Primary School Students’ Computational Thinking in Solving Mathematics Problems Based on Learning Style

Abstract

Computational thinking is related to the ability to solve mathematical problems. This study aims to describe the computational thinking of primary school students with visual, auditory, and kinesthetic learning styles in solving mathematical problems as measured by indicators of abstraction, decomposition, algorithmic thinking, and generalization. This research is descriptive qualitative research. Data collection techniques using questionnaires, assignments, and interviews. Data analysis techniques using technical triangulation. The results showed that the computational thinking of students with visual and auditory learning styles fulfills all indicators of every aspect of computational thinking. Both identify important information by mentioning known and asked information, making mathematical models, solving problems by breaking them down into several parts, and solving them to get the right results. Both provide logical arguments regarding the method used, generalize the problem and apply the solution to similar problems. The difference lies in the mathematical form created. The mathematical form made by visual learning styles is more complete than auditory learning styles. This causes the settlement steps to also be different. Meanwhile, kinesthetic learning styles make mistakes when understanding the problem and making mathematical models, so the completion steps and the final results obtained are not appropriate. So, students need to get used to solving problems that can train their computational thinking skills so that students will get used to thinking systematically and logically