Papers by Heather Hill

2 papers
From Scoring to Explanations: Evaluating SHAP and LLM Rationales for Rubric-based Teaching Quality Assessment (2026.findings-acl)

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Challenge: a framework for sentence-level interpretability of rubric-based scoring is proposed . aaron e. smith: automated scoring models provide little insight into why scores are produced .
Approach: They propose a framework for sentence-level interpretability of rubric-based scoring that combines Shapley-value attributions with rationales generated by large language models.
Outcome: The proposed framework compares fine-tuned pretrained language models with large language models . it shows that fine- tuned models outperform LLMs in prediction accuracy but exhibit label compression toward mid-scale scores .
Measuring Conversational Uptake: A Case Study on Student-Teacher Interactions (2021.acl-long)

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Challenge: Despite extensive research showing the positive impact of uptake on student learning and achievement, there is little evidence that it is effective in teaching.
Approach: They propose a framework for computationally measuring uptake by releasing a dataset of student-teacher exchanges extracted from US math classroom transcripts annotated for uptake . they formalize uptake as pointwise Jensen-Shannon Divergence (pJSD) and conduct a linguistically-motivated comparison of different unsupervised measures.
Outcome: The proposed framework outperforms baseline measures in identifying uptake phenomena like question answering and reformulation.

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