Beyond Agreement: Calibrating Automated Scoring to Human Judgment Using Control Scripts

Mark Dulhunty, Alex Codoreanu, Nathan Zoanetti


Abstract
An ensemble automated scoring approach was evaluated against 260,000 responses spanning 55 constructed-response reading items. Performance was then compared to 27 human markers using 477 control scripts. The ensemble achieved perfect agreement on control scripts for 39 items (71%), matching or exceeding human marker performance and supporting operational quality assurance.
Anthology ID:
2026.aimecon-wip.11
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:
79–85
Language:
URL:
https://aclanthology.org/2026.aimecon-wip.11/
DOI:
Bibkey:
Cite (ACL):
Mark Dulhunty, Alex Codoreanu, and Nathan Zoanetti. 2026. Beyond Agreement: Calibrating Automated Scoring to Human Judgment Using Control Scripts. In Proceedings of the Artificial Intelligence in Measurement and Education Conference (AIME-Con): Works in Progress, pages 79–85, Wyndham Grand Pittsburgh Downtown, Pittsburgh, Pennsylvania, United States. National Council on Measurement in Education (NCME).
Cite (Informal):
Beyond Agreement: Calibrating Automated Scoring to Human Judgment Using Control Scripts (Dulhunty et al., AIME-Con 2026)
Copy Citation:
PDF:
https://aclanthology.org/2026.aimecon-wip.11.pdf