Using AI to Activate Students’ Prior Knowledge in Reading Comprehension Activities: Insights from Moroccan Classrooms

   Abstract: This Paper Explores the pedagogical potential of Artificial Intelligence (AI) in supporting the activation of surdents’ prior knowledge as a means to enhance reading comprehension in English as a Foreign Language (EFL) classroom. Grounded in Schemata Theory. It synthesizes recent international and regional research to examine how AI tools can assist Moroccan EFL teachers in designing pre-reading activities that tap into learners’ background knowledge. In Moroccan classrooms, many students struggle to comprehend English texts due to unfamiliar cultural references and limited exposure to the target language. Activating prior knowledge has long been recognized as a key strategy for improving comprehension, yet its implementation remains largely traditional. This paper proposes how emerging AI applications—such as generative chatbots (e.g., ChatGPT), visual content generators, and adaptive pre-reading platforms—can be used to personalize schema activation, offer multimodal scafolding and enhance learner engagement. Drawing on recent literature, this paper highlights examples of classroom applications from different EFL contexts and discusses their relevance to Morocco. It also addresses challenges such as digital access, teacher preparedness, and the ethical use of AI-generated content. The session concludes with practical recommendations for Moroccan EFL educators and policymakers seeking to enhance reading instruction through AI-supported strategies, advocating for a blended approach that positions AI as a pedagogical aid rather than a replacement for teacher expertise.

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