Enhancing Explainability of Knowledge Learning Paths: Causal Knowledge Networks

• URL: http://arxiv.org/abs/2406.17518v2
• Date: Wed, 26 Jun 2024 01:25:44 GMT
• Title: Enhancing Explainability of Knowledge Learning Paths: Causal Knowledge Networks
• Authors: Yuang Wei, Yizhou Zhou, Yuan-Hao Jiang, Bo Jiang,
• Abstract summary: A reliable knowledge structure is a prerequisite for building effective adaptive learning systems. We propose a method for constructing causal knowledge networks. We also introduce a dependable knowledge-learning path recommendation technique.
• Score: 6.792267409396434
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: A reliable knowledge structure is a prerequisite for building effective adaptive learning systems and intelligent tutoring systems. Pursuing an explainable and trustworthy knowledge structure, we propose a method for constructing causal knowledge networks. This approach leverages Bayesian networks as a foundation and incorporates causal relationship analysis to derive a causal network. Additionally, we introduce a dependable knowledge-learning path recommendation technique built upon this framework, improving teaching and learning quality while maintaining transparency in the decision-making process.

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