How mathematical disposition shapes computational thinking in solving systems of linear equations: A flowchart-supported qualitative study - Azizia, Ananda Jullailatul; Masrukan; Susilo, Bambang Eko; Arifuddin, Ahmad (Universitas Hamzanwadi, 2025)
Computational thinking (CT) is a vital 21st-century skill in mathematics education, enabling students to solve problems systematically through decomposition, pattern recognition, abstraction, and algorithmic thinking. However, students’ mathematical disposition—encompassing beliefs, habits of mind, and affective tendencies—may significantly influence CT development. Guided by the affective–cognitive interaction model, this study aimed to explore how mathematical disposition shapes students’ CT skills, particularly in solving systems of three-variable linear equations using self-constructed, flowchart-supported algorithmic representations. A descriptive qualitative approach was adopted, with six students (two each from high, medium, and low disposition levels, identified via questionnaire) participating. Data collection involved a disposition scale, CT test, interviews, and documentation. Findings revealed that high-disposition students successfully demonstrated all CT indicators and produced coherent flowcharts. Medium-disposition students showed variability: some met all criteria, while others faltered in algorithmic design. Low-disposition students managed only basic decomposition and pattern recognition, with incomplete abstraction and fragmented flowcharts. These results suggest a strong link between affective factors and cognitive performance in CT tasks. Implications highlight the importance of integrating disposition-aware scaffolding—such as interactive visual tools and guided reflection—to support diverse learners and enhance CT development in mathematics classrooms.