Supporting Self-Regulated Learning in Immersive Virtual Reality: A State-of-the-Art Review and an Evaluation Framework

Background: Self-Regulated Learning (SRL) is a prerequisite for academic success, but supporting its complex cognitive, metacognitive, and motivational processes is challenging, especially in technology-rich environments. While Immersive Virtual Reality (IVR) affords high immersion, it concurrently imposes a "transposition challenge" by perceptually decoupling learners from their external regulatory affordances, such as physical notebooks or chronometers, thereby disrupting established self-regulation loops unless endogenous virtual alternatives are systematically integrated. Consequently, physical regulation strategies (such as note-taking or time-checking) cannot be directly transferred into IVR. Objectives: This article systematically explores the intersection of SRL and IVR to provide a theoretical synthesis, map existing research onto Zimmerman's three-phase cyclical model, and propose a novel, theory-grounded framework for evaluating and designing SRL-supportive IVR environments. Methods: A state-of-the-art review, anchored in Zimmerman's model and integrated with the Cognitive Theory of Multimedia Learning (CTML) and the Cognitive Affective Model of Immersive Learning (CAMIL), examined support mechanisms across the Forethought, Performance, and Self-Reflection phases. Results and Conclusions: The review highlights a significant disparity: while the Performance phase is often supported, critical metacognitive processes in Forethought (planning, goal setting) and Self-Reflection (causal attribution, adaptive inference) are frequently neglected. To bridge this gap, this study systematizes the Self-Regulated Learning Support Framework (SRL-SF), a theoretically grounded heuristic that differentiates between general and domain-specific scaffolding. This framework is operationalized as an open-access, interactive web-based audit tool designed to facilitate quantitative evaluation of IVR environments. This framework urges instructional designers to shift towards a "cognition-first" approach. This work provides an actionable methodology for creating adaptive, cognition-centric IVR environments.