2025
Borchers, C., Fleischer, H., Schanze, S., Scheiter, K., & Aleven, V. (2025). High Scaffolding of an Unfamiliar Strategy Improves Conceptual Learning but Reduces Enjoyment Compared to Low Scaffolding and Strategy Freedom. Computers & education, 236, Article 105364. https://doi.org/10.1016/j.compedu.2025.105364
Borchers, C., Zhang, J., Fleischer, H., Schanze, S., Aleven, V., & Baker, R. S. (2025). Large Language Models Generalize SRL Prediction to New Languages Within But Not Between Domains. Journal of Educational Data Mining, 17(2), 24-54. https://doi.org/10.5281/zenodo.17073680
Borchers, C., Fleischer, H., Yaron, D. J., McLaren, B. M., Scheiter, K., Aleven, V., & Schanze, S. (2025). Problem-Solving Strategies in Stoichiometry Across Two Intelligent Tutoring Systems: A Cross-National Study. Journal of Science Education and Technology, 34(2), 384–400. https://doi.org/10.1007/s10956-024-10197-7
Bruckermann, T., Neugebauer, T.-G., Schanze, S., Schomaker, C., & Werning, R. (2025). Die LeibnizLernlandschaft: Diversität und Digitalität (L2D2): Ein Ort für eine interdisziplinäre, strukturübergreifende inklusive Lehrkräftebildung an der Leibniz Universität Hannover. In U. Stadler-Altmann, F. Herrmann, P. Kihm, & A. Schulte-Buskase (Eds.), Atlas der Hochschullernwerkstätten: Ein (un-)vollständiges Kompendium (pp. 342-353). (Lernen und Studieren in Lernwerkstätten). Verlag Julius Klinkhardt. https://doi.org/10.35468/6148
Fleischer, H., Noglik, A., Borchers, C., & Schanze, S. (2025). Does Student Learning Rate Depend on Feedback Type and Prior Knowledge? In C. Mills, G. Alexandron, D. Taibi, G. Lo Bosco, & L. Paquette (Eds.), Proceedings of the 18th International Conference on Educational Data Mining, EDM 2025 (pp. 571-577). (Proceedings of the International Conference on Educational Data Mining). International Educational Data Mining Society. Advance online publication. https://doi.org/10.31234/osf.io/an3bx_v1, https://doi.org/10.5281/zenodo.15870227
Fleischer, H., Borchers, C., Schanze, S., & Aleven, V. (2025). Error Classification in Stoichiometry Tutoring Systems with Different Levels of Scaffolding: Comparing Rule-Based Classification and Machine Learning. In K. Tammets, S. Sosnovsky, R. Ferreira Mello, G. Pishtari, & T. Nazaretsky (Eds.), Two Decades of TEL. From Lessons Learnt to Challenges Ahead - 20th European Conference on Technology Enhanced Learning, EC-TEL 2025, Proceedings: 20th European Conference on Technology Enhanced Learning, EC-TEL 2025 Newcastle upon Tyne and Durham, UK, September 15–19, 2025 Proceedings, Part II (pp. 126-131). (Lecture Notes in Computer Science; Vol. 16064 LNCS). https://doi.org/10.1007/978-3-032-03873-9_12, https://doi.org/10.35542/osf.io/edpgk_v1
Navarrete, E., Nehring, A., Schanze, S., Ewerth, R., & Hoppe, A. (2025). A Closer Look into Recent Video-based Learning Research: A Comprehensive Review of Video Characteristics, Tools, Technologies, and Learning Effectiveness. International Journal of Artificial Intelligence in Education, 35(4), 1631-1694. https://doi.org/10.1007/s40593-025-00481-x, https://doi.org/10.48550/arXiv.2301.13617
Nehring, A., & Schanze, S. (2025). Turning the Plurality of Chemistry into a Resource for Learning: A Core Competency of Chemistry Teachers. Science & education, 34(4), 2051-2078. https://doi.org/10.1007/s11191-025-00624-5
2024
Bickes, C., Schanze, S., & Sieve, B. F. (2024). Sprache und Kommunikation im Chemieunterricht. In J. Paul, S. Schanze, & B. F. Sieve (Eds.), Fachdidaktik Chemie in Theorie und Praxis (1 ed., pp. 399-430). Springer Spektrum. https://doi.org/10.1007/978-3-662-69820-4_12
Grüß-Niehaus, T., Hundertmark, S., & Schanze, S. (2024). Und was kommt an? Konzeptentwicklung als ein Teil des Lernens. In J. Paul, S. Schanze, & B. F. Sieve (Eds.), Fachdidaktik Chemie in Theorie und Praxis (1 ed., pp. 109-140). Springer Spektrum. https://doi.org/10.1007/978-3-662-69820-4_4
