Publikationen und Projekte der AG Kubsch
Publikationen
2024
Ludwig, Thobias, Kubsch, Marcus, Sorge, Stefan, Kardas, Engin (20249: Quellen von Unsicherheit beim Experimentieren - Welche Rolle spielen verschiedene Arten von Unsicherheit beim Experimentieren? In https://www.researchgate.net/publication/383177840_Quellen_von_Unsicherheit_beim_Experimentieren Karademir, O., Borgards, L., Di Mitri, D., Strauß, S., Kubsch, M., Brobeil, M., Grimm, A., Gombert, S., Rummel, N., Neumann, K., & Drachsler, H. (2024). Following the Impact Chain of the LA Cockpit. An Intervention Study Investigating a Teacher Dashboard’s Effect on Student Learning. In Journal of Learning Analytics, 1-14. https://doi.org/10.18608/jla.2024.8399 Nordine, Jeffrey, Kubsch, Marcus, Fortus, David, Krajcik, Joseph, Neumann, Knut (2024). Middle school students' use of the energy concept to engage in new learning: What ideas matter? In Journal of Research in Science Teaching, 1–32. https://doi.org/10.1002/tea.21950 Karademir, Onur, Di Mitri, Daniele, Schneider, Jan, Jivet, Ioana, Allmang, Jörn, Gombert,Sebastian,Kubsch, Marcus, Neumann, Knut, Drachsler, Hendrik (2024). I don't have time! But keep me in the loop: Co-designing requirements for a learning analytics cockpit with teachers. In Journal of Computer Assisted Learning,1–19. https://doi.org/10.1111/jcal.12997 Fiedler, K., Kubsch, M., Neumann, K. & Nordine, J. (2024). Der potentiellen Energie ein Zuhause geben. |
Kubsch, M. & Nordine, J. (2024). Auf das System kommt es an. |
Tschisgale, P., Steegh, A., Petersen, S., Kubsch, M., Wulff, P. & Neuman, K. (2024). Are science competitions meeting their intentions? a case study on affective and cognitive predictors of success in the Physics Olympiad. |
Kubsch, M. (2024). What affects the continued learning about energy? Evidence from a 4-year longitudinal study. |
Tschisgale, P., Steegh, A., Kubsch, M., Petersen, S. & Neumann, K. (2024). Towards a more individualised support of science competition participants – identification and examination of participant profiles based on cognitive and affective characteristics. |
Graulich, N., Arnold, J., Sorge, S. & Kubsch, M. (2024). Lehrkräftebildung von morgen - Beiträge der Naturwissenschaftsdidaktiken zur Förderung überfachlicher Kompetenzen. |
Nauermann, L., Sorge, S., Garrecht, C., Bernholt, S., Kubsch, M. & Steegh, A. (2024). Gemeinsam globale Herausforderungen angehen - Ein Seminarkonzept zur Erstellung digitaler Unterrichtsmaterialien in den Naturwissenschaften. |
Kubsch, M. & Neumann, I. (2024). Science Denial im naturwissenschaftlichen Unterricht begegnen. |
2023
Kubsch, M., Strauß, S., & Bernholt, S. (2023). Integrating perspectives to promote knowledge integration: How knowledge integration, learning progressions and instructional science can complement each other. |
Kubsch, M., Sorge, S. & Wulff P. (2023). Emotionen beim Reflektieren in der Lehrkräftebildung. |
Taylor, J. A., Bowen, G. M., Kubsch, M., Summers, R., Sezen-Barrie, A., Patrick, P., Lachapelle, C., Warfa, A. & Guzey, S. S. (2023). Crossing boundaries between research and practitioner communities: The role of research use and cross-community journal authorship. |
Krist, C. & Kubsch, M. (2023). Bias, bias everywhere: A response to Li et al. and Zhai and Nehm. |
Tschisgale, P., Wulff, P. & Kubsch, M. (2023). Integrating artificial intelligence-based methods into qualitative research in PER – A case for computational grounded theory. |
Fiedler, K., Kubsch, M., Neumann, K. & Nordine, J. (2023). Fields in middle school energy instruction to support continued learning of energy. |
Kubsch, M., Neumann, K., Rochnia, M. & Gräsel, C. (2023). 50 Jahre Unterrichtswissenschaften – Themen der empirischen Lehr-Lern-Forschung im Wandel. |
Grimm, A., Steegh, A., Colakogul, J., Kubsch, M. & Neumann, K. (2023). Positioning Responsible Learning Analytics in the Context of STEM Identities of Under-Served Students. |
Grimm, A., Kubsch, M., Steegh, A. & Neumann, K. (2023). Learning Analytics in Physics Education: Ethical, Equity-Focused Decision-Making Lacks Guidance! |
Gombert, S., Di Mitri, D., Karademir, O., Kubsch, M., Kolbe, H., Tautz, S., Grimm, A., Bohm, I., Neumann, K. & Drachsler, H. (2023). Coding energy knowledge in constructed responses with explainable NLP models. |
2022
Kubsch, M., Czinczel, B., Lossjew, J., Wyrwich, T., Bednorz, D., Bernholt, S., Fiedler, D., Strauß, S., Cress, U., Drachsler, H., Neumann, K. & Rummel, R. (2022). Towards Learning Progression Analytics – Developing Learning Environments for the Automated Analysis of Learning using Evidence Centered Design. |
Kubsch, M., Rosenberg, J. M. & Krist, C. (2022). Distributing epistemic functions and tasks—A framework for augmenting human analytic power with machine learning in science education research. |
Kubsch, M., Fortus, D., Neumann, K., Nordine, J. & Krajcik, J. (2022). The interplay of students’ motivational profiles and science learning. |
Rosenberg, J., Kubsch, M., Dogucu, M. & Wagenmakers, E. (2022). A Bayesian perspective on uncertainty and probability in science education. |
Kubsch, M., Wulff, P. & Buschhüter, D. (2022). Schwerpunkttagung Maschinelles Lernen und computerbasierte Textanalysen: Potentiale und Herausforderungen für die Naturwissenschaftsdidaktik. |
Kubsch, M. & Weßnigk, S. (2022). Die Wärmebildkamera im Kontext Mechanik gewinnbringend einsetzen. |
Fiedler, K., Kubsch, M., Neumann, K. & Nordine, J. (2022). Der potentiellen Energie ein Zuhause geben – Felder als didaktisches Hilfsmittel im Anfangsunterricht zum Energiekonzept. |
Kubsch, M. & Hamerski, P. C. (2022). Dynamic Energy Transfer Models. |
Kubsch, M., Caballero, D. & Uribe, P. (2022). Once More with Feeling: Emotions in Multimodal Learning Analytics. |
2021
Kubsch, M., Sorge, S., Arnold, J. & Graulich, N. (2021). Lehrkräftebildung neu gedacht – Ein Praxishandbuch für die Lehre in den Naturwissenschaften und deren Didaktiken. |
Kubsch, M., Rosenberg, J. M. & Krist, C. (2021). Beyond Supervision: Human / Machine Distributed Learning in Learning Sciences Research. |
Rosenberg, J. M. & Kubsch, M. (2021). Considering K-12 Learners’ Use of Bayesian Methods. |
Sorge, S., Kubsch, M., Breuer, J., Syskowski, S. & Wöhlke, C. (2021). Lehrkräftebildung neu gedacht – Ergebnisse des GDCP Hackathon 2020. |
Kubsch, M., Opitz, S., Nordine, J., Neumann, K., Fortus, D. & Krajcik, J. (2021). Exploring a pathway towards energy conservation through emphasizing the connections between energy, systems, and fields. |
Kubsch, M., Stamer, I., Steiner, M., Neumann, K. & Parchmann, I. (2021). Beyond p-values: Using Bayesian Data Analysis in Science Education Research. |
Kubsch, M. & Sorge, S. (2021). Unterstützungsmöglichkeiten beim Erklären und Argumentieren im Physikunterricht. |
Fischer, J., Steinmann, T., Kubsch, M., Laumann, D., Weßnigk, S., Neumann, K. & Kerres, M. (2021). Die Rettung der Phänomene! - Phänomenbasiertes Lernen initiieren und strukturieren durch Leitfragen. |
2020
Bowen, M., Taylor, J., Patrick, P., Summers, R., Kubsch, M., Warfa, A., Sezen-Barrie, A., Guzey, S. & Lachapelle, C. (2020). Understanding the Use of Academic Research in Science Education Practitioner Journals. |
Kubsch, M., Nordine, J., Fortus, D., Krajcik, J. & Neumann, K. (2020). Supporting Students in UsingEnergy Ideas to Interpret Phenomena: The Role of an Energy Representation. |
Kubsch, M., Touitou, I., Nordine, J., Fortus, D., Neumann, K. & Krajcik, J. (2020). Transferring Knowledge in a Knowledge-in-Use Task—Investigating the Role of Knowledge Organization. |
2019
Stamer, I., Kubsch, M., Thiele, M., Höffler, T., Schwarzer, S. & Parchmann, I. (2019). Scientists, Their Work, and how Others Perceive Them: Self-Perceptions of Scientists and Students’ Stereotypes. |
Kubsch, M. & Cukurova, M. (2019). Diagnosing Student Competencies about the Concept of Energy in a Digital Learning Environment. |
Fortus, D., Kubsch, M., Bielik, T., Krajcik, J., Lehavi, Y., Neumann, K., Nordine, J., Opitz, S. & Touitou, I. (2019). Systems,transfer, and fields: Evaluating a new approach to energy instruction. |
Kubsch, M., Nordine, J., Neumann, K., Fortus, D. & Krajcik, J. (2019). Probing the Relation between Students’ Integrated Knowledge and Knowledge-in-Use about Energy using Network Analysis. |
Kubsch, M., Nordine, J., Neumann, K., Fortus, D. & Krajcik, J. (2019). Measuring Integrated Knowledge – A Network Analytical Approach. |
2018
Kubsch, M., Nordine, J. & Neumann, K. (2018). Der System-Transfer-Ansatz. Den Energietransfer zwischen Systemen ins Zentrum stellen. |
Kubsch, M., Nordine, J., Neumann, K., Fortus, D. & Krajcik, J. (2018). Lerntrajektorien im Energiekonzept. |
Kubsch, M. & Nordine, J. (2018). Energietransferdiagramme als kognitive Unterstützung in der Mittelstufe. |
2017
Kubsch, M., Nordine, J. & Hadinek, D. (2017). Using smartphone thermal cameras to engage students’ misconceptions about energy. |
2016
Kubsch, M., Illenseer, T. F. & Duschl, W. J. (2016). Accretion disk dynamics: α-viscosity in self-similar self-gravitating models. |
2014
Meißner, M., & Haertig, H. (2014). Smartphone astronomy. |
Schlagwörter
- Publikationen