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

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International Journal of Computer Applications
© 2015 by IJCA Journal
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 and S n Perera. Article: Enabling Effective Personalized Learning: Determinants for Knowledge based Web Information Retrieval Systems. International Journal of Computer Applications 116(2):19-24, April 2015. Full text available. BibTeX

@article{key:article,
	author = {Y.d. Jayaweera and Md. Gapar Md. Johar and S.n. Perera},
	title = {Article: Enabling Effective Personalized Learning: Determinants for Knowledge based Web Information Retrieval Systems},
	journal = {International Journal of Computer Applications},
	year = {2015},
	volume = {116},
	number = {2},
	pages = {19-24},
	month = {April},
	note = {Full text available}
}

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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