Data Science and Big Data in Upper Secondary Schools: A Module to Build up First Components of Statistical Thinking in a Data Science Curriculum Rolf Biehler, Daniel Frischemeier, Susanne Podworny, Thomas Wassong, Lea Budde, Birte Heinemann and Carsten Schulte Abstract Within the framework of a design-based research project, computer science educators and statistics educators at Paderborn University designed a pilot course on the subject of data science and big data. It addresses upper secondary students and was realized by weekly sessions (three hours) over seven months. The whole course that is intended to introduce upper secondary school students to the field of data science consists of four modules. In module 1, the learners are introduced into the basics of statistics and big data and it aims at developing their data competence and data awareness. In the sec- ond module, learners are introduced to machine learning and programming based, among others, on examples from module 1. In the third and fourth module, learners can apply their knowledge gained in modules 1 and 2 and Rolf Biehler · Daniel Frischemeier · Susanne Podworny · Thomas Wassong Institute of Mathematics, Paderborn University, Paderborn, Germany Lea Budde · Birte Heinemann · Carsten Schulte Institute of Computer Science, Paderborn University, Paderborn, Germany biehler@math.upb.de dafr@math.upb.de podworny@math.upb.de wassong@math.upb.de lea.budde@uni-paderborn.de heinemann@informatik.rwth-aachen.de carsten.schulte@uni-paderborn.de Archives of Data Science, Series A (Online First) DOI: 10.5445/KSP/1000087327/28 KIT Scientific Publishing ISSN 2363-9881 Vol. 5, No. 1, 2018