The DOI matches its Crossref record; 52 of the 52 references it cites were found in a registry or an index.
Faculty Perceptions about Teaching Online: Exploring the Literature Using the Technology Acceptance Model as an Organizing Framework
Open accessAbstract
Academic leaders can better implement institutional strategic plans to promote online programs if they understand faculty perceptions about teaching online. An extended version of a model for technology acceptance, or TAM2 (Venkatesh & Davis, 2000), provided a framework for surveying and organizing the research literature about factors that have influenced faculty’s adoption of online delivery methods for courses and their willingness to continue to teach online. This paper presents the results of a synthesis of 67 empirical studies about faculty teaching online published between 1995 and 2015, using TAM2 constructs as an organizing framework. This validated model provided a lens for understanding research about faculty perceptions of the user-friendliness and ease of use of technology for online course delivery, as well as the overall experience of teaching online. Studies in this review revealed concerns among faculty regarding their perceived barriers to student success in online classes, uncertainty about their image as online instructors, technical support needs, and their desire for reasonable workload and manageable class enrollments in online classes.
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Cites
Perceived usefulness, perceived ease of use, and user acceptance of information technology
Davis, F. D. (1989) · MIS Quarterly · doi:10.2307/249008 · Cited by 68,483
A Theoretical Extension of the Technology Acceptance Model: Four Longitudinal Field Studies
Venkatesh, V., & Davis, F. D. (2000) · Management Science · doi:10.1287/mnsc.46.2.186.11926 · Cited by 23,066
Computer Self-Efficacy: Development of a Measure and Initial Test
Compeau, D. R., & Higgins, C. A. (1995) · MIS Quarterly · doi:10.2307/249688 · Cited by 6,553
A Model of the Antecedents of Perceived Ease of Use: Development and Test
Venkatesh, V., & Davis, F. D. (1996) · Decision Sciences · doi:10.1111/j.1540-5915.1996.tb01822.x · Cited by 3,802
A Model of the Antecedents of Perceived Ease of Use: Development and Test
Venkatesh, V., & Davis, F. D. (1996) · Decision Sciences · doi:10.1111/j.1540-5915.1996.tb00860.x · Cited by 3,792
Davis, F. D. (1993) · International Journal of Man-Machine Studies · doi:10.1006/imms.1993.1022 · Cited by 2,964
A meta-analysis of the technology acceptance model
King, W. R., & He, J. (2006) · Information & Management · doi:10.1016/j.im.2006.05.003 · Cited by 2,906
Technology acceptance model: a literature review from 1986 to 2013
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Cited by
Merhi, M., Hone, K., & Tarhini, A. (2019) · Technology in Society · doi:10.1016/j.techsoc.2019.101151 · Cited by 555
Elshami, W., Taha, M. H., Abuzaid, M., Saravanan, C., Al Kawas, S., & Abdalla, M. E. (2021) · Medical Education Online · doi:10.1080/10872981.2021.1920090 · Cited by 346
Moralista, R. B., & F. Oducado, R. M. (2020) · Universal Journal of Educational Research · doi:10.13189/ujer.2020.081044 · Cited by 253
“ChatGPT seems too good to be true”: College students’ use and perceptions of generative AI
Baek, C., Tate, T., & Warschauer, M. (2024) · Computers and Education: Artificial Intelligence · doi:10.1016/j.caeai.2024.100294 · Cited by 306
Mirata, V., Hirt, F., Bergamin, P., & van der Westhuizen, C. (2020) · International Journal of Educational Technology in Higher Education · doi:10.1186/s41239-020-00209-y · Cited by 135
Metadata
- Authors
- Wingo, N. P., Ivankova, N. V., & Moss, J. A.
- Venue
- Online Learning
- Publisher
- The Online Learning Consortium
- Published
- 2017-03-21
- Volume
- 21
- Issue
- 1
- ISSN
- 1092-8235 (ISSN-L)
- 2472-5730
- 2472-5749
- OpenAlex
- W2601662722
- Cited by
- 328
- References
- 52
- FWCI
- 86.24
- Type
- journal article
- Language
- en
- Open access
- diamond
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- Wingo, N. P., Ivankova, N. V., & Moss, J. A. (2017). Faculty Perceptions about Teaching Online: Exploring the Literature Using the Technology Acceptance Model as an Organizing Framework. Online Learning. https://doi.org/10.24059/olj.v21i1.761
Data sources
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.
