Technology Acceptance in Metaverse-Enhanced Education

The metaverse offers a convergence of virtual and augmented reality, persistent 3D environments and social interaction tools, poised to transform educational practice. Technology acceptance in this context examines how learners and educators come to adopt and sustain use of these immersive platforms. Foundational models such as the Technology Acceptance Model (TAM) and the Unified Theory of Acceptance and Use of Technology (UTAUT) have been extended to capture metaverse-specific factors including perceived enjoyment, personal innovativeness, flow experience and perceived cyber risk. Key enablers of uptake include clear instructional design, seamless integration with existing learning management systems, robust technical infrastructure and supportive institutional policies. Conversely, privacy concerns, technical complexity and unequal access to hardware present significant barriers. Empirical studies demonstrate that when perceived usefulness and ease of use are high, behavioural intention to engage with metaverse learning rises, leading to enhanced motivation, collaboration and knowledge retention across disciplines. Attention is now shifting towards longitudinal evaluation, adaptive content delivery and inclusive design to ensure global and equitable impact.

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Technology Acceptance in Metaverse-Enhanced Education publication trend

The graph below shows the total number of articles in technology acceptance in metaverse-enhanced education across all publications each year (not limited to Nature Index journals).

Technical terms

Technology Acceptance Model (TAM): A theoretical framework positing that perceived usefulness and perceived ease of use determine users’ attitudes and behavioural intention towards new technology.

Unified Theory of Acceptance and Use of Technology (UTAUT): A synthesis model identifying performance expectancy, effort expectancy, social influence and facilitating conditions as core predictors of technology adoption.

Perceived usefulness: The degree to which a user believes that using a system will enhance their learning performance.

Perceived ease of use: The degree to which a user believes that interacting with a system will require minimal effort.

Behavioural intention: A user’s expressed likelihood or willingness to use a technological system in a given context.

Perceived cyber risk: The user’s assessment of potential threats to privacy, security or data integrity associated with technology use.

References

1. “Extending the Technology Acceptance Model (TAM) to Predict University Students’ Intentions to Use Metaverse-Based Learning Platforms”. Education and Information Technologies (2023).
2. Factors Affecting Learners’ Adoption of an Educational Metaverse Platform: An Empirical Study Based on an Extended UTAUT Model. Mobile Information Systems (2022).
3. Influencing Factors of Usage Intention of Metaverse Education Application Platform: Empirical Evidence Based on PPM and TAM Models. Sustainability (2022).