OBSTACLES TO INTEGRATING ARTIFICIAL INTELLIGENCE INTO PROGRAM ACCREDITATION AT SAUDI UNIVERSITIES: A FIELD STUDY

Abstract

The study aimed to identify the regulatory, legislative, material, and human obstacles to employing Artificial Intelligence (AI) applications in program accreditation procedures and processes at Saudi universities. The study adopted a mixed-methods approach utilizing an Explanatory Sequential Design. A questionnaire was used as a quantitative instrument administered to a sample of (436) members of development and quality committees and external reviewers, while interviews were conducted as a qualitative instrument with a purposive sample of (13) participants to interpret the findings. The study yielded several results, most notably that regulatory, legislative, material, and human obstacles exist to a high degree. Regulatory and legislative obstacles ranked first, followed by human obstacles, and finally material obstacles.