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

Background: Self-Regulated Learning (SRL) is critical for success, but Immersive Virtual Reality (IVR) creates a "transposition challenge". IVR isolates learners from their conventional regulatory tools, necessitating new, virtually-native support mechanisms. Methods: We address this design challenge by conducting a state-of-the-art review of the literature. The review is systematically structured using Zimmerman's three-phase cyclical model (forethought, performance, self-reflection) to map existing support mechanisms. Findings: The review reveals significant gaps in the literature, particularly in the support for learners' metacognitive (e.g., planning) and motivational (e.g., self-efficacy) processes. Contribution: Building on this analysis, we propose the Self-Regulated Learning Support Framework (SRL-SF), a novel, theory-grounded tool. To bridge theory and practice, this framework is operationalized as a freely available, interactive web-based tool to guide systematic audits. This work synthesizes a fragmented field and advances theory by providing an actionable design framework for supporting the whole learner.