By Roger Nkambou, Riichiro Mizoguchi, Jacqueline Bourdeau
The notion for this publication on clever Tutoring structures (ITS) was once sparked through the luck of the ITS’08 foreign convention. The variety of shows and their caliber bore witness to the power and adulthood of the sector, and the keenness of the contributors held out a promise of sustainability and cutting edge study. lengthy existence to ITS examine! The ebook is split into 5 elements. The introductory chapters to those elements, which summarize foundations, advancements, strengths and weaknesses in all the parts 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 really is our wish that each one readers will locate the publication informative and thought-provoking.
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Extra resources for Advances in Intelligent Tutoring Systems
2 Semantic Networks An important feature of human memory is the high number of connections or associations between the pieces of information it contains. Semantic networks are one of the knowledge representation languages based on this capacity. The basic idea of a semantic network representation is very simple: There are two types of primitives: nodes and links or arcs.. Nodes, on the one hand, correspond to objects or classes of objects in the world Links or arcs, on the other hand, are unidirectional connections between nodes that correspond to relationships between these objects.
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).
The semantics of a language refers to the fact that the message unambiguously means what it is supposed to mean. For example, consider the language construct “A subconcept of B”: Does this mean that all instances of A are also instances of B, or parts of B, or special kinds of B? Clearly defined and wellunderstood semantics are essential for sound inference procedures. Whatever language is chosen, the expert module must guarantee mutual understanding between the actions of the system and those of the learner.