Improving the Computational Thinking Abilities of Junior High School Students Through Problem-Based Learning
Abstract
This study aims to improve the Computational Thinking (CT) abilities of seventh-grade students at SMPN 37 Surabaya, based on initial findings indicating that most students in this class exhibit low CT abilities. Efforts to improve CT abilities were made through implementing the Problem-Based Learning (PBL) model, which is effective in facilitating problem-solving skills. The research method used was Classroom Action Research (CAR) with a spiral approach by Stephen Kemmis and Robin McTaggart, conducted over multiple cycles to monitor the gradual development of students' CT abilities. Data were collected through post-tests at the end of each cycle to evaluate improvements in students' CT abilities. Data analysis was conducted using a CT assessment rubric, categorizing students based on CT skills and foundations. The data analysis results indicated an increase in CT scores across each research cycle. In Cycle I, there was an increase of 0.2 in CT scores, with a completion rate of and an average CT score of . In Cycle II, the CT score improvement reached , with a completion rate of and an average CT score of . These findings demonstrate that the implementation of the PBL model significantly improves students' CT abilities. The progression from low to medium and high skill categories by the end of Cycle II highlights the effectiveness of PBL in developing students' CT abilities, making this model relevant for improving critical and systematic thinking skills among students.
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