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dc.contributor.authorPatel, Ashoken
dc.contributor.authorKinshuken
dc.date.accessioned2014-08-26T10:53:03Z
dc.date.available2014-08-26T10:53:03Z
dc.date.issued1996
dc.identifier.citationPatel A. and Kinshuk (1996) Applied Artificial Intelligence for Teaching Numeric Topics in Engineering Disciplines. Lecture Notes in Computer Science, 1108, pp. 132-140en
dc.identifier.isbn9783540614913
dc.identifier.issn0302-9743
dc.identifier.urihttp://hdl.handle.net/2086/10207
dc.description.abstractThis paper presents a model of Computer Integrated Learning Environments (CILE) as adopted by TLTP Byzantium and the role of an Intelligent Tutoring Tool (ITT) within this model. It reviews the implementation of artificial intelligence, discussing the methodology used in storing the knowledge rules and their application by the inference engine. An ITT is a fine grain tutoring tool that provides for learning as well as assessing the conceptual knowledge with the help of a student model, a remote expert model and a local expert model. The dominant consideration in the design of an ITT is to keep the feedback short and simple and to drop to a finer grain size, through a suitable interface, wherever necessary. Other aspects of the ITT design are also discussed and some of the main features and weaknesses are identified.en
dc.language.isoenen
dc.publisherSpringer Berlin Heidelbergen
dc.subjectArtificial Intelligenceen
dc.subjectComputer Integrated Learning Environmentsen
dc.subjectIntelligent Tutoring Toolsen
dc.subjectIntelligent Tutoring Systemsen
dc.titleApplied artificial intelligence for teaching numeric topics in engineering disciplinesen
dc.typeBook chapteren
dc.identifier.doihttps://doi.org/10.1007/BFb0022600
dc.peerreviewedYesen
dc.funderHigher Education Funding Councils of UK - TLTP Programmeen
dc.projectidTLTP Byzantiumen


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