Artificial Intelligence Applications in Quality Management Systems of Philippine Higher Education Institutions

Abstract

AbstractTo ensure quality assurance, Higher Education Institutions (HEIs) implement a Quality Management System (QMS) anchored on international benchmarks like ISO 9001:2015 Standards. With the COVID-19 pandemic, quality audits have become more challenging. Also, to address the lapses due to human error and lack of technical knowledge in clause identification during audit processes, an artificial intelligence (AI)-enabled QMS is presented. This study successfully demonstrated how AI-enabled QMS can match audit findings in accreditation compliance reports and internal quality audit reports with the clauses of ISO 9001:2015. Audit findings corpus data gathered are within the span of the last five years, which serve as the dataset to be employed. After data pre-processing, a long short-term memory (LSTM) deep neural network was created and trained using MATLAB. The AI model achieved a combined classification accuracy (CA) of 82.15% and predicted 70% of the examined audit findings in actual implementation. Further analyses illustrate how AI can be maximized in generating useful and precise and useful audit reports for HEIs to develop and implement globally competitive educational policies, programs, and standards.KeywordsArtificial intelligenceAudit reportPhilippine higher education institutionsISO 9001:2015Quality Management Systems