Abstract: Since the beginning of distance education with the rapid evolution of technology, the social network plays a vital role in the educational process to enforce the interaction been the learners and teachers. There are many Web 2.0 technologies, services and tools designed for educational purposes. This research aims to investigate instructors’ acceptance towards web-based learning systems in higher educational institutes in Kingdom of Bahrain. Questionnaire is used to investigate the instructors’ usage of Web 2.0 and the factors affecting their acceptance. The results confirm that instructors had high accessibility to such technologies. However, patterns of use were complex. Whilst most expressed interest in using online technologies to support learning activities, learners seemed cautious about other values associated with web-based system, such as the shared construction of knowledge in a public format. The research concludes that there are main factors that affect instructors’ adoption which are security, performance expectation, perceived benefits, subjective norm, and perceived usefulness.
Abstract: Using the technology acceptance model (TAM), this
study examined the external variables of technological complexity
(TC) to acquire a better understanding of the factors that influence the
acceptance of computer application courses by learners at Active
Aging Universities. After the learners in this study had completed a
27-hour Facebook course, 44 learners responded to a modified TAM
survey. Data were collected to examine the path relationships among
the variables that influence the acceptance of Facebook-mediated
community learning. The partial least squares (PLS) method was used
to test the measurement and the structural model. The study results
demonstrated that attitudes toward Facebook use directly influence
behavioral intentions (BI) with respect to Facebook use, evincing a
high prediction rate of 58.3%. In addition to the perceived usefulness
(PU) and perceived ease of use (PEOU) measures that are proposed in
the TAM, other external variables, such as TC, also indirectly
influence BI. These four variables can explain 88% of the variance in
BI and demonstrate a high level of predictive ability. Finally,
limitations of this investigation and implications for further research
are discussed.