A Feasibility Study on Retrieval Practice Using Large Language Models

Marcus Leong; Jennifer Rose; Lisa Dierker; Antonio Laverghetta Jr.

A Feasibility Study on Retrieval Practice Using Large Language Models

Marcus Leong, Jennifer Rose, Lisa Dierker, Antonio Laverghetta Jr.

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Abstract

Retrieval practice supports learning but requires educators to build large item banks. We compared LLM-generated and human-written retrieval practice items in an introductory psychology course to test whether LLM items match instructor-written ones in quality. LLM items exhibited overall weaker psychometric properties, suggesting that human supervision may remain necessary during item generation for retrieval practice.

Anthology ID:: 2026.aimecon-main.21
Volume:: Proceedings of the Artificial Intelligence in Measurement and Education Conference (AIME-Con): Full Papers
Month:: October
Year:: 2026
Address:: Wyndham Grand Pittsburgh Downtown, Pittsburgh, Pennsylvania, United States
Editors:: Joshua Wilson, Christopher Ormerod, Magdalen Beiting-Parrish
Venue:: AIME-Con
SIG:
Publisher:: National Council on Measurement in Education (NCME)
Note:
Pages:: 194–203
Language:
URL:: https://aclanthology.org/2026.aimecon-main.21/
DOI:
Bibkey:
Cite (ACL):: Marcus Leong, Jennifer Rose, Lisa Dierker, and Antonio Laverghetta Jr.. 2026. A Feasibility Study on Retrieval Practice Using Large Language Models. In Proceedings of the Artificial Intelligence in Measurement and Education Conference (AIME-Con): Full Papers, pages 194–203, Wyndham Grand Pittsburgh Downtown, Pittsburgh, Pennsylvania, United States. National Council on Measurement in Education (NCME).
Cite (Informal):: A Feasibility Study on Retrieval Practice Using Large Language Models (Leong et al., AIME-Con 2026)
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PDF:: https://aclanthology.org/2026.aimecon-main.21.pdf

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Preformatted

@inproceedings{leong-etal-2026-feasibility,
    title = "A Feasibility Study on Retrieval Practice Using Large Language Models",
    author = "Leong, Marcus  and
      Rose, Jennifer  and
      Dierker, Lisa  and
      Laverghetta Jr., Antonio",
    editor = "Wilson, Joshua  and
      Ormerod, Christopher  and
      Beiting-Parrish, Magdalen",
    booktitle = "Proceedings of the Artificial Intelligence in Measurement and Education Conference ({AIME}-Con): Full Papers",
    month = oct,
    year = "2026",
    address = "Wyndham Grand Pittsburgh Downtown, Pittsburgh, Pennsylvania, United States",
    publisher = "National Council on Measurement in Education (NCME)",
    url = "https://aclanthology.org/2026.aimecon-main.21/",
    pages = "194--203",
    ISBN = "979-8-9983004-0-0",
    abstract = "Retrieval practice supports learning but requires educators to build large item banks. We compared LLM-generated and human-written retrieval practice items in an introductory psychology course to test whether LLM items match instructor-written ones in quality. LLM items exhibited overall weaker psychometric properties, suggesting that human supervision may remain necessary during item generation for retrieval practice."
}

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%0 Conference Proceedings
%T A Feasibility Study on Retrieval Practice Using Large Language Models
%A Leong, Marcus
%A Rose, Jennifer
%A Dierker, Lisa
%A Laverghetta Jr., Antonio
%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 leong-etal-2026-feasibility
%X Retrieval practice supports learning but requires educators to build large item banks. We compared LLM-generated and human-written retrieval practice items in an introductory psychology course to test whether LLM items match instructor-written ones in quality. LLM items exhibited overall weaker psychometric properties, suggesting that human supervision may remain necessary during item generation for retrieval practice.
%U https://aclanthology.org/2026.aimecon-main.21/
%P 194-203

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Markdown (Informal)

[A Feasibility Study on Retrieval Practice Using Large Language Models](https://aclanthology.org/2026.aimecon-main.21/) (Leong et al., AIME-Con 2026)

A Feasibility Study on Retrieval Practice Using Large Language Models (Leong et al., AIME-Con 2026)

ACL

Marcus Leong, Jennifer Rose, Lisa Dierker, and Antonio Laverghetta Jr.. 2026. A Feasibility Study on Retrieval Practice Using Large Language Models. In Proceedings of the Artificial Intelligence in Measurement and Education Conference (AIME-Con): Full Papers, pages 194–203, Wyndham Grand Pittsburgh Downtown, Pittsburgh, Pennsylvania, United States. National Council on Measurement in Education (NCME).