ManuScript Details
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Paper Id:
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IJARW3201
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Title:
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IQA-AI: A CONCEPTUAL FRAMEWORK FOR AI-RESPONSIVE INTERNAL QUALITY ASSURANCE IN VIETNAMESE UNIVERSITIES OF TECHNOLOGY AND ENGINEERING
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| Published in: |
International Journal Of All Research Writings |
| Publisher: |
IJARW |
| ISSN: |
2582-1008 |
| Volume / Issue: |
Volume 8 Issue 3 |
| Pages: |
7
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| Published On: |
9/11/2026 9:34:43 PM (MM/dd/yyyy) |
Main Author Details
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Name:
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Bui Thu Hai |
| Institute: |
Faculty of Information Technology, Nam Dinh University of Technology Education, Vietnam |
Co - Author Details
| Author Name |
Author Institute |
| Le Van Vinh |
Vinh University of Technology and Engineering |
| Thai Anh Tuan |
Vinh University of Technology and Engineering |
| Nguyen Sy Khanh |
Vinh University of Technology and Engineering |
Abstract
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Research Area:
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Artificial Intelligence |
| KeyWord: |
internal quality assurance, generative artificial intelligence, engineering education, authentic assessment, academic integrity, data governance |
| Abstract: |
Generative artificial intelligence (AI) challenges a foundational assumption of internal quality assurance (IQA): an assessed artefact can no longer be treated automatically as trustworthy evidence of a learner’s own competence. This article develops IQA-AI, a conceptual framework for AI-responsive IQA in Vietnamese universities of technology and engineering. The research combines structured document analysis and an international framework crosswalk of ESG 2015, AUN-QA 3.0 and UNESCO guidance with an exploratory descriptive comparison of five Vietnamese institutions. The institutional dataset covers three enabling conditions: doctoral-qualified faculty, internet bandwidth per 1,000 students and the proportion of accredited programmes. Substantial cross-institutional variation was observed, with coefficients of variation of 46.1%, 47.0% and 40.6%, respectively. These data do not measure AI readiness directly, but empirically support a differentiated rather than uniform implementation pathway. The proposed framework comprises six connected components: institutional AI policy, AI-responsive learning outcomes, authentic assessment, academic integrity and AI ethics, quality data governance, and continuous improvement with accountability. A three-phase roadmap links baseline diagnosis, controlled piloting and evidence-based scaling. The study contributes an analytically traceable framework and context-grounded recommendations, while recognising that effectiveness must be tested through expert validation and institutional pilots. |
Citations
Copy and paste a formatted citation or use one of the links to import into a bibliography manager and reference.
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IEEE
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Bui Thu Hai, Le Van Vinh, Thai Anh Tuan, Nguyen Sy Khanh, "IQA-AI: A CONCEPTUAL FRAMEWORK FOR AI-RESPONSIVE INTERNAL QUALITY ASSURANCE IN VIETNAMESE UNIVERSITIES OF TECHNOLOGY AND ENGINEERING", International Journal Of All Research Writings,
vol. 8, no. 3, pp. 28-34, 2026.
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MLA
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Bui Thu Hai, Le Van Vinh, Thai Anh Tuan, Nguyen Sy Khanh "IQA-AI: A CONCEPTUAL FRAMEWORK FOR AI-RESPONSIVE INTERNAL QUALITY ASSURANCE IN VIETNAMESE UNIVERSITIES OF TECHNOLOGY AND ENGINEERING." International Journal Of All Research Writings,
vol 8, no. 3, 2026, pp. 28-34.
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APA
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Bui Thu Hai, Le Van Vinh, Thai Anh Tuan, Nguyen Sy Khanh (2026). IQA-AI: A CONCEPTUAL FRAMEWORK FOR AI-RESPONSIVE INTERNAL QUALITY ASSURANCE IN VIETNAMESE UNIVERSITIES OF TECHNOLOGY AND ENGINEERING. International Journal Of All Research Writings,
8(3), 28-34.
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IQA-AI: A CONCEPTUAL FRAMEWORK FOR AI-RESPONSIVE INTERNAL QUALITY ASSURANCE IN VIETNAMESE UNIVERSITIES OF TECHNOLOGY AND ENGINEERING
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IQA-AI: A CONCEPTUAL FRAMEWORK FOR AI-RESPONSIVE INTERNAL QUALITY ASSURANCE IN VIETNAMESE UNIVERSITIES OF TECHNOLOGY AND ENGINEERING
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