GENERATIVE AI GOVERNANCE IN DISTANCE HIGHER EDUCATION: ALIGNING UZBEKISTAN’S DIGITAL LEARNING METHODOLOGY WITH INTERNATIONAL STANDARDS

Аннотация

Generative artificial intelligence has entered higher education faster than any previous technology, and distance learning is its most exposed frontier. Students in online programmes now routinely use generative tools to brainstorm, draft and revise, while institutions struggle to articulate what is permitted, what is prohibited and how academic integrity is to be preserved. This paper develops a governance framework for generative AI in distance higher education and applies it to Uzbekistan's digital-learning context. Drawing on UNESCO's humancentred guidance, the European Union's evolving regulatory approach and comparative universitypolicy studies, we construct a five-stage governance-maturity ladder and a decision matrix that translates principles into classroom-level rules. We document a widening gap between student adoption and institutional policy, analyse where generative AI is actually used across student, faculty and administrative roles, and map current programmes onto the maturity ladder. We conclude that governance, not prohibition, is the realistic path, and that aligning national methodology with international standards offers emerging economies a credible route to trustworthy AI-enabled distance education.