How a Computational Thinker Solves a Non-Routine Geometry Task: A Single-Case Study

Abstract

Problem-solving has become a core element of the mathematics curriculum, where students are encouraged to solve non-routine and higher-order thinking problems (HOTS). However, based on empirical observations in classrooms reveal that many students still struggle to solve problems. Many students often struggle to determine where to begin, especially when faced with non-routine or HOTS tasks of geometry problems.  This study investigates how a student with strong computational thinking (CT) skills approaches and solves such problems. This study employs a descriptive qualitative design. The subject was selected using purposive sampling, in which one participant was chosen from a total of 48 respondents based on specific criteria, namely providing correct answers and demonstrating the four components of CT. The findings reveal that the subject utilized four main stages: decomposition, pattern recognition, abstraction, and algorithmic design. In the decomposition phase, the student broke down the square into smaller triangles to simplify the problem. In the pattern recognition stage, the student identified recurring geometric configurations, such as right triangles. During abstraction, irrelevant information was discarded to focus on key components. Finally, the student applied a sequential algorithm involving triangle similarity and the Pythagorean theorem to determine the side length of the square. These findings highlight the potential of computational thinking in enhancing problem-solving performance in geometry. The implications of these findings indicate that CT skills can be applied in instructional design, particularly in problem-solving activities. Students can be guided in engaging in CT processes by using simple questions aligned with each CT component.