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
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
This work shows that LLMs can be used to strategically target expert attention, shortening months of codebook revision to days without sacrificing labeling performance.
Ze-Yu He, Zhu-Qian Zhou, Kirk P. Vanacore et al.· 0 citations
This work proposes a fully local cascade framework that reframes de-identification from open-ended entity recognition to constrained privacy triage, and evaluates three reviewer configurations against same-family LLM-only baselines and a commercial API on math tutoring transcripts from two large platforms.
Hao-Chen Zhang, Zhu-Qian Zhou, Kirk P. Vanacore et al.· arXiv.org· 0 citations
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