Analysis of students' statistical reasoning ability based on personality types - Nasution, Eline Yanty Putri; Yulia, Putri; Handican, Rhomiy (Al-Jabar: Jurnal Pendidikan Matematika, 2025)
Purposes: This research investigates the extent to which personality traits, as defined by the MBTI framework, influence students' ability to reason statistically in the context of a mathematical statistics course. The study particularly focuses on examining how distinct cognitive tendencies, categorized within the MBTI’s four dimensions, affect students’ capabilities in understanding, organizing, presenting, and interpreting statistical information. Method: A qualitative case study approach was adopted involving eleven students enrolled in a mathematics education program at a higher education institution in Indonesia. Participants completed the MBTI questionnaire to determine their personality classifications. In addition, a statistical reasoning assessment was administered to evaluate their cognitive strategies across established reasoning indicators. Observational data and written explanations were also gathered to enrich the analysis. The findings were interpreted through descriptive qualitative techniques, with triangulation applied to ensure accuracy and credibility. Findings: The analysis revealed that students identified with the STJ and ESTJ personality types exhibited more proficient reasoning patterns, particularly in applying logical steps and organizing data systematically. On the other hand, participants with NTJ or ISFJ traits showed challenges in representing data visually and articulating their thought processes clearly. Interestingly, the Introvert and Extrovert distinction did not appear to influence performance in a meaningful way. Significance: This study offers insights into the role of personality in learning statistics. It emphasizes the need for differentiated instructional methods. Adapting teaching strategies to accommodate varied personality profiles may enhance student engagement and conceptual mastery in statistical learning environments.