LLM simulators exhibit near-zero selective response to targeted misconception feedback and behave sycophantically, but SFT and SFS-aligned RL improve this property.
qdkt: Question-centric deep knowledge tracing.arXiv preprint arXiv:2005.12442, 2020
2 Pith papers cite this work. Polarity classification is still indexing.
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BAIM enriches knowledge tracing item representations by deriving stage-level embeddings from Polya's four problem-solving stages and routing them adaptively per learner context, yielding consistent gains over pretraining baselines on two datasets.
citing papers explorer
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Simulating Students or Sycophantic Problem Solving? On Misconception Faithfulness of LLM Simulators
LLM simulators exhibit near-zero selective response to targeted misconception feedback and behave sycophantically, but SFT and SFS-aligned RL improve this property.
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Behavior-Aware Item Modeling via Dynamic Procedural Solution Representations for Knowledge Tracing
BAIM enriches knowledge tracing item representations by deriving stage-level embeddings from Polya's four problem-solving stages and routing them adaptively per learner context, yielding consistent gains over pretraining baselines on two datasets.