Applying Evidence-Centered Design to Automated Evals of AI-Powered Assessment Systems

Kristen DiCerbo, Britte Haugan Cheng, John Whitmer


Abstract
This paper demonstrates an application of Evidence-Centered Design (ECD) as a principled approach to design automated evaluations of AI-powered assessment outputs. We demonstrate this application through Khan Academy’s “Explain Your Thinking” conversational agent for mathematics items, showing how ECD’s layered models can be translated into rigorous and interpretable systems to demonstrate validity, reliability and fairness in AI systems to diverse audiences.
Anthology ID:
2026.aimecon-wip.42
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:
329–334
Language:
URL:
https://aclanthology.org/2026.aimecon-wip.42/
DOI:
Bibkey:
Cite (ACL):
Kristen DiCerbo, Britte Haugan Cheng, and John Whitmer. 2026. Applying Evidence-Centered Design to Automated Evals of AI-Powered Assessment Systems. In Proceedings of the Artificial Intelligence in Measurement and Education Conference (AIME-Con): Works in Progress, pages 329–334, Wyndham Grand Pittsburgh Downtown, Pittsburgh, Pennsylvania, United States. National Council on Measurement in Education (NCME).
Cite (Informal):
Applying Evidence-Centered Design to Automated Evals of AI-Powered Assessment Systems (DiCerbo et al., AIME-Con 2026)
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PDF:
https://aclanthology.org/2026.aimecon-wip.42.pdf