The Effect of Digital Didactic Intervention on Measures of Central Tendency Towards Students’ Statistical Thinking - Cipta, Eliva Sukma; Suryadi, Didi; Herman, Tatang; Jupri, Al ((JIML) JOURNAL OF INNOVATIVE MATHEMATICS LEARNING, 2026)
Statistical thinking is an essential competency for prospective mathematics teachers in responding to data-driven decision making within the context of Society 5.0. However, learning obstacles frequently emerge in higher education statistics courses due to instructional practices that emphasize procedural computation rather than conceptual and contextual understanding. This study aims to describe the implementation of a didactical design to reduce students’ learning obstacles in statistical thinking through the topic of measures of central tendency. A qualitative descriptive method was employed involving 38 mathematics education students enrolled in an introductory statistics course. The didactical design integrated the Theory of Didactical Situations (TDS) and the DORA model (Describe, Organize, Represent, Analyze–Interpret) and was delivered through an interactive e-module developed on the AnyFlip platform. Data were collected using a post-implementation statistical thinking test based on DORA, classroom observations, semi-structured interviews, and reflective field notes. Learning activities were organized into four TDS stages action, formulation, validation, and institutionalization to support reflective and adidactical learning processes. The results indicate that students were able to construct statistical concepts more meaningfully and reduce previously identified learning obstacles, particularly in linking numerical results with graphical representations. In conclusion, the integration of TDS and the DORA model supported by interactive e-modules effectively enhances students’ statistical thinking skills, as evidenced by the reduction of learning obstacles among prospective mathematics teachers.