Author

Clayton Cohn

3 papers indexed here

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#natural language process... Preprint Oct 2026

Agreement Is Not Validity: Cross-Model LLM Consensus in Diagnosing Student Failure Modes in K-12 Math Tutoring Dialogue

In K-12 mathematics tutoring, student-tutor dialogue provides rich evidence of learners'problem-solving processes and sources of difficulty. Learning analytics research increasingly relies on large language models (LLMs) to extract such information from dialogue for a variety of downstream tasks, including knowledge tr...

Clayton Cohn, J. Fonteles, Kirk P. Vanacore et al. · 0 citations

#artificial intelligence Preprint Sep 2026

Examining Variation in How Guided AI Tutors Resolve Student Impasses

For learning analytics, these findings identify impasse depth and type as observable, turn-level dialogue signals that analytics can use to trigger graduated, state-sensitive assistance in real time.

Bakhtawar Ahtisham, Kirk P. Vanacore, Alessandra O. Napoli et al. · 0 citations

#natural language process... Preprint Apr 2025

CoTAL: Human-in-the-Loop Prompt Engineering for Generalizable Formative Assessment Scoring and Feedback

CoTAL is introduced, an LLM-based approach to formative assessment scoring that leverages Evidence-Centered Design to align assessments and rubrics with curriculum goals, and incorporates chain-of-thought prompting and teacher and student feedback to iteratively refine questions, rubrics, and LLM prompts.

Clayton Cohn, S. AshwinT., Naveeduddin Mohammed et al. · 5 citations