Abstract
Serious games are an attempt to leverage the inherent motivation in game-like scenarios for an educational application and to transpose the learning goals into real-world applications. Unfortunately, serious games are also very costly to develop and deploy. For very abstract domains like mathematics, already the representation of the knowledge involved becomes a problem.
We propose the
that uses OMDoc/Mmt theory graphs to represent and track the underlying knowledge in serious games. In this paper we report on an implementation and experiment that tests the method. We obtain a simple serious game by representing a “word problem” in OMDoc/Mmt and connecting the Mmt API with a state-of-the-art game engine.
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Notes
- 1.
The name “scroll” is meant to evoke the fact that the knowledge contained in it is a valuable commodity in the game.
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Kohlhase, M. et al. (2020). FrameIT: Detangling Knowledge Management from Game Design in Serious Games. In: Benzmüller, C., Miller, B. (eds) Intelligent Computer Mathematics. CICM 2020. Lecture Notes in Computer Science(), vol 12236. Springer, Cham. https://doi.org/10.1007/978-3-030-53518-6_11
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