Project Data Science in school (ProDaBi III)
Overview
Key Facts
- Keywords:
- Data Science Education, AI Education
- Research profile area:
- Transformation and Education
- Project type:
- Knowledge transfer
- Project duration:
- 08/2023 - 07/2026
- Contribution to sustainability:
- Quality Education
- Funded by:
- Deutsche Telekom Stiftung
- Website:
-
Homepage
More Information
Selected Publications
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).
Exploration of Location Data: Real Data in the Context of Interaction with a Cellular Network
L. Höper, S. Podworny, C. Schulte, D. Frischemeier, in: Proceedings of the IASE 2021 Satellite Conference, International Association for Statistical Education, 2022.
Zur neuen Bedeutung von Daten in Data Science und künstlicher Intelligenz
L. Höper, 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.
Using data cards for teaching data based decision trees in middle school
Show all publications
S. Podworny, Y. Fleischer, S. Hüsing, R. Biehler, D. Frischemeier, L. Höper, C. Schulte, in: O. Seppälä, 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.