The main objective of the project was to develop courses to provide university students in the field of biomedicine modern, timely, and up-to-date learning experiences that will enable them to develop skills and competences in biomedical data management, data analysis and modelling, and to identify, analyse and handle ethical challenges within modern biomedicine.
The Nordic network for master’s programmes in biomedicine, NordBioMedNet (established 2013) is an experienced, well-functioning collaboration between the Universities of Turku, Eastern Finland, Bergen, Southern Denmark and Karolinska Institutet.
The network identified a real need for additions to biomedical education to give students the best opportunities for a successful career and foster their employ ability. As modern biomedical research produces massive data generated by high-throughput methods, students need to develop computational and analytical skills to manage and utilise “big data” and “rich data”. Moreover, knowledge and tools in
bioethics are also increasingly important due to present rapid technological development in biomedicine with, for example, a new era of modern genomic/genetic research ripe with very critical and difficult ethical issues.
During the project we developed Open educational resources (OERs) that provides needed education and training in different aspects of computational science and computational biomedicine (bioinformatics, bioimaging), with a focus on analysis and interpretation of “big data” and education in bioethics.
The project combined the expertise of the partners to provide truly interdisciplinary (ethics, biomedicine, informatics and imaging) content to the courses, and the use of learning analytics provides insight into and qualitative improvement of course design, student progression, support for self-regulated learning, and peer and teacher feedback.
The interinstitutional and transdisciplinary team of collaborators means that both students and teachers are exposed to different online pedagogical practices used by the collaborating universities, and these practices are applied in developing local teaching.
Furthermore, the project brings together the students and teachers to work in multi-national, -cultural and -disciplinary groups, in the spirit of socio constructivism.
The project resulted in three independent courses, all available to students world-wide on open platforms
- Biomedical ethics
- Translational digital pathology
- Introduction to computational biomedicine and machine learning
Each course consists of modules that can be taken as a whole, or separately. The courses can also be implemented as learning tools in local courses.
IO2 consists of two finished modules
- Introduction to Translational Pathology | Computational biomedicine (mooc.no)
- Disease Model Pathology | Computational biomedicine (mooc.no)
IO4: All course material is collected in GitHub, starting point: