Experience: 3-5 years industry experience in a mechanical and/or manufacturing engineering field required; 10-15 years career industry experience preferred. Industry experience must be within the last 5 years” (ad68). 7.5.2.7 Other qualities and skills required The job advertisements presented a variety of skills dependent upon the role a successful candidate was to take. The most defining differences were positions with teaching, research, and service and positions with a primary research requirement. The two areas most prominent in difference were the level of leadership expected and the proficiency of computer languages and computer skills. The types of leadership described in the advertisements included leadership of teams of students, of faculty in the department and professional societies, and with industry. The word, leadership, occurred 43 times in the 200 job advertisements evaluated. All levels of positions coded in the study – tenure track all ranks, chair, instructor, lecturer, professor-of-practice, postdoctoral scholar, research support – included instances of leadership requirements in the positions. Leadership often occurred with a requirement to demonstrate management, mentoring, vision, innovation, motivation, inspiration, and strong academic skills. One advertisement for a tenure track assistant professor in a non-U.S. university stated as a required skill, “Leadership: it’s important for you to possess leadership skills that help you work effectively with and garner respect from students, parents, school management, and the community” (ad113). An open rank tenure track position in a U.S. university required “Strong organizational skills as demonstrated by a record of leadership and responsibility in industry” (ad105). An advertisement for a chair position and full professor rank stated, “The University seeks an innovative and visionary leader with the desire and ability to lead the department into 169 the future, to catalyze innovations in teaching and curricula at both the undergraduate and graduate levels, and to promote growth of sponsored research and graduate education. The candidate will work collaboratively with internal and external constituencies to develop new partnerships and professional relationships” (ad178). Postdoctoral scholar positions were most likely to include specific computer language and computer skills. “Experience in using Finite Element analysis and modeling, specifically using LS-DYNA; Experience with finite element pre- and post-processors (e.g., HyperMesh, LS-PrePost, etc.); Experience generating 2D and 3D drawings using CAD software (e.g., AutoCAD, SOLIDWORKS, etc.)” (ad186). “Must have expertise in computational fluid dynamics modeling and relevant software packages (e.g., OpenFoam). Code development knowledge and high-performance computing is desired. Must be interested in biological fluids modeling, particularly for the respiratory system” (ad42). “Strong programming skills in Matlab and/or Python. …. Required Knowledge, Skills, and Abilities Knowledge in one or more of the following subject areas: multi-physics modeling, structures, system dynamics, experimental design and testing, hydro- (or aero-) dynamics, multidisciplinary design optimization, and control. Knowledge/experience in computational methods: Computational structural dynamics (CSD), computational fluid dynamics (CFD), optimization methods, and computer aided design (CAD) codes. Experience or basic knowledge in one or more of the following codes/methods: Siemens NX or similar CAE software, OpenFOAM, OpenFAST, OpenMDAO, AeroDyn, HydroDyn, interFOAM, waves2Foam. … Basic knowledge in the Linux operating system, open-source codes, GitHub, and parallel processing” (ad80). Multidisciplinary work was also proposed for postdoctoral scholars, “The candidate is expected to work in a highly collaborative multi-disciplinary environment with other post- 170 doctoral associates, PhD and undergraduate students, as well as faculty members” (ad26). This position included specific experience with “Deep learning, Neurorobotic systems, Assistive technologies, Robotic prostheses, Exoskeletons, Electromyography, and Embedded systems development” and a requirement for a “solid competency with the standard implementation tools used in robotic and embedded systems (e.g., C, C++, Linux, MATLAB, Python, Deep Learning software, Robot Operating System) is required” (ad26). A similar postdoctoral opportunity had a focus on algorithm design. “As part of this work, the successful applicant will work on sensor data processing and data fusion, 3D scene understanding, semantic feature extraction and semantic SLAM, multi-robot distributed SLAM, hardware-aware energy-efficient implementation, and navigation and path planning in complex dynamic uncertain environments. The algorithmic development will need to take into account various uncertainties and possible adversarial elements wherein some agents in a swarm have been modified by an adversary. The work will include algorithm design, prototype implementation (e.g., in Matlab/Python), deployment (to the agents' onboard computational hardware using the Robot Operating System), and experimental testing (on unmanned vehicle swarms). A solid competency with the standard implementation tools used in autonomous robots and embedded systems (e.g., C, C++, Linux, MATLAB, Python, Robot Operating System, Ardupilot, Solidworks, Gazebo Physics Engine Simulator) is required” (ad30). One faculty position included a requirement for “proficiency in a minimum of two (2) of the following: SolidWorks, AutoCAD 2D and 3D, Revit, and PCB and layout” (ad36). Other positions were more general and listed “Computer Simulation, and Computer Aided Design” (ad40). Another, an instructor role, included a requirement for “experience with Machine Tool Technology, CNC G-Code programming, and CAD/CAM software is a plus. Familiarity with 171 AutoCAD, or other 3D design software” (ad69). An associate professor role required “programming with MATLAB, Computational Tools (FEA/CFD)” (ad86). Not all postdoctoral scholar positions required expertise; at times familiarity was required. However, the advertisement’s lists of familiarity also included proficiencies. “Proficient with Microsoft Office, specifically Excel, Word, and Power Point. Proficient in MATLAB or similar mathematical analysis software. Proficient in finite element analysis development and application and/or AM materials testing. Familiarity with additive manufacturing, particularly large-scale material extrusion processes. Familiarity with a commercial finite element program - preferably ABAQUS. Familiarity with static and fatigue testing of additively manufactured components. Familiarity with additive manufacturing structural damage and defect mechanisms. Familiarity with non-destructive testing is desirable, particularly ultrasonics, but not required. Ability to read and interpret materials test standards” (ad53). 7.5.3 Skills most frequently specified as preferred Although not required, candidates with preferred qualifications were stated to be preferred in the application and review process. The content coded as preferred qualifications can be organized into five themes: teaching, research, service, specific classification and language proficiency, and specific knowledge. 7.5.3.1 Teaching Although only one job advertisement studied included team-based learning and problem-based learning (Warnock & Mohammadi-Aragh, 2016) as a required qualification, many advertisements included experience teaching and willingness to use alternative delivery methods, 172 including online and educational technology tools, as preferred qualifications. “Experience in project-based or active classrooms” (ad83), “skill in the use of educational technology and alternative delivery methods” (ad15), and “experience with learning communities or team teaching” (ad1) are examples of the preferred expectation for teaching. Work with online learning, teaching specific student audiences, and attention to the diversity of the campus community were identified within the coded preferred qualifications. For example, faculty are expected to develop and implement course designs in a variety of modalities, advise students, and encourage service learning: “Experience with a variety of instructional methods, and willingness to develop and implement online courses. Student advising experience. Experience using high impact practices such as learning communities, capstone courses, undergraduate research, service learning and collaborative projects as part of pedagogical practices. Demonstrated ability to develop and implement instructional approaches such as service learning, civic engagement, and learning communities” (ad36). Specific roles and environments were identified in which the faculty member would work. “Preference will be given to candidates with experience working with or teaching community college students and to those with an understanding and appreciation of the role of the community college in higher education” (ad110). Of the 200 job advertisements, 154 included a statement specifically about diversity initiatives, priorities to build a diverse faculty and student body, commitment to equitable, diverse, and inclusive workforce and learning environments. Within the preferred qualifications were specific statements about preference to candidates with an “ability to contribute through teaching and/or service to the diversity, cultural sensitivity, and excellence of the academic community” (ad161) and “Demonstrated ability to communicate and work effectively with 173 diverse campus community” (ad163). Not only were the job advertisements stating that contributions to diversity, equity, and inclusion were part of the culturally diverse communities, they were stating that preference would be to candidates who have documentation of their commitment and experience working with diverse students in diverse work environments. 7.5.3.2 Research A record of research was identified as a required qualification. The occurrence of research or its stemmed words was noted in 150 of the 200 job advertisements studied. Within the preferred qualifications, the level of research was defined with preference to those with a promising publication and research record. For example, “a record of publication in reputable, peer-reviewed journals and conference proceedings” (ad101) was included in a job advertisement that also had a required qualification for research. Preference was also listed for those with “experience in securing or showing promise for national-level external funding” (ad126). One job advertisement mentioned the changes that are occurring in the workplace and their initiatives to advance the processes. They stated that preference is to candidates who could “train syntegrative leaders with Management skills, International perspective, Discipline-specific knowledge, and adaptability in Industry” (ad92) to work with 4th Industrial Revolution. 7.5.3.3 Service Many job advertisements required a commitment to service-related activities including advising, management of ABET accreditation, and service to professional societies. Others included a statement of preference and encouraged candidates to include documentation in their 174 application materials, “demonstrated record of service and volunteerism broadly related to their research, teaching, and/or equity, diversity, and inclusivity” (ad101). 7.5.3.4 Specific classification and language proficiency Requirements for citizenship or permission to work in a country were observed in the content coded as a preferred qualification. For example, “Employment at … University is regulated by … Labour Laws, and must comply with the regulations of the provincial government. These regulations stipulate who is eligible for legal employment with regard to obtaining work permits and visas. Please be advised candidates over 65 may be not eligible for a work visa in ,,,” (ad92). Preference was given to those with an “active secret government security clearance” (ad34). Those applying were not required to have the clearance already, however, candidates were encouraged to include statements for having a clearance for positions listed as being a “security sensitive position” (ad28). For many advertisements studied, citizenship, permission to work in a country, and security clearance were listed as required qualifications. English language proficiency was at times stated as preference. The statements associated with written and spoken English ranged from essential to welcomed. The advertisements studied included language proficiency in “written and spoken English” (ad106). Having a technical language expertise in English and Spanish was listed as a preferred qualification, “Bilingual: English/Spanish Understanding of manufacturing processes” (ad60). The welcome statement reinforced the requirement for English but did not state that the bilingual skill was required. For example, “… is a highly diverse campus with a wide range of languages spoken in addition to English. We welcome candidates who have experience with HSI/MSIs and/or who speak 175 Spanish, Vietnamese, American Sign Language, Chinese (Cantonese, Mandarin and other variations), Arabic, Tagalog, Farsi, French, or/and Yoruba” (ad28). The language proficiency preferred qualification could have been coded as specific knowledge. 7.5.3.5 Specific knowledge Within the job advertisements were preferences for specific knowledge that would benefit research centers, funded projects, or industry partnerships already in place at the college or university seeking the candidate. Areas of specific knowledge ranged from application of mechanical engineering topics to computer language and skills. Flexibility and desire to learn were preferred qualifications that were reinforced with statements such as “willingness to adopt new and emerging technologies” (ad110). Safety is a priority preferred qualification in 9 of the 200 job advertisements; however, 46 of the advertisements listed safety within their position description. Knowledge of laboratory safety procedures were included as a preferred requirement. Other formal specific safety knowledge was presented for the successful candidate to have an “OSHA Safety Certification” (ad2). Examples of the specific knowledge for which preference would be given to successful candidates include: • “Project management work experience” (ad15). • “Five years or more years of related work experience as an engineer industry or military. Two years of experience teaching in Career and Technical Education” (ad17). 176 • “Applications including but not limited to the mechanics of fluid flow in river, wetland, and lake/reservoir systems, coupling between local fluid dynamics and aquatic organism behavior and habitat preferences, or development of methods to better quantify fluid dynamics through laboratory and/or field experimentation” (ad46). • “Strong preference will be given to candidates with experience and expertise in Computational Methods, Thermo/fluid sciences, Manufacturing, and Senior Capstone Design” (ad86). • “Knowledge of and experience in photo-responsive nanomaterials would be an advantage” (ad106). • “emerging interests in engineering and the impact of engineering and STEM related work on modern society” (ad116). • “Strong computational skills, especially in computer-aided design and computer aided engineering tools” (ad113). • “Certified SolidWorks Professional Certification or better” (ad129) • “Knowledge in machine learning is also highly desirable” (ad189). • “Software experience: CREO, SolidWorks, Inventor, AutoCAD, Autodesk Pipe 3D, Four years of CAD related work experience” (ad198). These specific skills were next to statements such as strong preference to candidates, preference to candidates, or preferred qualifications. Candidates were encouraged to include documentation of these skills in their application materials. 177 7.5.4 Skills listed within the responsibilities The responsibilities for positions were often bulleted lists of what the successful candidate would be responsible to perform once hired. General statements related to faculty teaching and department service such as “Participate in department and college curriculum development. Deliver classroom and/or online course instruction. Conduct classroom research and other assessment/evaluation activities. Mentor and advise students. Participate in committee assignments and college-wide initiatives. Participate in department accreditation and review. Engage in scholarly and other professional development activities. Course assignments may include day, evening, and weekend hours, and off-site locations” (ad1) were common. Positions were defined with percentages such as “80% Teaching … 10% Service … 10% Research” (ad105) for roles that have high levels of teaching responsibility. Positions for research professorships and tenure track positions included statements with a focus on research. For example, a research professorship advertisement stated, “The candidate will help shape the research directions for the … Lab, lead the development and integration of computational predictions that parallel the experimental programs in place, publish and present their research findings, assist with graduate student advising, assist with proposal submissions, and report to project sponsors. The Assistant Research Professor will be a member of the … leadership team” (ad11). An example of a tenure track position stated, “The ideal candidate will bring an established record of or promise of a vigorous, interdisciplinary, and sustainable externally funded research program” (ad126). Specific statements were included about the responsibilities of the role as duties related to the work to be performed. These duties were delineated in the job advertisement. An example of specific responsibilities in a position description seeking a postdoctoral scholar is “Perform 178 mechanical tests on nuclear graphite with transmission electron microscopy and X-ray computed tomography. Analyze Data. Disseminate Data in journals and conferences. Collaborate with the national lab” (ad10). A tenure track assistant professor position stated “Teach undergraduate and graduate courses on topics of thermodynamics, fluid mechanics, heat transfer, thermal systems and/or renewable energy. Conduct research in at least one of the expertise areas listed above. Secure external funding for research. Participate in service to the department and university through committee work, recruitment, and interaction with industry” (ad104). 7.6 Discussion A common theme within the job advertisements analyzed using content analysis in this study was the collaborative nature of mechanical engineering. Statements such as “candidates will have the opportunity to work with a wide range of research groups and industry partners” (ad133) reinforce the coordination of efforts across fields of engineering and across disciplines. The faculty criteria for Mechanical and similarly names programs list that “The program must demonstrate that faculty members responsible for the upper-level professional courses maintain currency in their specialty area(s)” (ABET, 2022). With this collaboration are also industry partnerships, funded research, and contributions to the professional society. All advertisements analyzed in this study with tenure track positions required a doctorate or equivalent degree in Mechanical or related engineering, or in a field with significant overlap. Descriptions for instructors and lecturers often listed a required earned MS and a preferred PhD in mechanical engineering. These requirements for faculty ensure mechanical engineering programs seeking ABET accreditation meet the faculty and curriculum criteria. Criterion 6 of the 2022-2023 ABET criteria for accreditation state, “The program faculty must have appropriate qualifications and must have and demonstrate sufficient authority to ensure the proper guidance 179 of the program and to develop and implement processes for the evaluation, assessment, and continuing improvement of the program. The overall competence of the faculty may be judged by such factors as education, diversity of backgrounds, engineering experience, teaching effectiveness and experience, ability to communicate, enthusiasm for developing more effective programs, level of scholarship, participation in professional societies, and licensure as Professional Engineers.” (ABET, 2022). Many of the job advertisements included a combined degree of mechanical engineering and a second engineering field such as materials, biomedical, industrial, manufacturing, or engineering mechanics. Some advertisements were specific about alternative fields for the earned PhD in engineering. These closely related other fields of study included applied physics, applied mathematics, aerospace engineering, biomedical engineering, chemical engineering, civil engineering, computer science, electrical engineering, electrical engineering technology, electromechanical engineering technology, electronic, engineering mechanics, engineering technology, industrial engineering, manufacturing technology, mechatronics engineering, metallurgical engineering, nuclear engineering, physics, software engineering, and systems engineering. The job advertisement with a position that included teaching as one of the primary responsibilities included specific required and preferred qualifications for teaching experience and knowledge. These experiences were teaching in various modalities and media, using various techniques such as teamwork and problem-based learning (Warnock & Mohammadi-Aragh, 2016), and employing educational technology to support the presentation and practice of the skills. The curriculum requirements for ABET accreditation state, “In preparation for professional practice, the curriculum must include: a) principles of engineering, basic science, and mathematics (including multivariate calculus and differential equations); b) applications of 180 these topics to modeling, analysis, design, and realization of physical systems, components or processes; c) coverage of both thermal and mechanical systems; and d) in-depth coverage of either thermal or mechanical systems (ABET. 2022). Specific teaching responsibilities were presented in many of the job advertisements; however, the lack of specificity in others were supported by requirements that ensured the successful candidates met accreditations standards. For example, “…teaching different courses in general area of mechanical engineering design and structural mechanics. Experience in developing course specifications as per the national qualification framework and international accreditation standards” (ad113) reinforces the ABET and others accreditation criteria. Curriculum development expertise was as common a requirement in the job advertisements studied as were specific fields of engineering to be taught or researched. Candidates were requested to include their teaching or other philosophy statement with their materials in their application packet for consideration. Of the 200 job advertisements analyzed in this study, 74 job advertisements requested one or more of the following philosophy statements to be included in the application materials: teaching, research, leadership, learning, academic, administrative, education, and high-impact and student-centric. Students in master’s and doctoral programs would need to have instruction on how to prepare their philosophical statement. Those seeking chair positions were requested to include their administrative and leadership philosophy statements in their materials submitted for consideration. Computational and research skills are necessary for faculty to maintain currency in their specialty area. Computational and programming skills experience in Matlab, Python, C++, Linux, Deep learning software, machine learning, computational structural dynamics (CSD), computational fluid dynamics (CFD), optimization methods, and computer aided design (CAD) 181 codes (e.g., AutoCAD, Solidworks)were frequently listed. Specializations required experience or basic knowledge of one or more of the following Siemens NX or similar CAE software, OpenFOAM, OpenFAST, OpenMDAO, AeroDyn, HydroDyn, interFOAM, waves2Foam, HyperMesh, LS-PrePost, LS-DYNA, Linux operating system, open-source codes, GitHub, parallel processing, code development for high-performance computing, multi-physics modeling, structures, system dynamics, experimental design and testing, hydro- (or aero-) dynamics, multidisciplinary design optimization, control, neurorobotic systems, assistive technologies, robotic prostheses, exoskeletons, electromyography, embedded systems development, and robot operating systems. One specifically stated that evidence of certification for Solidworks was required to be included with the application materials. The type and depth of knowledge for MS and PhD students is dependent upon the projects they have selected and industry partners’ needs. Often, the job advertisement requirements included industry experience. Students with the role as computer modelling leader in group projects have a greater opportunity to improve their skills, thus meeting ABET outcomes (Liu & Baker, 2017) and preparing themselves for the workplace in either industry (Szatmary, 2019) or academia. The linkage of curriculum to industry partnerships, especially the capstone design program, was reinforced within the job advertisements studied. “The Mechanical Engineering Department has an established industry-funded capstone design program. The successful candidate will be responsible for capstone related classroom lectures for undergraduates, securing capstone project funding from sponsors, and coordinating with Mechanical Engineering faculty members in advising individual student projects. The candidate must be comfortable working with industry, in particular industries engaged in the design and/or manufacture of mechanical, electro-mechanical, or thermal-mechanical products. The successful candidate will 182 also teach courses such as CAD, mechanical design, dynamics and controls, and mechatronics” (ad105). This type of work reinforces course goals with respect to ABET learning outcomes and opportunity for excellent training for teamwork, industry work requirements with hands-on experience, and problem solving capacity (Liu & Baker, 2017; Liu & Baker, 2018; Liu & Baker, 2019; Liu, Baker, He, & Lai, 2019). The limitations of this study are that the job advertisements are from a single source, HigherEdJobs.com, and were active in February 2022. 7.7 Conclusion This study of 200 job advertisements for academic positions active in HigherEdJobs.com in February 2022, was to answer the research question, What skills are referenced as required by various industries and academia seeking candidates who have obtained graduate level mechanical engineering degrees? To answer this question, the descriptions were coded in NVivo with position title, required qualifications, preferred qualifications, and responsibilities. Licensure as a Professional Engineer and specialized skills to advance what is known in mechanical engineering are necessary for faculty members to meet the ABET criteria. Additional to ABET criteria and listed within the job advertisements were skills related to curriculum design and delivery decisions and evidence of a learning and teaching philosophy. Knowledge of computational and research methods are essential to help bridge collaborations of mechanical engineering with other fields and disciplines. Being part of a college or university in a teaching or research role is “an opportunity to join a team of dedicated professionals where you'll inspire motivated students to realize their educational and career goals. The position involves teaching a variety of engineering courses 183 with an emphasis on general and mechanical engineering skills and includes both classroom and lab instruction in an established engineering science curriculum. Additionally, the position involves support of the instruction in mechanical topics …”(ad110). Job advertisements not only market the position at the college or university, but they also market the field of mechanical engineering and its many opportunities for collaboration with other fields and advancements of engineering and technical processes. 184 CHAPTER VIII CONCLUSION 8.1 Discussion & Conclusion Through systematic evaluation techniques, this dissertation serves as a model for administrators to make programmatic design decisions for improvement of their programs. The six research projects culminated in an analysis of the knowledge, skills, and abilities the global workforce requires for mechanical engineering graduates. The first manuscript indicated that nearly 21% of PhD students and 14% of master’s students are in the top 9 programs. It also indicated 40% of PhD graduates in mechanical engineering are from the top 25 out of 182 programs. Average percent of research dollars, applications, and graduates declined as the ranking value increased. Top rated programs include minors and other program design decisions to enhance the breadth of their programs and prepare students for the global market. The second and third manuscripts discussed the important of course design improvements and the systematic assessment of skills in the classroom. The questionnaires developed confirmed the effectiveness and efficiency of the group design project in improving students’ skills in problem solving and multidisciplinary teams and confirmed the renovated course design and course materials met the learning needs of the students. Similar questionnaires and survey instruments should be implemented to ensure the skills desired by the program are translating to the students. 185 The fourth manuscript discusses the how the perception of importance affects the skills learned by students. Instructors organize the design, development, and implementation of their course work based on the necessary learning outcomes and the needs of their students and students will be motivated but what they perceive as most important. It examines the ratings of students and faculty for what each perceived to be the most important student outcomes as defined by ABET criteria. The fifth manuscript analyzed the professional skills required by industry for entry-level engineers. Programmatic design decisions should prioritize curriculum content and resource allocation that gives students maximum proficiency in the professional skills needed by industry. Engineering programs are preparing students in the skills of positive attitude, teams, and reliability; however, there is still a gap between the perceived importance and proficiency of these skills. The sixth manuscript examines the job advertisement qualifications and responsibilities that are needed for careers in academia. Mechanical engineering faculty job advertisements were analyzed through content analysis for the required qualifications, preferred qualifications, and specialty statements. The technical and professional skills that mechanical engineering graduates need to develop in order to improve the likelihood of employability are focused in the shifting towards Industry 4.0 and professional skills that reinforce the needed creativity and human element that Industry 4.0 technologies are not fulfilling. As people, machines, and products communicate in new ways in Industry 4.0, mechanical engineers are challenged to determine how these new technologies can benefit the customer. Reliability, ability to work in teams, responsibility, self-motivation, and positive attitude are rated as most important professional skills by industry. The 186 additional skills that are needed for graduate mechanical engineering students to be prepared for the global workforce are to be able to build their philosophy and diversify their areas of knowledge beyond their specific major to include modeling, instrumentation, and computation skills in a breadth of topics. The contribution of this dissertation is a launching point for future research to inform programmatic design of mechanical engineering undergraduate, master’s, and doctoral level education programs. These six research projects present overview of the skills needed by employers in the global workforce and assessment of those skills in mechanical engineering programs. 8.2 Overall Limitations The limitations of this study carry over from each of the six research projects. The first manuscript demonstrates the significant drop in scores that inform the ranking value. The score drops are reflected in the number of graduate student applications, funding, and faculty. This has led to a historically disproportionate number of students attending a small portion of the schools. The second and third manuscripts are representative of their respective courses and will need to be tested in additional sites. The fourth manuscript is representative of a small population of students and faculty at Mississippi State University and will need to be tested in a broader coverage of programs. The fifth manuscript has a broad coverage of participants, but not all respondents responded to all the questions. The missing data resulted in removal of the record for the paired difference analysis. The sixth manuscript came from single source, HigherEdJobs.com, and were active in February of 2022. 187 8.3 Recommendations for Future Studies This dissertation serves as a launching point for future research in process improvement of mechanical engineering programs. Additional research that would continue to impart significant contribution to this field includes: further identification of best practices in mechanical engineering programs; mixed-methods research in perceived expertise; analysis on the impact of industry 4.0, uncertainty, wicked problems and other complexity; further analysis of undergraduate courses with adapted questionnaire; and adaptation of the undergraduate questionnaire to graduate courses. 188 REFERENCES American Society for Engineering Education, "Engineering education for a changing world: A joint project by the engineering deans council and corporate roundtable of the American Society for Engineering Education," in American Society for Engineering Education, Washington, DC, 1994. "ABET | ABET Accreditation," ABET, [Online]. Available: https://www.abet.org. [Accessed 9 2021]. "Mechanical Engineering," Mississippi State University, 2021. [Online]. Available: http://catalog.msstate.edu/graduate/colleges-degree-programs/engineering/mechanical. [Accessed 9 2021]. "Number of People With Master's and Doctoral Degrees Doubles Since 2000," United States Census Bureau, 21 02 2019. [Online]. Available: https://www.census.gov/library/stories/2019/02/number-of-people-with-masters-and-phd-degrees-double-since-2000.html. [Accessed 9 2021]. "Requirements | Mississippi Board of Licensure for Professional Engineers and Surveyors," [Online]. Available: https://www.pepls.ms.gov/requirements. [Accessed 9 2021]. Aasheim, C.L.; Li, L.; Williams, S. Knowledge and skills requirements for entry-level Information and Technology workers: A comparison of industry and academia. J. Inf. Syst. Educ. 2009, 20, 349–356. Available online: https://eric.ed.gov/?id=EJ858065 (accessed on 3 May 2021). Accreditation Board for Engineering and Technology [ABET]. (2022a). About ABET. Retrieved from: https://www.abet.org/about-abet/ Accreditation Board for Engineering and Technology [ABET]. (2022b). Criteria for accrediting engineering programs, 2022-2023. Retrieved from: https://www.abet.org/accreditation/accreditation-criteria/criteria-for-accrediting-engineering-programs-2022-2023/ Accreditation Board of Engineering and Technology (ABET). Accreditation Policy and Procedure Manual (APPM) 2021– 2022. Available online: https://www.abet.org/wp-content/uploads/2021/01/A001-21-22-Accreditation-Policy-and-Procedure- Manual.pdf (accessed on 30 September 2021). 189 Accreditation Board of Engineering and Technology (ABET). History. Available online: https://www.abet.org/about-abet/ history/ (accessed on 30 September 2021). Adecco, Impact of the American Skills Gap. 7 June 2016. Available online: https://www.adeccousa.com/employers/resources/ skills-gap-in-the-american-workforce/ (accessed on 1 August 2021). Akay, A. (2008). A renaissance in engineering PhD education. European Journal of Engineering Education, 33(4), 403–413. https://doi.org/10.1080/03043790802253475 Akyazi, T.; Alvarez, I.; Alberdi, E.; Oyarbide, A.; Goti, A.; Bayon, F. Skills Needs of the Civil Engineering Sector in the European Union Countries: Current Situation and Future Trends. Appl. Sci. 2020, 10, 7226. [CrossRef] Akyazi, T.; Goti, A.; Oyarbide, A.; Alberdi, E.; Carballedo, R.; Ibeas, R.; García-Bringas, P. Skills Requirements for the European Machine Tool Sector Emerging from Its Digitalization. Metals 2020, 10, 1665. [CrossRef] Al-Bahi, A. M., Taha, M. A., & Turkmen, N. (2013). Teaching and Assessing Engineering Professional Skills. International Journal of Engineering Pedagogy (iJEP), 3(S3), pp. 13–20. https://doi.org/10.3991/ijep.v3iS3.2728 Aleamoni LM. Development and factorial validation of the Arizona Course/Instructor Evaluation Questionnaire. Educ Psychol Meas 1978; 38: 1063–1067. Andrews, J.; Higson, H. Graduate Employability, “Soft Skills” versus “Hard” business knowledge: A European study. High. Educ. Eur. 2008, 33, 411–422. [CrossRef] Arbeit C, Yamaner MI; National Center for Science and Engineering Statistics [NCSES]. (2021). Trends for Graduate Student Enrollment and Postdoctoral Appointments in Science, Engineering, and Health Fields at U.S. Academic Institutions between 2017 and 2019. NSF 21-317. Alexandria, VA: National Science Foundation. Retrieved from: https://ncses.nsf.gov/pubs/nsf21317/. Arcelay, I.; Goti, A.; Oyarbide-Zubillaga, A.; Akyazi, T.; Alberdi, E.; Garcia-Bringas, P. Definition of the Future Skills Needs of Job Profiles in the Renewable Energy Sector. Energies 2021, 14, 2609. [CrossRef] Autor, D.H. Why are there still so many jobs? The history and future of workplace automation. J. Econ. Perspect. 2015, 29, 3–30. Available online: https://economics.mit.edu/files/11563 (accessed on 3 May 2021). [CrossRef] Autor, D.H.; Levy, F.; Murnane, R. The skill content of recent technological change: An empirical exploration. Q. J. Econ. 2003, 118, 1279–1333. [CrossRef] B. Neiva, "Assessment of soft skills for engineering," 2019. 190 Berelson, B. (1952), Content analysis in communication research, Free Press, Glencoe, IL. Berger, G. Data Reveals the Most In-Demand Soft Skills among Candidates. 2016. Available online: https://business.linkedin. com/talent-solutions/blog/trends-and-research/2016/most-indemand-soft-skills (accessed on 3 May 2021). Beyond, I.T. IBM’s Role in Creating the Workforce of the Future. 2009. Available online: http://service-science.info/wp-content/ uploads/2010/10/2009_06-IBM-workforce.pdf (accessed on 3 May 2021). Bodmer, C., Leu, A., Mira, L. and Rutter, H. (2002). SPINE Successful Practices in International Engineering Education. Bonekamp, L., & Sure, M. (2015). Consequence of Indistry 4.0 on human labour and work organization. Journal of Business and Media Psychology, 6(1), 33–40. Borghans, L.; Ter Weel, B.; Weinberg, B.A. People skills and the labor market outcomes of underrepresented groups. Ind. Labor Relat. Rev. 2014, 67, 287–334. [CrossRef] Borrego, M., Froyd, J. E., & Hall, T. S. (2010). Diffusion of engineering education innovations: a survey of awareness and adoption rates in U.S. engineering departments. Journal of Engineering Education, 99(3), 185–207. https://doi.org/10.1002/j.2168-9830.2010.tb01056.x Bosi, F., Mazzocchi, E., Jatri, I., Dal Corso, F., Piccolroaz, A., Dederi, L., Bigoni, D., Cocquio, A., Cova, M., & Ordizzi, S. (2013). A collaborative project between industry and academia to enhance engineering education at graduate and PhD level in ceramic technology. International Journal of Engineering Education, 29(6), 1362–1370. Bougnol, M.-L., & Dulá, J. H. (2014). Technical pitfalls in university rankings. Higher Education, 69(5), 859–866. https://doi.org/10.1007/s10734-014-9809-y Bowen, W. G., Chingos, M. M., & McPherson, M. S. (2009). Crossing the finish line: Completing college at America’s public universities. Princeton, NJ: Princeton University Press Busteed, B. Higher Education’s Work Preparation Paradox; Gallup. 25 February 2014. Available online: https://news.gallup. com/opinion/gallup/173249/higher-education-work-preparation-paradox.aspx (accessed on 3 May 2021). Byrne M and Flood B. Assessing the teaching quality of accounting programs: an evaluation of the course experience questionnaire. Assess Eval High Educ 2010; 28: 135–145. Carey, A. S., Knizley, A. A., & Howard, I. L. (2018). Bridging disciplines while fueling engineering and management skills: A case study in transitioning from undergraduate research to graduate study. 2018 ASEE Southeastern Section Conference, Embry-Riddle Aeronautical University, Daytona Beach, Florida. March 4-6, 2018. 191 Cassel RN. A student course evaluation questionnaire. Improv Coll Univ Teach 1971; 19: 204–206. Cassel, R. (1971) A Student Course Evaluation Questionnaire, Improving College and University Teaching, 19:3, 204-206, DOI: 10.1080/00193089.1971.10533113. Chaibate, H., Hadek,A., Ajana, S., Bakkali, S., & Faraj, K. (2019).A comparative study of the engineering soft skills required by Moraccan job market. International journal of higher Education, 9(1).11. https://doi.org/10.5430/ijhe.v9n1p142 Chuchalin, A. (2018). Evolution of the CDIO approach: BEng, MSc, and PhD level. European Journal of Engineering Education, 45(1), 103–112. doi:10.1080/03043797.2017.1422694 Chuchalin, A., Daneikina, N., & Fortin, C. (2016). Application of CDIO approach to engineering BEng, MSc, and PhD programs design and implementation. Proceedings of the 12th International CDIO Conference, Turku University of Applied Sciences, Turku, Finland, June 12-16, 2016. Coffey, M., & Gibbs, G. (2001) The Evaluation of the Student Evaluation of Educational Quality Questionnaire (SEEQ) in UK Higher Education, Assessment & Evaluation in Higher Education, 26:1, 89-93, DOI: 10.1080/02602930020022318 Cohen, J. A power primer. Psychol. Bull. 1992, 112, 155–159. [CrossRef] Cole, F.L. (1988), “Content analysis”, Clinical Nurse Specialist, 2(1), 53–57, https://doi.org/10.1097/00002800-198800210-00025. Cottam, H. Revolution 5.0: A Social Manifesto. 2019. Available online: https://www.hilarycottam.com/wp-content/uploads/20 19/12/Social-Revolution-5.0-_dec19.pdf (accessed on 29 July 2021). Crawford, P.; Lang, S.; Fink, W.; Dalton, R.; Fielitz, L. Comparative Analysis of Soft Skills: What is Important for New Graduates? Perceptions of Employers, Alum, Faculty, and Students. 2011. Available online: http://www.aplu.org/members/commissions/ food-environment-and-renewable-resources/CFERR_Library/comparative-analysis-of-soft-skills-what-is-important-for- new-graduates/file (accessed on 3 May 2021). Crawley, E. F., Malmqvist, J., Ostlund, S., and Brodeur, D. R., Rethinking engineering education: The CDIO approach, New York, NY: Springer, 2007. Cruz, M., Saunders-Smits, G., & Groen, P. (2020) Evaluation of competency methods in engineering education: a systematic review, European Journal of Engineering Education, 45:5, 729-757, DOI: 10.1080/03043797.2019.1671810 Cupp, S., P. D. Moore and N. L. Fortenberry, "Linking student learning outcomes to instructional practices-PhaseI," in American Society for Engineering Education Annual Conference and Exposition, Salt Lake City, UT, 2004. 192 Deming, D.J. The growing importance of social skills in the labor market. Q. J. Econ. 2017, 132, 1593–1640. [CrossRef] Dichev, I. (2001). News or noise? Estimating the noise in US News University Rankings. Research in Higher Education, 42(3), 237–266. Dill, D. D., & Soo, M. (2005). Academic quality, league tables, and public policy: A cross-national analysis of university ranking systems. Higher Education, 49(4), 495–533. https://doi.org/10.1007/s10734-004-1746-8 European Network for Accreditation of Engineering Education, "EUR-ACE® Framework Standards and Guidelines," ENAEE, [Online]. Available: https://www.enaee.eu/eur-ace-system/standards-and-guidelines/#standards-and-guidelines-for-accreditation-of-engineering-programmes. [Accessed 9 2021]. Fernandes, P.R.d.S.; Jardim, J.; Lopes, M.C.d.S. The Soft Skills of Special Education Teachers: Evidence from the Literature. Educ. Sci. 2021, 11, 125. [CrossRef] Fernández-Miranda, S. S., Marcos, M., Peralta, M. E., & Aguayo, F. (2017). The challenge of integrating Industry 4.0 in the degree of Mechanical Engineering. Procedia Manufacturing, 13, 1229–1236. https://doi.org/10.1016/j.promfg.2017.09.039 Flanders, L.R.; Utterback, D. The management excellence inventory: A tool for management development. Public Adm. Rev. 1985, 45, 403–410. [CrossRef] Foss, M, Liu, Y-C. Project-based learning (PBL) center to bridge students with technology. In: Proceedings of intermountain engineering, technology, and computing conference, Orem, UT, 4–5 May 2020. Foss, M. and Liu, Y-C. Creating solutions through project-based and experimental learning: A case study of the concept center. International Journal of Engineering Education, 37(6), 2021, 1630-1642. Foss, M. and Liu, Y-C. Developing creativity through project-based learning, Proceedings of Wasatch Aerospace and Systems Engineering Mini-Conference, virtual conference, April 15-16, 2021. Ghiasi, A., Fountas, G., Anastasopoulos, P., & Mannering, F. (2019). Statistical assessment of peer opinions in higher education rankings. Journal of Applied Research in Higher Education, 11(3), 481–492. https://doi.org/10.1108/jarhe-09-2018-0196 Gilbert, R. (2004). A framework for evaluating the doctoral curriculum. Assessment & Evaluation in Higher Education, 29(3), 299–309. https://doi.org/10.1080/0260293042000188258 Gilbert, T.F. (1978). Human competence: Engineering worthy performance. McGraw-Hill. 193 Graaff, E.D., & Ravesteijn, W. (2001) Training complete engineers: Global enterprise and engineering education, European Journal of Engineering Education, 26:4, 419-427, DOI: 10.1080/03043790110068701 Gregorutti, G. (2015). Enriching higher education training through values and social engagement. Bulgarian Comparative Education Society, Paper presented at the Annual International Conference of the Bulgarian Comparative Education Society (13th, Sofia, Bulgaria, Jun 10-13, 2015) ERIC: ED568919 Grewal, R., Dearden, J. A., & Llilien, G. L. (2008). The University Rankings Game. The American Statistician, 62(3), 232–237. https://doi.org/10.1198/000313008x332124 Hall-Ellis, S.D. Cataloguer competencies: What do employers require? Cat. Classif. Q. 2008, 46, 305–330. [CrossRef] Han, X., Stocking, G., Gebbie, M. A., & Appelbaum, R. P. (2015). Will they stay or will they go? International graduate students and their decisions to stay or leave the U.S. upon graduation. PLOS ONE, 10(3), e0118183. https://doi.org/10.1371/journal.pone.0118183 Hancock, S., & Walsh, E. (2014). Beyond knowledge and skills: rethinking the development of professional identity during the STEM doctorate. Studies in Higher Education, 41(1), 37–50. https://doi.org/10.1080/03075079.2014.915301 Hanover Research. A Crosswalk of 21st Century Skills. 2011. Available online: https://www.scribd.com/document/328458075/ A-Crosswalk-of-21st-Century-Skills-Membership (accessed on 3 May 2021). Hansmann, H. (1999). Higher education as an associative good. SSRN Electronic Journal. https://doi.org10.2139/ssrn.192576 Harper, R. (2012), “The collection and analysis of job advertisements: a review of research methodology”, Library and Information Research, 36(112), 29–54. Hazelkorn, E. (2009). Rankings and the battle for world-class excellence. Higher Education Management and Policy, 21(1), 1–22. doi:10.1787/hemp-v21-art4-en He, G. and Liu, Y-C, “Development of a low-cost vibration damper dynamometer for suspension damper testing”, in Vibration Control of Structure (edited by S E Rahimi), IntechOpen, London, United Kingdom, 2022. Heckman, J.; Kautz, T. Hard evidence on soft skills. Labor Econ. 2012, 19, 451–464. [CrossRef] Heckman, J.; Stixford, J.; Urzua, S. The Effects of Cognitive and Noncognitive Abilities on Labor Market Outcomes and Social Behavior. J. Labor Econ. 2006, 24, 411–482. [CrossRef] 194 Hirudayaraj, M., Baker, R., Baker, F., & Eastman, M. (2021). Soft skills for entry-level engineers: What employers want. Education Sciences, 11, 641. https://doi.org/10.3390/educsci11100641 Hirudayaraj, Malar & Baker, Rose. (2018). HRD competencies: analysis of employer expectations from online job postings. European Journal of Training and Development. 42. 10.1108/EJTD-04-2018-0036. Horacek P. Laboratory experiments for control theory courses: A survey. Annu Rev Control 2000; 24: 151–162. Hsieh, H.F. and Shannon, S.E. (2005), “Three approaches to qualitative content analysis”, Qualitative Health Research, 15(9), 1277–1288, https://doi.org/10.1177/1049732305276687. Itani, M.; Srour, I. Engineering students’ perceptions of soft skills, industry expectations, and career aspirations. J. Prof. Issues Eng. Educ. Pract. 2016, 142, 04015005. [CrossRef] John, D.D.; Chen, Y. STEM Education Redefined. 2017 ASEE Annual Conference and Exposition. College Industry Partnership Division. 2017. Available online: https://digitalcommons.georgiasouthern.edu/civil-eng-facpubs/24/ (accessed on 3 May 2021). Jones, M.; Baldi, C.; Phillips, C.; Waikar, A. The hard truth about soft skills: What recruiters look for in business graduates. Coll. Stud. J. 2016, 50, 422–428. Kappelman, L.; Jones, M.C.; Johnson, V.; McLean, E.; Boonme, K. Skills for success at different stages of an IT professional’s career. Commun. ACM 2016, 59, 64–70. [CrossRef] Keller, J. M. (1983). Motivational design of instruction. In C.M. Reigeluth (Ed.), Instructional-design theories and models: An overview of their current status. Lawrence Earlbaum Associates. Keller, J. M. (1987). Strategies for stimulating the motivation to learn. Performance + Instruction, 26(8), 1–7. https://doi.org/:10.1002/pfi.4160260802 Kember D, Leung DY, Jones A, et al. Development of a questionnaire to measure the level of reflective thinking. Assess Eval High Educ 2000; 25: 381–395. Kerlinger, F.N. (1973), “Statement from the editor”, Review of Research in Education, Vol. 1 No. 1, pp. 5-8, doi: 10.3102/0091732x001001005. Kiritsis N, Huang Y-W and Ayrapetyan D. A multi-purpose vibration experiment using Labview. In: Proceedings of the 2003 American Society for Engineering Education annual conference & exposition, Nashville, TN, USA, 22–25 June 2003. 195 Klaassen, R. G. (2018). Interdisciplinary education: a case study. European Journal of Engineering Education, 43(6), 842–859. https://doi.org/10.1080/03043797.2018.1442417 Klaus, P. Communication breakdown. Calif. Job J. 2010, 28, 1–9. Klein, C.; DeRouin, R.E.; Salas, E. Uncovering Workplace Interpersonal Skills: A Review, Framework, and Research Agenda. In International Review of Industrial and Organizational Psychology; Hodgkinson, G.P., Ford, J.K., Eds.; Wiley: West Sussex, UK, 2006; pp. 79–126. Knizley, A. A. & Spayde, E. (2020). Recruiting and retaining women in engineering through car maintenance outreach program. Paper presented at 2020 ASEE Southeastern Section Conference. Auburn University, Auburn, Alabama, March 8-10, 2020. Knizley, A. A., Spayde, E. & Brocato, J. (2019). Developing appreciation for written communication in freshman mechanical engineering students. 2019 ASEE Southeastern Section Conference, NC State University, Raleigh, North Carolina, March 10-12, 2019 Krippendorff, K. (2004), Content analysis: An introduction to its methodology, 2nd ed., Sage, Thousand Oaks, CA. Kuczera, M & Field, S. (2013). A skills beyond school review of the United States, OECD reviews of vocational education and training. OECD Publishing. https://doi.org/10.1787/9789264202153-en Kuhn, P.; Weinberger, C. Leadership skills and wages. J. Labor Econ. 2005, 23, 395–436. [CrossRef] Lang, J.D., Cruse, S., McVey, F.D. and McMasters, J. (1999), Industry Expectations of New Engineers: A Survey to Assist Curriculum Designers. Journal of Engineering Education, 88: 43-51. https://doi.org/10.1002/j.2168-9830.1999.tb00410.x Lenci, S. (2018). Industry, faculty, and students' perceptions of the opportunities and constraints regarding the implementation of professional skills into technical education programs (Unpublished doctoral thesis). University of Calgary, Calgary, AB. https://doi.org/10.11575/PRISM/31775 http://hdl.handle.net/1880/106487 doctoral thesis Lenoir J. A combined vibrations and controls course for mechanical engineering. In: Proceedings of the 2005 American Society for Engineering Education annual conference & exposition, Chicago, IL, USA, 18–21 June 2005. Lindqvist, E.; Vestman, R. The Labor Market Returns to Cognitive and Noncognitive Ability: Evidence from the Swedish Enlistment. Am. Econ. J. Appl. Econ. 2011, 3, 101–128. [CrossRef] 196 Lippman, L. H., Ryberg, R., Carney, R., & Moore, K. A. (2015). Workforce connections: Key “soft skills” that foster youth workforce success: Toward a consensus across fields. Child Trends Publication #2105-24. Retrieved from: https://www.childtrends.org/wp-content/uploads/2015/06/2015-24WFCSoftSkills.pdf Liu, Y-C. A programming course including C# and MATLAB for mechanical engineering students. ASEE Comput Educ J 2011; 2: 106–112. Liu, Y-C. Design of instructional tools to facilitate understanding of fluid viscous dampers in a vibration and controls class and course assessment. In: Proceedings of 2020 ASEE annual conference & exposition, Montreal, Quebec, Canada, 21–24 June 2020. Liu, Y-C. Development of instructional courseware in thermodynamics education. Comput Appl Eng Educ 2011; 19: 115–124. Liu, Y-C. Implementation of MATLAB/Simulink into a vibration and control course for mechanical engineering students. In: Proceedings of 2020 ASEE southeast section conference, Auburn, AL, 8–10 March 2020. Liu, Y-C. Renovation of a mechanical engineering senior design class to an industry-tied and team-oriented course. Eur J Eng Educ 2017; 42: 800-811. Liu, Y-C. Teaching continuum mechanics in mechanical engineering program. J STEM Educ Innovations Res 2011; 12: 17–23. Liu, Y-C., Artigue AJ, Sommers JD, et al. Theo Jansen project in engineering design course and a design example. Eur J Eng Educ 2011; 36: 187–198. Liu, Y-C., Baker F. A new questionnaire for assessment of a mechanical engineering senior design class. International Journal of Mechanical Engineering Education 2018. Liu, Y-C., Baker, F, He, W-P, et al. Development, assessment, and evaluation of laboratory experimentation for a mechanical vibrations and controls course. Int J Mech Eng Educ 2019; 47: 315–337. Liu, Y-C., Baker, F. (2017). A new questionnaire of a mechanical engineering senior design class. International Journal of Mechanical Engineering Education, 46(4), 289–301. https://doi.org/10.1177/0306419017749579 Liu, Y-C., Baker, F. A course assessment tool for a mechanical engineering design class. In: Proceedings of ASEE SE section annual conference, Embry-Riddle Aeronautical University, Daytona Beach, FL, 4–6 March 2018. Liu, Y-C., Baker, F. A new questionnaire for assessment of a mechanical engineering senior design class. Int J Mech Eng Educ 2018; 46: 289–301. 197 Liu, Y-C., Baker, F. Development of vibration and control systems through student projects. In: Proceedings of 2019 ASEE southeast section conference, Raleigh, NC, 10–12 March 2019. Liu, Y-C., Baker, F., He, W., & Lai, W. (2019). Development, assessment, and evaluation of laboratory experimentation for a mechanical vibrations and controls course. International Journal of Mechanical Engineering Education, 47(4), 315–337. https://doi.org/10.1177/0306419018778040 Liu, Y-C., Dou Y-Q. Design of an industry-tied and team-oriented course for mechanical engineering seniors. In: Proceedings of ASEE SE section annual conference, University of Florida, Gainesville, FL, USA, 12–14 April 2015. Liu, Y-C., Whitaker S, Hayes C, Logsdon J, McAfee L, Parker R. Establishment of an experimental-computational framework for promoting Project-based learning for vibrations and controls education. International Journal of Mechanical Engineering Education. 2022;50(1):158-175. doi:10.1177/0306419020950250 Loughry, M.; Ohland, M.; Moore, D. Development of a theory-based assessment of team member effectiveness. Educ. Psychol. Meas. 2007, 67, 505–524. [CrossRef] Lyon PM and Hendry GD. The use of the course experience questionnaire as a mon- itoring evaluation tool in a problem-based medical program. Assess Eval High Educ 2002; 27: 339–352. Lyon, P., & Hendry, G. (2002) The Use of the Course Experience Questionnaire as a Monitoring Evaluation Tool in a Problem-based Medical Programme, Assessment & Evaluation in Higher Education, 27:4, 339-352, DOI: 10.1080/0260293022000001355 Machung, A. (1998). Playing the ranking game. Change: The Magazine of Higher Learning, 30(4), 12–16. https://doi.org/10.1080/00091389809602626 Maisiri, W.; Van Dyke, L. Industry 4.0 skills: A perspective of the South African manufacturing industry. SA J. Human Resour. Manag./SA Tydskr. vir Menslikehulpbronbestuur 2021, 19, a1416. [CrossRef] Male, Sally & Bush, Mark & Chapman, Elaine. (2009). Identification of competencies required by engineers graduating in Australia. in 2009 AAEE Conference, Adelaide, 2009. Martel, M. (2021). Fall 2021 International student enrollment snapshot. Retrieved from https://www.iie.org/en/Research-and-Insights/Publications/Fall-2021-International-Student-Enrollment-Snapshot Matteson, M.L.; Anderson, L.; Boyden, C. “Soft skills”: A phrase in search of meaning. Libr. Acad. 2016, 16, 71–88. [CrossRef] 198 McAlpine, L., Skakni, I., & Inouye, K. (2021). PhD careers beyond the traditional: integrating individual and structural factors for a richer account. European Journal of Higher Education, 11(4), 365–385. https://doi.org/10.1080/21568235.2020.1870242 McMasters, J. (2005, June), Boeing University Relations A Review And Prospects For The Future Paper presented at 2005 Annual Conference, Portland, Oregon. 10.18260/1-2—14328 Meredith, M. (2004). Why do universities compete in the ratings game? An empirical analysis of the effects of the U.S. News and World Report College Rankings. Research in Higher Education, 45(5), 443–461. https://doi.org/10.1023/b:rihe.0000032324.46716.f4 Miller, R.K. Building on math and science: The new essential skill for the 21st century engineer. Res.-Technol. Manag. 2017, 60, 53–56. [CrossRef] Mitchell, G.W.; Skinner, L.B.; White, B.J. Essential Soft Skills for Success in the Twenty-First Century Workforce as Perceived by Business Educators. Delta Pi Epsil. J. 2010, 52, 43–53. Morrison, J. Environment Scanning in Education Planning: Establishing a Trend Information System. 1993. Available online: https://files.eric.ed.gov/fulltext/ED361897.pdf (accessed on 3 May 2021). Motyl, B., Baronio, G., Uberti, S., Speranza, D., & Filippi, S. (2017). How will Change the Future Engineers’ Skills in the Industry 4.0 Framework? A Questionnaire Survey. Procedia Manufacturing, 11, 1501–1509. https://doi.org/10.1016/j.promfg.2017.07.282 Nair, C.S., Patil, A., & Mertova, P. (2009) Re-engineering graduate skills – a case study, European Journal of Engineering Education, 34:2, 131-139, DOI: 10.1080/03043790902829281 National Academy of Engineering, The Engineer of 2020: Visions of Engineering in the New Century, Washington, DC: National Academies Press, 2004. National Center for Science and Engineering Statistics [NCES}. (2022). Trends in Undergraduate and Graduate S&E Awards. Retrieved from: https://ncses.nsf.gov/pubs/nsb20223/trends-in-undergraduate-and-graduate-s-e-degree-awards National Foundation for American Policy, "International Students in Science and Engineering," Arlington, VA, 2021. National Labor Exchange, "O*NET Online," U.S. Department of Labor, 30 08 2021. [Online]. Available: https://www.onetonline.org/link/jobs/17-2141.00?j=1&st=&g=Go&ps=NLX. [Accessed 30 08 2021]. 199 National Research Council, Engineering education: designing an adaptive system, Washington, DC: National Academies Press, 1995. National Research Council. (2011). A data-based assessment of research-doctorate programs in the United States. Retrieved from: https://www.nationalacademies.org/our-work/an-assessment-of-research-doctorate-programs National Science Foundation [NSF]. (2022). How many degrees are earned in engineering, and what subfields are popular? Retrieved from: https://www.nsf.gov/nsb/sei/edTool/data/engineering-01.html O’Cathain, A.; Thomas, K.J. “Any other comments?” Open questions on questionnaires—A bane or a bonus to research? BMC Med. Res. Methodol. 2004, 4, 25. [CrossRef] OECD (2021). Building the future of education. Retrieved from: https://www.oecd.org/education/future-of-education-brochure.pdf Park, C. (2005). New Variant PhD: The changing nature of the doctorate in the UK. Journal of Higher Education Policy and Management, 27(2), 189–207. https://doi.org/10.1080/13600800500120068 Passow, H.J. (2012), Which ABET Competencies Do Engineering Graduates Find Most Important in their Work?. Journal of Engineering Education, 101: 95-118. https://doi.org/10.1002/j.2168-9830.2012.tb00043.x Pejic-Bach, M., Bertoncel, T., Meško, M., & Krstić, Ž. (2020). Text mining of industry 4.0 job advertisements. International Journal of Information Management, 50, 416–431. https://doi.org/10.1016/j.ijinfomgt.2019.07.014 Peters DL and Brelin-Fornari J. Addition of lab experiences to a course in dynamic systems with vibrations. In: Proceedings of the 2016 American Society for Engineering Education annual conference & exposition, New Orleans, LO, USA, 26–29 June 2016. Pike, G. R. (2004). Measuring quality: A comparison of U.S. News Rankings and NSSE Benchmarks. Research in Higher Education, 45(2), 193–208. https://doi.org/10.1023/b:rihe.0000015695.84207.44 Pócsová, J.; Bednárová, D.; Bogdanovská, G.; Mojžišová, A. Implementation of Agile Methodologies in an Engineering Course. Educ. Sci. 2020, 10, 333. [CrossRef] Pollack E. R., Sarrafian, G. A., & Grimm, M. J. (2021). What do mechanical engineers do? A content analysis of mechanical engineer’s job description. 2021 ASEE Annual Conference, Virtual Meeting, July 26-29, 2021. Prett, M.K. Definition: Soft Skills. 2019. Available online: http://searchcio.techtarget.com/definition/soft-skills (accessed on 3 May 2021). 200 Rainsbury, E.; Hodges, D.L.; Burchell, N.; Lay, M.C. Ranking workplace competencies: Student and graduate perceptions. Asia-Pac. J. Coop. Educ. 2002, 3, 8–18. Ramsden P. A performance indicator of teaching quality in higher education: the course experience questionnaire. Stud High Educ 1991; 16: 129–150. Ramsden, P. (1991) A performance indicator of teaching quality in higher education: The Course Experience Questionnaire, Studies in Higher Education, 16:2, 129-150, DOI: 10.1080/03075079112331382944 Rezaei AG and Davari A. Teaching vibration and control courses using animation, simulation, and experimentation. In: Proceedings of the 2005 American Society for Engineering Education annual conference & exposition, Chicago, IL, USA, 18–21 June 2005. Riley, D.R.; Horman, M.J.; Messner, J.I. Embedding leadership development in construction engineering and management education. J. Prof. Issues Eng. Educ. Pract. 2008, 134, 143–151. [CrossRef] Robles, M.M. Executive perceptions of the top 10 soft skills needed in today’s workplace. Bus. Commun. Q. 2012, 75, 453–465. [CrossRef] Ross, A.; Willson, V.L. Paired Sample T-Test. In Basic and Advanced Statistical Tests; Brill: Boston, IL, USA, 2017; pp. 17–19. Ruhala R. Four free-vibration laboratory experiments using two lumped mass appara- tuses with research caliber accelerometers and analyzer. In: Proceedings of the 2010 American Society for Engineering Education annual conference & exposition, Louisville, KY, USA, 20–23 June 2010. Schulz, B. The importance of soft skills: Education beyond academic knowledge. NAWA J. Commun. 2008, 2, 146–154. Shuman, L.J., Besterfield-Sacre, M. and McGourty, J. (2005), The ABET “Professional Skills” — Can They Be Taught? Can They Be Assessed?. Journal of Engineering Education, 94: 41-55. https://doi.org/10.1002/j.2168-9830.2005.tb00828.x Spencer RE and Aleamoni LM. A student course evaluation questionnaire. J Educ Meas 1970; 7: 209–210. Spencer, R. and Aleamoni, L. (1970). A Student Course Evaluation Quesitonaire. Journal of Educational Measurement, vol. 7, no. 3, pp. 209-210. Sridhara BS and White DH. Developing experiments for the vibration course with minimal expenditure. In: Proceedings of the 2012 American Society for Engineering Education annual conference & exposition, San Antonio, TX, USA, 10–13 June 2012. 201 STEMconnector’s Innovation Task Force [SITF]. STEM 2.0: An. Imperative for Our Future Workforce, 2nd ed.; 2014. Available online: https://www.stemconnector.com/download-resource/stem-2-0/# (accessed on 3 May 2021). Stephens, M. Essential Soft Skills. Libr. J. 2013, 138, 39. Sullivan GM and Artino AR Jr. Analyzing and interpreting data from Likert-type scales. J Grad Med Educ 2013; 5: 541–542. Sweitzer, K., & Volkwein, J. F. (2009). Prestige among graduate and professional schools: comparing the U.S. News’ Graduate School Reputation Ratings Between Disciplines. Research in Higher Education, 50(8), 812–836. https://doi.org/10.1007/s11162-009-9140-0 Szatmary, A. C. (2019). Evidence for design of mechanical engineering curriculum. Paper presented at the 2019 ASEE Annual conference & Exposition, Tampa, Florida, June 15-19,2019, Paper ID 26005. https://doi.org/10.18260/1-2--32769 Taggar, S.; Brown, T.C. Problem-solving team behaviors: Development and validation of BOS and a hierarchical factor structure. Small Group Res. 2001, 32, 698–726. [CrossRef] Taylor, M. Reform the PhD system or close it down. Nature, 472, 261 (2011). https://doi.org/10.1038/472261a The Steering Committee of the National Engineering Education Research Colloquies, "The research agenda for the new discipline of engineering education," Journal of Engineering Education, vol. 95, no. 4, pp. 259-261, 2006. Toakley, A. R. (2004). Globalization, sustainable development and universities. Higher Education Policy, 17, 311–324. Toner, P. (2011). Workforce skills and innovation: An overview of major themes in the Literature. OECD Education Working Papers. No. 55. OECD Publishing. https://doi.org/10.1787/5kgk6hpnhxzq-en Toor, S.U.R.; Ofori, G. Developing construction professionals of the 21st century: Renewed vision for leadership. J. Prof. Issues Eng. Educ. Pract. 2008, 134, 279–286. [CrossRef] Torpey, E. and D. Terrel, D., "Should I get a master’s degree?," U.S. Bureau of Labor Statistics, 9 2015. [Online]. Available: https://www.bls.gov/careeroutlook/2015/article/should-i-get-a-masters-degree.htm. [Accessed 9 2021]. Touloumakos, A.K. Expanded Yet Restricted: A Mini Review of the Soft Skills Literature. Front. Psychol. 2020, 11, 2207. [CrossRef] Trans. Gis 2014, 19, 641–652. [CrossRef] 202 Turner, J., & Baker, R. (2016). Updating performance improvement’s knowledge base: A call to resesarchers and practitioners using Gilbert’s behavior engineering model as an example. Performance Improvement, 55(6), 7–12. https://doi.org/10.1002/pfi.21590 Wachtel HK. Student evaluation of college teaching effectiveness: a brief review. Assess Eval High Educ 1998; 23: 191–212. Ward, A.E., Baruah, B., Gbadebo, A., Jackson, N.J. (2017). What do job adverts tell Higher Education about the ‘shape’ of Biomedical Engineering Graduates?. In: Vlad, S., Roman, N. (eds) International Conference on Advancements of Medicine and Health Care through Technology; 12th - 15th October 2016, Cluj-Napoca, Romania. IFMBE Proceedings, vol 59. Springer, Cham. https://doi.org/10.1007/978-3-319-52875-5_10 Warnock, J. N., & Mohammadi-Aragh, M. J. (2016). Case study: Use of problem-based learning to develop students’ technical and professional skills. European Journal of Engineering Education, 412), 142–153. https://doi.org/10.1080/03043797.2015.1040739 Washington State Human Resource Council. Employer Perspectives on Soft Skills: 2014 Survey Report. Available on- line: https://wastatecouncil.shrm.org/sites/wastatecouncil.shrm.org/files/Soft%20Skill%20Survey%20Rpt%20-%20Sum%20 of%20Findings%20-%20031615.pdf (accessed on 3 May 2021). Weber, M.R.; Finley, D.A.; Crawford, A.; Rivera, D. An exploratory study identifying soft skills competencies in entry-level managers. Tour. Hosp. Res. 2009, 9, 353–361. [CrossRef] Whiteman, W.E. (2003). Mechanical engineering curricula; a baseline study for the future effects of ABET EC2000. International Journal of Mechanical Engineering Education, vol. 21, no. 4, pp. 327-338. Wikle, T.A.; Fagin, T.D. Hard and soft skills in preparing GIS professionals: Comparing perceptions of employers and educators. Williams, R., & Van Dyke, N. (2007). Reputation and reality: ranking major disciplines in Australian universities. Higher Education, 56(1), 1–28. https://doi.org/10.1007/s10734-007-9086-0 Wilson KL, Lizzio A and Ramsden P. The development, validation and application of the Course Experience Questionnaire. Stud High Educ 2006; 22: 33–53. Wilson, K., Lizzio, A., & Ramsden, P. (1997) The development, validation and application of the Course Experience Questionnaire, Studies in Higher Education, 22:1, 33-53, DOI: 10.1080/03075079712331381121 Windels, K.; Mallia, K.L.; Broyles, S.J. Soft skills: The difference between leading and leaving the advertising industry? J. Advert. Educ. 2013, 17, 17–27. [CrossRef] 203 Wong, K. V. (2016). Global college rankings. Journal of Modern Mechanical Engineering and Technology, 3(1), 1–6. World Economic Forum. Building a Common Language for Skills at Work: A Global Taxonomy. 2021. Available online: http://www3.weforum.org/docs/WEF_Skills_Taxonomy_2021.pdf (accessed on 29 July 2021). World Economic Forum. Centre for the New Economy and Society: Chief Economists Outlook. 2021. Available online: http://www3.weforum.org/docs/WEF_Chief_Economists_Outlook_June_2021.pdf (accessed on 29 July 2021). World Economic Forum. Digital Culture: The Driving Force of Digital Transformation. 2021. Available online: http://www3.weforum.org/docs/WEF_Digital_Culture_Guidebook_2021.pdf (accessed on 29 July 2021). World Economic Forum. Technology Futures: Projecting the Possible, Navigating What’s Next. 2021. Available online: http://www3.weforum.org/docs/WEF_Technology_Futures_GTGS_2021.pdf (accessed on 29 July 2021). Yeung, R., Gigliotti, P., & Nguyen-Hoang, P. (2018). The impact of U.S. News College Rankings on the compensation of college and university presidents. Research in Higher Education, 60(1), 1–17. https://doi.org/10.1007/s11162-018-9501-7 Zappe, S., Litzinger, T., & Nguyen, H. (2010). An investigation of first year students’ perceptions of global awareness. 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