Enhancing Explainability of Knowledge Learning Paths: Causal Knowledge Networks
<|reference_start|>Enhancing Explainability of Knowledge Learning Paths: Causal Knowledge Networks: 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.<|reference_end|>
@article{wei2024enhancing,
    title={Enhancing Explainability of Knowledge Learning Paths: Causal Knowledge
  Networks},
    author={Yuang Wei, Yizhou Zhou, Yuan-Hao Jiang, Bo Jiang},
    journal={arXiv preprint arXiv:2406.17518},
    year={2024},
    archivePrefix={arXiv},
    eprint={2406.17518},
    primaryClass={cs.AI cs.SI}
}