Analisis Kemampuan Computational Thinking Berdasarkan Gaya Kognitif melalui Problem-Based Learning pada Siswa SMA

Dina Muthi'Ah, Elah Nurlaelah, Dian Usdiyana

Abstract


Computational thinking  is the ability to solve problems through the indicators decomposition, pattern recognition, abstraction, and algorithmic thinking. One of the factors contributed to differences in students’ computational thinking  skills was cognitive style, which reflects individual characteristics in processing information and solving problems. This study aimed to analyze computational thinking  skills based on field-dependent and field-independent cognitive styles through problem-based learning among high school students. This research employed a qualitative approach with an embedded single-case study design. The participants were XI grade students from a senior high school in Bandung. Data were collected using the Group Embedded Figures Test (GEFT), computational thinking  tests, lesson plans (RPP), and interview guidelines. The results show that students with a field dependent (FD) cognitive style are able to fulfill the indicators of decomposition, and pattern recognition. However, they encounter difficulties in abstraction and algorithmic thinking. FD students can generally identify problems, recognize basic patterns, and outline steps for solving problems, but they struggle to filter essential information to construct general principles and structuring solution steps. On the other, students with a field independent (FI) cognitive style are able to fulfill all four computational thinking  indicators. FI students can identify information, recognize patterns, formulate general principles, and construct problem-solving algorithms in a logical and structured manner. These findings suggest that differences in cognitive style affect the computational thinking  abilities of high school students when solving mathematical problems.

Keywords


computational thinking; cognitive style; problem-based learning

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References


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DOI: https://doi.org/10.17509/sigmadidaktika.v13i1.89610

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