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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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“These results highlight the importance of aligning digital technologies with students’ academic and sustainability goals, reinforcing the theoretical assumption that relevance enhances perceived value and functional utility within TAM [ 5, 98 ] .”
Firnanda, F. A., & Sukarmin, S. (2026) · Indonesian Journal of Science and Mathematics Education · doi:10.24042/ijsme.v9i2.31931
Kiswanto, E., & Maududy, R. (2026) · Indonesian Journal of Multidisciplinary on Social and Technology · doi:10.69693/ijmst.v4i3.11528
Soffer-Vital, S., Awad, N., Kaloti-Hallak, F., Horenstein, V., Ronen, H., & Atzmon, G. L. (2026) · Teaching and Teacher Education · doi:10.1016/j.tate.2026.105763
Petridou, E., Vaiopoulou, J., Μαντελάκη, Φ., Molohidis, A., & Hatzikraniotis, E. (2026) · Education Sciences · doi:10.3390/educsci16081233
Alrefaee, Y. M. H., & Al-Shammari, A. H. (2026) · Discover Education · doi:10.1007/s44217-026-01944-6 · Cited by 1
“Al-Adwan et al. [2] demonstrated in their study “Immersive Learning Meets Theory: Modeling Eduverse Adoption in Higher Education” that traditional acceptance models require contextualization when applied to emerging technologies in specialized professional or educational settings.”
Nurfadilla, R., Zafrullah, Putra, M. A. I. P., Hatimah, K., Suardi, I. K., & Najib, M. I. (2026) · Jurnal Penelitian Pendidikan IPA · doi:10.29303/jppipa.v12i7.15090
Kumari, G. G., Alharthi, S., & Singh, P. (2026) · European Journal of Education · doi:10.1111/ejed.70806
Identifying at-Risk Students in Educational Metaverse Using TAM and Data Analysis
Naimi, E., & Abed, M. (2026) · Future education and learning spaces · doi:10.1007/978-981-95-8852-7_18
Bhaskar, P., Mughairi, H. A., & Riyami, T. K. A. (2026) · Quality & Quantity · doi:10.1007/s11135-026-03035-y
Sucipto, Kristianto, V. A., Budi, L., & Sofian, F. (2026) · MATEC Web of Conferences · doi:10.1051/matecconf/202642303005
“First, digital learning experience reflects students' psychological and evaluative experience when interacting with a digital learning ecosystem — for example, perceived usefulness, enjoyment, satisfaction and wellbeing, and anxiety — which influence continuance intention and use [1, 2, 13, 15].”
From Algorithm to ESL Education: Theoretical Foundation
Alkindi, A. (2026) · Springer eBooks · doi:10.1007/978-981-95-9563-1_5
Zhang, L., Du, Y., & Li, Y. (2026) · Frontiers in Psychology · doi:10.3389/fpsyg.2026.1869785
Sustainable Education with Metaverse Based Language Teaching
Raman, K., Wong, W. L., & Khairuddin, N. I. (2026) · English language education · doi:10.1007/978-3-032-31366-9_11
Lokito, A. G., Kuang, T. M., & Setiawan, S. (2026) · Jurnal Akuntansi · doi:10.24912/ja.v30i2.3730
“While prior studies have largely treated TAM as a technology-centric model (Al-Adwan et al., 2023; Songkram & Osuwan, 2022; Zhou et al., 2022), this study incorporates both individual learning characteristics and domain-specific beliefs to more precisely capture how students form intentions to…”
Gosain, S., & Gosain, K. (2026) · Knowledge and Process Management · doi:10.1002/kpm.70148
Jang, Y.-T. J. (2026) · Education and Information Technologies · doi:10.1007/s10639-026-14138-2
“More recently, empirical studies have also revealed PE’s positive influence on the adoption of AI-assisted learning applications (Khoa & Tran, 2024 ; Wang et al., 2025 ; Xu & Thien, 2025 ) and metaverse-based learning platforms (Al-Adwan et al., 2023 ).”
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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