{"date_updated":"2026-06-29T07:47:44Z","publication_status":"published","year":"2026","status":"public","title":"Informal approaches to predictive modeling: fostering data literacy and critical engagement through decision tree construction","author":[{"full_name":"Fleischer, Franz Yannik","last_name":"Fleischer","orcid":"https://orcid.org/0000-0003-0318-0329","first_name":"Franz Yannik","id":"42660"},{"full_name":"Biehler, Rolf","first_name":"Rolf","last_name":"Biehler","id":"16274"}],"publication_identifier":{"issn":["1863-9690","1863-9704"]},"doi":"10.1007/s11858-026-01806-3","user_id":"37888","main_file_link":[{"url":"https://link.springer.com/article/10.1007/s11858-026-01806-3","open_access":"1"}],"_id":"66074","publisher":"Springer Science and Business Media LLC","language":[{"iso":"eng"}],"abstract":[{"text":"<jats:title>Abstract</jats:title>\r\n                  <jats:p>This study investigates how secondary students construct and evaluate decision trees in an open exploratory task using CODAP. By analyzing students’ tree products and oral self-reports, we identified different data-based and context-based approaches to predictor selection and stopping criteria. Students engaged with key ideas of predictive modeling, including classification, model construction, accuracy, generalization, and interpretability. Informal exploration offered rich opportunities for subsequent teaching by enabling students to begin reconstructing central technical ideas and critical tensions of predictive modeling through diverse but meaningful reasoning approaches.</jats:p>","lang":"eng"}],"publication":"ZDM – Mathematics Education","citation":{"ieee":"F. Y. Fleischer and R. Biehler, “Informal approaches to predictive modeling: fostering data literacy and critical engagement through decision tree construction,” <i>ZDM – Mathematics Education</i>, 2026, doi: <a href=\"https://doi.org/10.1007/s11858-026-01806-3\">10.1007/s11858-026-01806-3</a>.","apa":"Fleischer, F. Y., &#38; Biehler, R. (2026). Informal approaches to predictive modeling: fostering data literacy and critical engagement through decision tree construction. <i>ZDM – Mathematics Education</i>. <a href=\"https://doi.org/10.1007/s11858-026-01806-3\">https://doi.org/10.1007/s11858-026-01806-3</a>","short":"F.Y. Fleischer, R. Biehler, ZDM – Mathematics Education (2026).","chicago":"Fleischer, Franz Yannik, and Rolf Biehler. “Informal Approaches to Predictive Modeling: Fostering Data Literacy and Critical Engagement through Decision Tree Construction.” <i>ZDM – Mathematics Education</i>, 2026. <a href=\"https://doi.org/10.1007/s11858-026-01806-3\">https://doi.org/10.1007/s11858-026-01806-3</a>.","mla":"Fleischer, Franz Yannik, and Rolf Biehler. “Informal Approaches to Predictive Modeling: Fostering Data Literacy and Critical Engagement through Decision Tree Construction.” <i>ZDM – Mathematics Education</i>, Springer Science and Business Media LLC, 2026, doi:<a href=\"https://doi.org/10.1007/s11858-026-01806-3\">10.1007/s11858-026-01806-3</a>.","bibtex":"@article{Fleischer_Biehler_2026, title={Informal approaches to predictive modeling: fostering data literacy and critical engagement through decision tree construction}, DOI={<a href=\"https://doi.org/10.1007/s11858-026-01806-3\">10.1007/s11858-026-01806-3</a>}, journal={ZDM – Mathematics Education}, publisher={Springer Science and Business Media LLC}, author={Fleischer, Franz Yannik and Biehler, Rolf}, year={2026} }","ama":"Fleischer FY, Biehler R. Informal approaches to predictive modeling: fostering data literacy and critical engagement through decision tree construction. <i>ZDM – Mathematics Education</i>. Published online 2026. doi:<a href=\"https://doi.org/10.1007/s11858-026-01806-3\">10.1007/s11858-026-01806-3</a>"},"type":"journal_article","oa":"1","department":[{"_id":"363"}],"date_created":"2026-06-29T07:43:33Z"}