Educational Twin: The Influence of Artificial XR Expert Duplicates on Future Learning

TL;DR

Problem: educators cannot attend individually to every student in large classes; XR and AI enable digital twins that tutor students remotely. The paper provides a conceptual analysis of opportunities and challenges across scalability, social dynamics, and version control, and formulates open research questions. Key contributions synthesize existing work on AI avatars, XR representations, and social learning, while highlighting ethical, privacy, bias, and governance concerns. The discussion aims to guide responsible development of AI/XR educational twins that augment human educators without compromising trust, empathy, or pedagogical intent.

Abstract

Currently, it is impossible for educators to be in multiple places simultaneously and teach each student individually. Technologies such as Extended Reality (XR) and Artificial Intelligence (AI) enable the creation of realistic educational copies of experts that preserve not only visual and mental characteristics but also social aspects crucial for learning. However, research in this area is limited, which opens new questions for future work. This paper discusses how these human digital twins can potentially improve aspects like scalability, engagement, and preservation of social learning factors. While this technology offers benefits, it also introduces challenges related to educator autonomy, social interaction shifts, and ethical considerations such as privacy, bias, and identity preservation. We outline key research questions that need to be addressed to ensure that human digital twins enhance the social aspects of education instead of harming them.