The goal of the overall project is the digitalisation of teaching in the field of nursing and health management. To achieve that, existing lectures will be recorded and organised in a semantic structure, so that at the end of the project, the lecture materials will interactively support both on-site lectures and distance learning. Furthermore, case-based dialogue system will be provided that will help the students to learn how to practically cope with different nursing cases.
The sub-project "Probabilistic state estimation with causal models" addresses the development of causal models describing how students learn in a specific case (situation). The causal model will make use of log data from the dialogue the student had with the tutoring system in order to provide situation-aware learning analysis. This will be achieved through probabilistic state estimation based on the causal model and the corresponding observation model that map the observations to the states in the causal model. The results from the learning analysis will be used as a basis for the development of models for assisting the students. Depending on the situation, these models provide appropriate strategies for supporting the student.
- Project title: Joint project DigiCare: Digital Training of Nursing and Health Management
- Sub-project at MMIS: Probabilistic state estimation with causal models
- Project homepage: https://pidi.informatik.uni-rostock.de/forschung/projekte/digicare/
- Runtime: 01.07.2019 - 30.06.2022
- Sponsor: Europäischer Sozialfond ESF
- Budget: > 300.000 Euro at MMIS (about 2.300.000 Euro in total)
- Reference number: ESF/14-BM-A55-0020/19
- Practical Computer Science Group, Institute of Computer Science, University of Rostock
- Junior Research Group CoMSA²t, University of Rostock
- University of Applied Science Neubrandenburg, Department of Health, Nursing, and Management
- German Centre for Neurodegenerative Diseases Rostock / Greifswald
- University Library, University of Rostock