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        <title>Programmatic Tiered Prompting for LLM Generation of ELA &amp; Math Items</title>
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            <title>Proceedings of the Artificial Intelligence in Measurement and Education Conference (AIME-Con): Coordinated Session Papers</title>
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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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            <namePart type="given">Magdalen</namePart>
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    <abstract>Using the LBIDAT protocol, we evaluated items generated by three LLMs (Claude, Gemini, GPT) across six zero-shot prompting tiers for 8th-grade standards. Neither prompt tier nor model affected defect severity. ELA items were consistently poor; mathematics items passed the low bar while falling short of appropriate grade-level cognitive complexity.</abstract>
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%0 Conference Proceedings
%T Programmatic Tiered Prompting for LLM Generation of ELA & Math Items
%A Whitecomb, David
%A Wine, Marjorie
%A Hoffman, Alexander
%Y Wilson, Joshua
%Y Ormerod, Christopher
%Y Beiting-Parrish, Magdalen
%S Proceedings of the Artificial Intelligence in Measurement and Education Conference (AIME-Con): Coordinated Session Papers
%D 2026
%8 October
%I National Council on Measurement in Education (NCME)
%C Wyndham Grand Pittsburgh Downtown, Pittsburgh, Pennsylvania, United States
%@ 979-8-9983004-2-4
%F whitecomb-etal-2026-programmatic
%X Using the LBIDAT protocol, we evaluated items generated by three LLMs (Claude, Gemini, GPT) across six zero-shot prompting tiers for 8th-grade standards. Neither prompt tier nor model affected defect severity. ELA items were consistently poor; mathematics items passed the low bar while falling short of appropriate grade-level cognitive complexity.
%U https://aclanthology.org/2026.aimecon-sessions.29/
%P 267-273

Markdown (Informal)

[Programmatic Tiered Prompting for LLM Generation of ELA & Math Items](https://aclanthology.org/2026.aimecon-sessions.29/) (Whitecomb et al., AIME-Con 2026)

• Programmatic Tiered Prompting for LLM Generation of ELA & Math Items (Whitecomb et al., AIME-Con 2026)

ACL

• David Whitecomb, Marjorie Wine, and Alexander Hoffman. 2026. Programmatic Tiered Prompting for LLM Generation of ELA & Math Items. In Proceedings of the Artificial Intelligence in Measurement and Education Conference (AIME-Con): Coordinated Session Papers, pages 267–273, Wyndham Grand Pittsburgh Downtown, Pittsburgh, Pennsylvania, United States. National Council on Measurement in Education (NCME).