BiomedChallenge: Enhancing Student Learning in Data Science

Active learning methodologies promote student inquiry, discovery and problem-solving in real-life situations. This paper presents the results of implementing a data challenge called BiomedChallenge, for undergraduate and graduate students in the field of biomedicine. The challenge aimed to provide students with an opportunity to practically apply their acquired knowledge to solve a real problem collaboratively in groups of 2 or 3 students. The task involved applying the complete radiomics procedure to classify brain tumors as patients or controls, as well as writing a technical paper describing the procedure and the obtained results. Groups with the highest accuracy were rewarded. The students regarded the BiomedChallenge as a highly positive and motivating activity, enhancing their understanding of real-life biomedical case problems. Moreover, the activity successfully met the technical objectives.