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Decision-Making in Cognitive Tutoring Systems

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Advances in Intelligent Tutoring Systems

Part of the book series: Studies in Computational Intelligence ((SCI,volume 308))

Abstract

Human teachers have capabilities that are still not completely uncovered and reproduced into artificial tutoring systems. Researchers have nevertheless developed many ingenious decision mechanisms which obtain valuable results. Some inroads into natural artificial intelligence have even been made, then abandoned for tutoring systems because of the complexity involved and the computational cost. These efforts toward naturalistic systems are noteworthy and still in general use. In this chapter, we describe how some of this AI is put to work in artificial tutoring systems to reach decisions on when and how to intervene. We then take a particular interest in pursuing the path of “natural” AI for tutoring systems, using human cognition as a model for artificial general intelligence. One tutoring agent built over a cognitive architecture, CTS, illustrates this direction. The chapter concludes on a brief look into what might be the future for artificial tutoring systems, biologically-inspired cognitive architectures.

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Dubois, D., Nkambou, R., Quintal, JF., Savard, F. (2010). Decision-Making in Cognitive Tutoring Systems. In: Nkambou, R., Bourdeau, J., Mizoguchi, R. (eds) Advances in Intelligent Tutoring Systems. Studies in Computational Intelligence, vol 308. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-14363-2_8

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