ABSTRACT
We examine the impact of implementing active pedagogical method-ologies in three successive data science courses for a biology curriculum at the University of Mons, Belgium. Blended learning and ipped classroom ap-proaches were adopted, with an emphasis on project-based biological data anal-ysis. Four successive types of exercises of increasing dificulties were proposed to the students. Tutorials written with the R package learnr were identified as a critical step to transition between theory and the application of the con-cepts. The cognitive workload needed to complete the learnr tutorials was measured for the three courses and it was only lower for the last course, sug-gesting students needed a long time to get used to their software environment (R, RStudio and git). Data relative to students' activity, collected primar-ily from the ongoing assessment, were also used to establish student pro_les according to their learning strategies. Several suboptimal strategies were ob-served and discussed. Finally, the timing of students contributions, and the intensity of teacher-learner interactions related to these contributions were an-alyzed before, during and after the mandatory distance learning due to the COVID-19 lockdown. A lag phase was visible at the beginning of the first lockdown, but the students' work was not markedly affected during the second lockdown period which lasted much longer. © 2023 Sociedad Espanola de Investigacion Osea y del Metabolismo Mineral (SEIOMM). All rights reserved.