Using artificial intelligence to provide a ‘flipped assessment’ approach to medical education learning opportunities
Year: 2024
Type: article
Study design: Clinical Trial
Abstract: PURPOSE: Generative AI can potentially streamline the creation of practice exam questions. This study sought to evaluate medical students' confidence using generative AI for this purpose, and overall attitudes towards its use. MATERIALS AND METHODS: The study used a mixed-methods approach with a pre-post intervention design. 68 medical and physician associate students were recruited to attend a workshop where they were shown how to use Google Bard (now Gemini) to write exam questions before being encouraged to do this themselves with guidance. A survey was completed before and after. Seven students also participated in a follow-up focus group. RESULTS: < 0.001) after the workshop. Qualitative feedback highlighted pros and cons of using generative AI to write exam questions, alongside some concerns about its implementation. Students noted other positive uses in the curriculum and expressed a desire for institutional clarity on appropriate AI use. CONCLUSIONS: While increased confidence is positive, rigorous evaluation of AI-generated question quality is needed to confirm accuracy. Teaching students to use generative AI to create and critique practice questions represents a means of encouraging appropriate AI use.
Source: Medical Teacher
Authors: Samuel Birks, James Gray, Claire Darling-Pomranz
Institution: University of Sheffield
Language: English
Subfield: Health Informatics
Field: Medicine
Domain: Health Sciences
Open Access status: hybrid
OpenAlex ID: W4404891178