Assessing Current Instructional Practices In General Biology One (Bio1010) And Arguing For A Model-Centered Curriculum

This collected papers dissertation focused on the argument for the need to adapt and develop a model-centered General Biology I course through the analyses of current instructional practices at a large, public, Hispanic-serving university. This dissertation included a comparison of General Biology I course sections taught in two differing formats, one is a traditional lecture with face-to-face meetings and the other is an online instruction setting. The comparison of these sections was accomplished through the use of a conceptual inventory, student attitude survey, drop-fail-withdraw (DFW) rates, and Social Network Analysis. This comparison found that there was no detectible significant difference between course type for both the conceptual understanding and formation of student-to-student networks. It was also found that there was a significant difference between course type when looking at students’ attitudes towards Biology and success in the two course types. Additionally in a second study the project used a phenomoenographic analysis of student interviews that explored the students’ use of scientific models when asked about plant cells and animal cells. It was found that during the analysis of students’ ideas that students predominantly used a single model function. The cell types of focus in the second study were two models that were identified, in a third study, through a coded analysis of faculty interviews and textbook analysis. These models are viewed as essential for students to possess an understanding of upon completion of General Biology I. The model-based course that this study argued for is based on a curricular framework initially developed for use in introductory physics courses. University Modeling Instruction courses in physics (UMI-P) have been linked to improved student conceptual understanding positive attitudinal shifts, and decreased DFW rates. UMI, however, has not been expanded for implementation within the other science disciplines. Drawing from the success of UMI within physics this dissertation focused on the argument for the need for the adaptation and development of UMI for introductory biology