Data-Driven and AI-Based Higher Education Accreditation: International Experiences and Implications for Vietnam
DOI:
https://doi.org/10.65150/EP-jmrr/V2E5/2026-08Keywords:
higher education quality, data, accreditation, artificial intelligence, digital transformationAbstract
This paper investigates the application of data and artificial intelligence (AI) to innovate higher education accreditation in the context of digital transformation. The study employs document analysis and theoretical synthesis, combined with international experience comparison, to clarify the trend of data-driven accreditation. Findings reveal that higher education accreditation is shifting from periodic evaluation models to continuous quality monitoring based on data, with AI playing a supportive role in analysis, visualization, and early warning. However, Vietnam’s accreditation system remains limited in terms of data standardization, system interoperability, and technological capacity. Accordingly, the study proposes a data- and AI-driven accreditation model built upon three pillars: institutional and governance frameworks, data and technological infrastructure, and human resource capacity, accompanied by a phased implementation roadmap. The research contributes scientific foundations and policy implications for innovating higher education accreditation in Vietnam in the digital era.
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Copyright (c) 2026 Tran Thi Ngat (Author)
This work is licensed under a Creative Commons Attribution 4.0 International License.
