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<p>This paper presents a dynamic gamification architecture for an Extended Reality–Artificial Intelligence (XR-AI) virtual training environment designed to&#xa0;enhance STEM education&#xa0;through immersive, adaptive, and kinesthetic learning.&#xa0;As a supplement to online coursework,&#xa0;advanced realistic scenarios can be replicated in the virtual world&#xa0;through&#xa0;XR-AI based&#xa0;remote labs and collaborative&#xa0;activities&#xa0;for engineering training with options to manipulate variables in real-time and analyze the corresponding outcomes. Different XR platforms, such as Unity, can integrate AI to support adaptive learning environments. These environments enable students to manipulate real-time variables in simulated scenarios and receive immediate feedback, thus fostering deeper conceptual understanding.&#xa0;Preliminary design concepts and future implementation plans are presented to&#xa0;demonstrate&#xa0;the viability of this approach. Security and privacy are discussed via a defense-in-depth approach spanning client, middleware, and backend layers, incorporating AES-256 encryption, multi-factor authentication, role-based access control (RBAC)&#xa0;and GDPR/FERPA compliance. Factors such as sensor exploitation, perceptual manipulation, and virtual physical harm are&#xa0;identified, with mitigation strategies embedded at the design stage. Finally, the importance of&#xa0;maintaining&#xa0;learning integrity and ensuring educator oversight is emphasized.</p>

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Exploring the integration of extended reality (XR) and artificial intelligence (AI) for remote STEM education and assessment

  • 期刊论文

  • 出版模式：

    开放获取

  • 发表日期：

    2026年6月1日

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  • Neda Adib,
  • Shadeeb Hossain,
  • Natalie Sommer

摘要

This paper presents a dynamic gamification architecture for an Extended Reality–Artificial Intelligence (XR-AI) virtual training environment designed to enhance STEM education through immersive, adaptive, and kinesthetic learning. As a supplement to online coursework, advanced realistic scenarios can be replicated in the virtual world through XR-AI based remote labs and collaborative activities for engineering training with options to manipulate variables in real-time and analyze the corresponding outcomes. Different XR platforms, such as Unity, can integrate AI to support adaptive learning environments. These environments enable students to manipulate real-time variables in simulated scenarios and receive immediate feedback, thus fostering deeper conceptual understanding. Preliminary design concepts and future implementation plans are presented to demonstrate the viability of this approach. Security and privacy are discussed via a defense-in-depth approach spanning client, middleware, and backend layers, incorporating AES-256 encryption, multi-factor authentication, role-based access control (RBAC) and GDPR/FERPA compliance. Factors such as sensor exploitation, perceptual manipulation, and virtual physical harm are identified, with mitigation strategies embedded at the design stage. Finally, the importance of maintaining learning integrity and ensuring educator oversight is emphasized.