MATHEMATICAL REPRESENTATION IN PROBLEM-SOLVING: A COMPARATIVE STUDY OF REFLECTIVE AND IMPULSIVE COGNITIVE STYLES

Abstract

Mathematical representation is a crucial skill that enables students to express, interpret, and connect mathematical concepts through visual, symbolic, and verbal forms. This study explores the differences in mathematical representation skills between students with reflective and impulsive cognitive styles in solving two-variable linear inequality system problems. Using a qualitative descriptive approach, four high school students were selected based on their cognitive styles through the Matching Familiar Figure Test (MFFT). Data were collected through problem-solving tasks and semi-structured interviews. The findings indicate that reflective students demonstrate strong mathematical representation abilities, particularly in organizing and translating information across visual, symbolic, and verbal representations. They exhibit a structured and analytical approach to problem-solving, ensuring accuracy and coherence in their representations. In contrast, impulsive students struggle with problem organization, symbolic representation, and verbal explanation, often producing incomplete and less structured representations due to their tendency to prioritize speed over accuracy. These results highlight the influence of cognitive style on mathematical representation and suggest the need for tailored instructional strategies. Future research should expand the study to a broader mathematical scope and implement targeted interventions to enhance students' representation skills according to their cognitive characteristics.