ArticleMedEdPublish (2016)2025
Is your curriculum GenAI-proof? A method for GenAI impact assessment and a case study.
Article in MedEdPublish (2016), 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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7 authors.
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Abstract
Background: Generative AI (GenAI) can complete tasks that previously could only be performed successfully by humans. Although GenAI provides many opportunities, it also poses risks such as invalid assessments and irrelevant learning outcomes. This article presents a broadly applicable method to (1) determine current assessment validity, (2) assess which learning outcomes are impacted by student GenAI use and (3) decide whether to alter assessment formats and/or learning outcomes. This is exemplified by a case-study on our Medical Informatics curriculum. We developed a five-step method to evaluate and address the impact of GenAI. Together with the respective lecturers, all assessments in the courses comprising a curriculum are analysed and subsequently adapted to address the impact of GenAI usage. Results: 57% (55/96) of assessments, especially for courses involving writing and programming, were at risk of reduced validity and relevance. GenAI impact on assessment validity was closer related to the content and structure of assessments than to their complexity according to Bloom's taxonomy. During educational retreats, lecturers discussed the relevance of impacted learning outcomes and whether students should be able to achieve them with or without GenAI. Furthermore, the results led to a plan to increase GenAI literacy and the intentional use by students during their education. For this purpose, course coordinators were asked to either adjust their manner of assessment to preclude GenAI use, or to alter learning outcomes to include GenAI use and literacy. For 64% of the impacted assignments (35/55) the assessment format was adapted and for 36% (20/55) the learning outcomes were adapted. Conclusion: The majority of assessments in our curriculum were at risk of reduced assessment validity and relevance of learning outcomes, necessitating adaptations of either the manner of the assessment or learning outcomes. The proposed method and case-study offer a replicable framework for educational institutions facing similar challenges.
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