2024
2025
A Dashboard for University Student Guidance
Funding:

Supported by the Ministry of Science (NRW, GER) as part of the project KI:edu.nrw.


This project focuses on the development of an interactive dashboard to support academic advising in higher education. Combining insights from our previous projects, the dashboard visualises course difficulty, student preparedness and individual learning trajectories. Developed in collaboration with advisors at Ruhr University Bochum and as part of the KI:edu.nrw initiative, the dashboard integrates modular, tile-based visualisations and uses Item Response Theory (IRT) to produce interpretable, valid and time-sensitive analyses. It enables advisors to assess student-specific pass probabilities and track shifts in course difficulty, improving decision-making and promoting individualised study planning.

Find the current public version here (click).


Publications

    2024

  • Empowering Advisors: Designing a Dashboard for University Student Guidance
    Baucks, F., & Wiskott, L.
    In P. Salden & Leschke, J. (Eds.), Learning Analytics und Künstliche Intelligenz in Studium und Lehre: Erfahrungen und Schlussfolgerungen aus einer hochschulweiten Erprobung (pp. 27–44) Wiesbaden: Springer Fachmedien Wiesbaden
  • 2023

  • Von der Forschung in die Praxis: Entwicklung eines Dashboards für die Studienberatung
    Baucks, F., & Wiskott, L.
    Abstract presented at 2nd Learning AID
  • Ein Dashboard für die Studienberatung: Technische Infrastruktur und Studienverlaufsplanung im Projekt KI:edu.nrw
    Baucks, F., Leschke, J., Metzger, C., & Wiskott, L.
    In Workshop Proceedings of the 21th Fachtagung Bildungstechnologien (DELFI) (pp. 185–188) Bonn: Gesellschaft für Informatik e.V.

The Institut für Neuroinformatik (INI) is a research unit of the Faculty of Computer Science at the Ruhr-Universität Bochum. Its scientific goal is to understand the fundamental principles through which organisms generate behavior and cognition while linked to their environments through sensory and effector systems. Inspired by our insights into such natural cognitive systems, we seek new solutions to problems of information processing in artificial cognitive systems. We draw from a variety of disciplines that include experimental psychology and neurophysiology as well as machine learning, neural artificial intelligence, computer vision, and robotics.

Universitätsstr. 150, Building NB, Room 3/32
D-44801 Bochum, Germany

Tel: (+49) 234 32-28967
Fax: (+49) 234 32-14210