Junior High School Student’s Computational Thinking Ability in Solving Mathematical Problems

The low ability of students to solve mathematical problems through key aspects such as decomposition, pattern recognition, abstraction, and algorithmic thinking occurs due to a lack of creative strategies in learning. This study aims to provide an in-depth understanding of these obstacles and propose more effective learning strategies. This research is qualitative descriptive research. The subjects of this study were 40 students of grade VII junior high school. Research subjects with low computational thinking skills or obtained the lowest total score of 5 students. The data collection method used in this study was by computational thinking skills test and in-depth interview. The computational thinking ability test was carried out using questions adapted from the Bebras Task questions that had been tested for validity and reliability. The results of this study are (1) the computational thinking ability of grade VII junior high school students is classified as medium with the percentage of each component of computational thinking ability is 47.25% (decomposition), 35.25% (pattern recognition and generalization), 50.38% (abstraction), and 29.88% (thinking algorithms); (2) Obstacles faced by students in solving mathematical problems that cause students who have computational thinking skills, categories including students who are not accustomed to sorting information as activities in the components of abstraction skills and the core of computational thinking skills. The implications of these findings suggest that research subjects in the lower category computational thinking skills have a tendency to struggle in mastering the abstraction skill component.