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        <title>Building Teacher Capacity to Generate and Evaluate Math Items with Small LLMs</title>
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        <namePart type="given">Minseok</namePart>
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            <namePart type="given">Joshua</namePart>
            <namePart type="family">Wilson</namePart>
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        <name type="personal">
            <namePart type="given">Christopher</namePart>
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                <roleTerm authority="marcrelator" type="text">editor</roleTerm>
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        <name type="personal">
            <namePart type="given">Magdalen</namePart>
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    <abstract>Small language models can run offline in a classroom, but they make mathematical errors no teacher can afford to miss. This work-in-progress proposes a measurement-grounded professional development model in which upper-elementary teachers use local LLMs to generate and critically evaluate items; an illustrative pilot demonstrates feasibility, teacher-impact study planned.</abstract>
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%0 Conference Proceedings
%T Building Teacher Capacity to Generate and Evaluate Math Items with Small LLMs
%A Kim, Minseok
%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 kim-2026-building
%X Small language models can run offline in a classroom, but they make mathematical errors no teacher can afford to miss. This work-in-progress proposes a measurement-grounded professional development model in which upper-elementary teachers use local LLMs to generate and critically evaluate items; an illustrative pilot demonstrates feasibility, teacher-impact study planned.
%U https://aclanthology.org/2026.aimecon-wip.44/
%P 344-349

Markdown (Informal)

[Building Teacher Capacity to Generate and Evaluate Math Items with Small LLMs](https://aclanthology.org/2026.aimecon-wip.44/) (Kim, AIME-Con 2026)

• Building Teacher Capacity to Generate and Evaluate Math Items with Small LLMs (Kim, AIME-Con 2026)

ACL

• Minseok Kim. 2026. Building Teacher Capacity to Generate and Evaluate Math Items with Small LLMs. In Proceedings of the Artificial Intelligence in Measurement and Education Conference (AIME-Con): Works in Progress, pages 344–349, Wyndham Grand Pittsburgh Downtown, Pittsburgh, Pennsylvania, United States. National Council on Measurement in Education (NCME).