Identifying technology leadership competencies for Nebraska\u27s K–12 technology leaders

The role of K–12 school technology leadership is complex and varied. It requires a person with diverse skills and abilities who can provide guidance to teachers, administrators, and Boards of Education who are involved in the purchase and implementation of technology for schools. The newness of the role in education makes it virtually impossible for one to already have expertise in all aspects of this position, yet very little attention has been given to the formal preparation of the technology leader. Using the competencies recommended by the International Society for Technology in Education (ISTE), Nebraska technology leaders rated the competencies based on the level of importance to their position and their overall proficiency level of applying those competencies. Technology leaders also identified the predominant learning method, formal or self-directed, in which they acquired the majority of the competencies and rated the level of effectiveness for that learning method. Descriptive statistics and repeated-measure one-way ANOVA\u27s were used to analyze the data. Due to the number of tests run to identify significant differences between competency constructs, the alpha level of .05 was adjusted to .0009 using the Bonferrioni method. The analysis showed multiple significant differences between the levels of importance placed on the constructs recommended by ISTE. Competencies in the area of Staff Development were identified to be most important throughout all forms of analysis. The perceived level of proficiency in applying the competencies, on a four-point Likert scale of Not Proficient (1) to Very Proficient (4), reported a mean of 2.68. Ninety-five percent of the respondents indicated the predominant learning method to be self-directed, while the effectiveness of that learning method, on a 4-point Likert scale of Not Effective ( 1) to Very Effective (4), had a mean of 2.98. The level of importance placed on competencies were fairly consistent when construct means were compared to the (1) age of the respondent, (2) years of experience as a technology leader, (3) classification of school district, and (4) highest degree earned