FoundationalASSIST: An Educational Dataset for Foundational Knowledge Tracing and Pedagogical Grounding of LLMs

FoundationalASSIST introduces a 1.7-million interaction K-12 educational dataset with full question text, student responses, and Common Core alignment, specifically designed to evaluate whether LLMs can perform knowledge tracing (predicting student performance) and pedagogical grounding (understanding assessment item properties). The paper evaluates four frontier LLMs on these tasks, revealing significant gaps in their ability to predict student performance and understand item discrimination.

Can Large Language Models understand how students learn? As LLMs are deployed for adaptive testing and personalized tutoring, this question becomes urgent -- yet we cannot answer it with existing resources. Current educational datasets provide only question identifiers and binary correctness labels, rendering them opaque to LLMs that reason in natural language. We address this gap with FoundationalASSIST, the first English educational dataset providing the complete information needed for researc

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