Empirical Analysis on Factors Impacting Mobile Learning Acceptance in Higher Engineering ...

198 Pages·2016·5.36 MB·English

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Doctoral Dissertations Graduate School
5-2014
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Yu Huang
University of Tennessee - Knoxville, [email protected]
Follow this and additional works at: https://trace.tennessee.edu/utk_graddiss
Part of the Engineering Education Commons, and the Industrial Engineering Commons
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Huang, Yu, "Empirical Analysis on Factors Impacting Mobile Learning Acceptance in Higher Engineering
Education. " PhD diss., University of Tennessee, 2014.
https://trace.tennessee.edu/utk_graddiss/2751
This Dissertation is brought to you for free and open access by the Graduate School at TRACE: Tennessee
Research and Creative Exchange. It has been accepted for inclusion in Doctoral Dissertations by an authorized
administrator of TRACE: Tennessee Research and Creative Exchange. For more information, please contact
[email protected].
To the Graduate Council:
I am submitting herewith a dissertation written by Yu Huang entitled "Empirical Analysis on
Factors Impacting Mobile Learning Acceptance in Higher Engineering Education." I have
examined the final electronic copy of this dissertation for form and content and recommend
that it be accepted in partial fulfillment of the requirements for the degree of Doctor of
Philosophy, with a major in Industrial Engineering.
Xueping Li, Major Professor
We have read this dissertation and recommend its acceptance:
Mehmet Aydeniz, Tami Wyatt, James Ostrowski, Rapinder Sawhney
Accepted for the Council:
Carolyn R. Hodges
Vice Provost and Dean of the Graduate School
(Original signatures are on file with official student records.)
University of Tennessee, Knoxville
Trace: Tennessee Research and Creative
Exchange
Doctoral Dissertations Graduate School
5-2014
Empirical Analysis on Factors Impacting Mobile
Learning Acceptance in Higher Engineering
Education
Yu Huang
[email protected]
This Dissertation is brought to you for free and open access by the Graduate School at Trace: Tennessee Research and Creative Exchange. It has been
accepted for inclusion in Doctoral Dissertations by an authorized administrator of Trace: Tennessee Research and Creative Exchange. For more
information, please [email protected].
To the Graduate Council:
I am submitting herewith a dissertation written by Yu Huang entitled "Empirical Analysis on Factors
Impacting Mobile Learning Acceptance in Higher Engineering Education." I have examined the final
electronic copy of this dissertation for form and content and recommend that it be accepted in partial
fulfillment of the requirements for the degree of Doctor of Philosophy, with a major in Industrial
Engineering.
Xueping Li, Major Professor
We have read this dissertation and recommend its acceptance:
Mehmet Aydeniz, Tami Wyatt, James Ostrowski, Rapinder Sawhney
Accepted for the Council:
Carolyn R. Hodges
Vice Provost and Dean of the Graduate School
(Original signatures are on file with official student records.)
Empirical Analysis on Factors
Impacting Mobile Learning
Acceptance in Higher Engineering
Education
A Dissertation
Presented for the
Doctor of Philosophy
Degree
The University of Tennessee, Knoxville
Yu Huang
May 2014
(cid:13)c by Yu Huang, 2014
All Rights Reserved.
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Acknowledgements
First and foremost, I dedicate this dissertation to my mother and father for their love,
encouragement, patience, and unconditional support.
My sincerest appreciation and gratitude go to my research advisor Dr. Xueping Li and
committee member Dr. Mehmet Aydeniz. Especially, I would like to thank Dr. Xuping Li
for his patience, guidance and mentoring not only during this research project but my entire
doctorate education. His advice, encouragement, and knowledge have been invaluable. I also
would like to thank Dr. Mehmet Aydeniz for his advice and suggestions on implementation
of this research project. Completion of this project would not be possible without their
support.
Furthermore, myappreciationandgratitudegotomyotherresearchcommitteemembers:
Dr. Tami Wyatt, Dr. James Ostrowski, and Dr. Rapinder Sawhney. Their advice
throughout this research process was invaluable.
I would like to thank University of Tennessee for facilitation in the administration of the
research instrument.
Special thanks and dedication go to my extended family: my grandmother, my uncle
and aunt, and my cousin. Thank you all for your caring and support in my achievement no
matter how great or small. My family’s love has been my guiding light and the main driving
force for the accomplishment of this dream.
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Abstract
Owing to technological advancements and decreasing costs of mobile devices and services,
there is a significant change in learning environment that demands for mobility. Such
change has enabled a new way of learning, that is, mobile learning. The emergence and
prevalenceofmobilelearninghelpsflexibilityindeliveringeducation,meetinglearners’needs,
and supporting learning activities without confining to physical locations or time. Mobile
learning indicates a new opportunity for education system research and development. The
acceptance of mobile learning by students is critical to the successful implementation of
mobile learning systems. Therefore, it is important to understand the factors that affect
students’ perceptions of mobile learning. Encouraged by this new trend in learning, this
research employs both quantitative and qualitative research methodologies to explore the
factors that affect students’ intention to use mobile devices for learning.
Based on the Unified Theory of Acceptance and Use of Technology (UTAUT), this
research formulates the factors, including performance expectancy, effort expectancy,
social influence, facilitating conditions, self-efficacy, ubiquity, self-management of learning,
attainment value, service quality, and perceived enjoyment, and testable hypotheses that are
critical to answer research questions and fulfill research objectives. In order to quantify these
factors and test research hypotheses, a data collection instrument adapted from previous
studies is developed and administered. The results indicate that performance expectancy,
perceived enjoyment, ubiquity, service quality, attainment value, and self-management of
learning are significant predictors of behavioral intention to use mobile learning; facilitating
conditions, social influence, effort-expectancy, and self-efficacy are found to be insignificant.
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Additionally, thisresearchexaminesthedifferencesonintentiontousemobilelearningacross
studentgroupsofage,gender,collegelevel,yearsofusingmobiledevices,currentandplanned
of mobile device ownership, and prior mobile learning experience via comparison analysis.
This research provides university administrators and educators the understandings on the
factors that influence student acceptance of mobile learning and the capability to build
strategies and policies that incorporate these factors into planning and design phases of
mobile learning system implementations.
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Table of Contents
1 Introduction 1
1.1 Research Motivation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3
1.2 Problem Statement . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5
1.3 Research Questions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6
1.4 Research Purpose . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6
1.5 Organization of the Study . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7
2 Literature Review 8
2.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8
2.2 Mobile Learning: M-Learning . . . . . . . . . . . . . . . . . . . . . . . . . . 9
2.3 Mobile Learning Application in Education . . . . . . . . . . . . . . . . . . . 10
2.3.1 Collaborative Learning . . . . . . . . . . . . . . . . . . . . . . . . . . 10
2.3.2 Situated Learning . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 12
2.3.3 Scaffolding . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 13
2.3.4 Modeling and Argumentation . . . . . . . . . . . . . . . . . . . . . . 15
2.4 Mobile Learning Affordances . . . . . . . . . . . . . . . . . . . . . . . . . . . 17
2.5 Mobile Learning Constraints . . . . . . . . . . . . . . . . . . . . . . . . . . . 20
2.6 Summary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 21
3 Methodology 22
3.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 22
3.2 Unified Theory of Acceptance and Use of Technology (UTAUT) . . . . . . . 22
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