«Title: Enhanced technology acceptance model to explain and predict learners' behavioural intentions in learning management systems Name: Abdullah ...»
Title: Enhanced technology acceptance model to explain and predict
learners' behavioural intentions in learning management systems
Name: Abdullah Al-Aulamie
This is a digitised version of a dissertation submitted to the University of
It is available to view only.
This item is subject to copyright.
Enhanced Technology Acceptance Model to Explain and Predict
Learners' Behavioural Intentions in Learning Management Systems
UNIVERSITY OF BEDFORDSHIREEnhanced Technology Acceptance Model to Explain and Predict Learners' Behavioural Intentions in Learning Management Systems by
The developed model variables identification focuses on two motivation aspects, extrinsic and intrinsic. The developed model consisted of ten variables in total, which can be categorised into three groups. First, the extrinsic variables consisting of information quality, functionality, accessibility, and user interface design. Second, the intrinsic variables are consisting of computer playfulness, enjoyment, and learning goal orientation. Third, the TAM variables consisting of perceived usefulness, perceived ease of use and behavioural intention. Moreover, to validate and examine the developed model, a questionnaire tool was developed for data collection.
Furthermore, the data was collected from electronically from three universities over six weeks.
The research findings supported the developed model. Additionally, the identified variables were good critical in predicting and explaining students' acceptance of LMSs.
The research applied structural equation modelling for statistical analysis using IBM AMOS. The research results confirmed the applicability of the developed model to explain the Saudi students' acceptance of LMSs. The developed model explained high variance among the dependent variables outperforming the excising models. The research improved the explanatory power of the TAM model through the identified variables. Furthermore, the research results showed that the extrinsic variables were stronger predictors of students' perceived usefulness, perceived ease of use and behavioural intention. In addition, the results showed that males and females perception towards the LMS was significantly different. The male students' acceptance towards LMSs was higher than females. Moreover, enjoyment was the stronger determinant of females' behavioural intention.
Dedication To my parents, my wife and to my lovely daughter (Danah) for their love, support and encouragement.
Acknowledgement My sincere apperception goes to my director of studies Dr Ali Mansour who have supported, guided and encouraged me throughout all this time. I would like also to thank my former supervisory team members, Dr Osei Adjei and Dr Herbert Daly.
I would like also to express my gratitude to King Faisal University and the Saudi Cultural Bureau in London for their academic and financial support during the period of my study.
I am also delighted to acknowledge all the help and support that I have received from the staff at University of Bedfordshire, friends, and colleagues.
List of Publications Al-Aulamie, A., Mansour, A., Daly, H. and Adjei, O., 2012. The effect of intrinsic motivation on learners' behavioural intention to use e-learning systems. In 2012 International Conference on Information Technology Based Higher Education and Training (ITHET). Istanbul, Turkey 21-23 June 2012, 1-4. Washington: IEEE Computer Society.
Al-Aulamie, A., Mansour, A. and Daly, H., 2013. INVESTIGATING THE DIRECT EFFECT OF INTRINSIC MOTIVATION ON LEARNERS’ BEHAVIOURAL INTENTION. In Proceedings of International Conference Information Systems 2013. Lisbon, Portugal 13-15 March 2013, 353-357.
DECLARATIONI declare that this thesis is my own unaided work. It is being submitted for the degree of degree of Doctor of Philosophy at the University of Bedfordshire.
It has not been submitted before for any degree or examination in any other University.
Table of ContentsList of Figures
List of Tables
Chapter One: Introduction
1.2 Research Motivation
1.3 Research Problem
1.4 Research Aims and Objectives
1.5 Research Methodology
1.6 Research Scope and Limitations
1.7 Thesis Structure
Chapter Two: Theories of Technology Acceptance Models
2.1 Theory of Reasoned Action (TRA)
2.1.1 Limitations of the Theory of Reasoned Action
2.2 Theory of Planned Behaviour (TPB)
2.2.1 Limitations of the Theory of Planned Behaviour
2.3 The Technology Acceptance Model (TAM)
2.3.1 The External Variables Identification
2.3.2 Limitations of the Technology Acceptance Model
Chapter Three: The Developed Model and Research Hypotheses
3.1 The Technology Acceptance Model in the E-learning Setting
3.1.1 The Technology Acceptance Model without Extension
3.1.2 The Extension of the Technology Acceptance Model
3.2 Identifying the External Variables
3.3 The Research Hypotheses
3.3.1 Information Quality (IQ)
3.3.2 Functionality (FL)
3.3.3 Accessibility (A)
3.3.4 User Interface Design (UID)
3.3.5 Computer Playfulness (CP)
3.3.6 Enjoyment (E)
3.3.7 Learning Goal Orientation (LGO)
I 3.3.8 Perceived Usefulness (PU) and Perceived Ease of Use (PEOU)
3.3.9 Gender Differences
3.4 The Developed Model
Chapter Four: The Research Methodology
4.1 The Research Process
4.2 The Research Design
4.5 Data collection
4.5.1 Questionnaire Development
4.5.2 Questionnaire Administration and Ethical Consideration
4.6 Data Analysis
Chapter Five: Data Analysis
5.1 Data Screening
5.1.1 Missing Data
5.1.2 Descriptive Statistics
5.1.4 Univariate and Multivariate Outliers
5.1.6 Conllinearity and Multicollinearity
5.2 Confirmatory Factor Analysis (CFA)
5.2.2 Goodness of Fit measures (GOF)
5.2.3 Constructs Validity
5.3 Structural Equations Modelling (SEM)
5.3.1 The Fit of the Developed Model
5.3.2 The Developed Model Results
5.4 The Moderating Effect of Gender
Chapter Six: Discussion
6.1 Results Discussion
6.2 The Developed Model Performance
6.3 The Extrinsic and Intrinsic Variables
6.4 The Moderating Effect of Gender
6.4.1 Gender Differences and TAM Constructs
6.4.2 Gender Differences and the External Variables
Chapter Seven: Conclusion
7.1 Research Objectives
7.2 The Research Contributions
7.3 Results’ Implication
7.4 Summary of the Research Findings
7.5 Limitations and Future Research
Appendix A - Research Questionnaire
Appendix B – Measured Variables
III List of Figures
Figure 2-1: Theory of reasoned action (Ajzen and Fishbein, 1980)
Figure 2-2: Theory of planned behaviour (Aizen, 1991)
Figure 2-3: Technology Acceptance Model (TAM) (Davis et al., 1989)
Figure 3-1: The developed model
Figure 5-1: The measurement model in IBM AMOS
Figure 5-2A: The developed model
Figure 5-2B: The developed model representation in IBM AMOS
Figure 5-3: The developed model results
Figure 6-1: The developed model results
Figure 6-2: The developed model results for males
Figure 6-3: The developed model results for females
IV List of Tables Table 2-1: Summary TAM studies in different information system contexts (Han, 2003)..............13 Table 2-2: Examples perceived usefulness and perceived ease of use measures (Han, 2003).......14 Table 3-1: The variance explained in the three studies
Table 3-2: The developed model variables
Table 5-1: Descriptive statistics
Table 5-2: The measured variables mean
Table 5-3: Skewness and Kurtosis results
Table 5-4: Multivariate outlier results for the four highest observations
Table 5-6: Tolerance results
Table 5-7: The factor loading for the measured variables
Table 5-8: The research model fit summary
Table 5-9: Squared Multiple Correlations
Table 5-10: Refined model fit summary comparison
Table 5-11: Constructs’ validity
Table 5-12: The research model fit results
Table 5-13: Hypotheses testing results
Table 5-14: The chi-square ∆ for the measurement model
Table 5-15: The chi-square ∆ for the structural model
Table 5-16: The significantly different hypotheses over genders
Table 5-17: The explained variance for the dependent variables between genders
Table 6-1: The explained variance comparison among perceived usefulness (PU), perceived ease of use (PEOU) and behavioural intention (BI)
Table 6-2: The research variables dimensions
Table 6-3: The direct and indirect effect of perceived usefulness and perceived ease of use.......82 Table 6-4: List of the significant and insignificant paths between genders
Chapter One: IntroductionThis chapter will present the research background of e-learning systems and the Technology Acceptance Model (TAM) developed by Davis, 1989 as both aspects form the basis of this research. The research background, will introduce the concept and benefits of e-learning systems, describe the purpose of TAM. Furthermore, the chapter will explain the research motivation, the research problem, then aims and objectives. Finally, the chapter will describe the research methodology, the scope and limitations, and detailed description of the thesis structure.
1.1 Background E-learning has become the new paradigm for modern teaching and it can be defined as “a webbased system that makes information or knowledge available to users or learners and disregards time restrictions or geographic proximity” (Sun et al., 2008). The use of technology in learning emerged from the development and advancement in the information and communication technologies (Hsia, 2007). Today, many educational institutions, business organisations and are interested in e-learning, it is considered to be the fastest growing segment in today’s global educational market with a worth value of $2.3T USD and is expected to grow to $69B USD by 2015 (Hezel Associates, 2005 cited in Wagner et al., 2008).
E-learning breaks the resurrection of time and place by enabling people to learn whenever and wherever they want. Moreover, e-learning can be divided into two main types: asynchronous and synchronous. In the asynchronous type, the e-learning system works as a supporting tool where students can use emails, discussion boards, online quizzes and assignments to help them study and to communicate with their instructor (e.g. Learning Management Systems, Blackboard, Moodle). The synchronous type is always used in distance learning where the class is given by the instructor live and online via the use of media such as live chat and videoconferencing enabling learners and teachers to communicate in real time (Hrastinski, 2008).
Today, educational institutions are shifting their learning paradigm from teacher-centred to learner-centred learning by offering new innovative online courses. These courses allow universities to expand their educational territories beyond time, space, and to enhance their traditional learning courses (Lee et al., 2009). The use of technology in learning will enhance the
learning experience, and benefit by (Bouhnik and Marcus 2006):
Allowing anytime and anyplace concepts; students will have access to the system in their • own convenient time and place.
Allowing group collaboration; students are able to communicate with each other and with • their instructors using forums, chat rooms and video conferencing.
Moreover, in the information Systems (IS) domain learners' acceptance of e-learning can be predicted and explained to provide a better understanding of their motivation to use the system.
The technology acceptance model (TAM) is of the main models used to investigate individuals' acceptance (i.e. intention to use) information technology (IT). The area of technology acceptance is constantly developing due to the rapid advancement in IT. Usage and acceptance are the two major disciplines contributed to the development of models and theories dealing with technology acceptance. The focus of the technology acceptance models differ from one field to another. For example, psychology and sociology studies focus on the acceptance behaviour of the individual.
While information systems studies focus on the technology characteristics in relation to the individual acceptance.