Revealing Students’ Computational Thinking Error Patterns in Solving Two-Variable Linear Inequality Systems - Israil Sitepu; Delvi Kristiani Jaluhu; Sinta Dameria Simanjuntak; Ribka Kariani br Sembiring (AlphaMath : Journal of Mathematics Education, 2026)
This study aims to identify and describe patterns of students’ computational thinking errors in solving systems of linear inequalities in two variables. Specifically, it examines errors occurring at each stage of computational thinking, such as problem decomposition, pattern recognition, abstraction, and algorithm construction, as well as the underlying factors contributing to these errors. A qualitative descriptive approach was employed. The participants consisted of 36 tenth-grade students. Data were collected through written tests, observation, and semi-structured interviews to explore students’ cognitive processes in depth. The data were analyzed through data reduction, data display, and conclusion drawing. The findings indicate that students experienced errors at all stages of computational thinking. Students encountered difficulties identifying relevant information during problem decomposition, recognizing conceptual relationships during pattern recognition, transforming problems into appropriate mathematical representations during abstraction, and constructing systematic solution procedures during algorithm construction. These errors were primarily attributed to insufficient conceptual understanding, difficulties in interpreting problem statements, and limitations in formulating effective problem-solution strategies. These findings provide valuable insights into students’ learning difficulties and may serve as a foundation for designing more effective instructional strategies to enhance students’ computational thinking skills.