Computation is becoming the tool of choice for knowledge workers to solve problems in all disciplines. In order to strengthen the computational skills of all students, it is crucial to bridge computational skills with the skills from the different domains of studies – it requires a “transversal” approach, cutting across established disciplines and domains. To that end, computational thinking (CT) skills should be addressed embedded within the study of other disciplines; it should allow students of any domain to assess if problems in their domain can be solved computationally and to develop competencies to solve those problems with the help of computation and data analysis. This computationally-supported problem solving within domains needs a strong understanding of typical research questions and application scenarios within the domain, as well as typical methods and their limits. Thus, the development of teaching and learning activities on transversal CT needs to be a joint effort of domain experts and CT experts, i.e., in an interdisciplinary collaboration between computer science and subject-matter experts (mathematicians, physicists, chemists, biologists, engineers, economists, social scientists).

Using CT in the process of solving domain-specific problems puts data and thus digital information systems into an increasingly important role across domains. Beyond the mere manipulation of the data workflow (collection, cleaning, analyzing, storing, visualizing, etc.), it is of utmost importance that students develop the skills and attitudes to responsibly work with data, especially considering the potential social and environmental impact of any decision and action in their process of data treatment; this includes responsible communication of data-driven conclusions and decisions to peers and the public.

• Start date : 01.01.2021
• End date :  31.12.2024
• Amount: CHF 550 000 (EPFL), CHF 930 000 (ETH), CHF 235 200 (UniNe)
• Financing : Swissuniversities​ P-8 (Renforcement des digital skills dans l’enseignement)