How can an active learning approach enhance how key topics in public policy, public administration, and governance are taught? This article describes four educational game scenarios that illustrate decision-making processes in social inclusion policies. Various governance aspects can be examined through these games, including accountability reforms, crisis management, challenges in implementing artificial intelligence in social service provision, and market regulation. All these cases have been developed within the framework of the P-Cube project, an Erasmus + project that aims to foster active learning through the use of educational games for teaching public policy. The first case illustrates the effect of regulation on nursing home services, and aims to examine the implications of establishing independent agencies to regulate specific social sectors and the involvement and participation of the market and stakeholders in these regulatory bodies. The second case explores the application of artificial intelligence and automated decision-making in a surveillance system for detecting welfare fraud, in which the main learning objective is to discuss governance implications and consequences for social innovation and inclusion. The third case examines the implementation of alternative solutions for providing school meals to children from low-income families during the COVID-19 pandemic. The main objective here is to explore the role of participatory mechanisms in driving policy change and to identify the factors influencing their degree of effectiveness. The fourth case explores the potential ways of regulating the rights of workers employed in the digital platform-based economy. Our cases target graduate and postgraduate students in political science, public administration, public policy, social policy, and other related fields. They also offer valuable insights for practitioners, specifically public managers at different organizational levels.
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