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Towards a Semantically Driven E-learning Framework

by Suhare M. Solaiman, Imtiaz Hussain Khan, Muazzam Ahmed Siddiqui
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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 177 - Number 11
Year of Publication: 2019
Authors: Suhare M. Solaiman, Imtiaz Hussain Khan, Muazzam Ahmed Siddiqui
10.5120/ijca2019919510

Suhare M. Solaiman, Imtiaz Hussain Khan, Muazzam Ahmed Siddiqui . Towards a Semantically Driven E-learning Framework. International Journal of Computer Applications. 177, 11 ( Oct 2019), 22-28. DOI=10.5120/ijca2019919510

@article{ 10.5120/ijca2019919510,
author = { Suhare M. Solaiman, Imtiaz Hussain Khan, Muazzam Ahmed Siddiqui },
title = { Towards a Semantically Driven E-learning Framework },
journal = { International Journal of Computer Applications },
issue_date = { Oct 2019 },
volume = { 177 },
number = { 11 },
month = { Oct },
year = { 2019 },
issn = { 0975-8887 },
pages = { 22-28 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume177/number11/30942-2019919510/ },
doi = { 10.5120/ijca2019919510 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-07T00:45:35.787806+05:30
%A Suhare M. Solaiman
%A Imtiaz Hussain Khan
%A Muazzam Ahmed Siddiqui
%T Towards a Semantically Driven E-learning Framework
%J International Journal of Computer Applications
%@ 0975-8887
%V 177
%N 11
%P 22-28
%D 2019
%I Foundation of Computer Science (FCS), NY, USA
Abstract

E-learning offers great benefits over the conventional learning process. However, the huge unstructured information, which is freely available on the Web poses significant challenges in accessing the desired information in a timely manner. To tackle this problem different information retrieval (IR) approaches have been proposed in literature. These approaches are predominantly influenced by classical keyword-based IR techniques. However, with recent technological advances and a flood of information on the Web, the performance of keyword-based IR techniques has greatly suffered. Therefore, recently some more intelligent IR techniques have been proposed to enhance the utility of e-learning systems. In this study, a semantically oriented ontology-based personalized framework is proposed for effective e-learning. The proposed framework is implemented and its effectiveness is thoroughly assessed as a case study to learn Java programming language. The proposed system is evaluated on an indigenous medium-sized corpus ((2600 documents) in terms of standard accuracy measures for IR. The findings in this paper reveal that semantic based IR for e-learning is a robust methodology and it can advance the field of e-learning in an elegant manner.

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Index Terms

Computer Science
Information Sciences

Keywords

Information retrieval Semantic similarity Semantic annotation Keywords-based retrieval Ontology Query expansion

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