New Orleans, Louisiana
June 26, 2016
June 26, 2016
August 28, 2016
Educational Research and Methods
This research paper examines the decisional balance that faculty encounter when choosing to adopt evidence-based instructional practices. Several models, such as the Concerns-Based Adoption Model (CBAM) and Diffusion of Innovation (DOI), have identified stages in the process where faculty choose to adopt and persist using alternative teaching approaches. While several studies have identified the common barrier to this adoption, there has been little examination regarding the decisional balance between these restricting factors and those that drive faculty to utilize the instructional approach. Applying a quantitative methodology, this study examines the following research questions: 1) How do faculty perceive the balance between driving and restricting factors to implement active learning, 2) What professional demographics are significant factors for the implementation of active learning instructional practices. The study presented in this paper utilizes quantitative data from a survey distributed to faculty in the College of Engineering at a medium sized STEM focused institution. The survey utilized a force-field analysis methodology that required respondents to relatively rate driving and restricting factors using a Likert scale. The driving and restricting factors included in these items were identified from prior studies and interviews with the respondents prior to survey development. Additional items included the usage of commonly referenced evidence-based instructional practices and faculty professional demographics. The survey had an overall response rate of 75% with a reliability of .82. Analyses included a scoring of decisional balance that identified if respondents were more toward or against the implementation of active learning and a factor analysis that identified which driving and restricting factors and faculty demographics significantly impacted the usage of active learning. Despite a majority of participants weighting items in favor of active learning implementation, less faculty identified usage of the instructional practice. Departmental culture, academic rank, and student academic level were identified as being the strongest predictors towards active learning usage, whereas class time and class setting restricted usage. These findings suggest further opportunity for active learning implementation that will overcome the significant barriers and enhance the driving factors.
Pembridge, J. J., & Jordan, K. L. (2016, June), Balancing the Influence of Driving and Restricting Factors to Use Active Learning Paper presented at 2016 ASEE Annual Conference & Exposition, New Orleans, Louisiana. 10.18260/p.27281
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