A SYSTEMATIC REVIEW OF ARTIFICIAL INTELLIGENCE APPLICATIONS IN HIGHER EDUCATION: LOCATING THE ROLE OF EDUCATORS

Abstract

Although artificial intelligence (AI) is becoming increasingly important in higher education, little research has examined these phenomena from an educational perspective. Through a comprehensive evaluation of 146 peer-reviewed empirical studies published between 2007 and 2018, this paper addresses the lack of pedagogical and ethical considerations in current AI-oriented publications. Based on accepted rules for evidence synthesis, the review used a methodical approach, including papers indexed in Scopus, Web of Science, and EBSCO Education Source. With only 6.2% of academics having an eye toward education, the statistics show a predominance of papers from Computer Science and STEM fields. Four main areas define artificial intelligence applications in higher education: intelligent tutoring systems, adaptive systems and personalisation, assessment and evaluation, and profiling and prediction. Only a tiny minority of research addressed ethical issues or instructional frameworks; most employed quantitative approaches. This assessment concludes that while artificial intelligence shows potential for improving educational processes, current research lacks significant input from teachers and remains technologically oriented. It advocates for multidisciplinary cooperation and theory-based methods to ensure that AI supports ethical norms and educational objectives.