@inproceedings{xie-etal-2026-measuring-collaborative,
title = "Measuring Collaborative Reasoning with {LLM}s",
author = "Xie, Dawei and
Eze, Tochukwu and
Worsley, Marcelo",
editor = "Wilson, Joshua and
Ormerod, Christopher and
Beiting-Parrish, Magdalen",
booktitle = "Proceedings of the Artificial Intelligence in Measurement and Education Conference ({AIME}-Con): Full Papers",
month = oct,
year = "2026",
address = "Wyndham Grand Pittsburgh Downtown, Pittsburgh, Pennsylvania, United States",
publisher = "National Council on Measurement in Education (NCME)",
url = "https://aclanthology.org/2026.aimecon-main.74/",
pages = "656--665",
ISBN = "979-8-9983004-0-0",
abstract = "We present CRS, a framework representing group reasoning as contributions, relations, and derived structure. Evaluating five LLMs on student discussions, we find that reasoning is classifiable but not reliably segmentable, with identification being the bottleneck. Prompting improves labeling far more than identification; participation is recoverable, yet fine-grained structure is hard."
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%0 Conference Proceedings
%T Measuring Collaborative Reasoning with LLMs
%A Xie, Dawei
%A Eze, Tochukwu
%A Worsley, Marcelo
%Y Wilson, Joshua
%Y Ormerod, Christopher
%Y Beiting-Parrish, Magdalen
%S Proceedings of the Artificial Intelligence in Measurement and Education Conference (AIME-Con): Full Papers
%D 2026
%8 October
%I National Council on Measurement in Education (NCME)
%C Wyndham Grand Pittsburgh Downtown, Pittsburgh, Pennsylvania, United States
%@ 979-8-9983004-0-0
%F xie-etal-2026-measuring-collaborative
%X We present CRS, a framework representing group reasoning as contributions, relations, and derived structure. Evaluating five LLMs on student discussions, we find that reasoning is classifiable but not reliably segmentable, with identification being the bottleneck. Prompting improves labeling far more than identification; participation is recoverable, yet fine-grained structure is hard.
%U https://aclanthology.org/2026.aimecon-main.74/
%P 656-665
Markdown (Informal)
[Measuring Collaborative Reasoning with LLMs](https://aclanthology.org/2026.aimecon-main.74/) (Xie et al., AIME-Con 2026)
ACL
- Dawei Xie, Tochukwu Eze, and Marcelo Worsley. 2026. Measuring Collaborative Reasoning with LLMs. In Proceedings of the Artificial Intelligence in Measurement and Education Conference (AIME-Con): Full Papers, pages 656–665, Wyndham Grand Pittsburgh Downtown, Pittsburgh, Pennsylvania, United States. National Council on Measurement in Education (NCME).