Testing and Validating a Faculty Blended Learning Adoption Model
Bibliographic Data
| ID | 22163305 |
|---|---|
| Authors | Ahmed Antwi-Boampong (0000-0003-2887-2807, Aalborg University, corresponding author) |
| Year | 2022 |
| Volume | 7 |
| Publication date | 2022-04-06 |
| Open Access | Yes |
| Type | ARTICLE |
| Venue | Frontiers in Education (JOURNAL) |
| Journal identifiers | ISSN: 2504-284X • E-ISSN: 2504-284X |
| Publisher | Frontiers Media SA (PUBLISHER • CH) |
| DOI | 10.3389/feduc.2022.851921 |
| OpenAlex | W4226369042 |
| Language | EN |
| References cited | 63 |
Faculty members are crucial to Blended Learning’s success in higher education. Despite substantial research into the elements that drive faculty adoption of BL, few have developed a model to explain how these factors combine and influence faculty intentions to teach in this mode. This study used data collected from 207 professors from 18 universities across Africa, the United States, Europe, and the Middle East to test and validate a Faculty Blended Learning Adoption Model which was derived from a Grounded Theory study. Four model constructs (institutional hygiene readiness, student BL disposition, faculty technology ready, and Pedagogy Technology Fit for BL) mediated by motivation were tested to predict faculty Blended Learning adoption using structural equation modeling. The results demonstrated an excellent model fit, with three of the six hypotheses in this study being supported. Faculty desire to utilize BL was found to be influenced by faculty technology readiness and task technology fit for BL, but not by institutional hygiene readiness or student BL disposition. This research presents a useful model for university administrators to use in their BL implementations. A thorough understanding of this model can assist decision-makers in identifying the factors that influence future faculty acceptance or resistance to blended learning, as well as helping them in enhancing acceptance and usage
Blended Learning · Disposition · Educational technology · Higher education · Implementation · Knowledge management · Mathematics education · Medical education · Pedagogy · Political science · Structural equation modeling · Technology Acceptance Model · Computer Science · Innovative Teaching and Learning Methods · Medicine · Online and Blended Learning · Psychology · Social Psychology · Technology-Enhanced Education Studies
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| Highly cited | No |
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