AI-INTEGRATED QUALITY MANAGEMENT SYSTEMS IN HIGHER EDUCATION: ENHANCING TRANSPARENCY, ACCOUNTABILITY, AND INSTITUTIONAL PERFORMANCE
https://doi.org/10.59982/18294359-26.1-ao-02
Abstract
Artificial intelligence (AI) is transforming quality assurance in higher education from a compliance-oriented, periodic activity into an integrated quality management system (QMS) that involves continuous monitoring, predictive analytics, and data-driven institutional governance. Artificial intelligence can enhance important processes like assessment, learning analytics, and performance evaluation. It also brings complex challenges of transparency, accountability, fairness, and ethical governance.
This study investigates the application of AI in quality assurance from the perspective of quality management theory, with a focus on the significance of continuous improvement models, especially the Plan–Do–Check-Act (PDCA) cycle, risk-based thinking, and stakeholder involvement. Based on recent empirical studies, international policy frameworks and the theoretical literature, the paper proposes an AI-integrated quality management framework for higher education institutions.
Our findings indicate that AI contributes to institutional effectiveness when embedded in transparent, accountable and human-centric quality management systems underpinned by explainable processes, traceable evidence and strong governance mechanisms. The paper further argues that AI literacy and ethical oversight, as well as adherence to international standards and regulations, are necessary for sustainability in implementation.
Keywords: artificial intelligence (AI), quality management system (QMS), higher education, quality assurance, PDCA cycle, institutional governance, data-driven decision-making.
PAGES : 29-36