ARTIFICIAL INTELLIGENCE IN HIGHER EDUCATION: A SYSTEMATIC REVIEW OF APPLICATIONS, EDUCATIONAL OUTCOMES, CHALLENGES, AND FUTURE DIRECTIONS

Abstract

Artificial intelligence (AI) has become one of the most influential technologies in contemporary transformations in higher education, as its applications are no longer limited to technical and administrative aspects, but have extended to learning, teaching, assessment, and academic decision-making support. Recent literature has shown the expansion of the use of AI technologies in universities, through smart teaching systems, adaptive learning, predictive analytics, and machine assessment, and all the way to generative AI applications. Despite the opportunities provided by these technologies to improve the quality of education and personalize learning experiences, their use simultaneously raises educational, ethical, and organizational challenges that call for an integrated examination of the available research evidence (Crompton & Burke, 2023). This study aims to provide a systematic review of the literature related to the use of artificial intelligence in higher education, focusing on its main applications and effects on learning and teaching processes, as well as identifying the most prominent challenges associated with its employment and future research trends in this field. The study starts from the importance of moving from looking at artificial intelligence as a technical tool to analyzing it within an integrated educational context that clarifies its relationship with learners, teachers, assessment processes, and educational management, especially in light of the rapid development of artificial intelligence applications in educational institutions (Chiu et al., 2023).