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cs.CL2026

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

Clayton Cohn, Joyce Fonteles, Kirk Vanacore +5

In K-12 mathematics tutoring, student-tutor dialogue provides rich evidence of learners' problem-solving processes and sources of difficulty. Learning analytics research increasing…

cs.CL2026

Experts Rise Where LLMs Disagree: Using Cross-Model Disagreement to Target Expert Effort in LLM Codebook Revision for Large-Scale Annotation

Zeyu He, Zhuqian Zhou, Kirk Vanacore +2

Large-scale text annotation brings expert insight to millions of documents, often through a codebook that AI annotators follow. Developing a robust codebook, however, takes months.…

cs.CL2026

Redact or Keep? A Fully Local AI Cascade for Educational Dialogue De-Identification

Haocheng Zhang, Zhuqian Zhou, Kirk Vanacore +2

Educational dialogue is a valuable but sensitive resource for research: the same transcripts that capture authentic learning often capture personally identifiable information (PII)…

cs.CL2026

Domain-Adapted Retrieval for In-Context Annotation of Pedagogical Dialogue Acts

Jinsook Lee, Kirk Vanacore, Zhuqian Zhou +2

Automated annotation of pedagogical dialogue is a high-stakes task where LLMs often fail without sufficient domain grounding. We present a domain-adapted RAG pipeline for tutoring…

cs.CL2026

Tutor Move Taxonomy: A Theory-Aligned Framework for Analyzing Instructional Moves in Tutoring

Zhuqian Zhou, Kirk Vanacore, Tamisha Thompson +2

Understanding what makes tutoring effective requires methods for systematically analyzing tutors' instructional actions during learning interactions. This paper presents a tutor mo…