The DOI matches its Crossref record; 116 of the 116 references it cites were found in a registry or an index.
Extending the technology acceptance model (TAM) to predict university students’ intentions to use metaverse-based learning platforms
Open accessAbstract
Metaverse, which combines a number of information technologies, is the Internet of the future. A media for immersive learning, metaverse could set future educational trends and lead to significant reform in education. Although the metaverse has the potential to improve the effectiveness of online learning experiences, metaverse-based educational implementations are still in their infancy. Additionally, what factors impact higher education students' adoption of the educational metaverse remains unclear. Consequently, the aim of this study is to explore the main factors that affect higher education students' behavioral intentions to adopt metaverse technology for education. This study has proposed an extended Technology Acceptance Model (TAM) to achieve this aim. The novelty of this study resides in its conceptual model, which incorporates both technological, personal, and inhibiting/enabling factors. The empirical data were collected via online questionnaires from 574 students in both private and public universities in Jordan. Based on the PLS-SEM analysis, the study identifies perceived usefulness, personal innovativeness in IT, and perceived enjoyment as key enablers of students' behavioral intentions to adopt the metaverse. Additionally, perceived cyber risk is found as the main inhibitor of students' metaverse adoption intentions. Surprisingly, the effect of perceived ease of use on metaverse adoption intentions is found to be insignificant. Furthermore, it is found that self-efficacy, personal innovativeness, and perceived cyber risk are the main determinants of perceived usefulness and perceived ease of use. While the findings of this study contribute to the extension of the TAM model, the practical value of these findings is significant since they will help educational authorities understand each factor's role and enable them to plan their future strategies.
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“They also aligned with evidence from mobile learning research showing that positive attitudes can strengthen students’ intention to use new technologies [91].”
From Advancing Undergraduate Student Mental Healthcare of Social Anxiety Disorder: Evaluating the Acceptance of AR-Assisted Cognitive Behavioral Therapy Through TAM-Based Constructs. (2026) · cites this paper as [91]
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Cited by
Sorted by citations
Exploring User Adoption of ChatGPT: A Technology Acceptance Model Perspective
Ma, J., Wang, P., Li, B., Wang, T., Pang, X. S., & Wang, D. (2024) · International Journal of Human-Computer Interaction · doi:10.1080/10447318.2024.2314358 · Cited by 308
“While this study did not consider variables such as initial trust, perceived risk, and anthropomorphic traits within the TAM framework (Al-Adwan et al., 2023; Quan et al., 2023), it is critical to acknowledge the importance of these factors in prior research.”
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Metadata
- Authors
- Al-Adwan, A. S., Li, N., Al-Adwan, A., Abbasi, G. A., Albelbisi, N. A., & Habibi, A.
- Affiliations
- Xi’an Jiaotong-Liverpool University (CN)
- Al-Ahliyya Amman University (JO)
- King Fahd University of Petroleum and Minerals (SA)
- University of Malaya (MY)
- Universitas Jambi (ID)
- Corresponding author
- Al-Adwan, Amer
- ORCID
- Venue
- Education and Information Technologies
- Published
- 2023-04-28
- Volume
- 28
- Issue
- 11
- Pages
- 15381-15413
- ISSN
- 1360-2357 (ISSN-L)
- 1573-7608
- PMC
- PMC10140721
- OpenAlex
- W4367316498
- Cited by
- 637
- References
- 116
- Citations by year
- 2026: 169 · 2025: 244 · 2024: 191 · 2023: 33
- FWCI
- 732.78
- Type
- book chapter
- Language
- en
- Update notices
- correction (2023-06-02)
- Open access
- hybrid
- doi.org
- Locations
- Education and Information Technologies (publishedVersion, cc-by)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- Figshare (submittedVersion, cc-by)
- Funders
- Hamad bin Khalifa University
- Topics
- Social Sciences › Decision Sciences › Information Systems and Management › Technology Adoption and User Behaviour
- Social Sciences › Education › Education and Learning Interventions
- Social Sciences › Education › Online and Blended Learning
- Keywords
- metaverse, technology acceptance model, technology adoption, behavioral intention, university students, perceived usefulness, perceived ease of use, perceived enjoyment, personal innovativeness, self-efficacy, immersive learning, online learning
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