Background Conceptual links between economics and modern data science pose challenges for students and lecturers alike. The present article aims to enhance education and training of students and practitioners by integrating modern empirical research skills into their economic competencies. Aim This paper introduces a classroom game designed to simulate real-world economic scenar- ios, enhancing understanding of procurement markets and regulatory roles within society. In addition, the paper provides supporting teaching material in order to implement the game. The incorporation of this classroom game can contribute to the preparation of the next generation of professionals to be better equipped to address challenges in the era of big data. Method Participants’ success in the game’s first two parts hinges on their comprehension of market dynamics. In the third part, drawing from recent literature on machine-learning-based cartel detection, participants analyze whether bid patterns are indicative of collusive (cartel) behavior. In this part of the game, the success of the participants now role-playing as employees of an antitrust authority, depends on data-science skills. Results The classroom game introduced in the present article was implemented with a class of ten students, serving both as a proof of concept and as a means to gain practical insights. The game proves to be a suitable tool for social-science educators to incorporate the interdisciplinary nature of modern economics into their curricula. It is suited for participants with varying levels of data-science expertise. Moreover, it demonstrates how key lessons from scientific articles can 1 be taught in an application-oriented manner, enhancing participants’ ability to apply theoretical knowledge in real-world contexts. Conclusion Incorporating the classroom game presented in this paper into educational curricula supports students in effectively integrating data-science skills with economic reasoning.
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