Exploring the Integration of Extended Reality and Artificial Intelligence (AI) for Remote STEM Education and Assessment

This paper presents a dynamic gamification architecture for an Extended Reality Artificial Intelligence virtual training environment designed to enhance STEM education through immersive adaptive, and kinesthetic learning. The proposed system can be introduced in four phases: Introduction Phase, Component Development Phase, Fault Introduction and Correction Phase and Generative AI XR scenarios Phase. 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 and GDPR or FERPA compliance. Risks such as sensor exploitation, perceptual manipulation, and virtual physical harm are identified, with mitigation strategies embedded at the design stage. Potential barriers to large scale adoption-including technical complexity, cost of deployment, and need for cybersecurity expertise are discussed.

Publication Details

Journal
ArXiv.org
Published
2025-09-04
Primary Topic
Geochemistry and Geologic Mapping
Type
article
Field-Weighted Citation Impact
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article

Exploring the Integration of Extended Reality and Artificial Intelligence (AI) for Remote STEM Education and Assessment

ArXiv.org
Geochemistry and Geologic Mapping
article

Exploring the Integration of Extended Reality and Artificial Intelligence (AI) for Remote STEM Education and Assessment

article en

Abstract

This paper presents a dynamic gamification architecture for an Extended Reality Artificial Intelligence virtual training environment designed to enhance STEM education through immersive adaptive, and kinesthetic learning. The proposed system can be introduced in four phases: Introduction Phase, Component Development Phase, Fault Introduction and Correction Phase and Generative AI XR scenarios Phase. 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 and GDPR or FERPA compliance. Risks such as sensor exploitation, perceptual manipulation, and virtual physical harm are identified, with mitigation strategies embedded at the design stage. Potential barriers to large scale adoption-including technical complexity, cost of deployment, and need for cybersecurity expertise are discussed.

ArXiv.org
Openalex Percentile: Top 48%
Geochemistry and Geologic Mapping
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