Instructional technologies can be effective tools to foster student engagement, but university faculty may be reluctant to integrate innovative and evidence-based modern learning technologies into instruction. It is important to identify the factors that influence faculty adoption of instructional technologies in the teaching and learning process. Based on Rogers' diffusion of innovation theory, this quantitative, nonexperimental, one-shot cross-sectional survey determined what attributes of innovation (relative advantage, compatibility, complexity, trialability, and observability) predict the probability of faculty adopting the audience response system (ARS) into instruction. The sample for the study consisted of 201 faculty who have current teaching appointments at a university in the southeastern United States. Binary logistic regression analysis was used to determine the attributes of innovation that predict the probability of faculty adopting the ARS into instruction. The data indicated that the attributes of compatibility and trialability significantly predicted faculty adoption of ARS into instruction. Based on the results of the study, a professional development project that includes 3 full days of training and experiential learning was designed to assist faculty in adopting ARS into instruction. Because the current study only included the faculty at a single local university, future studies are recommended to explore a more holistic view of the problem from different institutions and from other stakeholders who may contribute to the process of instructional technology adoption. The project not only contributes to solving the local problem in ARS adoption, but it is also instrumental in promoting positive social change by fostering evidence-based teaching strategies and innovations that maximize student learning.
| Identifer | oai:union.ndltd.org:waldenu.edu/oai:scholarworks.waldenu.edu:dissertations-2528 |
| Date | 01 January 2015 |
| Creators | Chan, Tan Fung Ivan |
| Publisher | ScholarWorks |
| Source Sets | Walden University |
| Language | English |
| Detected Language | English |
| Type | text |
| Format | application/pdf |
| Source | Walden Dissertations and Doctoral Studies |
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