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    <abstract>This study investigates the performance of Neural Network-based IRT estimation in multistage adaptive language assessment with small item banks and short tests. Results showed that accuracy improved with larger samples and more training information. Moderate distribution shifts were largely accommodated under higher iteration conditions, whereas larger shifts continued to reduce estimation accuracy.</abstract>
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%0 Conference Proceedings
%T Evaluating Neural Network-Based IRT in Multistage Adaptive Testing with Small Item Banks
%A Hong, Seong Eun
%Y Wilson, Joshua
%Y Ormerod, Christopher
%Y Beiting-Parrish, Magdalen
%S Proceedings of the Artificial Intelligence in Measurement and Education Conference (AIME-Con): Works in Progress
%D 2026
%8 October
%I National Council on Measurement in Education (NCME)
%C Wyndham Grand Pittsburgh Downtown, Pittsburgh, Pennsylvania, United States
%@ 979-8-9983004-1-7
%F hong-2026-evaluating
%X This study investigates the performance of Neural Network-based IRT estimation in multistage adaptive language assessment with small item banks and short tests. Results showed that accuracy improved with larger samples and more training information. Moderate distribution shifts were largely accommodated under higher iteration conditions, whereas larger shifts continued to reduce estimation accuracy.
%U https://aclanthology.org/2026.aimecon-wip.48/
%P 377-381

Markdown (Informal)

[Evaluating Neural Network-Based IRT in Multistage Adaptive Testing with Small Item Banks](https://aclanthology.org/2026.aimecon-wip.48/) (Hong, AIME-Con 2026)

• Evaluating Neural Network-Based IRT in Multistage Adaptive Testing with Small Item Banks (Hong, AIME-Con 2026)

ACL

• Seong Eun Hong. 2026. Evaluating Neural Network-Based IRT in Multistage Adaptive Testing with Small Item Banks. In Proceedings of the Artificial Intelligence in Measurement and Education Conference (AIME-Con): Works in Progress, pages 377–381, Wyndham Grand Pittsburgh Downtown, Pittsburgh, Pennsylvania, United States. National Council on Measurement in Education (NCME).