Reading motivation and contextualized text design: possibilities of artificial intelligence in the classroom
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This essay proposes an Artificial Intelligence-Supported Contextualized Reading Didactic Model (MDLC-IA) aimed at primary and secondary school teachers to enhance reading motivation among students who show limited interest in traditional school texts. The model is grounded in the principles of situated literacy, intrinsic motivation theory, and multimodal literacy, recognizing that reading becomes more meaningful when texts are connected to students' contexts, experiences, and interests. Within this framework, generative artificial intelligence is conceived as a teacher co-creation tool for designing personalized, context-based reading materials that incorporate the cultural and everyday realities of local communities. The model is organized into five interconnected stages: reading profile assessment, content contextualization, AI-assisted text design, implementation of reading mediation strategies, and continuous assessment combined with the ethical regulation of AI use. It concludes that artificial intelligence does not replace the teacher's role; rather, it strengthens teachers' pedagogical mediation by supporting more inclusive, meaningful, and context-responsive reading practices, ultimately fostering the development of reading competencies required to meet the educational challenges of the twenty-first century.
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