STUDENTS’ DEPENDENCY ON ARTIFICIAL INTELLIGENCE IN HIGHER EDUCATION: A SYSTEMATIC LITERATURE REVIEW

Abstract

The rapid development of artificial intelligence (AI) has significantly transformed higher education, particularly in supporting learning processes and academic tasks. However, alongside its benefits, concerns have emerged regarding students’ increasing dependency on AI technologies. This study aims to analyze the use of AI in higher education and examine the extent and implications of student dependency on AI. Employing a Systematic Literature Review (SLR) design, this research synthesizes findings from 23 peer-reviewed international journal articles published between 2019 and 2024. Data were collected from major academic databases and analyzed using a thematic analysis approach to identify key patterns related to AI usage and dependency in learning contexts. The findings reveal that AI provides substantial advantages, including enhanced learning efficiency, improved access to academic resources, and support in understanding complex concepts. However, the study also identifies a growing trend of students relying on AI as a primary tool for completing academic tasks, which may reduce critical thinking, academic independence, and engagement in deeper learning processes. Furthermore, issues related to academic integrity and assessment authenticity have become increasingly prominent. This study contributes to the literature by offering a comprehensive synthesis of both the benefits and risks of AI integration in higher education, emphasizing the need for balanced use. It suggests that clear academic policies and ethical guidelines are essential to ensure that AI functions as a supportive learning tool rather than a substitute for students’ intellectual development.