1. Enhancing Explainability of Knowledge Learning Paths: Causal Knowledge Networks
- Author
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Wei, Yuang, Zhou, Yizhou, Jiang, Yuan-Hao, and Jiang, Bo
- Subjects
Computer Science - Artificial Intelligence ,Computer Science - Social and Information Networks - 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., Comment: 8 pages, 3 figures, Educational Data Mining 2024, Human-Centric eXplainable AI in Education
- Published
- 2024