Do Synthetic Students Thrive? Validity and Fairness of Generated Assessment Data

Neba Nfonsang, Temple Lovelace


Abstract
Synthetic assessment data may reproduce response distributions while failing to preserve underlying construct structure. Using a retrieval-augmented generation (RAG) pipeline and a stratified majority Black and Latinx student sample, we evaluated synthetic responses using distributional and psychometric measures. Results highlight the importance of psychometric preservation alongside distributional similarity.
Anthology ID:
2026.aimecon-wip.57
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:
459–463
Language:
URL:
https://aclanthology.org/2026.aimecon-wip.57/
DOI:
Bibkey:
Cite (ACL):
Neba Nfonsang and Temple Lovelace. 2026. Do Synthetic Students Thrive? Validity and Fairness of Generated Assessment Data. In Proceedings of the Artificial Intelligence in Measurement and Education Conference (AIME-Con): Works in Progress, pages 459–463, Wyndham Grand Pittsburgh Downtown, Pittsburgh, Pennsylvania, United States. National Council on Measurement in Education (NCME).
Cite (Informal):
Do Synthetic Students Thrive? Validity and Fairness of Generated Assessment Data (Nfonsang & Lovelace, AIME-Con 2026)
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PDF:
https://aclanthology.org/2026.aimecon-wip.57.pdf