Students of Mathematics Education of Feminine Female in Probability Problem-Solving on Binomial Distribution Based Field-Independent Cognitive Styles

Abstract

This study aims to analyze the probabilistic thinking of a female undergraduate student in Mathematics Education who possesses feminine characteristics and a Field-Independent cognitive style. The subject, coded as MPI (Independent Female Student), was selected based on the needs of the study and met specific criteria: gender identity determined through a gender questionnaire, cognitive style identified using the Group Embedded Figures Test (GEFT), and mathematical ability assessed through UTBK SBMPTN questions. Among 20 students assessed, the majority demonstrated moderate mathematical ability, with MPI selected as a representative subject based on her profile. This research uses a descriptive qualitative method with a case study design. Data were collected through probability problem-solving tests and interviews and were analyzed through the processes of data reduction, data presentation, and conclusion drawing. The analysis was guided by Polya's four-stage problem-solving framework: understanding the problem, devising a plan, carrying out the plan, and looking back. The findings indicate that MPI exhibits generally good probabilistic thinking. She was able to understand the problems well, devise a plan, and execute her solution. However, some shortcomings were identified, particularly at the "devise a plan" stage, where she did not apply the combination formula appropriately, which led to errors in the use of the binomial distribution formula. Additionally, while the “looking back” stage was not evident in her written responses, reflective thinking was revealed during interviews. Overall, the study concludes that feminine female students with a Field-Independent cognitive style can demonstrate strong probabilistic thinking, though they may require further support in applying specific mathematical strategies. This research contributes to the understanding of how gender and cognitive style influence mathematical problem-solving in higher education, especially in the context of probability.