Mapping the scientific footprint: a bibliometric study of self-regulated learning in music education using network analysis

This study aims to analyze bibliometric trends and thematic relationships in studies on self-regulated learning and self-directed learning in music. Data collected from Scopus include 145 documents published between 2002 and 2024 and analyzed using Biblioshiny and VosViewer tools with the PRISMA approach. The results reveal six main thematic clusters that show a variety of research focuses. The first cluster highlights students' experiences and ease of use of learning technologies. The second cluster focuses on motivation, self-directed learning, and the integration of technologies such as artificial intelligence. The third cluster reviews the role of social robots in supporting self-directed learning. The fourth cluster discusses music teaching and education systems. The fifth cluster connects medical and psychological research with educational contexts, while the sixth cluster, the largest cluster, highlights humans as the main subject, focusing on music, psychology, and learning. This study contributes to understanding global trends, collaboration patterns, and main themes in the literature, as well as opening up opportunities for the development of self-directed learning strategies in music education.