Principled Approaches to Building AI Partners for Assessing and Supporting Small-Group Collaboration

Peter W Foltz, Chelsea Chandler, Mon-Lin Monica Ko


Abstract
Collaboration is complex and multifaceted, blending cognitive, social, and emotional components that resist simple measurement. We present a framework linking what is measured, where, and how evidence is warranted. This paper synthesizes key design dimensions for AI collaboration partners and demonstrates how they embed measurement science into practice.
Anthology ID:
2026.aimecon-wip.45
Volume:
Proceedings of the Artificial Intelligence in Measurement and Education Conference (AIME-Con): Works in Progress
Month:
October
Year:
2026
Address:
Wyndham Grand Pittsburgh Downtown, Pittsburgh, Pennsylvania, United States
Editors:
Joshua Wilson, Christopher Ormerod, Magdalen Beiting-Parrish
Venue:
AIME-Con
SIG:
Publisher:
National Council on Measurement in Education (NCME)
Note:
Pages:
350–357
Language:
URL:
https://aclanthology.org/2026.aimecon-wip.45/
DOI:
Bibkey:
Cite (ACL):
Peter W Foltz, Chelsea Chandler, and Mon-Lin Monica Ko. 2026. Principled Approaches to Building AI Partners for Assessing and Supporting Small-Group Collaboration. In Proceedings of the Artificial Intelligence in Measurement and Education Conference (AIME-Con): Works in Progress, pages 350–357, Wyndham Grand Pittsburgh Downtown, Pittsburgh, Pennsylvania, United States. National Council on Measurement in Education (NCME).
Cite (Informal):
Principled Approaches to Building AI Partners for Assessing and Supporting Small-Group Collaboration (Foltz et al., AIME-Con 2026)
Copy Citation:
PDF:
https://aclanthology.org/2026.aimecon-wip.45.pdf