methods. It includes the research design, survey instruments,
data collection, and statistical techniques for analyses. It also
describes the procedure followed and describes the motives
behind the specific techniques, methods, and approaches of
data collection. Finally, Chap. 6 discusses the reliability,
validity, and associated issues. Chapter 7 explains the process of data preparation, results, and preliminary data analysis. The prime focus of this chapter is the appropriateness
of the data obtained concerning data analysis. This chapter
presents the preliminary data results and the statistical
methods applied in data analysis. In this chapter, the personal profile of the participants and the descriptive data
analysis applied are discussed. The descriptive data analysis
of the core variables (PE, EE, SI, FC, HM, and H) and
moderating variables (experience, age, and cultural dimensions) are discussed. In the last section, the reliability, correlation, factor analysis, and regression analysis are
discussed. Hence, this chapter provides empirical evidence
regarding instructors’ adoption of LMS in HEIs in the
context of the Middle East in general and Saudi Arabia in
particular. Chapter 8 deals with a broad discussion on the
analysis of the results of the quantitative and suggest a
holistic strategy formulation model. This chapter deals with
a broad discussion on the analysis of the results of the
quantitative data and suggests a holistic strategy formulation
model. The key research questions have been addressed in
this chapter. Finally, Chap. 9 presents a summary of this
book project. This chapter provides an overview of the key
elements of research that was undertaken in this project. The
contributions and insights toward LMS adoption, implications for theory and practice regarding the use and adoption
of LMS, the limitations of the research presented here in this
book are discussed and the recommendations for future
research about wider acceptance and utility of learning
management systems across the work are made.
1.5 Summary
The adoption and use of instructional technology play an
important role in shaping the future of HEIs. The use of a
learning management system (LMS) is growing in higher
education. It has become an essential tool for instructors and
students in their teaching and learning process. Various
models and theories have been offered to investigate the
factors that influence the adoption of LMSs in the educational sector. Most technology adoption models were
developed and tested in Western cultures. Therefore, it is
very important to achieve a better knowledge of the impact
of cultural variables on the adoption of LMS. Thus, the
purpose of the study in this book is to employ the extended
version of ‘unified theory of acceptance and use of technology’ (i.e., UTAUT2) as a framework for determining
behavioral intention linked with the adoption and use of an
LMS among instructors at HEIs. This book provides
empirical evidence to the validity of the extended UTAUT2
model in the cultural context of higher educational institutions. With the extension of the UTAUT2 model, it forms a
new theoretical model that could help understand user
behavior associated with the adoption of LMS in the cultural
context of higher educational institutions (HEIs).
Hence, this chapter first presents the introduction of the
book by presenting the context, problem statement, and
critical research questions. Finally, this chapter presents a
summary of all chapters of this book.
References
Ajzen, I. (1985). From intentions to actions: A theory of planned
behavior. In J. Kuhl & J. Beckman (Eds.). Action–control: From
cognition to behavior (pp. 11–39), Heidelberg: Springer.
Al-Gahtani, S. S., Hubona, G. S., & Wang, J. (2007). Information
technology (IT) in Saudi Arabia: Culture and the acceptance and use
of IT. Information & Management, 44(8), 681–691. https://doi.org/
10.1016/j.im.2007.09.002.
Alghamdi, S. R. (2016). Use and attitude towards Learning Management Systems (LMS) in Saudi Arabian universities. Eurasia
Journal of Mathematics, Science & Technology Education, 12(9),
2309–2330. https://doi.org/10.12973/eurasia.2016.1281a.
Baptista, G., & Oliveira, T. (2015). Understanding mobile banking: The
unified theory of acceptance and use of technology combined with
cultural moderators. Computers in Human Behavior, 50, 418–430.
https://doi.org/10.1016/j.chb.2015.04.024.
Cheng, B., Wang, M., Moormann, J., Olaniran, B. A., & Chen, N.-S.
(2012). The effects of organizational learning environment factors
on e-learning acceptance. Computers & Education, 58(3), 885–899.
https://doi.org/10.1016/j.compedu.2011.10.014.
Cuban, L., Kirkpatrick, H., & P, C. (2001). High access and low use of
technologies in high school classrooms: Explaining an apparent
paradox. American Educational Research Journal, 38(4), 813–814.
Dillon, A., & Morris, M. G. (1996). Users acceptance of information
technology: theories and models. Annual Review of Information
Science and Technology, 31, 3–32.
Dutton, H., Cheong, P., & Park, N. (2004). The social shaping of a
virtual learning environment. Electronic Journal of E-Learning, 2
(2), 1–12. Retrieved from http://www.inf.ufes.br/*cvnascimento/
artigos/issue1-art3-dutton-cheong-park.pdf.
Fishbein, M., & Ajzen, I. (1975). Belief, attitude, intention, and
behavior: An introduction to theory and research. Don Mills,
Ontario: Addison-Wesley Publishing Company.
Henriksen, D., Mishra, P., & Fisser, P. (2016). Infusing creativity and
technology in 21st century education: a systemic view for change.
Journal of Educational Technology & Society Educational Technology & Society, 19(193), 27–37. http://about.jstor.org/terms.
Hew, T., Latifah, S., & Abdul, S. (2016). Computers & education
understanding cloud-based VLE from the SDT and CET
4
1 Adoption of LMS in the Cultural Context of Higher Educational …
data collection, and statistical techniques for analyses. It also
describes the procedure followed and describes the motives
behind the specific techniques, methods, and approaches of
data collection. Finally, Chap. 6 discusses the reliability,
validity, and associated issues. Chapter 7 explains the process of data preparation, results, and preliminary data analysis. The prime focus of this chapter is the appropriateness
of the data obtained concerning data analysis. This chapter
presents the preliminary data results and the statistical
methods applied in data analysis. In this chapter, the personal profile of the participants and the descriptive data
analysis applied are discussed. The descriptive data analysis
of the core variables (PE, EE, SI, FC, HM, and H) and
moderating variables (experience, age, and cultural dimensions) are discussed. In the last section, the reliability, correlation, factor analysis, and regression analysis are
discussed. Hence, this chapter provides empirical evidence
regarding instructors’ adoption of LMS in HEIs in the
context of the Middle East in general and Saudi Arabia in
particular. Chapter 8 deals with a broad discussion on the
analysis of the results of the quantitative and suggest a
holistic strategy formulation model. This chapter deals with
a broad discussion on the analysis of the results of the
quantitative data and suggests a holistic strategy formulation
model. The key research questions have been addressed in
this chapter. Finally, Chap. 9 presents a summary of this
book project. This chapter provides an overview of the key
elements of research that was undertaken in this project. The
contributions and insights toward LMS adoption, implications for theory and practice regarding the use and adoption
of LMS, the limitations of the research presented here in this
book are discussed and the recommendations for future
research about wider acceptance and utility of learning
management systems across the work are made.
1.5 Summary
The adoption and use of instructional technology play an
important role in shaping the future of HEIs. The use of a
learning management system (LMS) is growing in higher
education. It has become an essential tool for instructors and
students in their teaching and learning process. Various
models and theories have been offered to investigate the
factors that influence the adoption of LMSs in the educational sector. Most technology adoption models were
developed and tested in Western cultures. Therefore, it is
very important to achieve a better knowledge of the impact
of cultural variables on the adoption of LMS. Thus, the
purpose of the study in this book is to employ the extended
version of ‘unified theory of acceptance and use of technology’ (i.e., UTAUT2) as a framework for determining
behavioral intention linked with the adoption and use of an
LMS among instructors at HEIs. This book provides
empirical evidence to the validity of the extended UTAUT2
model in the cultural context of higher educational institutions. With the extension of the UTAUT2 model, it forms a
new theoretical model that could help understand user
behavior associated with the adoption of LMS in the cultural
context of higher educational institutions (HEIs).
Hence, this chapter first presents the introduction of the
book by presenting the context, problem statement, and
critical research questions. Finally, this chapter presents a
summary of all chapters of this book.
References
Ajzen, I. (1985). From intentions to actions: A theory of planned
behavior. In J. Kuhl & J. Beckman (Eds.). Action–control: From
cognition to behavior (pp. 11–39), Heidelberg: Springer.
Al-Gahtani, S. S., Hubona, G. S., & Wang, J. (2007). Information
technology (IT) in Saudi Arabia: Culture and the acceptance and use
of IT. Information & Management, 44(8), 681–691. https://doi.org/
10.1016/j.im.2007.09.002.
Alghamdi, S. R. (2016). Use and attitude towards Learning Management Systems (LMS) in Saudi Arabian universities. Eurasia
Journal of Mathematics, Science & Technology Education, 12(9),
2309–2330. https://doi.org/10.12973/eurasia.2016.1281a.
Baptista, G., & Oliveira, T. (2015). Understanding mobile banking: The
unified theory of acceptance and use of technology combined with
cultural moderators. Computers in Human Behavior, 50, 418–430.
https://doi.org/10.1016/j.chb.2015.04.024.
Cheng, B., Wang, M., Moormann, J., Olaniran, B. A., & Chen, N.-S.
(2012). The effects of organizational learning environment factors
on e-learning acceptance. Computers & Education, 58(3), 885–899.
https://doi.org/10.1016/j.compedu.2011.10.014.
Cuban, L., Kirkpatrick, H., & P, C. (2001). High access and low use of
technologies in high school classrooms: Explaining an apparent
paradox. American Educational Research Journal, 38(4), 813–814.
Dillon, A., & Morris, M. G. (1996). Users acceptance of information
technology: theories and models. Annual Review of Information
Science and Technology, 31, 3–32.
Dutton, H., Cheong, P., & Park, N. (2004). The social shaping of a
virtual learning environment. Electronic Journal of E-Learning, 2
(2), 1–12. Retrieved from http://www.inf.ufes.br/*cvnascimento/
artigos/issue1-art3-dutton-cheong-park.pdf.
Fishbein, M., & Ajzen, I. (1975). Belief, attitude, intention, and
behavior: An introduction to theory and research. Don Mills,
Ontario: Addison-Wesley Publishing Company.
Henriksen, D., Mishra, P., & Fisser, P. (2016). Infusing creativity and
technology in 21st century education: a systemic view for change.
Journal of Educational Technology & Society Educational Technology & Society, 19(193), 27–37. http://about.jstor.org/terms.
Hew, T., Latifah, S., & Abdul, S. (2016). Computers & education
understanding cloud-based VLE from the SDT and CET
4
1 Adoption of LMS in the Cultural Context of Higher Educational …