Michel Dumontier at EDLAB: How to educate the digital professional?

On 10 December, Michel Dumontier, Distinguished Professor of Data Science at Maastricht University and Director of the UM Institute for Data Science (IDS), came to EDLAB for a meeting with EDLAB faculty liaisons, the EDLAB team, and colleagues from the library. The meeting discussed the development and implications of data and related technology in our world, how to educate digital professionals and how to integrate data science in education.

IDS’ goal: establish a world-class center in data science research and education.

For this to happen we have to team up and innovate in education together. Data science is a hot topic in the Netherlands and around the world. However, most of the focus is on purely technical programmes coming out of the computer science discipline, rather than also focusing on ethics, thinking about the digital society and what responsible and scalable data science looks like.

At UM we envision education to be collaborative and interdisciplinary. We want people to be able to solve problems and understand data science – we want to create students who are both literate in data science and aware of issues proposed by the digital humanities: digital professionals. Of course, developing this should take place within a personalised and integrated learning experience, with research-based learning and team work.

If you aren’t part of the innovation curve you are going to be replaced by it

Michel presented the three-pronged approach to data science we are taking:

1. Enhance existing programmes and courses with data science (e.g. lectures, labs, modules, projects, thesis topics)
2. Create learning opportunities for youth and professionals (e.g. hosting a workshop for 11-year olds on ‘can a robot be your friend’, which encourages them to think critically about life and how they relate to things)
3. Develop new interfaculty programmes featuring data science and artificial intelligence in society.

He then explained some of the work done so far, such as hosting data science workshops, hackathons, internships and guest lectures. There is also a lot of work in progress, such as the development of an interfaculty Bachelor in Global Studies, and a FASoS Bachelor in Digital Society. This raises new challenges, because there are not many people capable of leading interdisciplinary courses of this kind on their own, so we need to find ways to enable multiple people to contribute and collaborate to the programme, in cost-effective ways.

The presentation was followed by a lively discussion about laying the foundations for cross-cutting interactions at UM and beyond. In particular, the role of data science in education innovation is something we want to explore further with the UM community.