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