By Roger Nkambou, Riichiro Mizoguchi, Jacqueline Bourdeau
The proposal for this e-book on clever Tutoring structures (ITS) was once sparked by means of the good fortune of the ITS’08 foreign convention. The variety of displays and their caliber bore witness to the power and adulthood of the sector, and the keenness of the individuals held out a promise of sustainability and leading edge examine. lengthy existence to ITS study! The ebook is split into 5 elements. The introductory chapters to those components, which summarize foundations, advancements, strengths and weaknesses in all of the components coated, are addressed to all readers. should you wish extra in-depth wisdom, we provide the ground to researchers who current their paintings, their effects, and their view of what the longer term holds. it truly is our desire that each one readers will locate the ebook informative and thought-provoking.
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Extra info for Advances in Intelligent Tutoring Systems
Nkambou et al. ): Advances in Intelligent Tutoring Systems, SCI 308, pp. 15–32. com © Springer-Verlag Berlin Heidelberg 2010 16 R. Nkambou to consider not only the nature and value of the domain knowledge, but also the formalisms used to represent and apply it. Many solutions have been put forward in an attempt to provide an explicit representation of domain expertise. The solutions presented have been drawn from fields such as philosophy, psychology, AI and education sciences. Philosophy, psychology and education sciences tend to focus on knowledge from an epistemological perspective which is essential for its treatment (Piaget 1997; Gagné 1985; Winograd and Flores 1986; Merrill and Twitchell 1994), whereas AI and cognitive sciences provide solutions that facilitate the expression and computational implementation of knowledge (Anderson 1996; Collins and Quillian 1969; Minsky 1975; Sowa 1984).
Semantic networks, which correspond to human memory, are cognitively plausible at the structural (representation) level, but not for their reasoning mechanism. In 1969, Collins & Quillian conducted a series of studies to test the psychological plausibility of semantic networks as models for both the organization of memory and human inferencing. The domain knowledge of SCHOLAR (Carbonell 1970) is that of South America geography. This domain knowledge model is represented using a semantic network whose nodes instantiate geographical objects and concepts.
First, we present the epistemological perspective by addressing its importance in the domain knowledge modeling process for the purposes of learning. Next, we explore various languages that are available to represent knowledge and are frequently used to develop domain models for ITSs. We focus on the expressiveness, inferential power and cognitive plausibility of these formalisms and provide examples of the ITSs in which they have been used. We also present two examples of languages which have a strong pedagogical emphasis.