Exploring technology acceptance of teacher educators

Allan H K Yuen, Bob Fox, Colin Evers, H F Lau and Deng Liping
The University of Hong Kong
Hong Kong SAR, China

In response to the growing importance of information and communication technology (ICT), both practitioners and researchers have great interest in the understanding of user acceptance and attitudes towards ICT. Special attention has been given to estimate a cognitive model that traces the way customers form and develop their perceptions of new technology and identifies the consequences of these perceptions on individual-level behavioral intention variables and hence usage that affect the strategic new product development of the manufacturer and the implementation of the firm in adopting new technologies.

Technology acceptance has been an important research area in business information systems. A number of well-supported models (Davis, 1989, 1993; Taylor & Todd, 1995; Venkatesh & Davis, 1996; Igbaria et al., 1997; Agarwal & Prasad, 1997; Compeau et al., 1999; Karahanna et al., 1999; Venkatesh, 2000; Koufaris, 2002; Venkatesh, Morris, Davis & Davis, 2003) have been developed to examine and to predict user technology acceptance in business organizations. With the announcement of ICT in education policies in many countries (Pelgrum & Anderson, 1999), teacher technology acceptance and use has become a critical area of concern to the integration of ICT in education (Yuen & Ma, 2002). Nevertheless, can the models in information systems be applied to understand and predict teacher technology acceptance? Are there any differences in ICT attitudes and acceptance between teachers and workers in other workplaces?

In this study, the issues of technology acceptance of teacher educators will be explored based on a case study taking place in the education faculty of a university in Hong Kong. The study aims to understand the existing practices of ICT uses among teaching staff and to explore the factors that foster technology acceptance and uses. Data collection chiefly included individual in-depth interviews of 13 teaching staff from six divisions of the faculty. Each interview lasted about 45 minutes. Seven categories emerged from the data analysis, namely, external challenges, organizational background, technology uses in different areas, administrative and technical support, professional development, reservations, and expectations. It is believed that these categories have important implications for the understanding of teacher technology acceptance as well as the fostering of technology acceptance and uses among teachers.