New teaching lab to prepare MBG students for automated laboratories

Today, there is a growing gap between the way students typically work in university teaching laboratories and the reality they encounter in many modern research and industrial laboratories.

While laboratory exercises at university are often carried out manually, an increasing number of processes in research and industrial laboratories are becoming automated. This can increase both capacity and reproducibility and make it possible to conduct far more experiments and work with larger amounts of data.

The new AUtolab teaching laboratory at the Department of Molecular Biology and Genetics aims to help bridge this gap.

The facility will be equipped with several liquid-handling robots capable of automating pipetting and other repetitive laboratory processes. Initially, the robots will be integrated into teaching in the Molecular Biology and Molecular Medicine degree programmes.

“The facility will be one of the first of its kind, giving us the opportunity to be at the forefront of developing teaching methods for laboratory automation in broad university degree programmes. Among other things, we hope to reduce the gap between practical teaching at universities and the reality our students will encounter in their future careers,” says Associate Professor Magnus Kjærgaard, principal applicant for the project.

From pipetting to experimental design

Manual laboratory exercises will continue to play an important role in teaching, as they give students a fundamental understanding of the individual steps involved in an experiment. With laboratory robots, however, part of the practical work can be automated. The ambition is that this will give students more room to focus on areas such as experimental design, hypotheses, programming and data interpretation.

At the same time, the robots will introduce students to programming in a very tangible way. The robots are controlled by code, allowing students to see directly how their digital instructions are translated into physical actions in the laboratory.

“Programming can seem quite abstract to many life science students. Here, the code is suddenly translated directly into an experiment that they can see happening in front of them. We hope this can make programming more tangible while also showing students why it is relevant to their field,” says Magnus Kjærgaard.

The project will, among other things, investigate how this connection between programming and practical laboratory work affects students’ motivation and their skills in computational thinking.

When the robots are not being used for teaching, the ambition is for AUtolab to function as a kind of automation makerspace, where Bachelor’s and Master’s students, among others, can explore the use of automation in their own projects.