Research Article

A review of automatic item generation techniques leveraging large language models

Volume: 12 Number: 2 June 1, 2025
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A review of automatic item generation techniques leveraging large language models

Abstract

This study reviews existing research on the use of large language models (LLMs) for automatic item generation (AIG). We performed a comprehensive literature search across seven research databases, selected studies based on predefined criteria, and summarized 60 relevant studies that employed LLMs in the AIG process. We identified the most commonly used LLMs in current AIG literature, their specific applications in the AIG process, and the characteristics of the generated items. We found that LLMs are flexible and effective in generating various types of items across different languages and subject domains. However, many studies have overlooked the quality of the generated items, indicating a lack of a solid educational foundation. Therefore, we share two suggestions to enhance the educational foundation for leveraging LLMs in AIG, advocating for interdisciplinary collaborations to exploit the utility and potential of LLMs.

Keywords

References

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Details

Primary Language

English

Subjects

Measurement Theories and Applications in Education and Psychology , Measurement and Evaluation in Education (Other)

Journal Section

Research Article

Early Pub Date

May 1, 2025

Publication Date

June 1, 2025

Submission Date

December 16, 2024

Acceptance Date

April 28, 2025

Published in Issue

Year 2025 Volume: 12 Number: 2

APA
Tan, B., Armoush, N., Mazzullo, E., Bulut, O., & Gierl, M. (2025). A review of automatic item generation techniques leveraging large language models. International Journal of Assessment Tools in Education, 12(2), 317-340. https://doi.org/10.21449/ijate.1602294

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