Serious games

Serious games are games designed for a purpose beyond pure entertainment, often used for training, education, or awareness campaigns. They combine game mechanics with educational or informative content to engage players and achieve specific learning or behavioural goals.

Key characteristics:

• Purpose-driven
  Serious games have a clear objective beyond fun, such as teaching a skill, promoting a behaviour, or raising awareness about an issue.
• Engaging and interactive
  They utilise game mechanics like challenges, rewards, and feedback to motivate players and facilitate learning through active participation.
• Contextualised learning
  Serious games integrate learning content within a relevant context.
• Multimodal learning
  They often incorporate various media elements like visuals, audio, and text.

Games

UnExpected Values: From Dystopia to Utopia
UnExpected Values is an educational strategy board game with an online component. In this game you take on the role of a CEO navigating dilemmas at the intersection of profit, ethics, and social responsibility. Every decision you make shapes not just your company's future, but the kind of society we live in. The dilemmas you will face are not fictional—they are inspired by real-life events and stories.

UnExpectedValues: From Dystopia to Utopia is created by JTS Grassroots Grant 2024 winner Angelos Konstantinidis.

AI+Hospital
A board game about AI in healthcare. How can AI improve healthcare? And how do we deploy AI in healthcare in an ethical way? These questions are the focus of the educational board game AI Hospital. These questions are the focus of the educational board game AI+Hospital, part of the online curriculum AIProHealth. An initiative of UMCG's Data Science Center in Health (DASH).

Project leader Peter Van Ooijen (DASH) is also theme coordinator 'Digital Healthcare' at the Jantina Tammes School.

Tetris AI (uc)
Catherine Sibert on the game: "Tetris AI is essentially a game of Tetris, although instead of the user making choices about where to place each piece, they instead adjust the weights of an AI model that uses those weights to select placements, which will be visually reflected in real time. The hope is that by taking a relatively familiar domain with understandable features, users will build better intuitions about how the relationships between different features can result in visibly different gameplay behavior. If we can get the initial mechanics working, we have several ideas for extending the tool, but all with the goal of making aspects of machine learning visible."

Tetris AI is developed by JTS Early Career Researcher Prize 2024 winner Catherine Sibert.