Bridging Theory and Practice: A Review of CT in K-12 Problem-Solving
DOI:
https://doi.org/10.31004/jerkin.v4i3.4265Keywords:
Computational Thinking, Problem Solving, K-12 EducationAbstract
The digital era demands students master 21st-century skills, with computational thinking (CT) as the fundamental cognitive foundation for problem-solving. Despite policies such as Indonesia's Kurikulum Merdeka integrating CT, significant implementation gaps persist due to insufficient comprehensive guidelines. This study aims to synthesize empirical evidence on CT implementation in enhancing K-12 students' problem-solving abilities through a Systematic Literature Review (SLR). Using ERIC, SpringerLink, ScienceDirect, IEEE Xplore, and Taylor & Francis databases via Publish or Perish, this research identified 973 articles, subsequently filtered to 27 final articles based on rigorous inclusion and exclusion criteria. Analysis reveals that algorithmic thinking (29%), debugging/evaluation (26%), and abstraction (24%) constitute the most dominant CT components developed. The plugged-in approach (69%) dominates implementation through structured/algorithm-based methods (50%) and game-based learning (31%), with Scratch (44%) and Code.org (38%) as primary platforms. The formulated implementation framework demonstrates developmentally appropriate progression from blended (unplugged-plugged) approaches in early elementary, game-based learning in middle elementary, to project-based learning in high school. Findings reveal that while block-based programming and game design are highly effective for algorithmic thinking and debugging, teaching abstraction remains challenging and requires more specific pedagogical strategies. This research contributes a comprehensive knowledge map bridging the gap between juridical policies and CT learning practices in the field, recommending future research directions for formal assessment development, teacher professional development, and interdisciplinary CT integration.
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