Silke Wrede

Silke Wrede (MA) Photo: Hardy Welsch

Silke Wrede (MA)

Research assistant in the project AI.EDU Research Lab 2.0

Email: silke.wrede

Universitätsstr. 27 – PRG / Building 5
Room A 106 (1st floor)
58097 Hagen

What is my role within CATALPA?

As an educational scientist, I explore in the AI.EDU Research Lab the use of artificial intelligence in higher education. In particular, I work on integrating AI into (existing) didactic teaching and learning scenarios, considering educational science paradigms. Furthermore, raising students' awareness of the topic of AI is a guiding theme in my work.

Why CATALPA?

In the research focus CATALPA, I appreciate the exchange with other researchers, which inspires my own work and enriches it with insights into other disciplines. The interdisciplinary research orientation encourages my professional development in the field of education and artificial intelligence and reveals synergies as well as new research interests. .

    • Research assistant in the project AI.EDU Research Lab 2.0 (since October 2022), previously in AI.EDU Research Lab (October 2018-September 2022)
    • Master degree in Education and Media - eEducation (2022), thesis topic in the field of AI-based feedback and digital hermeneutics
    • Co-establishment of the AI-ExpertLab Higher Education (since November 2020)
    • Researcher assistant in the chair of Educational Theory and Media Education (since July 2018)
    • Bachelor degree in Educational Science, FernUniversität in Hagen (2018)
    • Co-organization of the Mobile Learning Day (2013/14/15/17/18)
    • Other activities: psychomotility therapist at the child and youth psychiatry Hamm, multiple teaching experiences with different target groups in the field of movement, pedagogical head of an open all-day primary school.
    • Implementation of artificial intelligence in learning and teaching in higher education
    • Personalizing the support of students with AI methods and approaches (e g. personalized feedback, Recommendersystems, Expertsystems,…)
    • Considering ethical and trustworthy use of AI
    • Modelling a domain in a social science context
    • Fostering of understanding – AI in teaching and learning from the perspective of digital hermeneutics
    • AI.EDU Research Lab 2.0
  • 2023

    Conferences

    Books

    Chapters in Edited Books

    • Wrede, S. E., Gloerfeld, C., & de Witt, C. (2023). KI und Didaktik – Zur Qualität von Feedback durch Recommendersysteme. In C. de Witt, C. Gloerfeld, & S. E. Wrede (Eds.), Künstliche Intelligenz in der Bildung (pp. 133–154). Springer Fachmedien Wiesbaden. https://doi.org/10.1007/978-3-658-40079-8_7
    • Wrede, S. E., Gloerfeld, C., de Witt, C., & Wang, X. (2023). Künstliche Intelligenz und forschendes Lernen - ein ideales Paar im Hochschulstudium!? In T. Schmohl & A. Watanabe (Eds.), Künstliche Intelligenz in der Hochschulbildung (pp. 195–212). transcript.

    2022

    Conferences

    • Wang, X., Li, H., Zimmermann, A., Pinkwart, Niels., Wrede, S., van Rijn, L., de Witt, C., & Baudach, B. (2022). IFSE – personalized quiz generator and intelligent knowledge recommendation. 2022 IEEE 16th International Conference on Semantic Computing (ICSC), 201–208. https://doi.org/10.1109/ICSC52841.2022.00041

    Talks and Poster Presentations

    • Karolyi, H., & Wrede, S. (2022). Gestaltung formativer Feedbacks an Hochschulen mit Künstlicher Intelligenz und Trusted Learning Analytics [Presentation].

    2020

    Journals

    • Gloerfeld, C., Wrede, S., de Witt, C., & Wang, X. (2020). Recommender – potentials and limitations for self-study in higher education from an educational science perspective. International Journal of Learning Analytics and Artificial Intelligence for Education (iJAI), 2(2), 34. https://doi.org/10.3991/ijai.v2i2.14763

    Conferences

    • Wang, X., Gülenman, T., Pinkwart, N., de Witt, C., Gloerfeld, C., & Wrede, S. (2020). Automatic assessment of student homework and personalized recommendation. In M. Chang (Ed.), IEEE 20th international conference on advanced learning technologies (pp. 150–154). IEEE. https://doi.org/10.1109/ICALT49669.2020.00051