The DOI matches its Crossref record; 16 of the 16 references it cites were found in a registry or an index.
Institutional drivers and barriers to faculty adoption of blended learning in higher education
Abstract
Relatively little research on blended learning ( BL ) addresses institutional adoption, although such research would benefit institutions of higher education in strategically adopting and implementing BL . In a prior study, the authors proposed a framework for institutional BL adoption, identifying three stages: (1) awareness/exploration, (2) adoption/early implementation, and (3) mature implementation/growth. The framework also identified key strategy, structure and support issues universities may address at each stage. The current study applies that framework as well as Rogers' diffusion of innovations theory to determine the degree to which institutional strategy, structure and support decisions facilitate or impede BL adoption among higher education faculty. The authors also explore whether faculty members' innovation adoption category (innovator, early adopter, early majority, late majority or laggard) affects which decisions facilitate or impede BL adoption. To achieve these objectives, the authors surveyed 214 faculty members at a university in the adoption/early implementation stage, Brigham Young University‐Idaho. We found that the availability of sufficient infrastructure, technological support, pedagogical support, evaluation data and an institution's purpose for adopting BL would most significantly influence faculty adoption. We also identified a wide range of factors that would influence each category of innovation adopters.
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Self-citationBlended Learning in Higher Education: Framework, Principles, and Guidelines
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A framework for institutional adoption and implementation of blended learning in higher education
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Self-citationBlended learning in higher education: Institutional adoption and implementation
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Self-citationEmerging Practice and Research in Blended Learning
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Self-citationA time‐based blended learning model
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Anthony, B., Kamaludin, A., Romli, A., Raffei, A. F. M., Phon, D. N. A. L. E., Abdullah, A., & Ming, G. L. (2022) · Technology, Knowledge and Learning · doi:10.1007/s10758-020-09477-z · Cited by 312
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Metadata
- Authors
- Porter, W. W., & Graham, C. R.
- Venue
- British Journal of Educational Technology
- Publisher
- Wiley
- Published
- 2015-04-08
- Volume
- 47
- Issue
- 4
- Pages
- 748-762
- ISSN
- 0007-1013 (ISSN-L)
- 1467-8535
- OpenAlex
- W1606183485
- Cited by
- 277
- References
- 16
- FWCI
- 61.16
- Type
- journal article
- Language
- en
- Open access
- closed
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Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.