Crafting epistemic knowledge in statistics education via didactical engineering integrating the theory of didactical situations and the SECI model
Year: 2025
Type: article
Abstract: This study investigates the creation of epistemic knowledge through didactical engineering in statistics education. The objectives of this study are: (1) to explore whether the application of didactical engineering (DE) can produce epistemic knowledge in the context of statistics education, (2) to evaluate the effectiveness of integrating the Theory of Didactical Situations (TDS) and Nonaka’s SECI (Socialization, Externalization, Combination, Internalization) model in fostering students' understanding of statistical concepts, and (3) to analyze the variations in students' knowledge levels using cluster analysis. The research applies a didactical engineering approach, involving the design, implementation, observation, and a posteriori analysis of learning tasks related to statistics. Cluster analysis was employed to assess variations in student knowledge levels, allowing for targeted instructional design adjustments. The findings reveal that the integration of TDS and the SECI Model within didactical engineering significantly enhances students' understanding of statistical concepts. Students' knowledge evolved from pre-structural to extended abstract levels, with cluster analysis identifying key variations among learners. This study underscores the effectiveness of combining TDS and SECI in fostering epistemic knowledge in statistics education. The research highlights the importance of strategies that bridge tacit and explicit knowledge, offering valuable insights for curriculum development and teaching practice improvement in mathematics education.
Source: Discover Sustainability
Language: English
Subfield: Statistics and Probability
Field: Mathematics
Domain: Physical Sciences
SDG: Quality education
Open Access status: gold
Estimated APC paid: $1,390
OpenAlex ID: W4414554592