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An Agent based Personalized Intelligent e-learning

by Axita Shah, Sonal Jain
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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 20 - Number 3
Year of Publication: 2011
Authors: Axita Shah, Sonal Jain
10.5120/2411-3215

Axita Shah, Sonal Jain . An Agent based Personalized Intelligent e-learning. International Journal of Computer Applications. 20, 3 ( April 2011), 40-45. DOI=10.5120/2411-3215

@article{ 10.5120/2411-3215,
author = { Axita Shah, Sonal Jain },
title = { An Agent based Personalized Intelligent e-learning },
journal = { International Journal of Computer Applications },
issue_date = { April 2011 },
volume = { 20 },
number = { 3 },
month = { April },
year = { 2011 },
issn = { 0975-8887 },
pages = { 40-45 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume20/number3/2411-3215/ },
doi = { 10.5120/2411-3215 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T20:06:51.358492+05:30
%A Axita Shah
%A Sonal Jain
%T An Agent based Personalized Intelligent e-learning
%J International Journal of Computer Applications
%@ 0975-8887
%V 20
%N 3
%P 40-45
%D 2011
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Education is foundation of any modern society. Self Discovery is a key to an individual’s education success. Self Discovery learning is the ability of an individual to learn through personal experience and natural exploration. Online Discovery learning tends to be learner-driven and learner-initiated. Digital repository on web is supportive for online discovery learning. In recent era, availability of infrastructure, flexibility of time, learning resources and their means of sharing has increased adaptability of World Wide Web to learn and attain knowledge to a great extent. However, most of the e-learners find difficulty to select location specific, relevant and significant tutorial on the web. Search engines results pages are not based on the interest, knowledge level and literacy rate of learner. More amount of time spent on searching and filtering and comparatively less time is devoted in actual learning. This paper proposes an agent based personalized intelligent e-learning model. The essence of personalized search engine is to save learner’s time to re-rank future result list. This Model uses multiple agents which delivers personalized SERP (Search Engine Results Page) and is more suited for personalization of web pages based on learner’s query expanded to manifold queries with novel concept of keyword research and discover knowledge using browser’s behaviour. The proposed model uses web usage mining techniques to discover the knowledge of learner.

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Index Terms

Computer Science
Information Sciences

Keywords

Personalized Intelligent SERP (Search Engine Results Page)

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