@article{4643,
  author = {Yong Rokib},
  title = {Integrating Immersive VR and Data Mining for Improving Skills: Design and Evaluation of an Interactive Learning Platform},
  journal = {Journal of Information Technology Review},
  year = {2026},
  volume = {17},
  number = {1},
  doi = {https://doi.org/10.6025/jitr/2026/17/1/1-9},
  url = {https://www.dline.info/jitr/fulltext/v17n1/jitrv17n1_1.pdf},
  abstract = {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.},
}