The Cognitive Affective Model of Immersive Learning (CAMIL): a Theoretical Research-Based Model of Learning in Immersive Virtual Reality

TLDR

Immersive virtual reality lessons have surged in use, generating numerous studies and reviews, yet a comprehensive theoretical framework synthesizing these findings remains absent. The study introduces the Cognitive Affective Model of Immersive Learning (CAMIL) to unify existing IVR research and offers guidance for future research and instructional design. CAMIL defines presence and agency as core psychological affordances, linking immersion, control, and fidelity to six affective and cognitive factors—interest, motivation, self‑efficacy, embodiment, cognitive load, and self‑regulation—that collectively drive factual, conceptual, and procedural learning outcomes.

Abstract

There has been a surge in interest and implementation of immersive virtual reality (IVR)-based lessons in education and training recently, which has resulted in many studies on the topic. There are recent reviews which summarize this research, but little work has been done that synthesizes the existing findings into a theoretical framework. The Cognitive Affective Model of Immersive Learning (CAMIL) synthesizes existing immersive educational research to describe the process of learning in IVR. The general theoretical framework of the model suggests that instructional methods which are based on evidence from research with less immersive media generalize to learning in IVR. However, the CAMIL builds on evidence that media interacts with method. That is, certain methods which facilitate the affordances of IVR are specifically relevant in this medium. The CAMIL identifies presence and agency as the general psychological affordances of learning in IVR, and describes how immersion, control factors, and representational fidelity facilitate these affordances. The model describes six affective and cognitive factors that can lead to IVR-based learning outcomes including interest, motivation, self-efficacy, embodiment, cognitive load, and self-regulation. The model also describes how these factors lead to factual, conceptual, and procedural knowledge acquisition and knowledge transfer. Implications for future research and instructional design are proposed.