THE USE OF GENERATIVE ARTIFICIAL INTELLIGENCE FOR SELF-LEARNING IN UNIVERSITY STUDENTS

Abstract

Generative Artificial Intelligence is promptly evolving, reshaping various perspectives of university academia. Therefore, it is necessary to understand how these tools are involved in study habits. This systematic review integrates the existing research on using Generative Artificial Intelligence (GenAI) for self-learning in university students for their academic work. The main objectives of this review are to explore how students engage with generative AI tools to support independent learning processes, including content creation, problem-solving, and augmenting previous knowledge acquisition. It seeks to quantify the perceived advantages of using these technologies, particularly in personalized learning experiences, productivity gains, and overall ease of use. Furthermore, the research addresses the limitations and challenges of applying generative AI, such as those about accuracy issues, possible overdependence, ethical and moral factors that may arise when utilizing it in independent learning settings. To assess the impact of generative AI on students' critical thinking, creativity, and independent problem-solving skills. Using a systematic search of research papers [since 2024], we analyzed reported applications, benefits, challenges, and disadvantages regarding the above-mentioned theme. Mainly included individualized tutoring, self-researching, content creation, and writing assistance with benefits. As well as talking about disadvantages such as how AI affects critical thinking, plagiarism, and privacy concerns. Quantitative qualitative, and mixed-method research published in English exploring the Generative AI use for self-studying. The review involved 10 research studies comprising 2,608 individuals from several state universities. The findings clarify the need to develop students' AI literacy and clear university policies to ensure the use of those powerful tools is ethical and responsible.