December 2007 // Volume 45 // Number 6 // Research in Brief // 6RIB1

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Perceptions and Preferences of Extension Programming and Sources Among Extension Users and Non-Users: 10 Kansas Counties

Abstract
County Extension personnel are challenged to serve the public while facing changing population density and diversity. Moreover, needs and satisfaction vary among Extension clients and non-clients. With this in mind, 10 of the most populous counties in Kansas, with the aid of a university researcher, conducted an evaluation to determine programming needs of both clients and non-clients. Findings indicate that non-clients and clients prioritize programming differently and prefer different delivery mechanisms. The results have allowed these counties to tailor their programming and marketing efforts to these two unique groups, while also serving as a basis for a collective marketing plan.


Kristina M. Boone
Department Head
Department of Communications
Manhattan, Kansas
kboone@ksu.edu

Linda Sleichter
Marketing Specialist
Department of Communications
Manhattan, Kansas
lsleicht@oznet.ksu.edu

Rick Miller
County Director
Johnson County Extension Office
Olathe, Kansas
rmilller@oznet.ksu.edu

Sharon Breiner
Graduate Assistant
Manhattan, Kansas
glaenzer@ksu.edu

Kansas State University


Introduction

County Extension personnel are challenged to produce timely and useful services while considering two key issues: do people understand the function and value of Extension, and does Extension fulfill the needs of those that they serve? Finding the answers to these questions is particularly difficult in areas that are facing an increase in population density and diversity.

To better understand these issues among Extension clients and non-clients, a university researcher conducted an evaluation to determine the views of those groups, using the 10 most populous counties in Kansas. What the researcher found is refocusing the approach to addressing these groups and guiding programming and marketing efforts for the future.

Kansas counties have had strong Extension programming and maintained strong support in general from county boards. However, Kansas has seen increasing urbanization. In 2002, K-State Research and Extension realigned its areas, forming one of its five areas based not on geography but on population. This area comprises the most populous counties in the state. Prior to the formation of this new area, 10 of the most populous counties in the state decided to devise a marketing plan together and to collect data upon which to base that plan.

The counties were different in many ways, but facing a common issue: a dramatically changing county population. Kansas population grew 8.5% from 1990 to 2000, but these counties saw growth of 10% on average, indicating that much of the increase in population came from these more populous counties. These counties tended to have higher percentages of ethnicity and Hispanics. The percent of people under 18 years old also is higher in these counties than in the state in general. Income and percent of people living in poverty is variable in these counties, with some of the highest and lowest incomes and percentages in the state, further indicating the diversity in these counties. Despite growth in population, agriculture is still the highest land use in these areas (USDA Kansas Agricultural Statistics Service, 2001).

The Cooperative Extension Service, like other public institutions, is facing greater pressure for accountability and demonstration of results (Boone & Furbee, 1998; Chapman-Novakofski, Boeckner, Canton, Clark, Keim, Britten, & McClelland, 1997; Rennekamp, Warner, Nall, Jacobs, & Maurer, 2001). Extension is challenged to provide timely, useful service, which has become the organization's hallmark (Greene, 1995).

When a service is not recognized as having significant public value, citizens believe it should be purchased on the private market for a price (Kalambokidis, 2004). Information that illustrates the value of an organization is vital to the decision makers of an organization. When considering value, these decision makers analyze both customer service and measurement of performance through outcomes.

Meeting clientele needs has become increasingly difficult for Extension, as the audiences have grown and diversified. At the same time, resources have diminished (Smith & Swisher, 1986). Some systems have sought differing solutions to address these issues, including building relationships with other service organizations (Martin-Milius, 1994). In Kansas, demographic shifts have prompted a realignment of Extension areas, leading to a creation of an area office serving not a geographic region but population centers. These counties are working together to address urbanization issues and marketing efforts. For their marketing plan, they developed a study to analyze client and non-client attitudes and needs. The purpose of the study reported here was to guide marketing and planning processes.

A mixed-modal survey was used in which clients received a mail survey, while non-clients were contacted using a telephone survey (Dillman, 2000). Data were collected in fall 2002. The questionnaires were very brief and were evaluated by a panel of experts with K-State Research and Extension for face and content validity.

Findings indicate variability from county to county, but in general non-clients and clients prioritize programming differently and prefer different delivery mechanisms. The findings are being used as a basis for a collective marketing plan and as a means to achieve agreement among the counties.

Methods

Surveys were administered to Extension users and non-users in the summer and fall of 2002. These individuals were located in the 10 most populous counties in Kansas. Questionnaires were developed for both groups based on prior work in Johnson County. The survey relied upon the Johnson County instrument for reliability. The survey was mixed modal.

County offices submitted mailing lists for their users. A random sample of 150 was drawn from each county list. These surveys were then administered utilizing the Tailored Design Method (Dillman, 2000). For non-users, a sampling company drew random telephone numbers totaling 450 numbers per county. Trained data collectors telephoned non-users, for their responses.

Data was analyzed in the Department of Communications and Department of Statistics using SPSS/PC+.

Results

Data were collected from 481 known Extension users and 449 people who were randomly sampled from the same counties (referred to as "non-users" for this article). The summary data are presented here. For both samples, more women responded than men, although the percentage of men responding was not particularly low. In comparing users to non-users, users were generally older and had higher household income levels. More than 40% of non-users were younger than 45, while only 22% of users were under 45. Almost ¼ of non-users had incomes of less than $20,000 per year, while only 6% of users fell into the same category. Thirty-five percent of users had household incomes of $40,000 or less, while 53% of non-users earned $40,000 or less per year (Table 1).

Table 1.
Demographic Summary of Users and Non-Users

Variable% Users% Non-Users
Age18-34522
35-441720
45-542819
55-641615
65-741912
75+1612
GenderMale4332
Female5768
Income<$20,000624
$20,000-40,0002929
$41,000-60,0002724
$61,000-80,000179
$81,000-100,000128
>$100,00096
User N = 481
Non-user N = 449

Among non-users, there was significant recognition of the organization, much more so than in previous statewide surveys. Seventy percent had heard of the organization, and 56% correctly identified its affiliation with Kansas State University. Almost 40% indicated they had used the service at one time (Table 2).

Table 2.
Non-User Familiarity with K-State Research and Extension

Variable%
Heard of Organization
Yes70
No30
Used Service
Yes37
No63
University Affiliation
K-State56
KU12
Don't know23
No answer9
Other university3

Both user and non-user groups indicated satisfaction with the services/materials they had received from K-State Research and Extension (Table 3). This question was asked only of the non-users who had indicated they had received information/services from the organization. Of the users, 95% indicated that they were very satisfied or satisfied, while 93% of non-users indicated the same.

Table 3.
Satisfaction with K-State Research and Extension

Level of Satisfaction% Users% Non-Users
Very Satisfied6471
Satisfied3122
Neutral26
Dissatisfied21
Very Dissatisfied10

Data on preferred methods of delivery for educational information are presented in Table 4. For this question, respondents were asked to rate each method on a scale of 1 to 5, with 1 being not very likely to use and 5 being very likely to use. The mean is the average of the ratings, while the standard deviation (s.d.) provides a measure of the dispersion of the data. The mode is the most frequently occurring category, and, like the mean, is a measure of central tendency. The ranking based on means is presented as another way to compare the methods.

Among users, newsletters were the most highly rated method, followed by newspaper and classes/meetings. Television, which was not rated highly overall, received ratings of 5 from more than 20% of users, indicating that it is used highly by a portion of the group but not overall. Eighty-five percent of users indicated that they read the county Extension newsletter.

The non-user group rated the methods differently. Newspaper, television, and radio were rated the highest. Classes/meetings were rated lowest. The Internet was rated by 35% of non-users as not very likely to use, but 27% rated it as very likely to use, indicating that they either rely on it heavily or not at all.

Table 4.
Preferred Methods of Educational Information Delivery

MethodUserNon-UserT-value
Means.d.ModeRankMeans.d.ModeRank
Newsletter4.351.11512.941.432416.6667†
Internet2.651.55162.921.641*5-2.5763†
Newspaper3.561.39523.631.3251-0.7883†
TV2.861.481*43.621.2752-8.3978†
Radio2.831.49153.281.2433-5.0223†
Classes3.191.463/532.521.30167.4115†
Scale: 1=not very likely to use, 5=very likely to use
*Next most frequently occurring category was 5
†Of significant difference
Note: Of users, 85% indicated reading the county newsletter

The remaining questions asked both groups about the importance of subject matter areas on which K-State Research and Extension provides information/expertise. The groups were asked to rate the subject areas based on their importance to the respondents as individuals (Table 5) and their importance to the community (Table 6).

Among users, most subject areas were rated as important, with six subjects with modes of great importance (5). The mode for community development was 3, while the mode for family skills was 4. Family skills might have been rated somewhat lower because the user group was older. While the farming/ranching mode was 5, the next most frequently occurring category was 1, indicating a split distribution. Responses for environmental preservation and family skills clustered around ratings of 3, 4, and 5.

Non-users also rated subject areas highly, with all but farming receiving a mode of 5. Farming/ranching had the lowest mean and mode.

When asked to describe the importance subject areas to their communities, both user and non-user groups showed greater agreement. Standard deviations for every subject area decreased when compared to the data related to importance on an individual basis. Thus, there was less variability and greater agreement exhibited in the data.

Users rated every subject area high for the importance in the community, with each having a mode of 5. Modes for non-users were 5 in each area, except lawn and gardening, where they were equally split between 3 and 4. Interestingly, farming and ranching, which had a mode of 1 for individual importance to non-users, had a mode of 5 when the group viewed its importance to the community. This probably relates to the recognition of the economic value of agriculture to the community.

Table 5.
Importance of Subject Matter to Individual

MethodUserNon-UserT-value
Means.d.ModeRankMeans.d.ModeRank
Farming/ranching3.342.445*62.601.59175.510 †
Environment Preservation3.461.365**43.701.3254/5 -2.730†
Community Development3.151.20383.701.1654/5 -7.096†
Family Skills3.331.384**73.871.2653-6.235†
Health and Safety3.631.25534.131.1151-6.485†
Youth Development3.431.46553.881.2552 -5.050†
Lawn/Gardening4.061.11513.391.34568.271†
Scale: 1=little or no importance to you, 5=great importance to you
*Next most frequently occurring category was 1
**Categories of 3, 4, and 5 all with greater than 20 percent
***Included description of food and nutrition in phone survey
†Of significant difference

Table 6.
Importance of Subject Matter to Community

MethodUserNon-userT-value
Means.d.ModeRankMeans.d.ModeRank
Farming/ranching3.831.3556/73.471.45563.9088†
Environment Preservation3.911.1554/5/63.831.1355 1.0738
Community Development3.911.1654/5/64.091.0452-2.4965†
Family Skills3.831.1556/74.001.0553-2.3448†
Health and Safety3.911.1454/5/64.200.9651-4.1847†
Youth Development4.051.16514.071.0854-0.2721
Lawn/Gardening4.001.08523.411.183/477.9408†
Scale: 1=little or no importance to you, 5=great importance to you
*Included description of food and nutrition in phone survey
†Of significant difference

Discussion

Among non-users there was strong awareness of K-State Research and Extension and recognition of the tie to Kansas State University. This indicates success of these identity awareness programs.

Among those who had used K-State Research and Extension, there were high levels of satisfaction, both among users and non-users. Users differ from non-users in several important areas, and some of these are demonstrated by demographics. Users tended to be older and had higher incomes. They also preferred traditional methods of information delivery (newsletters and classes/meetings). Non-users were more oriented to mass media, which might be used to create more awareness and bring them to reliance on newsletters, etc. Among non-users, those who use the Internet rely on it for information but those who do not use the Internet did not value it as an information delivery method, a finding that demonstrates the digital divide.

Respondents rated Extension's subject areas as important for almost every category. Among users, the overall rating of farming/ranching was high, but there was a split in those data, with many users indicating it was unimportant to them. Users also exhibited less agreement on environmental preservation and community development, perhaps because these are considered more societal goods than individual goods.

There was greater agreement about the importance of subject areas to the community, with high ratings to all subjects. These data can be interpreted as community values/benefits. As one writes key messages they may consider positioning messages as individual or community benefits.

From a marketing perspective, these data could be used to build strategies to reach key audiences and reach beyond traditional clientele groups. Mass media may be an important tool for reaching these non-users. Once they have greater awareness of the organization, they may become more reliant on more traditional informational tools, especially newsletters. Given the pace of lifestyles today, it is doubtful that classes/meetings will grow much in popularity, but may be more important for particular hands-on/interactive learning activities or for particular targeted groups. The Internet also holds potential here. It is important as well to remember to provide existing users with the information and informational tools that they value and to continue to serve their needs.

References

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Chapman-Novakofski, K., Boeckner, L. S., Canton, R., Clark, C. D., Keim, K., Britten, P., & McClelland, J. (1997). Evaluating evaluation--What we've learned. Journal of Extension [On-line], 35(1). Available at: http://www.joe.org/joe/1997february/rb2.html

Dillman, D. A. (2000). Mail and Internet surveys: The tailored design method. Second Edition. John Wiley & Sons, Inc., New York. (p.217-244).

Greene, S. S. (1995). Cooperative Extension: The service challenge. Journal of Extension [On-line], 33(6). Available at: http://www.joe.org/joe/1995december/comm1.html

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Martin-Milius, T. (1994). University to community and back: Creating a customer focused process. Paper presented at the Fifth Annual Conference on TQM in Colleges and Universities: Reengineering the University. Chicago, IL.

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Rennekamp, R. A., Warner, P. D., Nall, M. A., Jacobs, C., & Maurer, R. C. (2001). An examination of customer satisfaction in the Kentucky Cooperative Extension Service. Journal of Extension [On-line], 39(2). Available at: http://www.joe.org/joe/2001april/rb5.html

Smith, M. F., & Swisher, M. E. (1986). The best little programming tool in Extension: Audience identification helps determine needs and justify programs. Journal of Extension [On-line], 24(3). Available at: http://www.joe.org/joe/1986fall/a3.html

U.S. Census (2001). State and county quick facts for Johnson County, Kansas. Available at: http://quickfacts.census.gov/qfd/states/20/20091.html

U.S. Department of Agriculture, Kansas Agricultural Statistics Service. (2001). 1997 Census of Agriculture County Profile, Johnson, Kansas. Available at: http://www.nass.usda.gov/census/census97/profiles/ks/ks.htm