By Etienne Wenger
Contributor note: ahead by means of John Seely Brown & James Greeno
Publish yr note: First released in 1987
Artificial Intelligence and Tutoring Systems, the 1st finished reference textual content during this dynamic sector, surveys study because the early Nineteen Seventies and assesses the cutting-edge. Adopting the viewpoint of the conversation of information, the writer addresses sensible matters fascinated with designing tutorial structures in addition to theoretical questions raised via investigating computational tools of information communique.
Weaving jointly the targets, contributions, and engaging demanding situations of clever tutoring process improvement, this well timed booklet comes in handy as a textual content in classes on clever tutoring platforms or computer-aided guideline, an creation for beginners to the sector, or as a reference for researchers and practitioners.
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Additional resources for Artificial Intelligence and Tutoring Systems: Computational and Cognitive Approaches to the Communication of Knowledge
Some systems monitor the student's activity very closely, adapting their actions to the student's responses but never relinquishing control. In mixedinitiative dialogues, the control is shared by the student and the system as they exchange questions and answers. The system must be able to respond to the student, but it can also ask questions whose answers help it understand what the student is trying to do, or what he knows. In guided-discovery learning or coached activities, the student is in full control of the activity, and the only way the system can direct the course of action is by modifying the environment.
However, all the circumstances in which decisions are necessary have to be anticipated, so that appropriate code can be written to capture these decisions. The strength of this traditional CAI approach resides in the paradigm's ability to take direct advantage of the pedagogical experience of human teachers and to reflect this expertise straightforwardly in the behavior of programs without an articulation of its underlying principles. Various directions of research efforts can be identified within the traditional CAI paradigm.
The order and manner in which topics are treated can produce very different learning experiences. In tutorial guidance, it is sometimes more effective to let the student search for a while than always to interrupt him. On the other hand, left completely to himself, the student will often get stuck or lost. Successful learning depends on a wide variety of factors, and the most informationally ac curate tutoring system is nonetheless defeated if it destroys the student's personal motivation or sense of discovery.
Artificial Intelligence and Tutoring Systems: Computational and Cognitive Approaches to the Communication of Knowledge by Etienne Wenger