Projekt Data Science in der Schule (ProDaBi III)
?berblick
Key Facts
- Profilbereich:
- Transformation und Bildung
- Laufzeit:
- 08/2023 - 07/2026
Detailinformationen
Ausgew?hlte Publikationen
Jupyter Notebooks for Teaching, Learning, and Doing Data Science
F.Y. Fleischer, S. Hüsing, R. Biehler, S. Podworny, C. Schulte, in: S.A. Peters, L. Zapata-Cardona, F. Bonafini, A. Fan (Eds.), Bridging the Gap: Empowering and Educating Today’s Learners in Statistics. Proceedings of the Eleventh International Conference on Teaching Statistics, International Association for Statistical Education, 2022.
Teaching and Learning Data-Driven Machine Learning with Educationally Designed Jupyter Notebooks
F.Y. Fleischer, R. Biehler, C. Schulte, Statistics Education Research Journal 21 (2022).
Using data cards for teaching data based decision trees in middle school
S. Podworny, Y. Fleischer, S. Hüsing, R. Biehler, D. Frischemeier, L. H?per, C. Schulte, in: O. Sepp?l?, A. Petersen (Eds.), Koli Calling ’21: 21st Koli Calling International Conference on Computing Education Research, Joensuu, Finland, November 18 - 21, 2021, ACM, 2021, p. 39:1-39:3.
Zur neuen Bedeutung von Daten in Data Science und künstlicher Intelligenz
L. H?per, S. Podworny, S. Hüsing, C. Schulte, Y. Fleischer, R. Biehler, D. Frischemeier, H. Malatyali, in: L. Humbert (Ed.), 19. GI-Fachtagung Informatik und Schule, INFOS 2021, Wuppertal, Germany, September 8-10, 2021, Gesellschaft für Informatik, Bonn, 2021, p. 345.
Exploration of Location Data: Real Data in the Context of Interaction with a Cellular Network
Alle Publikationen anzeigen
L. H?per, S. Podworny, C. Schulte, D. Frischemeier, in: Proceedings of the IASE 2021 Satellite Conference, International Association for Statistical Education, 2022.