Stochastic Learning Paths*

Jean-Claude Falmagne () and Jean-Paul Doignon ()
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Jean-Claude Falmagne: University of California, Irvine, Department of Cognitive Sciences, Institute of Mathematical Behavioral Sciences
Jean-Paul Doignon: Université Libre de Bruxelles, Département de Mathématique

Chapter 12 in Learning Spaces, 2011, pp 215-240 from Springer

Abstract: Abstract The stochastic theory presented in this chapter is more ambitious than those examined in Chapter 11. The description of the learning process is more complete and takes place in real time, rather than in a sequence of discrete trials. This theory also contains a provision for individual differences. Nevertheless, its basic intuition is similar, in that any student progresses through some learning path. As time passes, the student successively masters the items encountered along the learning path. The exposition of the theory given here follows closely Falmagne (1993, 1996). As before, we shall illustrate the concepts of the theory in the framework of an example. We star the title of this chapter because its concepts and results are not used elsewhere in this book.

Keywords: Learning Rate; Knowledge Structure; Knowledge State; Learning Function; Exponential Random Variable (search for similar items in EconPapers)
Date: 2011
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Persistent link: https://EconPapers.repec.org/RePEc:spr:sprchp:978-3-642-01039-2_12

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DOI: 10.1007/978-3-642-01039-2_12

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