The University of Southampton
University of Southampton Institutional Repository

A model of e-learning uptake and continuance in Higher Educational Institutions

A model of e-learning uptake and continuance in Higher Educational Institutions
A model of e-learning uptake and continuance in Higher Educational Institutions
To predict and explain E-learning usage in higher educational institutes (HEIs) better, this research conceptualized E-learning usage as two steps, E-learning uptake and continuance. The aim was to build a model of effective uptake and continuance of E-learning in HEIs, or ‘EUCH’.

The EUCH model was constructed by applying five grounded theories: Unified Theory of Acceptance and Use of Technology (UTAUT); Keller’s ARCS model; Theory of Reasoned Action (TRA); Cognitive Dissonance Theory (CDT); and Adaptation Level Theory (ALT). The preliminarystudy was conducted with experts and end users (students) to confirm the factors of E learning uptake and continuance. With confirmation through triangulation from at least two source of data (literature, expert and end user review), all the proposed factors were indeed confirmed. A longitudinal study was conducted in a Thai university to: (a) assess the model’s performance for E learning uptake and continued use; (b) validate the relationships between the proposed EUCH model variables; and (c) investigate the consequence of E-learning usage on students’ learning performance. The results of the longitudinal study suggested that: (a) the EUCH model does as well in predicting the uptake and continued use of E-learning as the existing comparative models (TAM, UTAUT and ECM), the improvement however was found in its explanation; (b) students’ initial expectations influence their uptake of E-learning and the changes in their expectation during usage time period have an influence on their continued use; (c) no influence was found from E-learning usage on students’ learning performance.

Even though the effect of E-learning usage to a student’s learning performance are not confirmed by the empirical results of this study, it could be argued that E-learning usage is an initial condition for realizing the benefits of E-learning on students and HEI: if there is no use, there will be no benefit. Although its predictive power and precision of equation prediction on E-learning uptake and continuance was not found to be an improvement on comparative models on purely statistical grounds, the EUCH model, which bridges the existing gap between findings on uptake and continuance of E-learning, provides an improved understanding of the processes of E-learning usage and the prediction of E-learning usage at any given time within a single model.
Pinpathomrat, Nakarin
ffe73a16-c7fa-4545-9916-23ffdb0ec0e7
Pinpathomrat, Nakarin
ffe73a16-c7fa-4545-9916-23ffdb0ec0e7
Gilbert, Lester
a593729a-9941-4b0a-bb10-1be61673b741

Pinpathomrat, Nakarin (2015) A model of e-learning uptake and continuance in Higher Educational Institutions. University of Southampton, Physical Sciences and Engineering, Doctoral Thesis, 439pp.

Record type: Thesis (Doctoral)

Abstract

To predict and explain E-learning usage in higher educational institutes (HEIs) better, this research conceptualized E-learning usage as two steps, E-learning uptake and continuance. The aim was to build a model of effective uptake and continuance of E-learning in HEIs, or ‘EUCH’.

The EUCH model was constructed by applying five grounded theories: Unified Theory of Acceptance and Use of Technology (UTAUT); Keller’s ARCS model; Theory of Reasoned Action (TRA); Cognitive Dissonance Theory (CDT); and Adaptation Level Theory (ALT). The preliminarystudy was conducted with experts and end users (students) to confirm the factors of E learning uptake and continuance. With confirmation through triangulation from at least two source of data (literature, expert and end user review), all the proposed factors were indeed confirmed. A longitudinal study was conducted in a Thai university to: (a) assess the model’s performance for E learning uptake and continued use; (b) validate the relationships between the proposed EUCH model variables; and (c) investigate the consequence of E-learning usage on students’ learning performance. The results of the longitudinal study suggested that: (a) the EUCH model does as well in predicting the uptake and continued use of E-learning as the existing comparative models (TAM, UTAUT and ECM), the improvement however was found in its explanation; (b) students’ initial expectations influence their uptake of E-learning and the changes in their expectation during usage time period have an influence on their continued use; (c) no influence was found from E-learning usage on students’ learning performance.

Even though the effect of E-learning usage to a student’s learning performance are not confirmed by the empirical results of this study, it could be argued that E-learning usage is an initial condition for realizing the benefits of E-learning on students and HEI: if there is no use, there will be no benefit. Although its predictive power and precision of equation prediction on E-learning uptake and continuance was not found to be an improvement on comparative models on purely statistical grounds, the EUCH model, which bridges the existing gap between findings on uptake and continuance of E-learning, provides an improved understanding of the processes of E-learning usage and the prediction of E-learning usage at any given time within a single model.

PDF
__soton.ac.uk_ude_personalfiles_users_jo1d13_mydesktop_Pinpathomrat.pdf - Other
Download (5MB)

More information

Published date: April 2015
Organisations: University of Southampton, Electronics & Computer Science

Identifiers

Local EPrints ID: 381506
URI: https://eprints.soton.ac.uk/id/eprint/381506
PURE UUID: 8b200a04-e76b-4531-831b-b2392f7d1d5e

Catalogue record

Date deposited: 19 Oct 2015 10:37
Last modified: 17 Jul 2017 20:26

Export record

Contributors

Author: Nakarin Pinpathomrat
Thesis advisor: Lester Gilbert

University divisions

Download statistics

Downloads from ePrints over the past year. Other digital versions may also be available to download e.g. from the publisher's website.

View more statistics

Atom RSS 1.0 RSS 2.0

Contact ePrints Soton: eprints@soton.ac.uk

ePrints Soton supports OAI 2.0 with a base URL of https://eprints.soton.ac.uk/cgi/oai2

This repository has been built using EPrints software, developed at the University of Southampton, but available to everyone to use.

We use cookies to ensure that we give you the best experience on our website. If you continue without changing your settings, we will assume that you are happy to receive cookies on the University of Southampton website.

×