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        <title>Evidence-Centered Design for AI-Driven Automated Item Generation in Applied Mathematics</title>
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        <namePart type="given">Elena</namePart>
        <namePart type="family">Oliveri</namePart>
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    <name type="personal">
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    <abstract>We discuss how human-led Evidence-Centered Design (ECD) can inform the development of AI-supported automated item generation (AIG), as well as how it can be used as a quality-control mechanism. In this particular application, we describe how we collaborated with Claude Sonnet 5 to produce kinematics items together with interactive tools through an AIG pipeline. A preliminary qualitative analysis of a small number of generated items suggested they have identifiable strengths and weaknesses, which we discuss in depth per item.</abstract>
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%0 Conference Proceedings
%T Evidence-Centered Design for AI-Driven Automated Item Generation in Applied Mathematics
%A Graf, Edith Aurora
%A Oliveri, Maria Elena
%A Oliveri, Giulia
%A Proctor, Emily
%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 graf-etal-2026-evidence
%X We discuss how human-led Evidence-Centered Design (ECD) can inform the development of AI-supported automated item generation (AIG), as well as how it can be used as a quality-control mechanism. In this particular application, we describe how we collaborated with Claude Sonnet 5 to produce kinematics items together with interactive tools through an AIG pipeline. A preliminary qualitative analysis of a small number of generated items suggested they have identifiable strengths and weaknesses, which we discuss in depth per item.
%U https://aclanthology.org/2026.aimecon-sessions.22/
%P 210-218

Markdown (Informal)

[Evidence-Centered Design for AI-Driven Automated Item Generation in Applied Mathematics](https://aclanthology.org/2026.aimecon-sessions.22/) (Graf et al., AIME-Con 2026)

• Evidence-Centered Design for AI-Driven Automated Item Generation in Applied Mathematics (Graf et al., AIME-Con 2026)

ACL

• Edith Aurora Graf, Maria Elena Oliveri, Giulia Oliveri, and Emily Proctor. 2026. Evidence-Centered Design for AI-Driven Automated Item Generation in Applied Mathematics. In Proceedings of the Artificial Intelligence in Measurement and Education Conference (AIME-Con): Coordinated Session Papers, pages 210–218, Wyndham Grand Pittsburgh Downtown, Pittsburgh, Pennsylvania, United States. National Council on Measurement in Education (NCME).