THEORY ON COMPUTATIONAL THINKING IN EDUCATION: A SYSTEMATIC REVIEW

Abstract

Computational Thinking (CT) has become integral to modern education, fostering problem-solving skills essential for navigating a technology-driven world. This Systematic Literature Review (SLR) explores the theoretical landscape underpinning the integration of CT in education. Despite the growing prominence of CT in education, a systematic understanding of the underlying theories remains elusive. This SLR aims to fill this gap by conducting a rigorous analysis of existing literature, discerning patterns and trends in the theoretical frameworks shaping the incorporation of CT into educational contexts. The Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) methodology guides this review. Advanced searching techniques are employed to enhance the precision and inclusiveness of the literature search. The search is executed across Scopus and Web of Science (WoS) databases, ensuring a comprehensive exploration of the available literature. The findings reveal a rich landscape of theoretical perspectives on CT in education. Expert validation emerges as a crucial aspect, and our analysis categorizes it into two prominent key themes: (1) Learning theory on CT and (2) Theory for analysis and validation of CT Instrument. This systematic review contributes a nuanced understanding of the theoretical foundations governing CT in education. By categorizing expert validations into learning theories and instrumental frameworks, this study informs educators, researchers, and policymakers on the diverse theoretical landscape. These insights lay the groundwork for future research endeavors and pedagogical innovations, enriching the ongoing dialogue on the role of CT in shaping the educational landscape.