The Effect of Scratch-Assisted Problem-Based Learning on Students’ Mathematical Computational Thinking Skills
DOI:
https://doi.org/10.35706/radian.v5i1.13473Keywords:
Linear Equations and Inequalities, Mathematical Computational Thinking, Mathematics Learning, Problem-Based Learning, ScratchAbstract
Computational thinking in mathematics is important to develop through learning, but students are not accustomed to activities involving decomposition, pattern recognition, abstraction, and algorithmic thinking. This study aims to determine whether students' mathematical computational thinking abilities after learning through PBL assisted by Scratch are better than those of students who learn without it. This study uses a quantitative approach with a quasi-experimental method. The sample consists of class VIII D as the experimental class with 35 students, and VIII G as the control class with 33 students, at SMPN 4 Tasikmalaya. The instrument was a computational thinking ability test validated by expert lecturers and tried out on class IX J students. Data were analysed using descriptive statistics, the Shapiro-Wilk normality test, the Levene homogeneity test, and the one-tailed Independent Sample T-Test at a 5% significance level. Results showed that the experimental class obtained an average score of 75.51, while the control class obtained 69.55. The one-tailed p-value was 0.001 < 0.05, so H₀ was rejected. Thus, students taught through Scratch-assisted PBL had better mathematical computational thinking abilities than those taught through PBL without Scratch. These findings indicate that Scratch can support PBL as an interactive medium that helps students solve mathematical problems in a more systematic, logical, and structured manner.
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