Designing for motivation, when there is none: lessons of designing a python-based data literacy program mandatory for all students.

With data exponentially growing lately, data literacy has become essential for individuals and organizations to prosper. Nonetheless, it is rare and seems an unattainable goal to the majority of people. Researchers, policymakers, and educators are exploring ways of getting learners excited about data, and the Leuphana University of Luneburg is not left behind in this quest. Starting in the winter semester of 2021/2022, all 1,450 first-year students will undergo basic data literacy education at Leuphana, which includes the teaching of related knowledge and skills as well as relevant ethical issues. In this paper, we theoretically explore how to design teaching-learning settings that, given heterogeneous learning groups, can transform initially unmotivated students into intrinsically motivated lifelong learners of data competencies. Furthermore, in light of our empirical experience, we derive and discuss design principles that will enable readers to find a context-adapted solution.