Abstract

This article presents a two-phase study exploring the usage of technology in higher education as well as the role of the general innovativeness in predicting the actual use of technology. During the first phase of the study, which involved 502 staff members, a descriptive analysis of their usage of social media, technological devices, and Microsoft Office 365 cloud services was performed, with various demographic variables being considered. During the second phase, which involved a subsample of 106 staff members, structural equation modeling (SEM) was used to examine a model in which the general innovativeness and the demographic variables acted as predictors of the actualized innovativeness. The results showed that the staff used social media, devices, and cloud services quite satisfactorily. The examination of their user profiles revealed that there were significant differences among the staff members on the basis of their demographic variables, especially their gender, job type, and discipline. The results of the SEM showed that the general innovativeness contributed positively, as was expected, to predicting the adoption of devices, non-academic social networking sites and Office 365 cloud services. The results further suggested that males were early adopters of devices, while academics were early adopters of commercial services and academic social networking sites. However, the academics appeared to lag behind the administrators in terms of adopting Office 365 cloud services. The implications of the study and directions for future research are also presented.

Highlights

  • Many studies have sought to illustrate how new technologies could assist with the educational process (Brown, 2012; Dermentzi et al, 2016; Hung & Yuen, 2010; Lim et al, 2015)

  • What kinds of technologies are used by staff members and who are the users? The first column (Users) in Table 2 represents the percentage of technology users from among the total sample

  • The results showed that the degree of usage of academic social networks ranged between 25% for ResearchGate and 19% for Academia.edu and Mendeley

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Summary

Introduction

Many studies have sought to illustrate how new technologies could assist with the educational process (Brown, 2012; Dermentzi et al, 2016; Hung & Yuen, 2010; Lim et al, 2015). Due to the numerous possibilities afforded by technologies, universities and colleges have sought to purchase and provide both their staff and their students with new technologies. Putting those technologies into service does not imply that staff and/or students are going to use them. Manca & Ranieri, 2016b) It is no longer debatable whether technologies can assist with the educational process, since it has been proved that they can. The question has become, “who is using the offered technologies?” For instance, Veletsianos and Kimmons (2013) suggested the need to investigate the profiles of technology users so as to determine the relationship between the usage of technology and staff members’ educational level, age, discipline, gender, and other personal characteristics

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