Artificial Intelligence and Self-Regulated learning Applications
(A systematic review by the Saudi Digital Library, 2020-2025)
DOI:
https://doi.org/10.33193/AJHASS.81Keywords:
Artificial Intelligence, Self-Regulated Learning, Systematic ReviewAbstract
This study aimed to reveal the volume of research on artificial intelligence and self-regulated learning according to publication year, the most targeted groups, the most prominent research methodologies used, the most prominent trends in terms of the topics addressed, and the results obtained; and finally, to present some future trends related to this phenomenon. To achieve these objectives, a survey of foreign and Arabic research in the Saudi Digital Library was conducted between 2022 and 2025. The data was analyzed quantitatively and qualitatively, and the study found that the peak of research interest in the study topic occurred in 2025, reflecting the growing interest in the intersection of artificial intelligence and self-regulated learning. A diversity of target samples was found (students, teachers, student teachers, and studies), with university students being the most targeted group in English-language studies. A clear diversity of methodologies was found in English-language studies, while Arabic studies relied heavily on quasi-experimental approaches. Quantitative methodologies were found to be the most frequently used, followed by qualitative, with a clear emphasis on methodological reviews. The study's findings revealed that employing artificial intelligence (AI) technologies in educational environments significantly contributes to enhancing learner autonomy and their ability to plan, monitor, and self-evaluate their learning. The results also confirmed that self-regulated learning is a fundamental requirement for effective learning in the digital age, especially given the rapid transformations in the field of education and the trend toward e-learning and smart learning. The study highlighted that the conscious and systematic integration of AI applications can provide more flexible and adaptable learning opportunities that cater to learners' individual needs and differences. Based on these findings, the study offered a set of recommendations that can contribute to developing educational practices and guiding researchers toward future research areas that deepen the scientific understanding of the relationship between AI and self-regulated learning, particularly within the Arab educational context.
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