By Etienne Wenger
Contributor note: ahead by way of John Seely Brown & James Greeno
Publish yr note: First released in 1987
Artificial Intelligence and Tutoring Systems, the 1st entire reference textual content during this dynamic sector, surveys learn because the early Seventies and assesses the state-of-the-art. Adopting the point of view of the communique of data, the writer addresses functional concerns taken with designing tutorial platforms in addition to theoretical questions raised via investigating computational equipment of data conversation.
Weaving jointly the targets, contributions, and interesting demanding situations of clever tutoring approach improvement, this well timed ebook turns out to be useful as a textual content in classes on clever tutoring structures or computer-aided guide, an creation for novices to the sphere, or as a reference for researchers and practitioners.
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This textbook provides case-based reasoning in a scientific strategy with pursuits: to provide rigorous and officially legitimate constructions for targeted reasoning, and to illustrate the variety of ideas, tools, and instruments on hand for plenty of purposes. within the chapters partially I the authors current the elemental parts of CBR with no assuming past reader wisdom; half II explains the middle equipment, in particular case representations, similarity issues, retrieval, version, evaluate, revisions, studying, development, and upkeep; half III bargains complex perspectives of those subject matters, also masking uncertainty and chances; and half IV exhibits the variety of data resources, with chapters on textual CBR, images, sensor facts and speech, conversational CBR, and information administration. The e-book concludes with appendices that provide brief descriptions of the fundamental formal definitions and strategies, and comparisons between CBR and different techniques.
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Additional info for Artificial Intelligence and Tutoring Systems: Computational and Cognitive Approaches to the Communication of Knowledge
For instance, decisions at the level of the interface can take on a pedagogical significance, and evaluations of the student's answers can be shared between the expert and the diagnostic module. Furthermore, these various tasks need not correspond to distinct modules in an actual system. Nevertheless, such distinctions reflect a useful level of abstraction, and these four components of knowledge communication systems constitute a traditional division of labor in the field. 1 summarizes some of the issues we have mentioned in connection with each component.
The most successful projects described in this book have required years of work by talented people, and have often gone through several generations of prototype systems involving major reconsidera tions of approach. Few of these systems have left the laboratory. These comments are not pessimistic. Teaching is difficult, and the fact that de signing intelligent tutoring systems requires such a deep understanding of the processes involved may well be a sign that we have found a method ology whereby we can start attacking general issues in a systematic way.
The design of graphic interfaces presents delicate problems of its own. In addition to the fact that such design is a laborious process, the use of graphic displays for communication purposes requires much sensitivity to a variety of human factors, and to the view of the domain that the displays present. The knowledge required for the translation function of the interface has been represented explicitly in instructional systems for some time, for instance in the form of parsing mechanisms. However, the idea of actively using knowledge about the expressiveness of the interface in the communication process is only now surfacing as the intelligent management of the screen and other media comes to be understood as a communication skill.