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A Knowledge Visualization Method Based on Knowledge Cube for Virtual Reality Learning
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AI
DOI：10.1002/cav.70096.png)
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Abstract
En 中文
Advances in microelectronic components and high-speed networks have enabled the widespread application of virtual reality (VR) technology in education. However, insufficient attention to knowledge visualization in VR learning has resulted in disorganized knowledge structures, comprehension difficulties, and mismatches between user experience and learning achievement. Therefore, we propose a Knowledge Cube (KC)-based visualization method to standardize knowledge encoding in VR learning. During courseware development, the instructor defines discrete knowledge as Events, organizes them into Event Groups, and populates data into a KC model to generate VR courseware. In subsequent VR learning, when learners search for task-relevant knowledge using the provided retrieval method, the KC model presents the corresponding events within interactive scenarios according to its predefined structure. Comparative experiments on different knowledge visualization methods revealed that, in VR learning, the KC method outperforms other VR approaches in both learning performance and efficiency. This method effectively guided learners to focus on the learning content and optimized the knowledge encoding in VR learning. This provides an operational framework for knowledge encoding in VR courseware design and emphasizes the importance of supporting effective learning behaviors over merely pursuing immersion, presenting a new perspective for refining the design approach of VR courseware.
Keywords:
courseware design
knowledge encoding
knowledge visualization
virtual reality learning
Journal
C
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1.7
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