Accuracy, but also relevance, personalisation, feasibility, creativity, ethics and bias: according to this study, critical AI literacy goes far beyond fact-checking.
The "critical literacy of AI" has become a visible educational goal, but remains unclear when it comes to providing practical guidance to students. Researchers have therefore analyzed student exchanges with a chatbot and their written reflections to understand how they judge, in practice, the content produced by AI. They distinguish seven stages in the conduct of AI-assisted university work and five roles that the tool supports.
Beyond the True and the False
Above all, the study identifies eight evaluation angles mobilized by the students: accuracy, completeness, fit to set-up, customization, practical utility, creativity, ethics and bias. For the authors, using AI critically is not simply a matter of tracking factual errors: it is a judgment that weighs the quality of knowledge, its adaptation to context, its feasibility, its creative value and its moral implications. Their framework is intended as a tool to help teachers move students from passive acceptance of responses to thoughtful and responsible use.
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