FROM CHALKBOARDS TO ALGORITHMS: THE TRANSFORMATION OF UZBEK EDUCATION
Annotatsiya
Despite the global surge in research on artificial intelligence (AI) in education, the pedagogical implications of AI integration within post-Soviet, nationally distinctive educational systems — such as that of Uzbekistan — remain substantially undertheorized. This article introduces an original conceptual framework, the Multilevel AI-Augmented Pedagogy Model (MAAPM), developed specifically to account for the structural, linguistic, cultural, and institutional characteristics of the Uzbek educational continuum — spanning preschool through higher education. The framework synthesizes three theoretical pillars: Vygotsky’s zone of proximal development (ZPD), Bloom’s revised taxonomy of educational objectives, and the newly proposed Pedagogical AI Mediation Theory (PAIMT). Drawing on the policy architecture of Uzbekistan’sEducation Development Strategy 2030 and Digital Uzbekistan 2030, the article argues that AI’s pedagogical value is not inherent in the technology itself but is constituted through the quality of mediation structures — human, institutional, and algorithmic — that surround it. The MAAPM identifies five original constructs: Adaptive Instructional Scaffolding (AIS), Culturally Responsive AI (CRAI), Multilingual Pedagogical Alignment (MPA), Formative Intelligence Loops (FIL), and Educator Agency Preservation (EAP). Implications for curriculum policy, teacher preparation, and national AI-in-education governance in Uzbekistan are discussed.
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