Evaluating an AI-Item Generation Tool for NAEP Mathematics

Cheryl Van Ness, Ilona Minchuk, Karen Parker


Abstract
This study evaluates the effectiveness of an AI-based system (Wilbur) for generating NAEP mathematics items. Results from this investigation indicate moderate success for content-focused items but substantial challenges for items intended to assess the NAEP Mathematical Practices. Transitioning from GPT-4 to GPT-5.2 improved item quality, though human revision remained essential.
Anthology ID:
2026.aimecon-sessions.20
Volume:
Proceedings of the Artificial Intelligence in Measurement and Education Conference (AIME-Con): Coordinated Session Papers
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:
196–202
Language:
URL:
https://aclanthology.org/2026.aimecon-sessions.20/
DOI:
Bibkey:
Cite (ACL):
Cheryl Van Ness, Ilona Minchuk, and Karen Parker. 2026. Evaluating an AI-Item Generation Tool for NAEP Mathematics. In Proceedings of the Artificial Intelligence in Measurement and Education Conference (AIME-Con): Coordinated Session Papers, pages 196–202, Wyndham Grand Pittsburgh Downtown, Pittsburgh, Pennsylvania, United States. National Council on Measurement in Education (NCME).
Cite (Informal):
Evaluating an AI-Item Generation Tool for NAEP Mathematics (Van Ness et al., AIME-Con 2026)
Copy Citation:
PDF:
https://aclanthology.org/2026.aimecon-sessions.20.pdf