Thesis (MSc) - Cyprus International University. Institute of Graduate Studies and Research Management Information Systems

Includes bibliography (sheets 52-56)

ABSTRACT
The Internet of Things (IoT) is a term used to describe a network of physical objects
that are connected to each other. They have special sensors and tools that allow them
to collect and share information with each other through the internet. This technology
has the potential to bring various benefits to different areas of our lives. IoT
technologies offer opportunities for creating smart classrooms, personalizing learning
experiences, and enhancing administrative efficiency in the educational context. The
aim of the study is to examine the factors influencing the adoption of IoT in higher
education. A quantitative research design is used in this study. A total of 400 students
participated in the study. A convenient sampling technique is employed, and the
research is carried out among higher education institutions in the Northern Cyprus. In
this research, the scale developed by Venkatesh, V., Thong, J. Y. L., & Xu, X. (2012),
Chin-Lung Hsu, Judy Chuan-Chuan Lin (2018) and Tan, P. J. B. (2013) were used. In
the case of performance expectancy, effort expectancy, and facilitating conditions they
all proved not to be a key factor, as most students are concerned with the privacy risk
that comes with the collection and use of their data, as well as whether their fellow
students are gaining value from the usage of IoT services. Perceived privacy risk had
the highest influence on predicting IoT usage among all the factors. For educational
purposes, IoT can be a platform for students to gain a better understanding of their
performance, drive greater innovation and knowledge sharing, and provide a platform
for educators to make data-driven decision making in a situation where a student's
academic performance needs to be addressed, however this factor shows that data
privacy remains a massive concern amongst users of technology and when
implementing any policy that requires the acquisition and use of such data, users must
be made to understand that their privacy is maintained.
Keywords: Behavioral Intention, Effort Expectancy, Performance Expectancy,
Perceived Privacy Risk, Perceived Value, Social Influence