Differences in mathematical problem-solving skills based on computational thinking in problem-based learning and conventional learning
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Abstract
Problem solving ability with Computational Thinking strategy is important for students. The study aims to determine the differences in mathematical problem solving ability with computational thinking on statistics material through the Problem Based Learning (PBL) model and conventional methods in class VII MTs Daarul Uluum Blitar. The study was conducted with a quasi-experiment through a pretest-posttest design with nonequivalent control group. Saturated samples were used in the study with class VII-B as the experimental class by implementing PBL and class VII-C as the control class. Data collection was carried out with a computational thinking ability test: decomposition, pattern recognition, abstraction, and algorithms to solve mathematical problems on statistics material. An independent sample t-test was conducted to answer the problem formulation. The results showed a significance value (2-tailed) of 0.019 (α <0.05), with an average pretest and posttest of the experimental class of 49 and 63, while the control class was 32 and 54. These findings indicate that the PBL model is effective in improving mathematical problem solving abilities based on computational thinking.
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