DiffusionLit

Review of Literature - Diffusion of Innovations - Summary [|Doc in PDF - DarrowDiffusionof InvLit ReviewNov2007.pdf]

__**Diffusion of Innovations - Review of Literature - October 27, 2007**__ - [|Blog Post Summary]

**“//One cannot seek knowledge about an innovation until he or she knows it exists//.”**
- Everett Rogers, 1963

//Theoretical Framework//

The framework entitled “Diffusion of Innovations” (DOI) was developed by Everett Rogers as the result of a study that took place by Ryan and Gross (Rogers, 2003). Ryan and Gross studied the diffusion of a new innovation at the time - hybrid seed corn - by farmers in Iowa. They had secured a grant from the research arm of Iowa State University for this purpose. It naturally followed that they would study the diffusion of the hybrid seed corn since the hybrid seed corn had been developed at the university. The university was interested in how the use of hybrid seed corn would diffuse throughout the state, so that, as other farm innovations were developed by the university, they would know the process of adoption (Singhal and Obregon, 2004). Rogers (2003) characterizes this study as the seminal work that defined diffusion theory.

Diffusion is the process by which an innovation is communicated through certain channels over time by members of a social system. An innovation is defined as any new idea, object or practice (Rogers, 1995). Rogers reviewed existing studies of innovations in agriculture, education, medicine, marketing and other disciplines and discovered common characteristics in each of these innovations (Rogers, 1995). He studied how innovations diffuse and become adopted including: hybrid seed corn, water purification in Egypt, adoption of family planning in Korea, and various educational innovations such as new math and kindergarten (Rogers, 2003). Rogers refined the DOI theory through ongoing research and identified various concepts and measurements that are utilized across a multitude of disciplines. Rogers discovered and other researchers validated, that all innovations result in a S-shaped curve of adoption over time. See Figure 1. Figure 1. S shaped curve indicates adoption of an innovation over time

Various educational studies that utilized Roger’s framework were examined for this review of literature. To understand the studies, it is important to first comprehend the various components of Rogers’ theory. The specific components included are: A) adopter categories; B) innovation-decision process; C) communication channels; D) role of a change agent; and E) attributes of an innovation.

//Adopter categories// include innovators, early adopters, early majority, late adopters, late majority and laggards as Figure 2 indicates. The five categories are exhaustive (except for nonadopters).

Similarly, as individuals or groups adopt an innovation, all go through similar stages called the //innovation-decision making process//. These stages include knowledge, persuasion, decision, implementation and confirmation. It is at the decision stage that individuals or groups chose to adopt or reject an innovation (Rogers, 2003).

//Communication channels// are divided into mass media and interpersonal. Mass media are characterized by mediums such as television, newspapers or websites. Interpersonal communication is defined as a two-way exchange of information between two or more people, usually in a face-to-face setting. Rogers has shown that the type of communication influences adoption at different stages of the innovation-decision making process and that the innovation category of individuals or groups are influenced by different communication channels utilized towards adoption of the innovation (Rogers, 2003).

The role of the //change agent// is another important aspect of Roger’s framework. Change agents provide the communication link between the innovation and the adoption of the innovation. Change agents usually have a certain expertise and status that causes them to be categorized as a change agent. Rogers identifies seven roles a change agent must understand in order for an innovation to become adopted. These roles include developing relationships, diagnosing problems, translating intent into action, and stabilizing the adoption. Specifically, “the change agent seeks to shift the clients from a position of reliance on the change agent to one of self-reliance” (Rogers, 2003).

Finally, the //attributes of the innovation// itself plays a role in its adoption. Rogers found that there are five attributes that facilitate the adoption of innovation. These five attributes are: relative advantage, compatibility, complexity, trialability, and observability. If these attributes are present, then the innovation is more likely to be adopted (Rogers, 2003).

Various educational researchers have applied the framework of the DOI in a variety of settings. This review of literature focused on the use of Roger’s DOI framework as it has been applied in K-12 and higher education settings with the adoption of various technology innovations. //Technology// is defined as information put into use in order to carry out some task while //technology transfer// is the application of information into use (Rogers, 1995). Figure 3 indicates which part of Roger’s framework was used for each study reviewed.

Figure 3. Categories of studies and Rogers’ framework chart for review of literature

& Upton (2000) || Sahin and Thompson (2006) ||  || Surendra (2001)
 * =  ||= **Adopter**
 * Categories** ||= **Innovation- Decision**
 * Making Process** ||= **Communication**
 * Channels** ||= **Role of**
 * Change Agent** ||= **Attributes of**
 * the Innovation** ||
 * **Higher Ed** || Signer, Hall

Signer, Hall & Upton (2000) || Surendra (2001)

Johnson (2001) || (2001) || Blankenship (1998) || Blankenship (1998) Frank, Zhao & Borman (2004) Hoerup (2001) || Frank, Zhao & Borman (2004) ||  ||
 * **K-12** || Hoerup

//Adopter Categories//

Signer, Hall & Upton (2000) and Hoerup (2001) both focused their research utilizing Roger’s adopter categories. Signer, Hall & Updton (2000) studied the degree of use of web-based course tools by college faculty at St. John’s University in New York. Utilizing a questionnaire tool, 204 faculty members responded to two different questionnaires in two different years. With this data, they found that at certain adopter categories, organizational incentives facilitate adoption. Furthermore, they concluded that it was critical for the individuals in the “early adopter” category to receive a variety of support such as training, user groups and summer grants to develop online courses (Signer, Hall & Upton, 2000). Hoerup (2001) conducted interviews with a group of seven fifth grade teachers in a school district who were beginning to integrate computer technology in the classroom. She found that the adopter category had a direct connection to the rate of adoption of others on the grade level team. Those who were termed early adopters who collaborated with those who were in the late majority caused the late majority to integrate the technology sooner than if the collaboration had not occurred (Hoerup, 2001). Overall, both research studies indicated that at certain adopter categories, individuals and groups need different types of support in order to adopt the technology.

//Innovative-Decision Making Process//

Sahin and Thompson (2006) and Blankenship (1998) applied the use of the innovative-decision making construct. Sahin and Thompson surveyed 117 faculty members of the college of education in Turkey, regarding their integration of technology into instruction. They concluded that utilizing collegial communication between faculty members who were further along the innovative-decision making continuum partnered with those who had not yet decided to adopt the technology, would facilitate the adoption of instructional technologies (Sahin and Thompson, 2006). Those faculty members who were already implementing instructional technologies had more positive attitudes about the use of technology for instruction than those who were not (Sahin and Thompson, 2006). Blankenship (1998) similarly focused on technology integration with teachers in grades Pre-Kindergarten through eighth grade. The survey instrument was administered to 233 teachers throughout this school district regarding their use of technology for instruction. Using a multiple regression analysis, frequency response matrices and study group meetings, the author found that with teachers at all grade levels, interpersonal communication channels and training positively affected the movement of the teachers along the innovative-decision making continuum (Blankenship, 1998).

//Communication Channels and Role of the Change Agent//

The importance of communication channels and the role of the change agent for an innovation to be adopted were indicated in a variety of studies (Surendra, 2001; Signer, Hall & Upton, 2000; Blankenship, 1998; Frank, Zhao and Borman, 2004; Hoerup, 2001). Surendra surveyed 109 professors at a community college in Ontario, Canada about their use of web based technology. He found that the diffusion factors that were crucial to adoption were community pressure and support. The more positive the innovation was communicated to others, the more likelihood there was of adoption. Signer, Hall and Upton (2000), Frank, Zhao and Lei (2006), and Hoerup (2001), whether in higher education or K-12 education, concluded that the informal interpersonal communication channels were important at many stages of adoption. Specifically, in their study of the integration of technology, Frank, Zhao and Lei (2006) surveyed teachers in 19 different schools as well as interviews of the administrators at each of the schools. They found that an influential person or change agent in the same social circle or group positively affected the communication of an innovation over time.

//Attributes of the Innovation//

Surendra (2001) and Johnson (2001) found that the innovation itself needs to have positive attributes if it is to be adopted. Surendra (2001), who surveyed community college faculty, found that the trialability of the web based technology was crucial to the technology being adopted. Johnson (2001) conducted surveys and interviews with 19 college faculty members regarding their use of web media objects. Her results were consistent with Surendra (2001). She found that the innovation attributes were among the predictors that lead a web media object to be adopted for use (Johnson, 2001).

Overall, these studies indicate that Roger’s framework regarding diffusion of an innovation can be applied to educational settings and, in particular to the adoption of various technologies in both higher educational and K-12 educational settings. The innovator category of individuals or groups in a school or college has an affect at how quickly an innovation is adopted (Signer, Hall & Upton, 2000; Hoerup, 2001). The interpersonal communication channels play a significant role in how and when an innovation is adopted (Surendra, 2001; Blankenship, 1998; Frank, Zhao and Borman, 2004). Influential individuals, who could also be termed change agents, who work with or teach similar subjects or grade levels with others, are critical in order to have all members of a group adopt an innovation (Frank, Zhao & Borman, 2004; Hoerup, 2001). Finally, if the technology innovation itself is not easy to understand or use, adoption is not likely to occur (Surendra, 2001; Johnson, 2001).

//References//

Blankenship, Strader K. (1998). Factors Related to Teacher Use of Computers in the Classroom. (Doctoral Dissertation, Virginia Polytechnic Institute and State University). //Networked Digital Library of Theses and Dissertations//. (VT 1998-04-27).

Frank, K., Zhao, Y., & Lei, J. (2006). The social life of technology: An ecological analysis of technology diffusion in schools. //Pedagogies: An international journal, 1//(2), 135–149.

Hoerup, Sharon L. (2001). Diffusion of an Innovation: Computer Technology Integration and the Role of Collaboration. (Doctoral dissertation, Virginia Polytechnic Institute and State University, 2001). //Networked Digital Library of Theses and Dissertations//. (VT 2001-12-06).

Johnson, K.T. (2001). Factors influencing the faculty adoption of web media objects: identification and recommendations. (Masters Thesis, Virginia Polytechnic Institute and State University, 2001). //Virginia Polytechnic Institute and State University Digital Library and Archives//. (ETD-02282002-172446). Available at [|http://scholar.lib.vt.edu/theses/available/etd-02282002-172446/.]

Rogers, E. M. (2003). //Diffusion of innovations// (5th ed.). New York: Free Press.

Rogers, E. M. (1995). //Diffusion of innovations// (4th ed.). New York: Free Press.

Sahin, I. & Thompson, A. (2006). Using Rogers’ theory to interpret instructional computer use by COE faculty. //Journal of Research on Technology in Education.// 39, 81-104.

Sahin, I. (2006). Detailed review of Rogers diffusion of innovations theory and educational technology-related studies based on Roger’s theory. //The Turkish Online Journal of Educational Technology//. 5 (2). Available at http://www.tojet.net/articles/523.htm.

Signer, B, Hall, C, & Upton, J. (2000). //A study of faculty concerns and developmental use of web based course tools//. Paper presented at the annual meeting of the American Educational Research Association (New Orleans, LA, April 2000).

Singhal, Arvind and Obregón, Rafael. (2004). A Conversation with Everett Rogers. //Communication Forum for Social Change Consortium//. Retrieved October 1, 2007 http://www.communicationforsocialchange.org/dialogues.php?id=240.

Surendra, S. (2001). Acceptance of web technology based education by professors and administrators of a college of applied arts and technology. (Doctoral dissertation, University of Toronto, 2001). //National Library of Canada//. Available at http://www.collectionscanada.ca/obj/s4/f2/dsk3/ftp04/NQ58603.pdf.

Zhao, Y., Frank, K. & Borman, K. (2004). Social capital and the diffusion of innovations within organizations: The case of computer technology in schools. //Sociology of Education,// 77, 148–171.