Journal of Information Technology Review Yong Rokib 17 1 2026 https://doi.org/10.6025/jitr/2026/17/1/1-9 https://www.dline.info/jitr/fulltext/v17n1/jitrv17n1_1.pdf This work explores the integration of immersive virtual reality (VR) technologies and data mining to enhance talent development in education. It highlights the limitations of traditional teaching models overemphasis on theory, lack of personalization, and disorganized resources and proposes an immersive learning platform built using Unity 3D and 3ds Max, compatible with the Oculus DK2 VR headset. The platform simulates realistic environments (e.g., virtual campuses) to foster deep engagement through interactivity, spatial realism, and intuitive navigation. A key innovation is the incorporation of data mining techniques, particularly artificial neural networks (using the perceptron rule), to process user interaction data, optimize system performance, and tailor learning experiences. Results show significant improvements post implementation: response time decreased from 2.3s to 0.78s, scene count doubled, and visual detail quality improved. Collision detection and dual mode roaming (automatic/manual) further enhance immersion and usability. The study concludes that combining immersive VR with targeted data mining creates a more effective, personalized, and scalable environment for cultivating innovative, interdisciplinary talents. However, challenges remain in reducing data redundancy and improving system speed. The platform demonstrates strong portability across devices and offers a replicable model for future VR-based educational systems.