By Etienne Wenger
Contributor note: ahead by means of John Seely Brown & James Greeno
Publish 12 months note: First released in 1987
Artificial Intelligence and Tutoring Systems, the 1st accomplished reference textual content during this dynamic quarter, surveys examine because the early Seventies and assesses the cutting-edge. Adopting the viewpoint of the communique of data, the writer addresses functional concerns fascinated by designing educational structures in addition to theoretical questions raised through investigating computational equipment of data communique.
Weaving jointly the targets, contributions, and interesting demanding situations of clever tutoring process improvement, this well timed e-book turns out to be useful as a textual content in classes on clever tutoring platforms or computer-aided guide, an advent for newbies to the sphere, or as a reference for researchers and practitioners.
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Additional info for Artificial Intelligence and Tutoring Systems: Computational and Cognitive Approaches to the Communication of Knowledge
For the output, they range from the mere display of prestored pieces of text typical of CAI to the use of fairly complex generic frames. Within these limits, flexibility varies according to the granularity of the pieces of knowledge with which individual pieces of text are associated. As a counterweight to technical difficulties, the restricted conceptual context in which the verbal communication takes place can facilitate the design of natural-language interfaces for practical instructional systems.
Fortunately, a perfectly accurate model of the student along all dimensions is not a sine qua non for reasonable pedagogical decisions, but even building a partial model that provides the required information is a challenge for computer-based systems. The student model: information The adaptability of an instructional system, obviously, is largely deter mined by the coverage and accuracy of the information contained in its student model. In fact, the idea of a student model is not new (Fletcher, 1975).
Goldstein and Papert (1977) explore the educational value of epistemological investigations inherent in artificial intelligence research. As a spokesman for the field's visions, Brown (1983a, 1983b, 1985) discusses many innovative concepts. Clancey's overview (1986b) is intended for a rather sophisticated audience: it provides an insightful reflection on the notion of "qualitative model" as an underlying theme for ITS. This page intentionally left blank Part II A panorama: people, ideas, and systems Now that we have briefly looked at some basic issues, we are ready to set out on a guided tour of specific research projects.
Artificial Intelligence and Tutoring Systems: Computational and Cognitive Approaches to the Communication of Knowledge by Etienne Wenger