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◆ Higher Education for the Future2025-12-08· Dialogical self

Reimagining Quality: Artificial Intelligence, Governance and the Politics of Data in Higher Education

Duong Anh Dung, Nguyen Thi Toan, Nguyen Duy Minh, Nguyen Quynh Anh

原始摘要(英文原文)· Original abstract
Artificial intelligence (AI) is rapidly reshaping how quality is defined, measured and governed in higher education. This article critically examines the cultural and ideological implications of AI integration in educational quality assurance, focusing on Vietnam as a site of contested technological translation. Drawing on Science and Technology Studies, the study explores how algorithmic systems reconfigure traditional pedagogical values, hierarchical relationships and conceptions of authority—shifting power from professional judgement to data infrastructures. In doing so, AI introduces a new epistemic regime that privileges quantification, predictability and managerial control, often at odds with local traditions of moral education and dialogical learning. The article argues that this transition is not merely technological but reflects deeper neoliberal logics and knowledge cultures that increasingly dominate global education policy. Through a mixed-methods approach combining bibliometric mapping, institutional case studies and practitioner surveys, the research reveals both the promises and frictions of AI-driven quality assurance. Rather than treating AI as a neutral instrument, the article positions it as a cultural actor that co-produces new forms of governance, visibility and exclusion.1 It concludes by calling for more reflexive, participatory and culturally situated approaches to educational technology.
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Reimagining Quality: Artificial Intelligence, Governance and the Politics of Data in Higher Education — 科研速览 Science Skim