Using a Hybrid of AI and Template-Based Method in Automatic Item Generation to Create Multiple-Choice Questions in Medical Education: Hybrid AIG.

ABSTRACT:

Background

Template-based automatic item generation (AIG) is more efficient than traditional item writing but it still heavily relies on expert effort in model development. While nontemplate-based AIG, leveraging artificial intelligence (AI), offers efficiency, it faces accuracy challenges. Medical education, a field that relies heavily on both formative and summative assessments with multiple choice questions, is in dire need of AI-based support for the efficient automatic generation of items.

Objective

We aimed to propose a hybrid AIG to demonstrate whether it is possible to generate item templates using AI in the field of medical education.

Methods

This is a mixed-methods methodological study with proof-of-concept elements. We propose the hybrid AIG method as a str

SUBMITTER: Kıyak YS 

PROVIDER: S-EPMC11990652 | biostudies-literature | 2025 Apr

REPOSITORIES: biostudies-literature