The Knowledge Creation Through Didactical Engineering on Statistics: Is the Knowledge Acquired Epistemic?

The Knowledge Creation Through Didactical Engineering on Statistics: Is the Knowledge Acquired Epistemic? | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article The Knowledge Creation Through Didactical Engineering on Statistics: Is the Knowledge Acquired Epistemic? Dadan Dasari, Agus Hendriyanto, Sani Sahara, I Putu Wisna Ariawan, and 2 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-5602732/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 26 Sep, 2025 Read the published version in Discover Sustainability → Version 1 posted 6 You are reading this latest preprint version 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. didactical engineering epistemic knowledge knowledge creation mathematics education SECI model statistics education theory of didactical situations Full Text Additional Declarations No competing interests reported. Cite Share Download PDF Status: Published Journal Publication published 26 Sep, 2025 Read the published version in Discover Sustainability → Version 1 posted Editorial decision: Revision requested 18 Aug, 2025 Reviewers agreed at journal 24 Jun, 2025 Editor assigned by journal 31 May, 2025 Reviewers invited by journal 09 May, 2025 Submission checks completed at journal 09 May, 2025 First submitted to journal 27 Apr, 2025 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-5602732","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":448792320,"identity":"ccf2150d-c018-496b-867a-dd4d86ce7b65","order_by":0,"name":"Dadan 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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\u0026rsquo;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. 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