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Bridging the Novice-Expert Gap via Models of Decision-Making: A Case Study on Remediating Math Mistakes (2024.naacl-long)

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Challenge: Our work explores the potential of large language models (LLMs) to close the novice-expert knowledge gap in remediating math mistakes.
Approach: They propose a method that uses cognitive task analysis to translate an expert’s latent thought process into a decision-making model for remediation.
Outcome: The proposed model can bridge the novice-expert knowledge gap by using cognitive task analysis to translate an expert’s latent thought process into a decision-making model for remediation.

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