A Proposed Model for E-learning Adaptability Measurement During COVID-19 Pandemic Using Data Mining Techniques
Dublin Core
Title
A Proposed Model for E-learning Adaptability Measurement During COVID-19 Pandemic Using Data Mining Techniques
Subject
E-Learning, Computer Aided Learning, Data Mining, E-learning Adaptation Model, Web Based Learning
Description
E-learning became the main medium of education in the world for the past two years. COVID-19 virus has pushed all the universities and academic institutions to utilize and activate E-learning platforms and systems. The sudden and urgent transformation from the regular traditional learning system to E-learning system has involved many challenges and limitations. Therefore, the need to evaluate and enhance the current E-learning mechanism in Iraq became very urgent and critical need. The target level was students at higher education institutes which include university students in Basra city. The data collected based on students’ evaluation and opinions about E-learning based on their interaction and usage during two years under COVID-19 spread era. This research involved applying data mining techniques to sample dataset and utilizing the obtained results as feedback for a proposed model suggested by the authors to measure adaptability. The proposed model is derived from the idea of the Technology Acceptance Model (TAM) with focus on the positivity as the main factor to measure adaptability. The results of the research showed approximate adaptation level of 52% which is very close compared to the actual situation in real life which involve limitations and challenges faced by Iraqi students.
Creator
Mahmood, Ibrahim Nasir
Abuzaraida, Mustafa Ali
Source
International Journal of Interactive Mobile Technologies (iJIM); Vol. 17 No. 01 (2023); pp. 74-95
1865-7923
Publisher
International Association of Online Engineering (IAOE), Vienna, Austria
Date
2023-01-10
Rights
Copyright (c) 2022 Ibrahim Nasir Mahmood, Mustafa Ali Abuzaraida
https://creativecommons.org/licenses/by/4.0
Relation
Format
application/pdf
Language
eng
Type
info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
Peer-reviewed Article
Identifier
Citation
Ibrahim Mahmood Nasir and Mustafa Abuzaraida Ali, A Proposed Model for E-learning Adaptability Measurement During COVID-19 Pandemic Using Data Mining Techniques, International Association of Online Engineering (IAOE), Vienna, Austria, 2023, accessed November 23, 2024, https://igi.indrastra.com/items/show/2429