The aim of this project is to study the development of the machine learning skills of lower secondary pupils (grades 7 to 9) within the natural sciences, including their ability to understand, critically evaluate, and participate responsibly in the development of machine learning models. Machine learning means a computer program using existing data to 'learn’ contexts, make predictions and recognise patterns.

The backdrop for the project is the increasing use of machine learning computer systems, which has a significant impact on all our lives. It is therefore essential that everyone learns to understand how these systems work and can be developed. This will enable people to participate in and take responsibility for the development of society (see the overall objective of primary and lower secondary school).

Biology has been selected as a case study because machine learning has been used within the subject for many years (for example in healthcare and the environment) and because pupils have many real-world opportunities for visual classification and profiling. It will also be possible to relate the programme to other science subjects, all of which have goals to understand and use models. It must then be possible for science teachers and their pupils in lower secondary schools and didactic researchers and other actors within the field to apply the programme.

The methodology is a combination of action research and design-based research: The programme will be developed and analysed in close collaboration between researchers and teachers, and the initial programme will be redesigned based on real-life testing, after which it will be retested and further redesigned.