Funnel Plot Analysis of Examinee Performance in Longitudinal Assessment

Aquia Richburg, Marcus Walker


Abstract
We identify content areas where examinees underperform in a longitudinal assessment for a high-stakes medical licensure exam. Using modified funnel plots with a moving baseline to account for item difficulty, we rank topics by relative performance. Preliminary results suggest reasons beyond item difficulty, informing future analyses supporting potential educational interventions.
Anthology ID:
2026.aimecon-wip.38
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:
298–305
Language:
URL:
https://aclanthology.org/2026.aimecon-wip.38/
DOI:
Bibkey:
Cite (ACL):
Aquia Richburg and Marcus Walker. 2026. Funnel Plot Analysis of Examinee Performance in Longitudinal Assessment. In Proceedings of the Artificial Intelligence in Measurement and Education Conference (AIME-Con): Works in Progress, pages 298–305, Wyndham Grand Pittsburgh Downtown, Pittsburgh, Pennsylvania, United States. National Council on Measurement in Education (NCME).
Cite (Informal):
Funnel Plot Analysis of Examinee Performance in Longitudinal Assessment (Richburg & Walker, AIME-Con 2026)
Copy Citation:
PDF:
https://aclanthology.org/2026.aimecon-wip.38.pdf