Many courses suffer from low cognitive activation of the students.?This can be addressed with assignments that students complete in and/or between sessions.?However, especially in larger courses it is hardly possible to give all students adaptive, elaborated and process-related feedback on their work.?Therefore, a generic Stud.IP plugin will be developed to enable structured forms of feedback by tutors (incl. lecturers) and peers.?Based on findings from feedback research, instructors should be able to use the plugin to determine (a) who gives feedback to whom on which task, (b) which criteria should be taken into account, and (c) how the feedback is processed by the recipients.?Subject-specific catalogs of effective feedback are developed as text modules that enable efficient feedback presentation, which is also conducive to a favorable error culture.?Initially, the Faculty of Applied Computer Science, the Faculty of Mathematics, Natural Sciences and Technology, and the Faculty of Economics are involved, since it is precisely here that large lectures are offered that benefit from an adaptive and at the same time efficient feedback system.?The transfer in the third year of the project will take place to the Faculty of Philological-Historical Sciences, the Faculty of Philosophical-Social Sciences, the 伟德国际_伟德国际1946$娱乐app游戏 and the Faculty of 伟德国际_伟德国际1946$娱乐app游戏icine.?In this way, the project is creating a feedback tool that can be used flexibly and integrated into Stud.IP, along with a large number of discipline-specific and customizable use cases.

2024

• Nuhn, E., Spang, L., & Timpf, S. (2024). getFeedback!: Feedback-based learning while identifying a caravan site location. AGILE: GIScience Series, 5, 42,? https://doi.org/10.5194/agile-giss-5-42-2024

• ?zbek, T., Daumiller, M., Roshany-Tabrizi, A., M?mke, T., & Kollar, I. (2024). Friendship or feedback?–Relations between computer science students’ goals, technology acceptance, use of an online peer feedback tool, and learning. Computers in Human Behavior Reports, 16, 100540. https://doi.org/10.1016/j.chbr.2024.100540

• Keller, M. V., Dresel, M., & Daumiller, M. (2024). Do achievement goals and self-efficacy matter for feedback use? Learning and Instruction, 93. https://doi.org/10.1016/j.learninstruc.2024.101948

• Greisel, M., Hornstein, J., Weidenbacher, A., Ott, J., & Kollar, I. (2024). Who wants to hear bad news? How the epistemic perspective determines the perception of peer feedback. In J. Clarke-Midura, I. Kollar, X. Gu, C. D'Angelo (Hrsg.), Proceedings of the 17th International Conference on Computer-Supported Collaborative Learning - CSCL 2024 (S. 221-224). Buffalo, IN: International Society of the Learning Sciences (ISLS). https://doi.org/10.22318/cscl2024.470012

• Hornstein, J., Greisel, M. & Kollar, I. (2024). Supporting Pre-Service Teachers’ Evidence-Informed Reasoning Through Peer-Feedback: Effects of Feedback Provision and Feedback Integration Scaffolds. In J. C. Midura, I. Kollar, X. Gu, & C. D‘Angelo (Hrsg.), Proceedings of the 17th International Conference of Computer-Supported Collaborative Learning – CSCL 2024 (S. 213-216). Buffalo: International Society of the Learning Sciences. https://doi.org/10.22318/cscl2024.961446

• Hornstein, J., Keller, M. V., Greisel, M., Dresel, M., & Kollar, I. (2024). Scaffolding the Peer-Feedback Process: A Meta-Analysis. In Lindgren, R., Asino, T. I., Kyza, E. A., Looi, C. K., Keifert, D. T., & Suárez, E. (Eds.), Proceedings of the 18th International Conference of the Learning Sciences - ICLS 2024 (pp. 2231-2232). International Society of the Learning Sciences. https://doi.org/10.22318/icls2024.833519

2023

• Bauer, E., Greisel, M., Kuznetsov, I., Berndt, M., Kollar, I., Dresel, M., Fischer, M. R., & Fischer, F. (2023). Using natural language processing to support peer-feedback in the age of artificial intelligence: a cross-disciplinary framework and a research agenda. British Journal of Educational Technology, 54(5), 1222-1245. https://doi.org/10.1111/bjet.13336
• Greisel, M., Bauer, E., Kuznetsov, I., Berndt, M., Dresel, M., Fischer, M., Kollar, I. & Fischer, F. (2023). How to use theory to implement natural language processing for peer-feedback. In C. Damsa, M. Borge, E. Koh, & E. Worsley (Hrsg.), Proceedings of the 16th International Conference of Computer-Supported Collaborative Learning – CSCL 2023 (S. 237-240). Montreal: International Society of the Learning Sciences. http://dx.doi.org/10.22318/cscl2023.108887

• ?zbek, T., M?mke, T., Roshany, A. & Kollar, I. (2023). Friends or feedback? Computer science students’ goals and their intention to use a feedback tool. In P. Blikstein, J. van Aalst, R. Kizito, & K. Brennan (Hrsg.), Proceedings of the 17th International Conference of the Learning Sciences – ICLS 2023 (S. 2090-2091). Montreal: International Society of the Learning Sciences. https://doi.org/10.22318/icls2023.227736

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• Thomas Bratzdrum
• Dr. Linda He???
• Julia Hornstein??????????????
• Melanie Keller
• Jonas Riesner?
• Aida Roshany??
• Dr. Anna Schneller??????
• Dr. Klaus Vogelgsang??
• Prof. Dr. Anna Bleuler?
• Prof. Dr. Claudia Claridge????????
• Prof. Dr. Georg Cleppien???????????
• Prof. Dr. Markus Dresel?????????????
• Prof. Dr. Dietmar Koch
• Prof. Dr. Tobias M?mke?????????????
• Prof. Dr. Katja Sarkowsky?????????
• Prof. Dr. Sabine Timpf
• Prof. Dr. Jennifer Kunz?
• Pascal Misch??
• Dr. Eva Nuhn
• Stefanie Helmschrott
• Dr. Martin Riedelsheimer
• Irada Ismayilova
• Dr. Christian Hoffmann
• Dr. Christina Kunzmann

• ????? Chair of Psychology
• Chair of Psychology with special emphasis on Educational Psychology
• Prof. Dr. Jennifer Kunz: Controlling
• Professorship for Geoinformatics
• Chair of Materials Engineering
• DigiLLab - Center for Digital Teaching and Learning