Applying the Technology Acceptance Model to ascertain the acceptance of learning technologies in international students and academics – a case study at Coventry University London

Abstract

Technology is transforming the way we live and work and has become a pervasive factor in UK Higher Education with universities incorporating learning technologies into their curricula and assessment strategies. As a result, academics have been encouraged to embed technology into their teaching practices in order to improve student engagement, student performance and to enable students to become digitally literate so that they can cope in a digitally-mediated society and technologyenabled future work environment. For a number of years learning technologies have been championed as valuable tools in which to enhance learning in UK Higher Education, although current educational research has yet to demonstrate their effectiveness in achieving student learning gains. Several reasons have been contended for this situation, including the lack of time afforded to academics, incongruence with pedagogical approaches and the Perceived Usefulness (PU) and Perceived Ease of Use (PEOU) of the technologies that are available. These issues have influenced technology acceptance in both students and academics. The Technology Acceptance Model (TAM) is one of several theories that have been used to ascertain technology acceptance and has been designed to understand how and why users accept and use a particular technology. Coventry University London (CUL) is a prime example of a UK Higher Education institution that has invested a great deal of time and money into the implementation of learning technologies and it was unclear if this investment had been successful in meeting expectations and supporting student learning outcomes. In this study, TAM was applied using a Constructivist Grounded Theory (CGT) methodology with fellow academics and international students in order to uncover the reasons why they accept and use a particular technology. International students were selected due to being the most dominant population at CUL. The CGT approach was particularly beneficial in generating rich and meaningful findings by co-constructing data with international students and academics via my unique institutional insider perspective. A selection of specific qualitative methods were applied to make the process as robust as possible. These included interviews with students and academics and focus groups with students after each set of interviews to explore relevant issues in greater depth. Lesson observations took place to clarify if academics used technology to the extent they stated in the interviews and to observe its effects on international student engagement at first-hand. A focus group was also conducted with learning technologists and in-depth interviews with senior management to develop a wider perspective on academic and student acceptance of specific technologies. As a result of this research, the Student and Academic Technology Acceptance Model (SATAM) was developed as a conceptual framework which identifies specific external variables that affect technology acceptance in academics and international students which ultimately lead to positive behavioural intention and actual system use. The empirical data confirmed the view that specific learning technologies play a significant role in engaging an array of students in their studies. New discoveries from the thesis indicate that academics are more influenced by the PEOU of learning technologies whereas students are more interested by their PU. Students were much more likely to accept a particular technology if it had a positive perceived effect on their academic performance and future employability. These findings demonstrate the need for the institution to reconfigure and enhance the clarity of its technology-enhanced learning strategy. It was also discovered that the level of support offered to academics needed to be improved so that they are able to develop their IT competencies and ultimately enable international students to achieve learning outcomes.

Date of Award	Apr 2019
Original language	English
Awarding Institution	Coventry University
Supervisor	Christine Broughan (Supervisor), Caroline Wilson (Supervisor) & Dimitar Angelov (Supervisor)