In this study, we analyse publicly accessible course catalogues from a sample of several European universities, examining the presence, framing, and disciplinary distribution of AI literacy content.

Module descriptors have been analysed for both explicit and implicit references to AI literacy, using a competency mapping framework based on the European DigComp 2.2 and UNESCO’s AI Competency Framework for Students.
The analysis shows what percentage of module descriptors mention AI literacy at all, broken down three ways.
• Overall rate across all module descriptors (e.g. "23% of all module descriptors contained at least one AI literacy reference")
• Rate by country (e.g. UK vs Germany vs France vs Spain vs Netherlands)
• Rate by discipline cluster (STEM vs social science vs humanities vs business vs education)
• Rate by explicit vs implicit distinction separately
The analysis highlights a clear disconnect between policy recommendations and actual curriculum content: AI literacy is largely present in computing and engineering programs, whereas disciplines like humanities, arts, and education show almost no such content.
The study also highlights the general trend in adopting AI Literacy between elite universities, middle-ranked ones and, finally, lower-tier universities.

This study presents one of the first large scale empirical assessments of AI literacy across European higher education curricula, delivering practical recommendations for curriculum developers and education policymakers aiming to put institutional AI strategies into practice.

Authors:
Ghita Kouadri Mostefaoui, University College London, United Kingdom

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Posted by James Alexander Gordon

Last updated: 2023-02-23 23:45:00

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