Proposition for an Intelligent Image based Computer Aided Education (IICAE)
Identifieur interne : 00E195 ( Main/Exploration ); précédent : 00E194; suivant : 00E196Proposition for an Intelligent Image based Computer Aided Education (IICAE)
Auteurs : Odile Thiéry ; Amos David ; Marion CréhangeSource :
English descriptors
Abstract
Image search consists of one or more sessions. Then with this strategy,we started the study of how this process could be used in CAE. We have realized an "expert" tutorial scale model in ornithology whose direct application is planed for natural science classes at a college in Nancy (France). The knowledge in ornithology was built with the help of a natural science teacher in the school where we intend to use the system. In this extended abstract, after having defined rapidly the four "supporting poles" for the elaboration of an IICAE system, we explain in paragraph III the knowledge that we have modelized in the form of semantic network applicable to various domains\, ; then in the following paragraph we give the architecture of an IICAE system applicable in all types of formation depending highly on the learner's model. We terminate with the presentation of the scale model that we have built using the C language nnand an inference engine called OPS5 on a micro-computer PC-AT and a videodisc VP831. We conclude with the future developments of our work.
Affiliations:
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Le document en format XML
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<front><div type="abstract" xml:lang="en" wicri:score="3336">Image search consists of one or more sessions. Then with this strategy,we started the study of how this process could be used in CAE. We have realized an "expert" tutorial scale model in ornithology whose direct application is planed for natural science classes at a college in Nancy (France). The knowledge in ornithology was built with the help of a natural science teacher in the school where we intend to use the system. In this extended abstract, after having defined rapidly the four "supporting poles" for the elaboration of an IICAE system, we explain in paragraph III the knowledge that we have modelized in the form of semantic network applicable to various domains\, ; then in the following paragraph we give the architecture of an IICAE system applicable in all types of formation depending highly on the learner's model. We terminate with the presentation of the scale model that we have built using the C language nnand an inference engine called OPS5 on a micro-computer PC-AT and a videodisc VP831. We conclude with the future developments of our work.</div>
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