DocumentCode
2399727
Title
Systems-Science-Based Knowledge Model and networked intelligent agent cognitive isomorphic instruction model
Author
Li, Yingchun
Author_Institution
Coll. of Inf. Technol., Beijing Normal Univ., Zhuhai, China
fYear
2011
fDate
8-10 June 2011
Firstpage
314
Lastpage
319
Abstract
Based on Systems-Science-Based Knowledge Model (SSBKM) this paper proposals the Network-based Artificial Intelligent Computer-Aided Instruction (NAICAI) that must manage to realize the following education characteristics and styles: to studying according to the each individualized pace and on one´s demand, to teach according to students aptitude, to study primary by oneself at the same time collaboratively. Based on this demand further proposed methods realizing NAICAI of fuzzy reasoning, intelligently estimating, isomorphism approaching and fitting, a web-based intelligent cognition- isomorphism teaching mode. With regard to this here is then presented a new formalized knowledge representation based on SSBKM; and in practice developed and proposed a based on-SSBKM but streamlined representation of extended intelligent semantic network for fuzzy reasoning and intellectually estimating of isomorphic degree of knowledge structures between teachers and students; provided the algorithms for the isomorphism approaching and fitting teaching mode.
Keywords
cognition; computer aided instruction; fuzzy reasoning; knowledge based systems; semantic networks; teaching; NAICAI; SSBKM; Web-based teaching; cognitive isomorphic instruction model; fuzzy reasoning; intellectually estimation; intelligent semantic network; knowledge representation; network based artificial intelligent computer-aided instruction; systems-science based knowledge model; Education; Fitting; Fuzzy reasoning; Intelligent agents; Semantics; Fuzzy reasoning; Intelligently estimating; Isomorphism approaching and fitting; NAICAI; SSBKM;
fLanguage
English
Publisher
ieee
Conference_Titel
System Science and Engineering (ICSSE), 2011 International Conference on
Conference_Location
Macao
Print_ISBN
978-1-61284-351-3
Electronic_ISBN
978-1-61284-472-5
Type
conf
DOI
10.1109/ICSSE.2011.5961920
Filename
5961920
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