Dr. Clara Schumacher

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Dr. Clara Schumacher Photo: privat

Dr. Clara Schumacher

Post-doctoral researcher in the LA-DIVA project

Email: clara.schumacher

Rudower Chaussee 25
Raum 3.415 (3. Etage)
12489 Berlin

What is my role within CATALPA?

As a post-doctoral researcher with a background in educational science I am working in the project LA-DIVA particularly on the pedagogical foundation of the features to be developed and how these are related to learning behavior and performance.

Why CATALPA?

The interdisciplinary project and research cluster offer interesting tasks, diverse exchange as well as good conditions to advance the scientific career. My goal is to develop educational technologies that integrate learning, computer and data sciences to provide learners and instructors with the support they need.

    • Post-doctoral researcher in the project LA-DIVA, Humboldt-Universität zu Berlin (since April 2020)
    • Doctoral degree (Dr. rer. Pol.) on the topic “Cognitive, Metacognitive, and Motivational Perspectives on Learning Analytics. Synthesizing Self-regulated Learning, Assessment, and Feedback with Learning Analytics”, University of Mannheim (2020)
    • Research assistant at the chair of Learning, Design and Technology (Prof. Dr. Dirk Ifenthaler), University of Mannheim (2015-2020)
    • Diploma in educational science (Diplom-Pädagogin) with focus on adult education, psychology and work psychology, University of Koblenz-Landau (2014)

  • My research interests are at the intersection of educational science and educational technologies with focus on learning analytics, self-regulated learning, feedback, assessment, collaborative learning, prompts and informal learning

  • LA-DIVA

  • 2024

    Conferences

    • Rüdian, S., Schumacher, C., Hanses, M., Kuzilek, J., & Pinkwart, N. (2024, July). Rule-based and prediction-based computer-generated feedback in online courses. IEEE International Conference on Advanced Learning Technologies (ICALT).

    2022

    Conferences

    • Schumacher, C., & Kuzilek, J. (2022). How do students perceive algorithmic grouping in higher education? Companion Proceedings of the LAK2022, 48.
    • Seidel, N., & Schumacher, C. (2022). Workshop Learning Analytics - Intertweening Learning Analytics and Adaptive Learning. In M. Mandausch & P. A. Henning (Eds.), Proceedings of the DELFI workshops 2022 (pp. 99–103). Gesellschaft für Informatik e.V. https://doi.org/10.18420/delfi2022-ws-20

    2021

    Conferences

    • Schumacher, C., & Kuzilek, J. (2021a). Perfect match? Investigating students’ perceptions about algorithmic grouping in higher education. 2021 AECT International Convention.
    • Schumacher, C., & Kuzilek, J. (2021b, June). Student perspectives on automatic grouping in higher education. Presented at Junges Forum für Medien Und Hochschulentwicklung, Virtual Conference, 09-06-2021.
    • Schumacher, C., Reich-Stiebert, N., Kuzilek, J., Burchart, M., Raimann, J., Voltmer, J.-B., & Stürmer, S. (2021, April). Group perceptions vs. Group reality: Exploring the fit of self-report and log file data in the process of collaboration. Companion Proceedings of Conference on Learning Analytics and Knowledge 2021, Virtual Conference, 15-04-2021.
    • Schumacher, C., Seidel, N., & Rzepka, N. (2021). Workshop Learning Analytics - Considering student diversity with regard to assessment data and discrimination. In A. Lingnau (Ed.), Proceedings of the DELFI workshops (pp. 113–119). https://repositorium.hs-ruhrwest.de/frontdoor/deliver/index/docId/733/file/DELFI_2021_WS.pdf

  • Spokesperson of the DELFI (GI) working group learning analytics https://learning-analytics.eu

  • Research Gate

Research Center CATALPA | 28.06.2024