Supporting Relational Knowledge Construction Through LLM-Assisted Concept Mapping in Virtual Reality

Virtual reality (VR) is increasingly used to enhance learning, yet its effectiveness in supporting conceptual understanding, particularly relational knowledge construction, remains underexplored. Relational knowledge construction involves identifying meaningful connections among concepts to form coherent representations that support knowledge organization, guide interpretation, and facilitate learning transfer. Based on a review of the challenges in relational knowledge construction, we proposed conceptual, relational, and metacognitive scaffolds, upon which we developed CmapVR, an immersive learning environment with LLM-supported features to implement the proposed scaffolds. A within-subject study (N = 16) compared CmapVR with three alternative learning conditions in a science concept learning task. Results showed that CmapVR supported more extensive and higher-quality relational knowledge construction than the other conditions, resulted in lower extraneous cognitive load, and was preferred by participants over browsing in VR. We discussed factors that may have contributed to these outcomes and provided insights for integrating LLMs into VR-based learning environments.

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Publication Details

Journal
International Journal of Human-Computer Interaction
Published
2026-08-26
DOI
https://doi.org/10.1080/10447318.2026.2719119
Primary Topic
Data Visualization and Analytics
Type
article
Field-Weighted Citation Impact
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article

Supporting Relational Knowledge Construction Through LLM-Assisted Concept Mapping in Virtual Reality

Bingyi Su, Fangyuan Cheng, Karen B. Chen
International Journal of Human-Computer Interaction
Data Visualization and Analytics
article

Supporting Relational Knowledge Construction Through LLM-Assisted Concept Mapping in Virtual Reality

Bingyi Su, Fangyuan Cheng, Karen B. Chen
article en

Abstract

Virtual reality (VR) is increasingly used to enhance learning, yet its effectiveness in supporting conceptual understanding, particularly relational knowledge construction, remains underexplored. Relational knowledge construction involves identifying meaningful connections among concepts to form coherent representations that support knowledge organization, guide interpretation, and facilitate learning transfer. Based on a review of the challenges in relational knowledge construction, we proposed conceptual, relational, and metacognitive scaffolds, upon which we developed CmapVR, an immersive learning environment with LLM-supported features to implement the proposed scaffolds. A within-subject study (N = 16) compared CmapVR with three alternative learning conditions in a science concept learning task. Results showed that CmapVR supported more extensive and higher-quality relational knowledge construction than the other conditions, resulted in lower extraneous cognitive load, and was preferred by participants over browsing in VR. We discussed factors that may have contributed to these outcomes and provided insights for integrating LLMs into VR-based learning environments.

International Journal of Human-Computer Interaction
North Carolina State University (US)
Openalex Percentile: Top 51%
Data Visualization and Analytics
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