Hüsing, S., Schulte, C., Sparmann, S., &; Bolte, M. (2024). Using Worked Examples for Engaging in Epistemic Programming Projects. Proceedings of the 55th ACM Technical Symposium on Computer Science Education V. 1.https://doi.org/10.1145/3626252.3630961 
LibreCat: /record/52379
DOI: 10.1145/3626252.3630961

Höper, L., &; Schulte, C. (2024). Empowering Students for the Data-Driven World: A Qualitative Study of the Relevance of Learning about Data-Driven Technologies. Informatics in Education.https://doi.org/10.15388/infedu.2024.19 
LibreCat: /record/53622
DOI: 10.15388/infedu.2024.19

Hüsing, S., Schulte, C., &; Winkelnkemper, F. (2023). Epistemic Programming. In Computer Science Education. Bloomsbury Academic.https://doi.org/10.5040/9781350296947.ch-022 
LibreCat: /record/40511
DOI: 10.5040/9781350296947.ch-022

Höper, L., &; Schulte, C. (2023). Paradigmenwechsel vom klassischen zum datengetriebenen Problemlösen im Informatikunterricht. MNU journal, 76(4), 314–320.
LibreCat: /record/46186

Winkelnkemper, F., Höper, L., &; Schulte, C. (2023). ARIadne – An Explanation Model for Digital Artefacts. Informatics in Education.https://doi.org/10.15388/infedu.2024.09 
LibreCat: /record/47151
DOI: 10.15388/infedu.2024.09

Höper, L., &; Schulte, C. (2023). The data awareness framework as part of data literacies in K-12 education. Information and Learning Sciences.https://doi.org/10.1108/ils-06-2023-0075 
LibreCat: /record/49655
DOI: 10.1108/ils-06-2023-0075

Terfloth, L., Schaffer, M., Buhl, H. M., &; Schulte, C. (2023). Adding Why to What? Analyses of an Everyday Explanation. 1st World Conference on eXplainable Artificial Intelligence (xAI 2023), Lisboa.https://doi.org/10.1007/978-3-031-44070-0_13 
LibreCat: /record/47448
DOI: 10.1007/978-3-031-44070-0_13

Sparmann, S., Hüsing, S., &; Schulte, C. (2023). JuGaze: A Cell-based Eye Tracking and Logging Tool for Jupyter Notebooks. Proceedings of the 23rd Koli Calling International Conference on Computing Education Research.https://doi.org/10.1145/3631802.3631824 
LibreCat: /record/52380
DOI: 10.1145/3631802.3631824

PODWORNY, S., Hüsing, S., &; SCHULTE, C. (2022). A PLACE FOR A DATA SCIENCE PROJECT IN SCHOOL: BETWEEN STATISTICS AND EPISTEMIC PROGRAMMING. STATISTICS EDUCATION RESEARCH JOURNAL, 21(2), Article 6.https://doi.org/10.52041/serj.v21i2.46 
LibreCat: /record/32335
DOI: 10.52041/serj.v21i2.46

Höper, L., Podworny, S., Schulte, C., &; Frischemeier, D. (2022). Exploration of Location Data: Real Data in the Context of Interaction with a Cellular Network. Proceedings of the IASE 2021 Satellite Conference.https://doi.org/10.52041/iase.nkppy 
LibreCat: /record/31407
DOI: 10.52041/iase.nkppy

Winkelnkemper, F., Huhmann, T., Bechinie, D., Eilerts, K., Lenke, M., &; Schulte, C. (2022). Supporting Geometry Learning Digitally-an Interdisciplinary Project to Foster Spatial Competences and Individual Learning Paths by Using Adaptable Algorithmic Feedback Capabilities. Society for Information Technology &; Teacher Education International Conference, 1407–1413.
LibreCat: /record/38158

Schulte, C., &; Winkelnkemper, F. (2022). Digitalisierung als Chance und Herausforderung - Bemerkungen aus der Didaktik der Informatik. In Theologie im Übergang - Identität - Digitalisierung - Dialog (pp. 117–135). Herder.
LibreCat: /record/39080

Huhmann, T., &; Winkelnkemper, F. (2022). SUPPORTING GEOMETRY LEARNING DIGITALLY THROUGH ADAPTABLE ALGORITHMIC FEEDBACK-CHALLENGES AND SOLUTIONS. EDULEARN22 Proceedings, 10017–10026.https://doi.org/10.21125/edulearn.2022.2416 
LibreCat: /record/38160
DOI: 10.21125/edulearn.2022.2416

Huhmann, T., Eilerts, K., &; Winkelnkemper, F. (2022). Pentomino Digital - Mit Einer App Geometrie Lernen. Mathematik Differenziert, 4–2022, 42–45.
LibreCat: /record/38162

Podworny, S., Fleischer, Y., &; Hüsing, S. (2022). Grade 6 Students’ Perception and Use of Data-Based Decision Trees. Bridging the Gap: Empowering and Educating Today’s Learners in Statistics. Proceedings of the Eleventh International Conference on Teaching Statistics.https://doi.org/10.52041/iase.icots11.t2h3 
LibreCat: /record/40510
DOI: 10.52041/iase.icots11.t2h3

Hüsing, S., &; Podworny, S. (2022). Computational Essays as an Approach for Reproducible Data Analysis in lower Secondary School. Proceedings of the IASE 2021 Satellite Conference.https://doi.org/10.52041/iase.zwwoh 
LibreCat: /record/30937
DOI: 10.52041/iase.zwwoh

Fleischer, Y., Biehler, R., &; Schulte, C. (2022). Teaching and Learning Data-Driven Machine Learning with Educationally Designed Jupyter Notebooks. Statistics Education Research Journal, 21(2), Article 7.https://doi.org/10.52041/serj.v21i2.61 
LibreCat: /record/35672
DOI: 10.52041/serj.v21i2.61

Fleischer, Y., Hüsing, S., Biehler, R., Podworny, S., &; Schulte, C. (2022). Jupyter Notebooks for Teaching, Learning, and Doing Data Science. 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.https://doi.org/10.52041/iase.icots11.t10e3 
LibreCat: /record/35674
DOI: 10.52041/iase.icots11.t10e3

Schulte, C., A. Becker, B., Divitini, M., &; Barendsen, E. (Eds.). (2021). ITiCSE 2021: 26th ACM Conference on Innovation and Technology in Computer Science Education, Virtual Event, Germany, June 26 - July 1, 2021 - Working Group Reports. ACM.https://doi.org/10.1145/3456565 
LibreCat: /record/25521
DOI: 10.1145/3456565

Schulte, C., A. Becker, B., Divitini, M., &; Barendsen, E. (Eds.). (2021). ITiCSE 2021: 26th ACM Conference on Innovation and Technology in Computer Science Education, Virtual Event, Germany, June 26 - July 1, 2021. ACM.https://doi.org/10.1145/3430665 
LibreCat: /record/25522
DOI: 10.1145/3430665