The DOI matches its Crossref record; 1 of the 1 references it cites were found in a registry or an index.
A path analysis of pre-service teachers' attitudes to computer use: applying and extending the technology acceptance model in an educational context
Abstract
The purpose of this study is to examine pre-service teachers' attitudes to computers. This study extends the technology acceptance model (TAM) framework by adding subjective norm, facilitating conditions, and technological complexity as external variables. Results show that the TAM and subjective norm, facilitating conditions, and technological complexity were significant determinants of pre-service attitudes to computer use. A multiple square correlation revealed that the proposed model in this study explained 48.7% of the attitude to computer use. Various contributions to research and practice are discussed.
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Cites
User Acceptance of Information Technology: Toward A Unified View1
Venkatesh, V., Morris, M. G., Davis, G. B., & Davis, F. D. (2003) · MIS Quarterly · doi:10.2307/30036540 · Cited by 45,035
Cited by
Modelling technology acceptance in education: A study of pre-service teachers
Teo, T. (2009) · Computers & Education · doi:10.1016/j.compedu.2008.08.006 · Cited by 1,009
Self-citationTarhini, A., Hone, K., Liu, X., & Tarhini, T. (2017) · Interactive Learning Environments · doi:10.1080/10494820.2015.1122635 · Cited by 445
Pan, X. (2020) · Frontiers in Psychology · doi:10.3389/fpsyg.2020.564294 · Cited by 329
“In the TAM (Davis et al., 1989), individuals’ attitude toward using technology (Teo, 2010, 2012; Jan and Contreras, 2011) was significantly predicted by perceived usefulness and ease of use of technology, which was in turn hypothesized to affect their behavioral intention to use technology and…”
BackgroundTeo, T. (2010) · Asia Pacific Education Review · doi:10.1007/s12564-009-9066-4 · Cited by 226
Self-citationGupta, K., & Arora, N. (2019) · South Asian Journal of Business Studies · doi:10.1108/sajbs-03-2019-0037 · Cited by 208
Sánchez-Prieto, J. C., Olmos-Migueláñez, S., & García-Peñalvo, F. J. (2016) · Computers in Human Behavior · doi:10.1016/j.chb.2015.07.002 · Cited by 205
Hsu, L. (2016) · Computer Assisted Language Learning · doi:10.1080/09588221.2016.1278024 · Cited by 164
Wang, F., King, R. B., Chai, C. S., & Zhou, Y. (2023) · International Journal of Educational Technology in Higher Education · doi:10.1186/s41239-023-00417-2 · Cited by 124
“First, our findings highlight the importance of creating a supportive environment that emphasizes the importance of AI and offers adequate technology resources and technical assistance to foster students’ intentions to learn AI ( Teo, 2010).”
BackgroundModeling Key Drivers of E-Learning Satisfaction among Student Teachers
Teo, T., & Wong, S. L. (2013) · Journal of Educational Computing Research · doi:10.2190/ec.48.1.d · Cited by 77
Self-citationTeacher knowledge for using technology to foster early literacy: a literature review
Belo, N., McKenney, S., Voogt, J., & Bradley, B. (2016) · Computers in Human Behavior · doi:10.1016/j.chb.2016.02.053 · Cited by 41
Metadata
- Authors
- Teo, T.
- Venue
- Interactive Learning Environments
- Publisher
- Informa UK Limited
- Published
- 2010-03
- Volume
- 18
- Issue
- 1
- Pages
- 65-79
- ISSN
- 1049-4820 (ISSN-L)
- 1744-5191
- OpenAlex
- W1986842164
- Cited by
- 297
- References
- 1
- FWCI
- 15.01
- 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).
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