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Enabling Effective Personalized Learning: Determinants for Knowledge based Web Information Retrieval Systems

by Y.d. Jayaweera, Md. Gapar Md. Johar, S.n. Perera
journal cover thumbnail

International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 116 - Number 2
Year of Publication: 2015
Authors: Y.d. Jayaweera, Md. Gapar Md. Johar, S.n. Perera
10.5120/20309-2352

Y.d. Jayaweera, Md. Gapar Md. Johar, S.n. Perera . Enabling Effective Personalized Learning: Determinants for Knowledge based Web Information Retrieval Systems. International Journal of Computer Applications. 116, 2 ( April 2015), 19-24. DOI=10.5120/20309-2352

@article{ 10.5120/20309-2352,
author = { Y.d. Jayaweera, Md. Gapar Md. Johar, S.n. Perera },
title = { Enabling Effective Personalized Learning: Determinants for Knowledge based Web Information Retrieval Systems },
journal = { International Journal of Computer Applications },
issue_date = { April 2015 },
volume = { 116 },
number = { 2 },
month = { April },
year = { 2015 },
issn = { 0975-8887 },
pages = { 19-24 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume116/number2/20309-2352/ },
doi = { 10.5120/20309-2352 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T22:55:58.975475+05:30
%A Y.d. Jayaweera
%A Md. Gapar Md. Johar
%A S.n. Perera
%T Enabling Effective Personalized Learning: Determinants for Knowledge based Web Information Retrieval Systems
%J International Journal of Computer Applications
%@ 0975-8887
%V 116
%N 2
%P 19-24
%D 2015
%I Foundation of Computer Science (FCS), NY, USA
Abstract

In the digitized World, information is entangled in a mesh of unstructured web. Finding and retrieving relevant web resources to suit the user's information requirement is a challenge. Moreover, understanding and adapting to cater to different user information requirements is also an uphill task. To achieve the desired outcome, it is needed to have user accepted technology. Therefore, web information retrieval systems, especially search engines, should be user centered. Technology Acceptance Model (TAM) provides a basis with which one traces how external variables influence belief, attitude, and intention to use. Two cognitive beliefs are posited by TAM; perceived usefulness and perceived ease of use. This empirical study explores the influence of Users and Environment characteristics on a modern web information retrieval system. This paper analyzes the variables to determine perceptions of usefulness, attitude and preferences leading towards frequent factors to influence typical TAM results.

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Index Terms

Computer Science
Information Sciences

Keywords

Information Retrieval Technology Acceptance Model (TAM) Learner Intention Environment Characteristics

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