June 2008 // Volume 46 // Number 3 // Research in Brief // 3RIB1
An Assessment of County Extension Agents' Adoption of eXtension
Are county agents using eXtension? The purpose of the descriptive study reported here was to determine if agents: (a) had heard of eXtension, (b) understood its purpose and functions, (c) had an opinion about eXtension, (d) had decided if they would use eXtension, (e) were currently using eXtension, and (f) had made a decision about using eXtension in the future. Data were collected from a random sample of Texas Cooperative Extension agents. The majority of respondents had little to no knowledge of eXtension. If eXtension is to gain popularity with agents, more effort must be put into encouraging its adoption.
The relevancy of Cooperative Extension in the 21st century has been called into question (Bull, Cote, Warner, & McKinnie, 2004; Crosby et al., 2002; Rasmussen, 1989). According to Accenture's (2003) business assessment of Cooperative Extension, "cultural and technological changes are quickly outpacing the traditional Extension delivery model" (p. 5). Extension has been challenged to meet the needs of consumers who demand 24-hour access to information (ECOP, 2005).
In response, Cooperative Extension publicly launched an online information resource known as eXtension in 2006. The goal for 2007 is to have at least 75% of all Extension employees as registered users (T. Meisenbach, personal communication, June 6, 2007). Yet, to date, little research has focused on the adoption of this innovation by county Extension agents. A clear need to address this gap in the literature exists, as the adoption of eXtension by county Extension agents is considered to be critical for its success (Accenture, 2003).
The theoretical framework for the study was based on Rogers' (2003) theory of the diffusion of innovations. Rogers defined the innovation-decision process as:
The process through which an individual (or other decision-making unit) passes from gaining initial knowledge of an innovation, to forming an attitude toward the innovation, to making a decision to adopt or reject, to implementation of the new idea, and to confirmation of this decision (p. 168).
The five stages that comprise the process are referred to as (a) knowledge, (b) persuasion, (c) decision, (d) implementation, and (e) confirmation. Early adopters are more likely to positively confirm their decision to implement the innovation than later adopters (Rogers, 2003). Therefore, knowledge of the distribution of individuals throughout the stages of the innovation-decision offers some predictive value for estimating the level of adoption that may occur.
The concept of the innovation-decision process was initially reported by Ryan and Gross (1943). The researchers studied the diffusion of hybrid seed corn and observed that the farmers progressed through a series of decisions and actions before deciding whether or not to adopt the innovation. These decisions and actions were eventually conceptualized as stages in Rogers' (2003) model of the innovation-decision process.
Absent from Rogers' (2003) model was a stage for individuals lacking knowledge and awareness of an innovation. Li (2004) proposed a sixth stage in the innovation-decision process to include such individuals. The incorporation of Li's "no knowledge" stage into Roger's innovation-decision process is useful for assessing marketing efforts designed to foster awareness of an innovation. For this reason, "no knowledge" was included as a stage in the study reported here.
The findings presented here are part of a larger study conducted to understand the influence of selected factors on the adoption of eXtension by Texas Cooperative Extension county Extension agents (Harder, 2007). (See "County Extension Agents' Perceptions of eXtension," Harder & Lindner, 2008, [this issue] for more findings from the study.) The study reported here established baseline data that can be used in a longitudinal assessment of the adoption of eXtension in Texas. Specifically, the researchers sought to determine Texas Cooperative Extension county Extension agents' stages in the innovation-decision process.
The target population was Texas Cooperative Extension county Extension agents employed in 2007. According to the Texas Cooperative Extension office, there were 533 county agents (K. A. Bryan, personal communication, February 12, 2007). Cochran's (1977) formula for calculating sample sizes was used to determine a sample size of 237 participants was needed. Random sampling was used to select the participants for the study (Gall, Gall, & Borg, 2007).
An online questionnaire was used to collect data. The original instrument was based on Li's (2004) study of the diffusion of distance education at the China Agricultural University and was modified by the researchers to fit the context of eXtension. The instrument was reviewed for content validity by a panel of experts composed of faculty members in the Department of Agricultural Education, Leadership, and Communications at Texas A&M University. A pilot test was conducted with Montana State Cooperative Extension county Extension agents to test for face validity and establish reliability.
Participants were asked to indicate their stage in the innovation-decision process by selecting one of six statements that most closely represented their level of involvement with eXtension. The statements each corresponded with a stage in the innovation-decision process (no knowledge, knowledge, persuasion, decision, implementation, and confirmation). Dillman's (2000) Tailored Design Method for Internet questionnaires was used to collect the data. Of the original 237 participant e-mail addresses, 236 were valid. Four reminders were sent in an effort to increase response rate (Dillman, 2000).
A final response rate of 66.90% (N = 158) was obtained. Eight participants opted out. There were 25 responses removed due to missing data, reducing the number of usable responses to 125. Early and late respondents were compared to control for non-response error. No significant difference (p > .05) between early and late respondents existed for participants' stage in the innovation-decision process, so the results of the study were generalizable to the target population (Lindner, Murphy, & Briers, 2001).
The data analysis was conducted by using frequencies and percentages to describe the participants' stages in the innovation-decision process. The use of frequencies and percentages is appropriate to describe categorical data (Gall, Gall, & Borg, 2007).
The objective of the study was to describe agents' stages in the innovation-decision process (no knowledge, knowledge, persuasion, decision, implementation, and confirmation). The majority of agents reported they were in the no knowledge (n = 39) or knowledge (n = 64) stages. The remaining agents were in the implementation (n = 10), persuasion (n = 4), decision (n = 4), or confirmation (n = 3) stages. The distribution of responding agents by stage in the innovation-decision process is shown in Table 1.
|Stage in the Innovation-Decision Process||Corresponding Items||f||%|
|No knowledge||I had never heard of eXtension before reading the description provided in this questionnaire.||39||31.20|
|Knowledge||I understand its purposes and features, but have not decided whether or not I like or dislike eXtension.||64||51.20|
|Persuasion||I have decided. I like or dislike eXtension.||4||3.20|
|Decision||I have decided. I will or will not use eXtension.||4||3.20|
|Implementation||I am using eXtension.||10||8.00|
|Confirmation||I have used eXtension long enough to evaluate whether or not eXtension will be part of my future in Extension.||3||2.40|
Figure 1 displays the percentage of respondents in each of the stages in the innovation-decision process. Due to space constraints, the stages are abbreviated as follows: NK = no knowledge, K = knowledge, P = persuasion, D = decision, I = implementation, and C = confirmation.
Distribution of Respondents in the Stages of the Innovation-Decision Process
Most of the respondents were in the early stages of the innovation-decision process. Thirty-nine (31.20%) agents reported they had "never heard of eXtension before reading the description provided in this questionnaire." The majority of agents (n = 64, 51.20%) had knowledge of eXtension, but had not decided their sentiment towards the program. Very few (n = 13, 10.40%) agents were currently using or had used eXtension.
The findings indicated a widespread lack of knowledge about eXtension. This is particularly troubling, in light of both national and state efforts to increase awareness. This study was timed to coincide with the national Web conference hosted by the eXtension administrative team, held February 21, 2007. Pre-notices for the study were purposively sent on February 22, 2007 to follow the national Web conference. The conference was open to any agent in any state across the country. The conference included a demonstration of the eXtension system, a progress report, and group discussion of eXtension issues (eXtension, n.d.).
Efforts to increase awareness of eXtension at the local level included a February 1, 2007, e-mail from the Head of Information Technology (IT) for Texas Cooperative Extension, which explicitly urged agents to register with eXtension (L. Lippke, personal communication). This was not the first time such an announcement was sent. On November 11, 2006, the Head of IT sent a system-wide message to agents in response to reported concerns about the legitimacy of e-mails being sent to agents from the marketing director of eXtension (L. Lippke, personal communication). A description of eXtension and two hyperlinks to eXtension were provided in that message. In addition, reference was made to four previous occasions on which agents were sent information about eXtension.
Li (2004) described "no knowledge" as "the stage when potential adopters had no knowledge about the innovation at the very beginning of their adoption behavior" (p. 170). Thirty-nine agents claimed to have no knowledge of eXtension, yet there were repeated attempts by state and national officials to provide knowledge about the innovation. It seems improbable that all thirty-nine agents were hired following the February e-mail, which may have caused their relative newness to the system to prevent familiarity with eXtension. Equally unlikely is the chance that the agents had failed to learn about eXtension because they lacked access to e-mail; the only way respondents could access the questionnaire for this study was by using the hyperlink and password provided to them via e-mail.
One explanation may be the respondents in the "no knowledge" category chose to ignore attempts to educate them about eXtension. Rogers (2003) described this phenomenon as selective exposure. Selective exposure is "the tendency to attend to communication messages that are consistent with the individual's existing attitudes and beliefs" (p. 171). Rogers further explained "Individuals consciously or unconsciously avoid messages that are in conflict with their existing predispositions" (p. 171). It is possible agents disregarded communication messages about eXtension because they did not perceive eXtension to be consistent with their attitudes and beliefs about Cooperative Extension. This may continue to be a problem in the future.
An innovation's consistency with a potential adopter's attitudes and beliefs is important in the knowledge stage (Rogers, 2003). During this time period, individuals begin to think about the relevancy of the innovation to their situation. Individuals will not progress beyond the knowledge stage in the innovation-decision process if they believe the innovation is irrelevant or if they lack "sufficient knowledge" to proceed to the persuasion stage (Rogers, p. 174). The large number (n = 64) of respondents in the knowledge stage implies the existence of at least one of these two obstacles to progression.
There was a low number of respondents in the persuasion (n = 4) and decision (n = 4) stages versus the implementation (n = 10) stage. This indicates potential adopters moved relatively quickly through the persuasion and decision stages. It may be assumed the respondents in the implementation stage had formed favorable perceptions of eXtension in the preceding stages. Those with negative perceptions about eXtension would have rejected the innovation in the decision stage and would not have reached implementation (Rogers, 2003). A follow-up study with the individuals in the implementation stage would be useful to determine if they eventually confirmed or rejected their decision to adopt eXtension.
The results of this study indicate Extension agents may not be prepared to promote eXtension to their peers or Extension clientele. The large number of respondents in the no knowledge and knowledge stages implies a widespread lack of both awareness and usage of eXtension. The agents in these early categories are poorly positioned to promote eXtension within their peer and/or community social networks.
Recommendations for practice, based on Rogers' (2003) theory of the diffusion of innovations, are to (a) develop a marketing plan that better communicates how eXtension addresses agents' needs, (b) provide more information about how to use eXtension properly, (c) utilize peer networking to promote eXtension rather than relying solely on mass communications, and (d) provide positive reinforcement for agents who have chosen to adopt eXtension. Implementing these recommendations would be expected to aid agents' progression through the stages in the innovation-decision process.
Research recommendations are to investigate (a) factors related to the potential occurrence of selective exposure, (b) factors related to the high number of respondents in the knowledge stage, (c) personal and professional factors influencing potential adopters' decisions to reject eXtension, (d) personal and professional factors influencing agents' decision to adopt eXtension, and (e) adopters' perceptions of eXtension.
Accenture. (2003, November). e-Extension pre-select business case. Washington, DC: U.S. Department of Agriculture.
Bull, N. H., Cote, L. S., Warner, P. D., & McKinnie, M. R. (2004). Is Extension relevant for the 21st century? Journal of Extension [On-line], 42(6). Available at: http://www.joe.org/joe/2004december/comm2.shtml
Cochran, W. G. (1977). Sampling techniques (3rd ed.). New York: John Wiley & Sons.
Crosby, G, Hamernik, D., Danus, E., Dorsey, M., Hegg, R., Jerkins, D., et al. (2002). Exploring new opportunities for Extension. Retrieved May 24, 2006 from: http://www.csrees.usda.gov/about/white_papers/pdfs/exploring.pdf
Dillman, D. A. (2000). Mail and Internet surveys: The tailored design method (2nd ed.). New York: John Wiley & Sons.
Extension Committee on Organization and Policy. (2005). Extension Committee on Organization and Policy Leadership Advisory Council 2005 report. Washington, DC: National Association of State Universities and Land-Grant Colleges.
eXtension. (n.d.) Retrieved March 22, 2007, from http://www.extension.org/
Gall, M. D., Gall, J. P., & Borg, W. R. (2007). Education research: An introduction (8th ed.). Boston: Pearson Education.
Harder, A. (2007). Characteristics and barriers impacting the diffusion of eXtension among Texas Cooperative Extension county Extension agents. Unpublished doctoral dissertation, Texas A&M University, College Station, TX.
Li, Y. (2004). Faculty perceptions about attributes and barriers impacting diffusion of Web-based distance education (WBDE) at the China Agricultural University. Dissertation Abstracts International, 65(7), 2460A. (UMI No. 3141422).
Lindner, J. R., Murphy, T. H., & Briers, G. E. (2001). Handling nonresponse in social science research. Journal of Agricultural Education, 42(4), 43-53.
Rasmussen, W. (1989). Taking the university to the people. Ames, IA: Iowa State University Press.
Rogers, E. M. (2003). Diffusion of innovations (5th ed.). New York: Free Press
Ryan, B., & Gross, N. C. (1943). The diffusion of hybrid seed corn in two Iowa communities. Rural Sociology, 8, 15-24.
Welcome to eXtension. (n.d.) Retrieved August 2, 2007, from http://www.extension.org/