It is widely accepted today that the impact of Internet technologies is significant on every aspect of people's life. This impact is felt in the ever increasing pace of transformation of the higher education sector, while more and more institutions are using the internet and web technologies in the classroom as part of the learning environment (Piccoli, Ahmad, & Ives, 2001). The advantages of internet-based learning mediums have been widely reported, recognized and accepted. Research suggests that technology-mediated learning environments allow for more study flexibility and broader accessibility (Lee, Cheung, & Chen,, 2005), may improve students' performance (Alavi, 1994) and corresponding evaluation of their learning experiences (Hiltz, 1995), and lead to higher computer self-efficacy (Piccoli et al., 2001). In addition, it provides benefits to academic institutions in terms of cost reductions and increased revenues (Saade & Bahli, 2005) and has the potential of making learning more student-centered (Cardler, 1997).
In general, like any information systems, user acceptance and usage are important primary measures of system success (DeLone & McLean, 1992). Without consideration of student involvement and participation, even the best developed system cannot be successful (Catchpole, 1993). Moreover, a successful web-based learning system should be widely adopted with active participation from students. It is therefore important to identify, study and better understand the variables that influence learning in virtual environments and which lead to significant impact on student satisfaction, performance and adoption. Considering the literature in the past decade, the technology acceptance model (TAM), which is an adaptation of theory of reasoned action (TRA), seems to be dominant in the IS literature on explaining individuals' IT usage behavior (Lee et al., 2005; Straub, Keil, & Brenner,, 1997; Taylor & Todd, 1995).
The application of TAM has targeted mostly in the use of commercial software, and recently the use of the internet/web. Very few studies however, applied the TAM to the online learning context in higher education. Moreover, the viability of TAM to explain individuals' acceptance behavior under the online learning context has been statistically confirmed in a recent study (Saade, Nebebe, & Tan, 2007). Literature on TAM studies show that there is a dominant emphasis (of TAM) on notions of instrumentality, focusing mainly on functional or extrinsic motivational drivers (Agarwal & Karahanna, 2000). In the context of student acceptance of web-based learning system (WLS), we believe intrinsic motivators representing a student's subjective feelings of joy, elation, pleasure, and positive holistic experience also play a critical role in explaining user acceptance and usage behavior of WLS. Researchers suggest that extrinsic and intrinsic motivators jointly determine the adoption of new technologies. Therefore, in this study, we postulate that incorporating both extrinsic (represented by perceived usefulness in TAM) and intrinsic motivation into TAM may enhance the explanation and prediction of student acceptance of WLS.
Furthermore, although many studies have examined user acceptance towards new technologies, most of them were conducted in developed countries using Western subjects, and thus on the whole may not be reflective of the adoption process in different cultural environments (Anandarajana, Igbaria, & Anakwe, 2002; Straub et al., 1997). Relatively few TAM research studies have been done in Asian, Middle Eastern, and African countries and found none that were in the context on web-based learning. There are however some studies reported in the Informing Science Institute Conferences on experiences in online learning in Arab and Chinese countries, but these studies were descriptive in nature and reporting on process alone. …