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        <title>Can LLMs Interpret Psychometric Parameters? Quantifying “Over-Knowledge” in LLM Student Simulation</title>
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        <namePart type="given">Kazunori</namePart>
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            <namePart type="given">Joshua</namePart>
            <namePart type="family">Wilson</namePart>
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            <namePart type="given">Magdalen</namePart>
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    <abstract>LLM simulation suffers from an “over-knowledge problem”, where models perform too well to represent struggling learners. We compare persona-, IRT-, and CDM-based prompting for student simulation and measure how well methods reflect expected behaviors and quantify this bias. Findings show LLMs follow IRT parameters, yet struggle to simulate real abilities.</abstract>
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%0 Conference Proceedings
%T Can LLMs Interpret Psychometric Parameters? Quantifying “Over-Knowledge” in LLM Student Simulation
%A Fukuhara, Kazunori
%A Domingue, Benjamin
%Y Wilson, Joshua
%Y Ormerod, Christopher
%Y Beiting-Parrish, Magdalen
%S Proceedings of the Artificial Intelligence in Measurement and Education Conference (AIME-Con): Full Papers
%D 2026
%8 October
%I National Council on Measurement in Education (NCME)
%C Wyndham Grand Pittsburgh Downtown, Pittsburgh, Pennsylvania, United States
%@ 979-8-9983004-0-0
%F fukuhara-domingue-2026-llms
%X LLM simulation suffers from an “over-knowledge problem”, where models perform too well to represent struggling learners. We compare persona-, IRT-, and CDM-based prompting for student simulation and measure how well methods reflect expected behaviors and quantify this bias. Findings show LLMs follow IRT parameters, yet struggle to simulate real abilities.
%U https://aclanthology.org/2026.aimecon-main.47/
%P 421-432

Markdown (Informal)

[Can LLMs Interpret Psychometric Parameters? Quantifying "Over-Knowledge" in LLM Student Simulation](https://aclanthology.org/2026.aimecon-main.47/) (Fukuhara & Domingue, AIME-Con 2026)

• Can LLMs Interpret Psychometric Parameters? Quantifying “Over-Knowledge” in LLM Student Simulation (Fukuhara & Domingue, AIME-Con 2026)

ACL

• Kazunori Fukuhara and Benjamin Domingue. 2026. Can LLMs Interpret Psychometric Parameters? Quantifying "Over-Knowledge" in LLM Student Simulation. In Proceedings of the Artificial Intelligence in Measurement and Education Conference (AIME-Con): Full Papers, pages 421–432, Wyndham Grand Pittsburgh Downtown, Pittsburgh, Pennsylvania, United States. National Council on Measurement in Education (NCME).