Personalized VR Learning Environments Using Cognitive AI Agents
DOI:
https://doi.org/10.63345/Keywords:
Personalized VR Learning, Cognitive AI Agents, Adaptive Learning, Virtual Reality, Educational TechnologyAbstract
Virtual reality (VR) has shown promise as an immersive educational medium, yet its full potential remains unrealized when experiences are one‐size‐fits‐all. This study presents the design, implementation, and evaluation of personalized VR learning environments enhanced by cognitive AI agents, which continuously monitor learner behavior and dynamically tailor instructional support. Leveraging an ACT‑R cognitive architecture integrated with Unity3D, our system tracks learners’ interactions—such as task completion time, error patterns, and navigation choices—to infer conceptual misunderstandings in real time. We conducted a controlled experiment with 60 undergraduate participants, randomly assigned to either a personalized VR condition (with AI agent) or a non‑personalized control VR. Pre‑ and post‑test assessments measured learning gains, while standardized questionnaires captured engagement and usability. Statistical analysis (two‑sample t‑tests, Cohen’s d) revealed that the personalized group achieved significantly higher knowledge gains (M=18.5 vs. 12.1, p<.001, d=1.32) and engagement scores (UEQ mean=4.2 vs. 3.5, p<.01). Complementary computational simulations using synthetic learner models demonstrated a 30% reduction in trials to mastery under adaptive scaffolding. User interviews highlighted the agent’s scaffolding prompts as clear, timely, and motivating. We conclude that embedding cognitive AI agents within VR significantly enhances learning efficacy and learner experience. Implications for scalable deployment, multi‑user collaboration, and longitudinal retention are discussed, alongside challenges in real‑time performance optimization and agent–learner rapport in complex domains.
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