DESIGNING AI-ENHANCED IMMERSIVE LEARNING MATERIALS VIEWED FROM DISTANCE LEARNERS' PERSPECTIVES: FROM IMMERSION TO IMPLEMENTATION

Abstract

The rapid advancement of artificial intelligence (AI) and immersive technologies is reshaping distance education by enabling more engaging and personalized learning experiences. However, a persistent gap remains between conceptual understanding and practical implementation for distance learners. This study addresses this gap by developing a learner-centered framework for designing AI-enhanced immersive learning materials in open and flexible distance learning (OFDL) contexts. Using a qualitative systematic literature review (SLR), the study synthesizes recent research on immersive learning, AI in education, and distance learning pedagogy. The findings identify key characteristics of immersive learning materials as perceived by learners: presence, experiential
meaning-making, personalization, interaction, engagement, feedback, accessibility, and authenticity. Accordingly, the study proposes the AIDE framework (AI-Driven Immersive Design for Education), which organizes the design process into five phases: Analyze, Immerse, Differentiate, Engage, and Sustain. In addition, a conceptual model is introduced to explain how instructional design influences multidimensional learning outcomes through immersive learning experiences. The study highlights that effective immersion depends on technological sophistication and on the quality and contextual relevance of learner experiences. It contributes by bridging theory and practice, offering practical design guidance, and emphasizing inclusive and sustainable approaches. Future research is needed to empirically validate the proposed framework and model.