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Games, Motivation, and Integrating Intuitive and Formal Understanding

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Artificial Intelligence in Education (AIED 2013)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 7926))

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Abstract

A central goal of education involves helping students develop deep understandings of complex models at the heart of core learning goals. Interestingly, an analogous goal of commercial recreational digital games involves helping players develop deep understandings of the models at the heart of those games. Given that games can motivate players to engage voluntarily over extended periods of time in developing understandings of complex game models, one may ask whether and how one might foster similar engagement with educational concepts and models. Much fanfare has accompanied claims about games’ potential for engagement and motivation, but many of those claims have focused on a shallow idea of “fun”. This talk takes a deeper view of motivation and learning by considering motivation and games through the lens of research on motivation to learn in classrooms. The talk then considers how research from the learning sciences, psychology, and science education can expand this motivation framework to scaffold the integration of intuitive and formal understanding through games for learning. Discussion of these ideas is framed in terms of examples from commercial game design and from our ongoing research and development of games to support physics learning. This talk builds on a submitted paper [3].

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References

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Clark, D.B. (2013). Games, Motivation, and Integrating Intuitive and Formal Understanding. In: Lane, H.C., Yacef, K., Mostow, J., Pavlik, P. (eds) Artificial Intelligence in Education. AIED 2013. Lecture Notes in Computer Science(), vol 7926. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-39112-5_57

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  • DOI: https://doi.org/10.1007/978-3-642-39112-5_57

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-39111-8

  • Online ISBN: 978-3-642-39112-5

  • eBook Packages: Computer ScienceComputer Science (R0)

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