<?xml version="1.0" encoding="UTF-8"?>
<modsCollection xmlns="http://www.loc.gov/mods/v3">
<mods ID="fernandez-etal-2026-cap">
    <titleInfo>
        <title>CAP: Cross-Ability Preferences to Align Student Simulators for Item Difficulty Prediction</title>
    </titleInfo>
    <name type="personal">
        <namePart type="given">Nigel</namePart>
        <namePart type="family">Fernandez</namePart>
        <role>
            <roleTerm authority="marcrelator" type="text">author</roleTerm>
        </role>
    </name>
    <name type="personal">
        <namePart type="given">Alexander</namePart>
        <namePart type="family">Scarlatos</namePart>
        <role>
            <roleTerm authority="marcrelator" type="text">author</roleTerm>
        </role>
    </name>
    <name type="personal">
        <namePart type="given">Christopher</namePart>
        <namePart type="family">Ormerod</namePart>
        <role>
            <roleTerm authority="marcrelator" type="text">author</roleTerm>
        </role>
    </name>
    <name type="personal">
        <namePart type="given">Andrew</namePart>
        <namePart type="family">Lan</namePart>
        <role>
            <roleTerm authority="marcrelator" type="text">author</roleTerm>
        </role>
    </name>
    <originInfo>
        <dateIssued>2026-10</dateIssued>
    </originInfo>
    <typeOfResource>text</typeOfResource>
    <relatedItem type="host">
        <titleInfo>
            <title>Proceedings of the Artificial Intelligence in Measurement and Education Conference (AIME-Con): Full Papers</title>
        </titleInfo>
        <name type="personal">
            <namePart type="given">Joshua</namePart>
            <namePart type="family">Wilson</namePart>
            <role>
                <roleTerm authority="marcrelator" type="text">editor</roleTerm>
            </role>
        </name>
        <name type="personal">
            <namePart type="given">Christopher</namePart>
            <namePart type="family">Ormerod</namePart>
            <role>
                <roleTerm authority="marcrelator" type="text">editor</roleTerm>
            </role>
        </name>
        <name type="personal">
            <namePart type="given">Magdalen</namePart>
            <namePart type="family">Beiting-Parrish</namePart>
            <role>
                <roleTerm authority="marcrelator" type="text">editor</roleTerm>
            </role>
        </name>
        <originInfo>
            <publisher>National Council on Measurement in Education (NCME)</publisher>
            <place>
                <placeTerm type="text">Wyndham Grand Pittsburgh Downtown, Pittsburgh, Pennsylvania, United States</placeTerm>
            </place>
        </originInfo>
        <genre authority="marcgt">conference publication</genre>
        <identifier type="isbn">979-8-9983004-0-0</identifier>
    </relatedItem>
    <abstract>We develop CAP, a preference optimization-based method for aligning LLM student simulators to student ability. It constructs preference pairs from IRT ability gaps, training the simulator to generate responses that better reflect prompted ability, enabling simulation-based estimation of open-ended item difficulty.</abstract>
    <identifier type="citekey">fernandez-etal-2026-cap</identifier>
    <location>
        <url>https://aclanthology.org/2026.aimecon-main.37/</url>
    </location>
    <part>
        <date>2026-10</date>
        <extent unit="page">
            <start>332</start>
            <end>344</end>
        </extent>
    </part>
</mods>
</modsCollection>

%0 Conference Proceedings
%T CAP: Cross-Ability Preferences to Align Student Simulators for Item Difficulty Prediction
%A Fernandez, Nigel
%A Scarlatos, Alexander
%A Ormerod, Christopher
%A Lan, Andrew
%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 fernandez-etal-2026-cap
%X We develop CAP, a preference optimization-based method for aligning LLM student simulators to student ability. It constructs preference pairs from IRT ability gaps, training the simulator to generate responses that better reflect prompted ability, enabling simulation-based estimation of open-ended item difficulty.
%U https://aclanthology.org/2026.aimecon-main.37/
%P 332-344

Markdown (Informal)

[CAP: Cross-Ability Preferences to Align Student Simulators for Item Difficulty Prediction](https://aclanthology.org/2026.aimecon-main.37/) (Fernandez et al., AIME-Con 2026)

• CAP: Cross-Ability Preferences to Align Student Simulators for Item Difficulty Prediction (Fernandez et al., AIME-Con 2026)

ACL

• Nigel Fernandez, Alexander Scarlatos, Christopher Ormerod, and Andrew Lan. 2026. CAP: Cross-Ability Preferences to Align Student Simulators for Item Difficulty Prediction. In Proceedings of the Artificial Intelligence in Measurement and Education Conference (AIME-Con): Full Papers, pages 332–344, Wyndham Grand Pittsburgh Downtown, Pittsburgh, Pennsylvania, United States. National Council on Measurement in Education (NCME).