Illustrative AI-Generated and Student-Generated MCQs: Random Sample of 30 Paired Items with Item-Level Discrimination Indices

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Authors: Dheyaa Al-Najafi
Cited by: 0

Abstract

This dataset contains a randomly sampled subset of 30 paired multiple-choice questions (MCQs) from a participant-blinded randomized controlled trial comparing AI-generated and student-generated MCQs for formative medical education assessment. Each pair includes one AI-generated and one student-generated MCQ aligned to the same MEDD 411 learning objective. The dataset includes question stems, answer options, answer keys, explanations, shared learning objectives, and de-identified item-level discrimination index values for transparency and reproducibility. AI-generated items were produced using a dual-LLM workflow involving ChatGPT-4.0 for item generation and Google Gemini v1.5 Flash for independent validation. Student-generated items were authored by senior medical students without AI assistance using a structured peer-review process. This public subset is provided to illustrate the item-development protocols and support reproducibility while preserving participant-level confidentiality.

Fields of Study & Subjects

Innovations in Medical Education Artificial Intelligence in Healthcare and Education Artificial Intelligence in Education

Publication details

Journal / source
Zenodo (CERN European Organization for Nuclear Research)
Publication date
18 January 2026
Language
EN
Document type
Dataset