Accepted for/Published in: JMIR Medical Education
Date Submitted: Jul 6, 2023
Open Peer Review Period: Jul 6, 2023 - Aug 31, 2023
Date Accepted: Aug 17, 2023
(closed for review but you can still tweet)
Anki Tagger: A Generative AI Tool for Aligning Third-Party Resources to Pre-Clinical Curriculum
ABSTRACT
Medical students complete much of their preclinical didactic learning outside of the classroom with the assistance of third-party resources instead of traditional lectures, such as Anki flashcard decks. In this research letter, we describe a novel method to efficiently select relevant flashcards from existing Anki decks and associate those cards with individual lectures within the user’s medical school curriculum. We selected flashcards from the AnKing flashcard deck that contained 35,152 flashcards and tagged them to the preclinical curriculum at our institution. The process developed is highly scalable, with individual lecture guides processed in minutes at a minimal computational cost. The feasibility of implementing Chat-GPT flashcard generation into pre-clerkship medical school curricula has not been evaluated and is an area of future study. Subsequently, a comparison of medical students’ satisfaction with self-made Anki flashcards compared to ChatGPT-tagged Anki flashcard decks should be conducted.
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© The authors. All rights reserved. This is a privileged document currently under peer-review/community review (or an accepted/rejected manuscript). Authors have provided JMIR Publications with an exclusive license to publish this preprint on it's website for review and ahead-of-print citation purposes only. While the final peer-reviewed paper may be licensed under a cc-by license on publication, at this stage authors and publisher expressively prohibit redistribution of this draft paper other than for review purposes.