AHCI RESEARCH GROUP

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OUR RESEARCH

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2025

Gao, H.; Xie, Y.; Kasneci, E.

PerVRML: ChatGPT-Driven Personalized VR Environments for Machine Learning Education Journal Article

In: International Journal of Human-Computer Interaction, 2025, ISSN: 10447318 (ISSN).

Abstract | Links | BibTeX | Tags: Backpropagation, ChatGPT, Curricula, Educational robots, Immersive learning, Interactive learning, Language Model, Large language model, large language models, Learning mode, Machine learning education, Machine-learning, Personalized learning, Support vector machines, Teaching, Virtual Reality, Virtual-reality environment, Virtualization

@article{gao_pervrml_2025,

title = {PerVRML: ChatGPT-Driven Personalized VR Environments for Machine Learning Education},

author = {H. Gao and Y. Xie and E. Kasneci},

url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-105005776517&doi=10.1080%2f10447318.2025.2504188&partnerID=40&md5=c2c59be3d20d02c6df7750c2330c8f6d},

doi = {10.1080/10447318.2025.2504188},

issn = {10447318 (ISSN)},

year  = {2025},

date = {2025-01-01},

journal = {International Journal of Human-Computer Interaction},

abstract = {The advent of large language models (LLMs) such as ChatGPT has demonstrated significant potential for advancing educational technologies. Recently, growing interest has emerged in integrating ChatGPT with virtual reality (VR) to provide interactive and dynamic learning environments. This study explores the effectiveness of ChatGTP-driven VR in facilitating machine learning education through PerVRML. PerVRML incorporates a ChatGPT-powered avatar that provides real-time assistance and uses LLMs to personalize learning paths based on various sensor data from VR. A between-subjects design was employed to compare two learning modes: personalized and non-personalized. Quantitative data were collected from assessments, user experience surveys, and interaction metrics. The results indicate that while both learning modes supported learning effectively, ChatGPT-powered personalization significantly improved learning outcomes and had distinct impacts on user feedback. These findings underscore the potential of ChatGPT-enhanced VR to deliver adaptive and personalized educational experiences. © 2025 Taylor & Francis Group, LLC.},

keywords = {Backpropagation, ChatGPT, Curricula, Educational robots, Immersive learning, Interactive learning, Language Model, Large language model, large language models, Learning mode, Machine learning education, Machine-learning, Personalized learning, Support vector machines, Teaching, Virtual Reality, Virtual-reality environment, Virtualization},

pubstate = {published},

tppubtype = {article}

}