Educational Twin: The Influence of Artificial XR Expert Duplicates on Future Learning
Project Overview
The document explores the transformative role of generative AI and Extended Reality (XR) technologies in education, emphasizing the innovative concept of educational twins—digital replicas of educators that facilitate personalized, scalable, and interactive learning experiences. These advancements aim to enhance student engagement and maintain vital social learning elements, offering a more tailored educational approach. However, the integration of such technologies brings forth significant challenges, including concerns over educator autonomy, the quality of social interactions, ethical considerations, and the potential disruption of traditional teaching roles. The findings suggest that while generative AI has the potential to revolutionize educational practices by making learning more accessible and engaging, careful attention must be paid to the implications for educators and the educational environment as a whole. Ultimately, the document highlights both the promise and the complexities of implementing generative AI in educational settings, necessitating a balanced approach to harness its benefits while addressing potential drawbacks.
Key Applications
Educational twins using AI and XR
Context: Large-scale educational environments needing personalized support for students.
Implementation: Integration of AI-driven models and XR technologies to create realistic educational replicas of educators.
Outcomes: Improved scalability, engagement, and preservation of social learning factors.
Challenges: Concerns about educator autonomy, social interaction shifts, privacy, bias, and identity preservation.
Implementation Barriers
Ethical and Social Challenges
Potential negative impacts on educator-student relationships and social dynamics due to reliance on AI-driven teaching.
Proposed Solutions: Further research into the implications of AI on social interactions in education; development of ethical frameworks for AI use.
Technical and Operational Challenges
Questions regarding the ownership, maintenance, and updates of AI-generated educator models, as well as the environmental impact of hardware requirements.
Proposed Solutions: Establishing clear guidelines for AI model management and exploring sustainable technology practices.
Project Team
Clara Sayffaerth
Researcher
Contact Information
For information about the paper, please contact the authors.
Authors: Clara Sayffaerth
Source Publication: View Original PaperLink opens in a new window
Project Contact: Dr. Jianhua Yang
LLM Model Version: gpt-4o-mini-2024-07-18
Analysis Provider: Openai