S. Hüsing, C. Schulte, S. Sparmann, and M. Bolte, “Using Worked Examples for Engaging in Epistemic Programming Projects,”10.1145/3626252.3630961__2024, doi:10.1145/3626252.3630961 .

S. Hüsing, C. Schulte, and F. Winkelnkemper, “Epistemic Programming,” in Computer Science Education, Bloomsbury Academic, 2023.

S. Sparmann, S. Hüsing, and C. Schulte, “JuGaze: A Cell-based Eye Tracking and Logging Tool for Jupyter Notebooks,”10.1145/3631802.3631824__2023, doi:10.1145/3631802.3631824 .

S. PODWORNY, S. Hüsing, and C. SCHULTE, “A PLACE FOR A DATA SCIENCE PROJECT IN SCHOOL: BETWEEN STATISTICS AND EPISTEMIC PROGRAMMING,”10.52041/serj.v21i2.46__STATISTICS EDUCATION RESEARCH JOURNAL, vol. 21, no. 2, Art. no. 6, 2022, doi:10.52041/serj.v21i2.46 .

S. Podworny, Y. Fleischer, and S. Hüsing, “Grade 6 Students’ Perception and Use of Data-Based Decision Trees,”10.52041/iase.icots11.t2h3__2022, doi:10.52041/iase.icots11.t2h3 .

S. Hüsing and S. Podworny, “Computational Essays as an Approach for Reproducible Data Analysis in lower Secondary School,”10.52041/iase.zwwoh__2022, doi:10.52041/iase.zwwoh .

Y. Fleischer, S. Hüsing, R. Biehler, S. Podworny, and C. Schulte, “Jupyter Notebooks for Teaching, Learning, and Doing Data Science,”10.52041/iase.icots11.t10e3__in Bridging the Gap: Empowering and Educating Today’s Learners in Statistics. Proceedings of the Eleventh International Conference on Teaching Statistics, 2022, doi:10.52041/iase.icots11.t10e3 .

S. Podworny et al., “Using data cards for teaching data based decision trees in middle school,”10.1145/3488042.3489966__in Koli Calling ’21: 21st Koli Calling International Conference on Computing Education Research, Joensuu, Finland, November 18 - 21, 2021, 2021, p. 39:1-39:3, doi:10.1145/3488042.3489966 .

S. Hüsing, “Epistemic Programming - An insight-driven programming concept for Data Science,”10.1145/3488042.3490510__in Koli Calling ’21: 21st Koli Calling International Conference on Computing Education Research, Joensuu, Finland, November 18 - 21, 2021, 2021, p. 42:1-42:3, doi:10.1145/3488042.3490510 .

K. Bovermann, Y. Fleischer, S. Hüsing, and C. Opitz, “Künstliche Intelligenz und maschinelles Lernen im Informatikunterricht der Sek. I mit Jupyter Notebooks und Python am Beispiel von Entscheidungsbäumen und künstlichen neuronalen Netzen,”10.18420/infos2021‑w283__in 19. GI-Fachtagung Informatik und Schule, INFOS 2021, Wuppertal, Germany, September 8-10, 2021, 2021, vol. P-313, p. 319, doi:10.18420/infos2021‑w283 .

L. Höper, S. Hüsing, H. Malatyali, C. Schulte, and L. Budde, “Methodik für Datenprojekte im Informatikunterricht,” LOG IN, vol. 41, no. 1, pp. 31–38, 2021.

S. Podworny, L. Höper, Y. Fleischer, S. Hüsing, and C. Schulte, “Data Science ab Klasse 5–Konkrete Unterrichtsvorschläge für künstliche Intelligenz unplugged und Datenbewusstsein,” INFOS 2021–19. GI-Fachtagung Informatik und Schule, 2021.

L. Höper et al., “Zur neuen Bedeutung von Daten in Data Science und künstlicher Intelligenz,” INFOS 2021–19. GI-Fachtagung Informatik und Schule, 2021.

S. Hüsing, N. Weiser, and R. Biehler, “Faszination 3D-Film: Entwicklung einer 3D-Konstruktion,” mathematik lehren, vol. 2021, no. 228, pp. 23–27, 2021.

S. Hüsing, N. Weiser, and R. Biehler, “Faszination 3D-Film: Entwicklung einer 3D-Konstruktion,” mathematik lehren, vol. 2021, no. 228, pp. 23–27, 2021.