The Role of Self-Regulated Learning in Enhancing Computational Thinking Skills: A Systematic Literature Review and Bibliometric Analysis

Abstract

Self-regulated learning (SRL) is widely recognized as one of the strongest predictors of academic success; however, its specific role in fostering the development of computational thinking (CT) has not been fully scrutinized. Objective: This study aims to map the development of research, identify key trends and themes, and analyze the intellectual structure of the literature at the intersection of SRL and CT through a systematic literature review and bibliometric analysis. Methods: A total of 38 Scopus-indexed journal articles were selected following the PRISMA 2020 guidelines, and their methodological quality was appraised using a structured five-criterion rubric adapted from established critical-appraisal criteria (Kmet et al., 2004). VOSviewer (v1.6.20) was used to visualize keyword co-occurrence networks and co-authorship networks, whilst Bibliometrix (R package v4.2.3) was used to analyze publication trends, author productivity, source impact, and thematic evolution. Findings: The analysis revealed significant growth in publications from 2017 to 2026, peaking in 2025. The United States, Taiwan, and China were the main contributors. Key thematic clusters included SRL scaffolding in programming education, metacognition and CT assessment, and personalized learning environments. The reciprocal relationship between SRL and CT is identified as the most prominent research trajectory in the recent period. Conclusion: This review highlights critical research gaps, particularly the scarcity of longitudinal studies and the still-limited representation of the Global South, whilst providing a roadmap for future empirical and pedagogical investigations at the intersection of SRL and CT. Keywords: self-regulated learning, computational thinking, bibliometric analysis, systematic literature review, VOSviewer, Bibliometrix.