<?xml version="1.0" encoding="UTF-8"?>
<modsCollection xmlns="http://www.loc.gov/mods/v3">
<mods ID="seo-2026-designing">
    <titleInfo>
        <title>Designing and Evaluating a Measurement-Oriented RAG Framework for ELL Writing Assessment</title>
    </titleInfo>
    <name type="personal">
        <namePart type="given">Daeryong</namePart>
        <namePart type="family">Seo</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): Works in Progress</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">979-8-9983004-1-7</identifier>
    </relatedItem>
    <abstract>This design-focused study compared measurement-oriented ELL_RAG with conventional RAG for writing-assessment analytics. ELL_RAG showed a descriptive advantage overall and on global/population-level tasks, while local-evidence performance was nearly equivalent. Findings support task–evidence alignment rather than universal superiority and highlight tool orchestration as a continuing design challenge.</abstract>
    <identifier type="citekey">seo-2026-designing</identifier>
    <location>
        <url>https://aclanthology.org/2026.aimecon-wip.15/</url>
    </location>
    <part>
        <date>2026-10</date>
        <extent unit="page">
            <start>104</start>
            <end>112</end>
        </extent>
    </part>
</mods>
</modsCollection>

%0 Conference Proceedings
%T Designing and Evaluating a Measurement-Oriented RAG Framework for ELL Writing Assessment
%A Seo, Daeryong
%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 seo-2026-designing
%X This design-focused study compared measurement-oriented ELL_RAG with conventional RAG for writing-assessment analytics. ELL_RAG showed a descriptive advantage overall and on global/population-level tasks, while local-evidence performance was nearly equivalent. Findings support task–evidence alignment rather than universal superiority and highlight tool orchestration as a continuing design challenge.
%U https://aclanthology.org/2026.aimecon-wip.15/
%P 104-112

Markdown (Informal)

[Designing and Evaluating a Measurement-Oriented RAG Framework for ELL Writing Assessment](https://aclanthology.org/2026.aimecon-wip.15/) (Seo, AIME-Con 2026)

• Designing and Evaluating a Measurement-Oriented RAG Framework for ELL Writing Assessment (Seo, AIME-Con 2026)

ACL

• Daeryong Seo. 2026. Designing and Evaluating a Measurement-Oriented RAG Framework for ELL Writing Assessment. In Proceedings of the Artificial Intelligence in Measurement and Education Conference (AIME-Con): Works in Progress, pages 104–112, Wyndham Grand Pittsburgh Downtown, Pittsburgh, Pennsylvania, United States. National Council on Measurement in Education (NCME).