Analysis of Students’ Thinking Processes in Solving Algebraic Problems Using a Computational Approach

Abstract

This study aims to analyze students’ thinking processes in solving algebraic problems using a computational approach. The study responds to the problem that many students can follow procedural examples in algebra but still struggle to explain their reasoning, represent unknown quantities, organize solution steps, and evaluate their answers. A qualitative approach with a descriptive case study design was used. The research involved eighth-grade students at a junior high school in Indonesia, with six key informants selected through purposive sampling based on high, medium, and low ability categories. Data were collected through algebraic problem-solving tests, semi-structured interviews, classroom observations, documentation, and field notes. The data were analyzed using an interactive model consisting of data reduction, data display, and conclusion drawing, supported by thematic coding based on computational thinking indicators. The findings reveal five main themes in students’ thinking processes: problem decomposition, pattern recognition, abstraction, algorithm construction, and solution evaluation. Students with stronger computational thinking were more systematic in identifying information, forming algebraic representations, arranging solution steps, and checking answers. Students with weaker computational thinking tended to rely on surface features, incomplete procedures, and limited evaluation. These findings contribute to a deeper understanding of the relationship between algebraic thinking and computational thinking. The study implies that teachers need to design algebra learning that emphasizes reasoning processes, strategy explanation, error revision, and reflective evaluation.