Generative AI in Distance Education: A Human-in-the-Loop Framework for Personalization, Inclusion and Academic Integrity

Generative Artificial Intelligence (GenAI) is creating new possibilities for distance education through conversational learning support, personalised explanations, automated feedback and multilingual assistance. However, its integration also raises concerns regarding academic integrity, unequal access, information reliability, learner autonomy and data privacy. This paper develops a conceptual framework for integrating GenAI into distance education through a human-in-the-loop approach. Drawing on relevant scholarly literature and international educational policy documents, the study examines the relationship between AI-supported personalisation, inclusive learning, human oversight and academic accountability. It proposes an integrated framework in which teachers and learners retain meaningful decision-making authority while AI provides supplementary educational support. The framework comprises five dimensions: human agency, equitable access, learner-centred personalisation, academic integrity and responsible data governance. The paper argues that technological availability alone cannot guarantee educational improvement; effective implementation also requires AI literacy, appropriate assessment practices, institutional policies and continuous human evaluation. The proposed framework offers conceptual guidance for higher-education institutions seeking to adopt GenAI responsibly in distance-learning environments. As a conceptual contribution, it requires subsequent empirical evaluation to establish its applicability across different educational contexts.