Research on Knowledge-Based Intelligent Tutoring System
Aiming at students’ learning process, and based on the analysis of tutorship rules of students’ learning after class, a Knowledge-Based Intelligent Tutoring System is given. The system comprehensively uses agent technology, the knowledge-based automatic reasoning, resource modeling for knowledge cla...
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| Published in | Applied Mechanics and Materials Vol. 55-57; pp. 1424 - 1429 |
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| Main Authors | , , , |
| Format | Journal Article |
| Language | English |
| Published |
Zurich
Trans Tech Publications Ltd
03.05.2011
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| Subjects | |
| Online Access | Get full text |
| ISBN | 9783037850992 303785099X |
| ISSN | 1660-9336 1662-7482 1662-7482 |
| DOI | 10.4028/www.scientific.net/AMM.55-57.1424 |
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| Abstract | Aiming at students’ learning process, and based on the analysis of tutorship rules of students’ learning after class, a Knowledge-Based Intelligent Tutoring System is given. The system comprehensively uses agent technology, the knowledge-based automatic reasoning, resource modeling for knowledge classification, field natural language understanding, data mining, computer networks, databases and other technologies. It creates a student-oriented self-motivated learning environment in which students can learn abundant knowledge of one or many subjects, send the problems encountered in their own learning to the system server by network, and get real-time multiple tutorship information as an excellent teacher do. |
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| AbstractList | Aiming at students' learning process, and based on the analysis of tutorship rules of students' learning after class, a Knowledge-Based Intelligent Tutoring System is given. The system comprehensively uses agent technology, the knowledge-based automatic reasoning, resource modeling for knowledge classification, field natural language understanding, data mining, computer networks, databases and other technologies. It creates a student-oriented self-motivated learning environment in which students can learn abundant knowledge of one or many subjects, send the problems encountered in their own learning to the system server by network, and get real-time multiple tutorship information as an excellent teacher do. |
| Author | Zhao, Ke Li, Ya Tao Yi, Zhen Zhen Xu, Wei |
| Author_xml | – givenname: Wei surname: Xu fullname: Xu, Wei email: xd_xuwei@tom.com organization: Xidian University : School of Electromechanical Engineering – givenname: Zhen Zhen surname: Yi fullname: Yi, Zhen Zhen email: yizzhen@yahoo.com.cn organization: Xidian University : School of Electromechanical Engineering – givenname: Ke surname: Zhao fullname: Zhao, Ke email: kzhao@xidian.edu.cn organization: Xidian University : School of Electromechanical Engineering – givenname: Ya Tao surname: Li fullname: Li, Ya Tao email: leeyetee@126.com organization: Xidian University : School of Electromechanical Engineering |
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| Cites_doi | 10.1109/etcs.2009.113 |
| ContentType | Journal Article |
| Copyright | 2011 Trans Tech Publications Ltd Copyright Trans Tech Publications Ltd. May 2011 |
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| DOI | 10.4028/www.scientific.net/AMM.55-57.1424 |
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| Keywords | Automatic Question Resource Model Knowledge Granularity Knowledge Base Agent Technology Automatic Reasoning Individual Tutoring Automatic Answer |
| Language | English |
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| Notes | Selected, peer reviewed paper from 2011 International Conference on Recent Trends in Materials and Mechanical Engineering (ICRTMME 2011), 27-28 January, 2011, China, Shenzhen ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 14 |
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| Title | Research on Knowledge-Based Intelligent Tutoring System |
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