Keeping humans in the loop efficiently by generating question templates instead of questions using AI: Validity evidence on Hybrid AIG.

Journal: Medical teacher
Published Date: Nov 27, 2024

Abstract

BACKGROUND: Manually creating multiple-choice questions (MCQ) is inefficient. Automatic item generation (AIG) offers a scalable solution, with two main approaches: template-based and non-template-based (AI-driven). Template-based AIG ensures accuracy but requires significant expert input to develop templates. In contrast, AI-driven AIG can generate questions quickly but with inaccuracies. The Hybrid AIG combines the strengths of both methods. However, neither have MCQs been generated using the Hybrid AIG approach nor has any validity evidence been provided.

Authors

  • Yavuz Selim Kıyak
    Department of Medical Education and Informatics, Faculty of Medicine, Gazi University, Ankara, Turkey.
  • Emre Emekli
    Department of Radiology, Eskişehir Osmangazi University, Eskişehir, Turkiye; Department of Medical Education, Gazi University, Ankara, Turkiye.
  • Özlem Coşkun
    Department of Medical Education and Informatics, Faculty of Medicine, Gazi University, Ankara, Turkey.
  • Işıl İrem Budakoğlu
    Department of Medical Education and Informatics, Faculty of Medicine, Gazi University, Ankara, Turkey.

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