Articles

The Development of RBL-STEM Learning Materials to Improve Students’ Computational Thinking Skills in Solving Rainbow Vertex Antimagic Coloring Problems and It’s Application for Batik Motif Design

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Computational thinking is thinking process that is needed in formulating problems and solutions, so that these solutions can be effective information processing agents in solving problems. Indicators of computational thinking consist of problem decomposition, algorithmic thinking, pattern recognition, abstraction and generalization. To improve higher-order thinking skills, we apply RBL learning integrated with STEM approach and their aplication to batik matif design. To improve students’ thinking skills, it is necessary to develop tools that support the success of learning activities. The learning tools that have been developed meet the criteria of valid, practical, and effective. The validity score obtained on each device is 3.58 for the student assignment plan (RTM), 3.47 for the student worksheet (LKM), and 3.64 for the learning outcomes test (THB). The observation result of the learning implementation score was 3.72 with a percentage of 93%. In addition to being valid and practical, the material also meets the criteria for effectiveness. On average, 95% of students in this trial class are classified as complete students and the response from students is positive. Based on the test results, researchers got 23 students who scored above 60. This means that 82% of students in this class have completed and met one of the effectiveness criteria. Student response questionnaires also give more positive responses than negative responses.

Development of RBL-STEM Learning Tools to Improve Students’ Computational Thinking Skills Solving Rainbow Antimagic Coloring Problems and Their Application to Traffic Flow Problems with Spatial Temporal Graph Neural Network

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Computational thinking is thinking process that is needed in formulating problems and solutions, so that these solutions can be effective information processing agents in solving problems. Indicators of computational thinking consist of problem decomposition, algorithmic thinking, pattern recognition, abstraction and generalization. To improve higher-order thinking skills, we apply RBL learning integrated with STEM approach. To improve students’ thinking skills, it is necessary to develop tools that support the success of learning activities. The learning tools that have been developed meet the criteria of valid, practical, and effective. The validity scores obtained by each device are 3.5 for the face-to-face plan, 3.41 for the student worksheet, and 3.56 for the learning outcomes test. The observation result of the learning implementation score was 3.8 with a percentage of 95%. There were 23 students who completed or around 88,46%, percentage of average score of student activities was 94.17%, and as many as 94.47% of students gave a positive response.