Application of AI-driven virtual reality (VR) in improving higher education student’s learning and engagement

Abstract

Purpose: Calls for personalised learning have increased interest in AI-enabled virtual reality (AI-VR) as a tool that can adapt instruction and support diverse learner needs. This study investigates the adoption and applicability of AI-VR in higher education and examines its influence on students’ learning and engagement. Design/methodology/approach: A quantitative design was used. Structured questionnaires were distributed through Google Forms to lecturers and students in UK higher education using judgemental sampling. A total of 278 respondents (69 lecturers and 209 students) completed the survey. Data were analysed using descriptive and inferential statistics in SPSS. Findings: Results indicate that AI-VR improves learning outcomes by strengthening knowledge acquisition, retention, and conceptual understanding. Participants reported higher engagement due to immersive, interactive environments that build confidence and support inclusive learning. Despite these benefits, levels of adoption and consistent applicability in higher education remain below expectation, influenced by digital readiness and infrastructure constraints. Originality/value: The study contributes to immersive learning research through the development of the AI-VR Immersive Learning Adoption Model (AILAM). The framework synthesises insights from existing literature to explain how adaptive AI-VR environments influence engagement, learning processes, and user readiness in higher education. AILAM clarifies the mechanisms through which AI-VR produces learning benefits and provides a structured foundation for future empirical inquiry and institutional decision-making.