The DOI matches its Crossref record; 8 of the 8 references it cites were found in a registry or an index.
Technology Acceptance Model in M-learning context: A systematic review
Abstract
Abstract Various review studies were conducted to provide valuable insights into the current research trend of the Technology Acceptance Model (TAM). Nevertheless, this issue still needs to be investigated from further directions. It has been noticed that research overlooks the investigation of TAM with regard to Mobile learning (M-learning) studies from the standpoint of different perspectives. The present study systematically reviews and synthesizes the TAM studies related to M-learning aiming to provide a comprehensive analysis of 87 research articles from 2006 to 2018. The main findings include that most of the TAM studies involving M-learning focused on extending the TAM with external variables, followed by the studies that extended the model by factors from other theories/models. In addition, the main research problem that was frequently tackled among all the analyzed studies was to examine the acceptance of M-learning among students. Moreover, questionnaire surveys were the primarily relied research methods for data collection. Additionally, most of the analyzed studies were undertaken in Taiwan, this is followed by Spain, China, and Malaysia, respectively among the other countries. Besides, most of the analyzed studies were frequently conducted in humanities and educational context, followed by IT and computer science context, respectively among the other contexts. Most of the analyzed studies were carried out in the higher educational settings. To that end, the findings of this review study provide an insight into the current trend of TAM research involving M-learning studies and form an essential reference for scholars in the M-learning context.
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Citations
Cites
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Cited by
Scherer, R., Siddiq, F., & Tondeur, J. (2019) · Computers & Education · doi:10.1016/j.compedu.2018.09.009 · Cited by 1,923
Technology acceptance model in educational context: A systematic literature review
Granić, A., & Marangunić, N. (2019) · British Journal of Educational Technology · doi:10.1111/bjet.12864 · Cited by 1,204
Salloum, S. A., Qasim Mohammad Alhamad, A., Al-Emran, M., Abdel Monem, A., & Shaalan, K. (2019) · IEEE Access · doi:10.1109/access.2019.2939467 · Cited by 651
Self-citationAl-Adwan, A. S., Li, N., Al-Adwan, A., Abbasi, G. A., Albelbisi, N. A., & Habibi, A. (2023) · Education and Information Technologies · doi:10.1007/s10639-023-11816-3 · Cited by 637
“In particular, the TAM has witnessed an increased level of use by scholars for the purpose of predicting learners’ acceptance of learning technologies (Shen et al., 2022; Al-Adwan, 2020; Al-Emran et al., 2018).”
BackgroundLiu, G., & Ma, C. (2024) · Innovation in Language Learning and Teaching · doi:10.1080/17501229.2023.2240316 · Cited by 511
Metadata
- Authors
- Al-Emran, M., Mezhuyev, V., & Kamaludin, A.
- Venue
- Computers & Education
- Publisher
- Elsevier BV
- Published
- 2018-10
- Volume
- 125
- Pages
- 389-412
- ISSN
- 0360-1315 (ISSN-L)
- OpenAlex
- W2805740843
- Cited by
- 628
- References
- 8
- FWCI
- 11.52
- Type
- journal article
- Language
- en
- Open access
- closed
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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.