Education being the citadel for one’s knowledge and learning opted for many innovations. One such innovation was science and technology. The development of such science and technology was beyond any imagination. Time was rationed for human being to learn and to educate himself. The advancement of science and technology paved way for education at his doors by offering distance education. He could enrich his knowledge and learn anything from anywhere and anywhere. He need not spend fixed timings to satiate and quench his thirst and could depend upon distance education. Technology promotes a collaborative, active, participatory, and individualized type of learning will change the way students are taught. With the use of such tools, Richardson (2006) identified ten important learning shifts in the future prospects. • Open content: open sources of information
• 24/7 learning
• Social, collaborative construction of meaningful knowledge • Teaching is conversation, not lecture
• Know “where” learning: knowing where to find information • Readers are no longer just readers
• The web as notebook
• Writing is no longer limited to text
• Mastery is the product, not the test
• Contribution, not completion, as the ultimate goal
In their study to explore the future trends of online education, Kim and Bonk discovered that, in the future, online cooperation, case-based learning and problem-based learning would be the preferred instructional methods for online instructors (Kim & Bonk, 2006). Presently, there is a lack of research in the area of Web 2.0 tools and their implications to students’ performance. Although much anecdotal research supports the use of the tool, pragmatic data and research have yet to be carried out in the area. The Web 2.0 tools will not only play a bigger role in education but will also encourage higher order intricacy thought, problem-solving and integration through collaboration and innovation.
This research was an adopter study  where the idiosyncratic approach is to “survey organizations in some population of interest to capture data about (1) the characteristics of those organizations and their implementation contexts and (2) the timing and/or extent of implementation of one or more innovations.” The researcher used a data set to scrutinize the acceptance of technology mediated distance education in the U.S. higher education sector. Perhaps the most prominent difference of this sector is its widespread heterogeneity among market participants in terms of their resources, market research and focus (e.g., research universities versus liberal arts colleges), and governance and mission (e.g., public versus private institutions). The literature on implementation of IT provides factors likely to influence the adoption of technology mediated distance. The two behaviours have generally been modelled as being influenced by the same set of factors that lead to initial use , ,  and .
Prior research has consistently shown a positive relationship between organization size and innovativeness . The most common reasons for this comprise economies of scale , slack resources , access to outside resources , and ability to bear implementation risks . Size should also be important in our context because larger institutions are more likely to have the technology infrastructure that is essential for providing TMDE. Therefore, we included institutional size (total enrolment) as a control and expected it to have a positive relationship with both acceptance and post-acceptance behaviour.
Organization and technology fit
An organization with a high tendency to innovate may still lag in acceptance if the innovation does not fit its needs, strategies, resources, or capabilities. The literature on the diffusion of IT support the importance of characteristics that capture the...