DOI: 10.3390/educsci16111842 ISSN: 2227-7102

Learning with Feedback Opportunities in Immersive Metaverse Environments: A Mixed-Methods Study of Cybersecurity Education

Tsz Cheung Chan, Jiaoyang Ding, Winnie Wong, Roger Wong, Bei Cai, Lan Yang, Hong Fu

Data security and privacy education increasingly requires learning experiences that engage students in applying knowledge to realistic situations. Guided by the Self-System Processes Model, this mixed-methods quasi-experimental study compared a self-selected traditional classroom workshop (n = 27) with a Spatial metaverse workshop (n = 30) among university students (N = 57), focusing on interactive learning and feedback opportunities. The metaverse format integrated immersive scenarios, mini-games, quizzes, and immediate task-based responses, while both formats used the same curriculum and 10-item knowledge test. Data were collected through pre- and post-tests, questionnaires, and focus-group interviews with metaverse participants. The metaverse group showed a larger score increase and reported higher engagement, comfort, and confidence. After adjustment for pre-test scores via ANCOVA, workshop format remained associated with post-test scores (adjusted difference = 0.77, 95% CI [0.15, 1.39]). Qualitative accounts highlighted the perceived value of contextualized activities and immediate responses for participation, alongside the need for better content–gameplay alignment and technical accessibility. The non-randomized design limits causal claims. The study offers preliminary evidence on feedback-responsive immersive environments in cybersecurity education and points to future work on how learners interpret and use multi-source feedback, particularly as educational feedback practices evolve in the GenAI era.

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