Examining the Role of Artificial Intelligence in Self-Regulated Learning

Abstract

In recent decades, self-regulated learning has emerged as one of the most significant concepts in modern education, empowering learners to actively and independently manage their learning process. At the same time, rapid advancements in artificial intelligence have led to the creation of innovative tools and platforms that can play a crucial role in supporting self-regulated learning. This article examines the role of artificial intelligence in enhancing self-regulated learning processes and employs a descriptive analysis of previous studies. The findings suggest that artificial intelligence, through tools for more accurate assessment, support for effective learning strategies, and the personalization of learning pathways, can significantly improve the efficiency and effectiveness of self-regulated learning. Additionally, case studies have shown that AI tools such as chatbots and recommendation systems, by providing instant feedback and analyzing learning behaviors, can increase motivation and self-efficacy among learners. However, the use of AI in self-regulated learning faces challenges and limitations, such as the need for large and accurate data, ethical issues, privacy concerns, and technical and operational challenges that require careful attention and management. The conclusion emphasizes the importance of employing artificial intelligence to enhance self-regulated learning processes, highlighting the need for further research to overcome existing challenges and develop effective solutions. Finally, the article offers recommendations for improving AI applications in self-regulated learning and outlines a promising future for this field.