Active Learning Games

This paper discusses active learning games as a potentially important pedagogical technique in support of formal classroom education. A brief review of the active learning literature is given, followed by a list of known active learning games relevant to the CDIO engineering education context. As a specific example of an active learning game we present the learning objectives, rules, and implementation of a “Genetic Algorithm Game” that is used to introduce this class of evolutionary optimization algorithms to graduate students. Genetic algorithms do not require mathematically advanced formulations. Nevertheless, many students are experiencing conceptual difficulties in understanding the abstract nature of genetic operators and how the algorithm is able to successfully search complex design spaces for good solutions. We have found that playing the “Genetic Algorithm Game” during class is an effective tool that helps students experience and reinforce the inner workings of genetic algorithms. This activity enhances conceptual learning and initial student feedback has been very positive. We believe that this example of an “in-class game” provides a template for similar active learning activities in other domains. Clearly, playing such games requires thought, preparation and time (typically between 10-30 minutes per game), as well as careful synchronization with the main lecture content. Faculty-student interactions are enhanced by assigning secondary materials for self-study and using the gained lecture time for active learning games that reinforce the primary materials and key concepts.