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In recent years, artificial intelligence (AI) has been increasingly integrated into educational settings. Traditional teaching methods often fail to explain complex anatomical structures in virtual environments where spatial visualization is critical. Despite offering familiar advantages, conventional teaching approaches do not offer educators real-time, adaptive support for interactive 3D content. To address these challenges, this study examines the application of generative AI tutor assistants in virtual reality classrooms. This assistant is specifically designed to support educators in teaching 3D cardiac visualization to students, which serves as a case study in this research. Initial expert evaluation (n=10) showed the AI tutor outperformed traditional methods across all measured dimensions including Realism Enhancement and Adaptive Learning abilities. The next phase of this research involves a comprehensive evaluation of the prototype with students and teachers, examining the AI tutor's ability to teach effectively, provide accurate content, and adapt to different learning needs of students.

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Integrating Generative AI Assistant into Social VR Classroom for Medical Education: System Design and Implementation

  • 会议论文

  • 发表日期：

    2026年

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  • Fatima-Ezzahra Boubakri,
  • Mohammed Kadri,
  • Fatima Zahra Kaghat,
  • Ahmed Azough,
  • Hamid Tairi

摘要

In recent years, artificial intelligence (AI) has been increasingly integrated into educational settings. Traditional teaching methods often fail to explain complex anatomical structures in virtual environments where spatial visualization is critical. Despite offering familiar advantages, conventional teaching approaches do not offer educators real-time, adaptive support for interactive 3D content. To address these challenges, this study examines the application of generative AI tutor assistants in virtual reality classrooms. This assistant is specifically designed to support educators in teaching 3D cardiac visualization to students, which serves as a case study in this research. Initial expert evaluation (n=10) showed the AI tutor outperformed traditional methods across all measured dimensions including Realism Enhancement and Adaptive Learning abilities. The next phase of this research involves a comprehensive evaluation of the prototype with students and teachers, examining the AI tutor's ability to teach effectively, provide accurate content, and adapt to different learning needs of students.