Predicting actual use of mobile technology in learning: towards e-learning culture framework

With the advent of communication technology evolution, learning becomes flexible and accessible at any time and anywhere. Educational technology researchers have extensively integrated the Theory of Acceptance Model (TAM) and Theory of Planned Behavior to link the beliefs and actions in mobile learn...

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Main Authors:	Syed Hassan, Sharifah Sariah, Landani, Zahra Mardani
Format:	Article
Language:	English
Published:	Science Publishing Corporation Inc 2018
Subjects:	H Social Sciences (General) HA154 Statistical data T Technology (General)
Online Access:	http://irep.iium.edu.my/64301/ http://irep.iium.edu.my/64301/ http://irep.iium.edu.my/64301/ http://irep.iium.edu.my/64301/1/64301_Predicting%20Actual%20Use%20of%20Mobile%20Technology.pdf

id	iium-64301
recordtype	eprints
spelling	iium-643012019-07-12T01:58:38Z http://irep.iium.edu.my/64301/ Predicting actual use of mobile technology in learning: towards e-learning culture framework Syed Hassan, Sharifah Sariah Landani, Zahra Mardani H Social Sciences (General) HA154 Statistical data T Technology (General) With the advent of communication technology evolution, learning becomes flexible and accessible at any time and anywhere. Educational technology researchers have extensively integrated the Theory of Acceptance Model (TAM) and Theory of Planned Behavior to link the beliefs and actions in mobile learning. This study attempted to predict a hypothesized model of mobile learning culture via smart phone. In this present study, the m-learning culture is conceptualized from the factors of attitude, ethical use, technology competent; technology reliance and social well being. Social well being from the perspectives of The Adaptive Structuration has been integrated to underpin the study. 185 samples were drawn from the population of Korea University. Using self constructed questionnaire for the survey, the analyses involved descriptive and simultaneous Multiple Regression Analysis (MRA). The study was supported by qualitative design via interviews. The findings indicate all predictors are significant except for technology reliance and ethical use. Social well being is the highest predictor for the m-learning via smartphone. This study has been explored from both quantitative and qualitative research which provide important empirical information to support m-learning culture and its predictors. The findings have contributed to a model of m-learning which extends the literature and existing models of TAM and Theory of Planned Behavior Science Publishing Corporation Inc 2018-05-22 Article PeerReviewed application/pdf en http://irep.iium.edu.my/64301/1/64301_Predicting%20Actual%20Use%20of%20Mobile%20Technology.pdf Syed Hassan, Sharifah Sariah and Landani, Zahra Mardani (2018) Predicting actual use of mobile technology in learning: towards e-learning culture framework. International Journal of Engineering & Technology, 7 (2.29). pp. 614-619. ISSN 2227-524X https://www.sciencepubco.com/index.php/ijet/article/view/13985/5623 10.14419/ijet.v7i2.29.13985
repository_type	Digital Repository
institution_category	Local University
institution	International Islamic University Malaysia
building	IIUM Repository
collection	Online Access
language	English
topic	H Social Sciences (General) HA154 Statistical data T Technology (General)
spellingShingle	H Social Sciences (General) HA154 Statistical data T Technology (General) Syed Hassan, Sharifah Sariah Landani, Zahra Mardani Predicting actual use of mobile technology in learning: towards e-learning culture framework
description	With the advent of communication technology evolution, learning becomes flexible and accessible at any time and anywhere. Educational technology researchers have extensively integrated the Theory of Acceptance Model (TAM) and Theory of Planned Behavior to link the beliefs and actions in mobile learning. This study attempted to predict a hypothesized model of mobile learning culture via smart phone. In this present study, the m-learning culture is conceptualized from the factors of attitude, ethical use, technology competent; technology reliance and social well being. Social well being from the perspectives of The Adaptive Structuration has been integrated to underpin the study. 185 samples were drawn from the population of Korea University. Using self constructed questionnaire for the survey, the analyses involved descriptive and simultaneous Multiple Regression Analysis (MRA). The study was supported by qualitative design via interviews. The findings indicate all predictors are significant except for technology reliance and ethical use. Social well being is the highest predictor for the m-learning via smartphone. This study has been explored from both quantitative and qualitative research which provide important empirical information to support m-learning culture and its predictors. The findings have contributed to a model of m-learning which extends the literature and existing models of TAM and Theory of Planned Behavior
format	Article
author	Syed Hassan, Sharifah Sariah Landani, Zahra Mardani
author_facet	Syed Hassan, Sharifah Sariah Landani, Zahra Mardani
author_sort	Syed Hassan, Sharifah Sariah
title	Predicting actual use of mobile technology in learning: towards e-learning culture framework
title_short	Predicting actual use of mobile technology in learning: towards e-learning culture framework
title_full	Predicting actual use of mobile technology in learning: towards e-learning culture framework
title_fullStr	Predicting actual use of mobile technology in learning: towards e-learning culture framework
title_full_unstemmed	Predicting actual use of mobile technology in learning: towards e-learning culture framework
title_sort	predicting actual use of mobile technology in learning: towards e-learning culture framework
publisher	Science Publishing Corporation Inc
publishDate	2018
url	http://irep.iium.edu.my/64301/ http://irep.iium.edu.my/64301/ http://irep.iium.edu.my/64301/ http://irep.iium.edu.my/64301/1/64301_Predicting%20Actual%20Use%20of%20Mobile%20Technology.pdf
first_indexed	2023-09-18T21:31:15Z
last_indexed	2023-09-18T21:31:15Z
_version_	1777412525574324224

Predicting actual use of mobile technology in learning: towards e-learning culture framework

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