Chapter 7: Summary, Conclusion and Recommendations
3.3 Use of Web 2.0 Technologies by Academics and Students
3.3.2 Broader Issues on Use of Technologies for TAL
3.3.2.2 Diffusion of Innovations
Diffusion is the “process by which an innovation is communicated through certain channels over time among the members of a social system” (Rogers 2003:5). These channels could include new technologies (such as Web 2.0) used for TAL activities. Innovation may also refer to ideas, practices or objects that appear new to an individual (Rogers 2003). Diffusion of innovation (DOI) theory developed by Rogers (2003) analyzes how an innovation diffuses in a social system (Mazman and Usluel 2009). It also describes the process by which an invention is communicated through certain channels to reach and be adopted by many users (Bwisa and Gacuhi 1999). Diffusion can be regarded as the spread of a new technology in an organization.
DOI theory is a widely used in the studies of ICTs. The DOI theory comprises of four key elements which are innovation, communication channels, time and social system. The items that appear new to users but useful in particular context are called innovations. Bwisa and Gacuhi (1999) described innovation as the modification or adaptation of a product or service that is novel only to a given setting, irrespective of whether it has been used somewhere before or not. For instance, the use of Web 2.0 technologies in the TAL setting is quite an innovation to educational activities which are traditionally conducted through the face-to-face method. A
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communication channel refers to a method by which information is transmitted from one person to another. For example, students can use the Facebook or e-mails to communicate with their peers. Time, which is the third component of DOI according to Rogers (2003), can be divided into three components, namely the innovation-decision process, the innovativeness of a person, and the adoption rate of the system. The social system can be described as a set of interconnected entities involved in common problem solving to achieve a goal (Rogers 2003).
The university may be considered as a social system where interaction and communication takes place among students and academics in order to achieve a common goal. That is, academics teach effectively and students learn to achieve academic success. These four major features determine whether a person would adopt or reject an innovation (Mohammad 2011).
In the context of this study, diffusion is a process by which TAL activities are accomplished through the use of Web 2.0 technologies over a period of time among academics and students.
Early instructional diffusion studies maintained that a substantial time lag is required for the widespread dissemination of new instructional ideas (Rogers 2003). This implies that before a technology could be said to have gained ground, there would be a time interval between the introduction of the innovation or technology and when it is been accepted and used. In academic environments, there has been a growing trend to incorporate technology to fulfill some of the technological expectations of students. As earlier revealed, today‟s students are considered as digital natives (Prensky 2001), and they use Web 2.0 applications on a regular basis (Madden and Fox 2006). Web 2.0 applications are expected to provide several benefits to these students and academics, given the ability of these applications to enable active participation of students, promote opportunities and environments for student participation and reflection, and foster a collaborative and active community of learners (Ferdig 2007).
However, the perceived characteristics of the user (Rogers 2003) can affect the rate of adoption of these technologies. Rogers (2003) also suggested some other characteristics of an innovation that could influence its rate of adoption, these include: relative advantage, compatibility, complexity, trialability and observability. Moore and Benbasat (1991) added four other characteristics, namely ease of use, image, visibility and result demonstrability.
Mohammad (2011) employed Rogers‟ DOI theory to specify the factors that influence student perceptions of adopting Web 2.0 applications as learning tools. Data was obtained via a survey instrument from 350 students and was statistically analyzed. Results showed that the level of
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awareness of Web 2.0 explained more than 32% of the variance in Web 2.0 adoption. This shows the power of awareness in predicting the diffusion and adoption of an innovation. The study result suggests that students with higher levels of awareness of Web 2.0 are more likely to use Web 2.0 as learning tools. Study findings further showed that Rogers' attributes of innovations, which were indicated as voluntariness, relative advantage, ease of use, compatibility, visibility, result demonstrability and trialability explained more than 9% of the variance on Web 2.0 adoption. Consistently with Almobarraz‟s (2007) research, these same attributes explained 33.2% on the rate of Internet adoption. Study results further revealed that obstacles which include skills, privacy, confidence and technical support explained more than 8% of the variance in Web 2.0 adoption as learning tools. It implies that the rate of diffusion of innovations can also be affected by problems foreseen in a technology. Thus in integrating Web 2.0 technologies in TAL, the impact of obstacles should be considered in order to allow for fast diffusion of the technologies in the university system.
Several other studies have been conducted on the diffusion of innovations in Africa such as that of Bwisa (1999) in Kenya; Van der Watt and Pretorius (2008) in South Africa; Conley and Udry (2001) in Ghana; and Oigiagbe, George and Owoyemi (2012) in Nigeria. Metseagharu (2010) investigated the factors that affect the diffusion of technology from research centres in industries in Nigeria. The study assessed the inventions of the Federal Institute for Industrial Research (FIIRO) and Project Development Agency (PRODA) which are composite flour and cassava pellet respectively. Findings show a low level of diffusion of innovations from the research centres in the industries in Nigeria. Moreover, the study identified that relevance of innovations either in terms of price or performance, inadequate manpower, inadequate policies, policies implementation and lack of funding as factors inhibiting the diffusion of technology.
The study recommended among others that stakeholders of innovations be actively involved in the spread of an innovation and that government provide vital policies that would create the right environment for diffusion.
Unlike most studies, Twiss (1992) identified some factors that were critical to favouring the spread of an innovation. They can be summarized as being the relevance of the innovation to an organization‟s corporate goals, effective project selection and evaluation system, organisations‟ receptiveness to the innovation, individual commitment to the innovation, creativity of the innovation and orientation on the profitability of the innovation to users. The
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present study aims at providing useful information that will help (1) the diffusion of Web 2.0 technologies into Nigerian university education; and (2) catalyse the development of national and institutional policy on integrating Web 2.0 technologies into TAL in the university environments in Nigeria. This study will elicit information through the use of questionnaires and interview schedule on what factors can encourage or be obstacles to the integration of Web 2.0 technologies in TAL in Nigeria universities.