Computational Thinking Abilities of Vocational School Students in Solving Quadratic Function Problems Using Python Programming Language - Putra, Misel Rajasyah Hadi; Siswono, Tatag Yuli Eko; Harini, Novita Vindri (Universitas Negeri Surabaya, 2025)
The Indonesian Minister of Education and Culture implemented the Merdeka Belajar Kampus Merdeka Curriculum in 2019, emphasizing computational thinking (CT) as a crucial 21st-century skill. Despite its importance in mathematics education, most Indonesian mathematics learning has not been oriented toward developing computational thinking abilities. Vocational school students majoring in Software Engineering possess programming knowledge that could potentially enhance their mathematical problem-solving through computational approaches. However, the extent of their CT abilities when applied to mathematical contexts remains unclear. This study aims to describe and analyze the computational thinking abilities of 10th-grade vocational school students majoring in Software Engineering when solving quadratic function problems using Python programming language. This qualitative research employed a case study approach with three purposively selected students representing different proficiency levels (high, moderate, and low) based on standardized programming and mathematics assessment criteria. Data were collected through written tests, structured observations, and semi-structured interviews. The assessment focused on four CT components: decomposition, pattern recognition, abstraction, and algorithmic thinking. The analysis revealed distinct patterns in CT abilities across proficiency levels. High-proficiency students (S1) demonstrated systematic problem decomposition, optimal pattern utilization, effective information filtering, and efficient algorithm development, achieving an average CT score of 91.25. Moderate-proficiency students (S2) showed adequate CT abilities with some limitations in systematic organization and strategic thinking, scoring 78.75 on average. Low-proficiency students (S3) exhibited significant difficulties across all CT components, particularly in problem decomposition and algorithmic thinking, with an average score of 64.25. The findings indicate that students' mathematical foundations significantly influence their CT development when integrated with programming tools. The computational thinking abilities of 10th-grade Software Engineering students vary considerably when solving quadratic function problems with Python assistance. Students with stronger mathematical foundations demonstrate superior CT performance across all components, while those with weaker foundations require substantial scaffolding. These findings highlight the need for differentiated instructional approaches that consider students' varying CT development levels in mathematics education.