Integrating Ai Literacy into Media and Information Literacy Education for Pre-Service Teachers: Pedagogical and Methodological Foundations

The rapid penetration of generative artificial intelligence technologies into the contemporary media ecosystem has fundamentally transformed competency requirements for media and information literacy education. Algorithmic content curation, AI-generated media (including deepfakes), and recommender systems have made integration of AI literacy with media and information literacy an urgent pedagogical-methodological task in pre-service teacher education. This study substantiates the pedagogical-methodological foundations of integrating AI literacy development into media and information literacy education for pre-service teachers, identifies the didactic conditions for this integration, and proposes a Bloom taxonomy-based methodology for systematic AI literacy development. The study employs theoretical-conceptual analysis, comparative pedagogical analysis, didactic modeling, and expert evaluation. The experimental research base included Gulistan State Pedagogical Institute, Andijan State Pedagogical Institute, and Fergana State University. A panel of 14 experts (PhD holders in pedagogical sciences) evaluated the proposed framework with strong inter-rater agreement (Kendall's coefficient of concordance W = 0.81, p < 0.001) and confirmed content validity (Lawshe's CVR = 0.79). The study substantiates five interconnected didactic conditions: integrated content, interactive methods, reflective analysis, ethical deliberation, and authentic media practice. A Bloom taxonomy-based methodology distributes AI literacy development across six cognitive levels — remembering, understanding, applying, analyzing, evaluating, and creating. Four developmental levels are identified: initial, intermediate, advanced, and innovative. The integration of AI literacy into media literacy education through the proposed framework provides a coherent foundation for developing pre-service teachers' competencies in conscious, critical, and responsible engagement with AI-mediated information environments.

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