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A Framework to Synchronize Transfer of Knowledge in Web based Intelligent Tutoring System

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IJCA Proceedings on International Conference on Benchmarks in Engineering Science and Technology 2012
© 2012 by IJCA Journal
ICBEST - Number 4
Year of Publication: 2012
Authors:
Mahendra A. Pund
Amit Bajare

Mahendra A Pund and Amit Bajare. Article: A Framework to Synchronize Transfer of Knowledge in Web based Intelligent Tutoring System. IJCA Proceedings on International Conference on Benchmarks in Engineering Science and Technology 2012 ICBEST(4):15-19, October 2012. Full text available. BibTeX

@article{key:article,
	author = {Mahendra A. Pund and Amit Bajare},
	title = {Article: A Framework to Synchronize Transfer of Knowledge in Web based Intelligent Tutoring System},
	journal = {IJCA Proceedings on International Conference on Benchmarks in Engineering Science and Technology 2012},
	year = {2012},
	volume = {ICBEST},
	number = {4},
	pages = {15-19},
	month = {October},
	note = {Full text available}
}

Abstract

Nowadays the Internet constitutes Web based information which is fast and provides face-to-face interaction with the user. E-learning on Internet is rising as a powerful tool for the tutoring system like the feature of direct learning as the Learning Management System. (LMS). But question that arises is whether this will replace human teacher. So in this paper an attempt is made to enhance the Intelligent Tutoring System (ITS) by presenting a way to improve the knowledge transfer from the sources trough the agent like tutor to the destiny like student. As we have generic framework for ITS with the content management, which are a formal framework for Advance Distributed Learning (ADL). The main theme, we describe the framework of synchronization of learners view with the deliverable contents for effective knowledge transfer in ITS and the role of each module in the system. Further it is proposed to enhance the ADL, that the independence of the knowledge can be organized by dynamically loading the concerned knowledge of the respective course. Our intelligent system can help in learning system to transfer knowledge with fine tuned channel so as to student and tutor can navigate through the online course materials, recommend learning goals, and generate appropriate reading sequences.

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