Evaluating self-directed learning competencies in digital learning environments: A meta-analysis

During the digital age, self-directed learning has emerged as an effective teaching strategy in designing class activities within the educational sphere, prompting an investigation into its impact on the effectiveness of instruction in the K-12 context. This article presents a meta-analysis aimed at examining the efficacy of self-directed learning in enhancing the learning performance of K-12 students. A comprehensive review of English-language publications up to December 2023 was conducted, drawing from major databases such as Embase, Scopus, PubMed, CINAHL, and the Web of Science. This rigorous selection process resulted in the identification of 17 studies, encompassing a total of 2,725 students who met the exacting inclusion criteria. Analysis of the data, facilitated by the use of Comprehensive Meta Analysis software, demonstrated that self-directed learning significantly improves students’ learning outcomes when compared with traditional teaching methods. This improvement is quantitatively supported by a standardized mean difference of 0.366 (95% CI [0.295, 0.438], p <.000). The findings from this meta-analysis advocate for the adoption of self-directed learning as an integral pedagogical approach in K-12 education, highlighting its potent ability to substantially elevate learning performance.