Perceived AI-driven virtual reality learning: examining immersive engagement, gamified motivation and knowledge retention in higher education

Purpose This study examined how perceived immersive involvement, student engagement, gamified motivation and knowledge retention are influenced within artificial intelligence (AI)-enabled virtual reality (VR) learning in higher education. Rather than evaluating a functional AI-VR system, the study investigates learners' reported experiences and expectations of AI-supported immersive environments. Guided by the immersive engagement and motivation Framework, which integrates experiential learning theory and self-determination theory, the research explored direct, indirect and serial mediation relationships among these psychological and experiential constructs, with accessibility inclusion included as a control factor. Design/methodology/approach A cross-sectional survey design was adopted to capture perceptions of AI-enabled VR learning. Primary data were collected from 278 lecturers and students across higher education institutions in the United Kingdom using a structured questionnaire distributed through digital platforms such as WhatsApp. Principal component analysis and reliability testing confirmed acceptable psychometric properties of the instrument (a = 0.815). Findings Mediation analysis using Hayes' PROCESS Macro (Model 6) revealed that perceived immersive involvement was associated (both directly and indirectly) with perceived knowledge retention through gamified motivation and the serial pathway involving engagement and motivation. Engagement alone did not significantly predict retention. The findings highlight how learners perceive AI-supported immersive environments as enhancing motivation and contributing to meaningful learning experiences. The study provides theoretical and practical insights for the design of inclusive, motivating and pedagogically aligned VR learning environments in higher education. Research limitations/implications This study relied on a cross sectional survey design, which does not allow observation of how immersive involvement, engagement and motivation evolve over time. Longitudinal or experimental designs would help clarify the temporal development of these relationships and provide stronger evidence of causal direction. The study also used self-reported measures for all constructs, including perceived knowledge retention. These measures capture learners interpretations of their experiences rather than objective performance. Future work should incorporate behavioural indicators, system usage data and performance- based assessments to provide a more comprehensive evaluation of learning outcomes in immersive environments. The sample was obtained through a non-probabilistic approach and consisted of lecturers and students from higher education institutions in the United Kingdom. This limits the generalisability of the findings to broader educational or organisational contexts. Studies that draw from more diverse populations, including professional learners and employees in technology mediated workplaces, would offer a richer understanding of how immersive environments influence engagement and motivation across settings. Practical implications Practically, the findings highlight several design considerations. Immersive modules should prioritise tasks that align with learning outcomes so that interactivity and sensory richness promote reflection and understanding rather than novelty. Adaptive elements that maintain an appropriate level of challenge may strengthen motivation and enhance learners perceptions of progress. Accessibility features can broaden engagement by reducing discomfort and improving usability across diverse groups. For organisations, immersive and AI supported learning tools may enhance workforce development. Motivation and engagement are recognised behavioural markers that influence successful adoption of digital technologies (Venkatesh and Davis, 2000). When immersive systems foster meaningful engagement, they can support organisational goals related to digital transformation, professional learning and continuous improvement. The findings therefore provide a behavioural perspective on how technology-mediated learning experiences may contribute to developing organisational capabilities (Schein, 2010). Social implications Theoretically, the study contributes to ongoing discussions about the role of motivation and engagement in virtual environments and how learners interpret AI supported experiences. The findings suggest that perceived adaptivity and interactive richness can influence how individuals judge their learning processes, which has implications for educational design and organisational capability development. As immersive and AI supported technologies continue to evolve, future research can build on these insights by integrating behavioural data and performance based assessments to deepen understanding of how immersive environments shape learning and development across contexts. Originality/value This study demonstrates that immersive experiences supported by AI within VR environments enhance learning effectiveness by strengthening engagement, motivation and knowledge retention. Drawing on experiential learning theory and self-determination theory, the findings reveal that immersion creates rich experiential contexts that anchor attention and facilitate reflection, while adaptive gamification nurtures autonomy and competence.