Extending the Technology Acceptance Model (TAM) to Predict University Students’ Intentions to Use Metaverse-Based Learning Platforms

• Published in: Education and information technologies 2023-11, Vol.28 (11), p.15381-15413
• Main Authors: Al-Adwan, Ahmad Samed, Li, Na, Al-Adwan, Amer, Abbasi, Ghazanfar Ali, Albelbisi, Nour Awni, Habibi, Akhmad
• Format: Article
• Language: English
• Subjects: Adoption (Ideas); College Students; Computer Appl. in Social and Behavioral Sciences; Computer Science; Computers and Education; Distance learning; Education; Education, Higher; Educational Change; Educational Technology; Educational Trends; Electronic Learning; Foreign Countries; Higher education; Information Systems Applications (incl.Internet); Information Technology; Intention; Online education; Private Colleges; Public Colleges; Self Efficacy; Student Attitudes; Student Behavior; Technology Acceptance Model; Technology Uses in Education; University students; User Interfaces and Human Computer Interaction
• ISSN: 1360-2357; 1573-7608
• DOI: 10.1007/s10639-023-11816-3

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.