THE IMPACT OF AI ON STUDENTS' INDEPENDENCY IN LEARNING: A SYSTEMATIC REVIEW
Keywords:
Artificial Intelligence, AI integration, independent learning, self-directed learning, systematic review, educational technologyAbstract
This study aims to examine the impact of AI integration on students’ independent learning through a systematic review of relevant scholarly literature. The research synthesizes findings from peer-reviewed journal articles focusing on studies that discuss the use of AI-based applications in educational settings and their influence on students’ self-directed or independent learning. The systematic review process involves identifying, selecting, and analyzing empirical and theoretical studies from reputable academic databases. The results indicate that AI integration contributes positively to students’ independent learning by facilitating personalized instruction, promoting self-regulated learning, increasing learning motivation, and enabling flexible access to learning resources. Furthermore, AI-powered tools such as intelligent tutoring systems, automated feedback systems, and adaptive learning platforms encourage students to take greater responsibility for their own learning processes. However, several challenges are also identified, including overreliance on technology, limited digital literacy, and ethical concerns related to data privacy and academic integrity. Overall, the findings highlight that the effective integration of AI can support the development of students’ independent learning when accompanied by appropriate pedagogical strategies and digital literacy support. This study provides insights for educators, researchers, and policymakers in understanding the role of AI in fostering autonomous learning in modern educational contexts.
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