Profiling Statistical Reasoning Development of Junior High School Students in Indonesia: From Procedural to Analytical Thinking

Abstract

In the digital era, statistical reasoning is a key competency required for students to interpret data and make evidence-based decisions. However, many students continue to struggle to progress beyond procedural stages toward deeper conceptual understanding. This study aims to identify the statistical reasoning profiles of eighth-grade students in Indonesia based on four developmental classifications: Idiosyncratic, Transitional, Quantitative, and Analytical. An exploratory case study design was employed with 27 students from a public junior high school in Bandung. Data were collected using the Statistical Reasoning Assessment Tool (SRAT) consisting of open-ended tasks and analyzed with a developmental rubric for statistical reasoning. Coding was conducted independently by two raters with high inter-rater reliability (Cohen’s κ = 0.87). Descriptive statistics, chi-square tests, and qualitative analyses of reasoning patterns and misconceptions were used to address the research questions. The findings revealed that most students were situated at the Quantitative level (63%), followed by Transitional (33%), and Idiosyncratic (4%), with no students reaching the Analytical level. These results indicate that while students were able to recognize and organize statistical information, they had not yet developed higher-order analytical reasoning skills. The implications highlight the need for pedagogical strategies that leverage digital technologies to move students beyond procedural competence toward analytical reasoning, through multi-representational approaches, engagement with authentic datasets, and inquiry-based learning, thereby supporting the development of data literacy as a 21st-century competency.