Students and lecturers develop generic data training in new trial ‘Datacrunching’ course

The world is full of data. You can get datasets from anywhere, but they’re not always in the format you’re looking for. So, you then need to fiddle about with them until you are able to read them, extract the story they’re trying to tell and present the results. Because generic data skills are not yet a standard part of the curriculum throughout HAS, Leo Jansen (Business Administration & Agribusiness), Tanja Speek (Applied Biology), Mel van Drunen (Geo Media & Design) and Reinier Krins (Geo Media & Design) developed a brand-new course they’ve called ‘Datacrunching’.

Trial version

A trial version of the course has been going for the past two months with 19 lecturers and 8 students from different study programmes participating. “The goal was to create a more precise definition of data skills and what students and lecturers need,” says Mel. “We thought we had it figured out but, because it’s about such a new field, we decided it would be wise to start with a trial version before we introduce data training throughout HAS. This enabled us to see whether what we’re offering is what people need.”

Insights into daily use

This was a good move, because it provided valuable insights for both the participants and the developers, which could be used immediately in everyday tasks. “All of us learned something from the course,” Mel explains. “One of the most important things we learned was that, if you want to get a grip on big data, you need to start with small, structured datasets. Participants learned how to use pivot tables, for example. They can help you bring the core of a dataset to the surface. Participants were also taught how to use graphs to discover the big picture in the data, and to then explain it using the graphs. Another eye-opener was how easy it is to transform ‘dirty’ data into clean sources of information.”

What’s needed?

During the course, it became clearer what the lecturers and students need. “We simply learned by just doing what HAS needs from data, and that at the same time we also saw that requirements can differ per study programme. Applied Biology, for example, focusses on monitoring innovation, and Horticulture & Arable Farming focusses on smart farming. So they don’t all need the same thing.”

More efficient and more fun

What’s good about running a trial course is that it’s becoming clear that, if you work more efficiently with data, it’s also more fun. Mel: “As the course progressed, both lecturers and students became increasingly enthusiastic. They sometimes even stayed after the evening course had finished, to solve data problems. ‘We should’ve had this 10 years ago’, is a comment we heard a lot.”

‘Datacrunching’ certificate

The 27 participants on the course received their certificate in Datacrunching on 9 May. At the same time, they carried out a brief evaluation. “It really ads to what you learn during your study programme,” one of the students commented. “It’s a foundation you just have to have, because data is only going to play an ever-increasing role in the future.” Another student said: “It was fun to be part of the creation of data skills training within HAS.” The lecturers completely agreed. “These tools allow you to link conclusions to the available data better.”

Improving the content and methodology

Leo, Tanja, Mel and Reinier are now going to further improve both the content and methodology behind the course. “An important question is still whether or not you need a concrete question before you start using a dataset, in order to get something out of your data. Sometimes the question might just be: what can I do with this data? By looking with an open mind, you can discover particular patterns. But even this approach could differ between the study programmes.”