LEARNING OBSTACLES IN DESCRIPTIVE STATISTICS: CHALLENGES IN STATISTICAL THINKING FOR PROSPECTIVE MATHEMATICS TEACHERS - Eliva Sukma Cipta; Didi Suryadi; Tatang Herman; Al Jupri (AKSIOMA: Jurnal Program Studi Pendidikan Matematika, 2026)
Statistical thinking is an essential competency for prospective mathematics teachers, as it enables them to understand, organize, represent, analyze, and interpret data effectively. However, many students still experience difficulties in understanding and applying descriptive statistics concepts, which may hinder the development of their statistical thinking skills. Therefore, identifying learning obstacles is necessary as a basis for designing more effective learning experiences. This study aims to identify the learning obstacles encountered by prospective mathematics teachers in descriptive statistics courses. The study employed Didactical Design Research (DDR) using a qualitative methodology within an interpretive paradigm. The participants were 38 prospective mathematics teachers enrolled at a private university in Bandung, Indonesia. The research instruments consisted of a statistical thinking test, semi-structured interview guidelines, and document analysis. Data were collected through tests, interviews, and document analysis and were analyzed through the processes of identification, classification, reduction, and verification. Data trustworthiness was established through methodological and source triangulation. The findings revealed that students experienced difficulties across all indicators of statistical thinking, including describing, organizing, representing, analyzing, and interpreting data. These difficulties were reflected in misconceptions regarding the relationship between mean, median, mode, and distribution skewness, the application of measures of position, the interpretation of data variability, and the analysis of relative performance. The study identified ontogenic, epistemological, and didactical obstacles that hindered the development of students’ statistical thinking. These findings provide an empirical basis for developing a hypothetical learning trajectory to enhance statistical thinking in descriptive statistics courses.