Artificial intelligence and education: Difference between revisions
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== Definition == | == Definition == | ||
'''Artificial intelligence and education''' refers to a research community that is interested in intersection of artificial intelligence research, learning and education. | |||
Typical sub-fields of study are [[intelligent tutoring system]]s, [[intelligent learning environment]]s, [[adapative hypertext]] systems. | Typical sub-fields of study are [[intelligent tutoring system]]s, [[intelligent learning environment]]s, [[adapative hypertext]] systems. | ||
== History == | |||
: Different motivations led scientists to apply artificial intelligence (AI) techniques to educational software and training software. On one hand, courseware developers were seeking for more powerful techniques for building systems. On the other hand, researchers in computer science and in cognitive psychology found an opportunity to develop and test new techniques or new theoretical models. This second line has probably been the most influential during the eighties. It led to major scientific contributions. For instance, designers transformed the [[expert system]] design to develop systems which fulfil the educational functions (explanation, diagnosis, ...) expected in a training software. This work contributed to the elicitation of strategic levels in expertise (Clancey, 1987) and, later, to the emergence of second generation expert systems (Steels, 1990). In others words, research on educational applications helped to develop the methodology for analyzing expertise (knowledge engineering). Similar contributions have been produced in cognitive psychology. The work on learner modelling (trying to infer what the learner knows or misunderstands) has been central to the formalisation and evaluation of cognitive models (Anderson et al, 1989). | |||
Revision as of 17:50, 29 March 2006
Definition
Artificial intelligence and education refers to a research community that is interested in intersection of artificial intelligence research, learning and education.
Typical sub-fields of study are intelligent tutoring systems, intelligent learning environments, adapative hypertext systems.
History
- Different motivations led scientists to apply artificial intelligence (AI) techniques to educational software and training software. On one hand, courseware developers were seeking for more powerful techniques for building systems. On the other hand, researchers in computer science and in cognitive psychology found an opportunity to develop and test new techniques or new theoretical models. This second line has probably been the most influential during the eighties. It led to major scientific contributions. For instance, designers transformed the expert system design to develop systems which fulfil the educational functions (explanation, diagnosis, ...) expected in a training software. This work contributed to the elicitation of strategic levels in expertise (Clancey, 1987) and, later, to the emergence of second generation expert systems (Steels, 1990). In others words, research on educational applications helped to develop the methodology for analyzing expertise (knowledge engineering). Similar contributions have been produced in cognitive psychology. The work on learner modelling (trying to infer what the learner knows or misunderstands) has been central to the formalisation and evaluation of cognitive models (Anderson et al, 1989).