Baltimore , Maryland
June 25, 2023
June 25, 2023
June 28, 2023
Software Engineering Division (SWED)
Diversity
28
10.18260/1-2--43991
https://peer.asee.org/43991
265
Elise has a BS in Computer Science and PhD in STEM Education. Her thesis was on interdisciplinary, collaborative computing using mixed methodologies. Elise combines her decade of teaching experience with her research background to create evidence-based computing education tools in her current role at Codio.
Megan McHugh has a BA in Communication and MA in Integrated Marketing Communications. With the perspective of a career centered in private sector technology and cybersecurity, she greatly values the contributions made by EdTech organizations, like Codio, to help faculty deliver better learning outcomes in CS and STEM for students of every level.
Despite the high volume of existing Computer Science Education research, the literature indicates that these evidence-based practices are not making their way into classrooms. While K12 faces pressures from policy and increasing opportunities through professional development to learn these best practices, Higher Education does not have the same accelerants. This paper proposes a variant on a response hierarchy model from marketing literature to illustrate how faculty become aware of and choose to adopt pedagogical interventions. We pose a series of research questions to refine the proposed model. We investigate if the volume of research about an intervention predicts faculty awareness of it. We ask if particular experienced and perceived challenges and benefits of a given intervention affect an intervention’s overall perceived level of benefit or challenge. We then look at which of these variables can predict intent and actual implementation of interventions. Finally, we considered confounding variables such as the unconscious influence of research results and demographic factors to see if there were aspects unaccounted for by the proposed model. We collected survey data from over 100 faculty members who teach CS in the United States and ran linear regressions, ANOVAs, and Welch’s t-tests, to address our wide range of research questions. Our results suggest that a simplified response hierarchy model holds explanatory power for illustrating how faculty members become aware of and choose to adopt evidence-based teaching interventions. We also found a lack of demographic confounding variables and re-produced that faculty, despite being researchers, are not swayed by education study results. By providing an evidence-based model for how faculty adopt teaching interventions, we offer new insights into how to effectively disseminate research results in a manner that increases the likelihood that the associated teaching interventions are adopted.
Deitrick, E., & Ball, J., & McHugh, M. (2023, June), Proposing a Response Hierarchy Model to Explain How CS Faculty Adopt Teaching Interventions in Higher Education Paper presented at 2023 ASEE Annual Conference & Exposition, Baltimore , Maryland. 10.18260/1-2--43991
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