October 2005
Volume 43 Number 5

Research in Brief

An Evaluative Study of the United States Cooperative Extension Service's Role in Bridging the Digital Divide

Chanda D. Elbert
Assistant Professor
Department of Agricultural Education
Texas A&M University
College Station, Texas
Celbert@tamu.edu

Antoine J. Alston
Associate Professor
Department of Agribusiness, Applied Economics and Agriscience Education
North Carolina A&T State University
Greensboro, North Carolina
alstona@ncat.edu

Introduction

Access to the Internet and other digital technologies has rapidly become a necessary tool to function in today's highly information-rich society. The Internet is utilized by Americans for a variety of tasks such as business transactions, personal correspondence, research and information gathering, and shopping. In order for an individual to advance economically, educationally, and socially, being digitally connected is even more vital. "Now that a large number of Americans regularly use the Internet to conduct daily activities, people who lack access to these tools are at a growing disadvantage. Therefore, raising the level of digital inclusion by increasing the number of Americans using the technology tools of the digital age is a vitally important national goal" (U.S. Department of Commerce, 2000).

This phenomenon of individuals lacking digital access is popularly known as the "digital divide." The digital divide, as defined by Cyber Outreach (2002), is "the gap that separates those who have access to technology and the Internet and those who do not, a disparity which exists along the lines of education, income, and race." What role can the United States Cooperative Extension Service play in alleviating the digital divide?

Digital Divide Demographic Overview

Overall, the number of households with access to the Internet has increased; additionally, more households are increasingly acquiring computers. The gap between rural households and households nationwide narrowed in 2000; however, a great disparity still exists. Additionally, in relation to age, while younger Americans are most likely to utilize the Internet, an increasing number of Americans over the age of 50 are becoming connected to the Web for leisure and occupational purposes.

The number of individuals using the Internet rose by a third from 32.7 in December 1998, to 44.4% in August of 2000 (U.S. Department of Commerce, 2000). However, disparities still exist economically, socially, ethnically, and racially. Individuals with the greatest access to digital technology are Whites and Asians/Pacific Islanders, who, on the average, have higher incomes, more education, and dual-parent households. Moreover, the information-poor are usually African-Americans or Hispanics, who, statistically, have lower incomes and education levels than the information rich and who also often reside in rural areas or central cities (Cyber Outreach, 2002).

According to Cyber Outreach (2002), households with incomes of $75,000 and higher are more than 20 times more likely to have access to the Internet than those at the lowest income levels and more than nine times as likely to have a computer at home. African-American and Hispanic households are approximately one-third as likely to have home Internet access, as are households of Asian/Pacific Islander descent and approximately two-fifths as likely as are White households. The theoretical framework for this study was guided by Rogers's (1995) diffusion of innovations theory.

Purpose and Objectives

The purpose of this study was to determine the perceptions of Extension administrators throughout the United States toward bridging the digital divide. Three objectives were developed to guide the study:

1. To determine the demographic characteristics of Extension administrators throughout the United States;

2. To determine the perceptions of Extension administrators regarding socio-demographics in relation to the digital divide;

3. To determine the role of Extension in bridging the digital divide as perceived by Extension administrators throughout the United States.

Methodology

A census study of all 82 state Extension Service directors as listed in the 2002 Directory of State Extension Service Directors and Administrators was conducted. A mixed mode survey design was utilized, combining traditional mailings with email surveying (Dillman, 2002). Researchers designed a survey instrument based on the objectives of the study. The instrument consisted of three sections: Part I. Digital Divide Socio-Demographic Characteristics, Part II. Extension in the Digital Divide, and Part III. Demographics. Parts I and II consisted of Likert-type items; Part III consisted of a series of open-ended and multiple-choice items.

The validity of the instrument was verified by a panel of university professors at both institutions. A pilot test of the instrument to measure instrument reliability was conducted in February 2003 with 15 of the state Extension directors and administrators listed in the directory. The survey was sent by email to Extension directors, with instructions to return the survey within a week: 10 surveys were returned. No adjustments were made to the instrument as a result of the pilot study. The pilot study resulted in a Cronbach's alpha reliability coefficient of .88; thus, the instrument was deemed to be reliable.

The final survey was conducted on the remaining 67 Extension administrators. An initial letter notifying the Extension administrators of the survey was sent by mail 1 week after the pilot study concluded. Respondents were asked to verify their correct email addresses if different from the ones stated in the letter by sending the correct ones electronically to the researchers. Those who preferred a traditional mail survey were allowed this option and were asked to notify the researchers accordingly.

One week after the initial mailing, the survey was sent to each administrator by email with instructions. After 1 week, a reminder email was sent, which resulted in 10 more surveys being received. After this had been accomplished, a full survey packet was mailed to all non-respondents through traditional mail, which resulted in five more surveys. Finally, follow-up phone calls were made to all nonrespondents in order to yield a maximum return rate; five more surveys were received from this round. The final response rate was 35% (N = 24).

Because the number of responses was small, because the pilot study participants were members of the target population, and because the pilot study did not result in any changes to the instrument, it was decided by the research team to pool the pilot study results with the final results, which yielded an overall all response rate of 43% (N = 36). In order to control for nonresponse error, Lindner, Murphy, and Briers (2001) recommended comparing early to late respondents. Research has shown that late respondents are often similar to nonrespondents; no differences were found.

Findings

Objective One

A substantial number of the respondents were male (86%). Nearly 80% were white, and 17% were black. The majority (86%) of Extension administrators possessed a doctorate and had been with Extension for an average of 11-15 years. Respondents had been administrators for an average of 11 years and had taken between three-five training programs in the area of technology since January 2000.

For the purpose of data analysis, readers should utilize the following specifications when interpreting Tables 1 and 2: 1-1.49 = Strongly Disagree; 1.50-2.49 = Disagree; 2.50-3.49 = Uncertain; 3.50-4.49 = Agree; and 4.5-5.0 = Strongly Agree.

Objective Two

The following results were found for objective two. In viewing Table 1, Extension administrators felt that 4-H could play an imperative role advancing in technology to improve their daily lives. While on the other hand, the mean scores indicated that the people who have most to gain are the least likely to have access to technology.

Objective Three

The following section presents the findings of this research study for objective three.

Conclusions

Based on the findings of this study, the following conclusions were reached.

1. Extension administrators perceived that the gap between rural and urban residents in relation to technology had narrowed, but still existed. In order for rural residents to take advantage of the benefits of technology, they must first be given exposure to its existence, shown the relative advantage of the technology, and allowed the opportunity to explore the innovation for their own personal use all major components of Roger's diffusion theory (1995). Extension could serve as a channel of communication to give exposure to digital technology, while simultaneously acting as a change agent encouraging more technology adoption.

2. 4-H was perceived to be a mechanism to infuse knowledge of technological innovation into youth. This directly corresponds to Roger's diffusion theory (1995), which emphasized that individuals or organizations can serve as change agents to bring about new innovations in a society. This idea was supported in a study conducted by Kolodinsky, Cranwell, and Rowe (2002) who reported that 4-H teens training senior citizens on the Internet resulted in a positive learning experience that was expressed by both groups.

3. Extension administrators perceived that minority and low-income communities could gain wider access to technology with the aid of Extension. Extension could serve as the change agent for innovation as outlined by Roger (1995). Kolodinsky et al. suggested that programs could be developed with teens/or senior citizens to reach diverse audiences such as economically disadvantaged youth and adults, special needs groups, and geographically dislocated.

4. Education was perceived as a contributing factor in whether an individual adopts a technology. This directly corresponds to Roger's diffusion theory (1995), which emphasized that innovators and early adopting individuals tend to be of higher educational levels. In contrast, a study conducted by Hall, Dunkelberger, Ferreira, Prevatt, and Martin (2003) found that education played only a supporting role in determining PC and internet adoption; however, when the researchers controlled for age, education was less significant. In this regard, it was found that adoption related to having young people in the household was positive in providing exposure to the use of technology.

5. Extension administrators were uncertain if the United States Cooperative Extension Service as a whole was adequately prepared to address the current digital divide. Additionally, they stated that county Extension offices should be equipped and staffed to serve as centers of learning for technology. Moreover, they indicated a need for Extension personnel to receive more training in the area of information technology. In relation to Roger's diffusion theory (1995), Extension personnel must be highly equipped and trained if they are to act as change agents in society, serving as models of innovations and practice.

Recommendations

Based on the conclusions of this study, the following recommendations are given.

1. Strategic partnerships should be formed between Extension and local community organizations to infuse technology through training programs and the establishment of community technology centers, particularly in rural, minority, and low-income communities.

2. Continuous in-service training programs in relation to digital technology should be provided to Extension personnel in order for them to serve as change agents in their respective localities.

3. Special funding should be provided to Extension organizations from state legislatures to help address the digital divide impacting society as a whole, in order to establish special technology initiatives.

4. States should assess how well their counties are actively addressing the needs in which administrators perceive to be important.

Implications

The "Digital Divide" has become more pronounced across racial, ethnic, economic, and geographic lines over the past decade as technology continues to advance. What role can the United States Cooperative Extension Service play in alleviating this growing national concern? In February 2002, The National Association of State Universities and Land-Grant Colleges (NASULGC) Extension Committee on Organization and Policy (ECOP) in the report "The Extension System--A Vision for the 21st Century" established Information Technology as an initiative. If Cooperative Extension is to expand its role as a "brand name" quality source for unbiased, research-based information and education, it must be cognizant of the growing Digital Divide throughout the United States and be a proactive source of change.

References

The Cooperative State, Research, and Extension Service, United States Department of Agriculture. (2002) State Extension Service directors and administrators directory. Retrieved July 3, 2002, from http://www.reeusda.gov/hrd/state.doc

Cyber Outreach (2002). What is the digital divide? Retrieved June 28, 2002 from http://www.sas.upenn.edu/~mxcantor/co/what.html

Dillman, D. A. (2000). Mail and Internet surveys-The tailored design method. New York: John Wiley and Sons.

Extension Committee on Organization and Policy. August 1995. Framing the future: Strategic framework for a system of partnerships. Champaign, IL: University of Illinois Cooperative Extension Service.

U.S. Department of Commerce. (2000). Falling through the net: Towards digital inclusion. National Telecommunications and Information Administration

Kolodinsky J. Cranwell M., & Rowe E. (2002). Bridging the generation gap across the digital divide: Teens teaching Internet skills to senior citizens. Journal of Extension [Online], 40(3). Available at: http://www.joe.org/joe/2002june/rb2.html

Lindner, J. R. (2002). Handling nonresponse in international agricultural and Extension education research. Journal of International Agricultural and Extension Education, 9(3), 55-60.

Lindner, J. R., Murphy, T. H., & Briers, G. (2001). Handling nonresponse in social science research. Journal of Agricultural Education, 42(4), 43-53.

National Association of State Universities and Land Grant Colleges – Extension Committee on Organization and Policy (ECOP) (2002). The Extension System--A vision for the 21st century. Washington D.C.: National Association of State Universities and Land Grant Colleges.

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

U.S. Department of Commerce, Economic and Statistics Administration National Telecommunications and Information Administration (October, 2000). Falling through the net: Toward digital inclusion: A report on America's access to technology tools.

An On-Line Survey Process for Assessing Impact of an Email-Delivered Pest Advisory

Sean Malone
Research Specialist
smalone@vt.edu

D. Ames Herbert, Jr.
Professor
herbert@vt.edu

Thomas P. Kuhar
Assistant Professor
tkuhar@vt.edu

Virginia Tech Department of Entomology
Blacksburg, Virginia

Introduction

Documenting impact is a necessary component of current Extension programming. This article describes a new email-delivered pest advisory and a survey process for evaluating its usefulness and impact. The process we used was relatively easy, required only a few hours of concentrated effort and expertise, was inexpensive, and generated very useful and reportable impact data.

The Internet has become an essential and cost-effective tool for Extension (Mayadas 1997; Muske, Goetting, & Vukonich, 2001). Tennessen, PonTell, Romine, and Motheral (1997) emphasize that Extension should maximize the use of the Internet to improve the efficiency of its operations. Since the early 1990's, integrated pest management (IPM) specialists in Virginia have been using email to convey information to Extension personnel and to their own circulation lists of growers and clientele. The information in these emails was further disseminated by Extension personnel forwarding the message, or by cutting and pasting the information into newsletters or Internet homepages. Although this system of information dissemination represented a vast improvement in efficiency over that of decades ago, it was not without its flaws. On occasion the forwarded content from a specialist would be taken out of context, or the author would not be credited for his or her work. Moreover, clientele and other Extension personnel would receive a jumble of information, sometimes from several different sources.

In July 2004 we launched the Virginia Ag Pest Advisory <http://www.sripmc.org/virginia/> in cooperation with the Southern Region IPM Center in Raleigh, NC. The advisory is a Web site that compiles pest updates from multiple IPM specialists. Specialists enter their update(s) at a time that is convenient, and each entry is categorized by commodity and pest group. The compiled advisory is automatically emailed once a week to the recipient list. Individual entries can be viewed or the entire newsletter. The advantage of this system to the recipient is that it is a single-source provider of updated pest information. Everything is in one location, and users become accustomed to having it delivered at the same time each week.

Documenting impact of Extension programs can be challenging. Mail, telephone, hand-out, and face-to-face surveys are useful but can be very time consuming, expensive, and hard to sustain year after year. The on-line survey process described here reached a large number of people easily, anonymously, and worked well to evaluate the impact of the new pest advisory.

Procedures

In order to assess the usefulness and impact of the Virginia Ag Pest Advisory, we conducted an on-line survey of all 346 email recipients at the end of the field season in 2004. The recipient list included 129 Virginia Cooperative Extension Agriculture and Natural Resource Agents linked by a listserv and 217 agricultural industry personnel and farmers. We used "survey.vt.edu" to design the questions and collect survey data. "Survey.vt.edu" is an Internet-based tool that is available to all Virginia Tech faculty, staff, and students. The survey Web site (http://survey.vt.edu) is designed for ease-of-use and can be accessed with any Internet browser. The Web site automatically compiles and summarizes the responses to the survey and an up-to-date summary report of the survey can be obtained at any time by the authorized administrators.

There were a total of nine survey questions concerning the advisory (five multiple choice and four short answer) concerning usage statistics, usefulness of the information and how it affected IPM practices, and suggestions for improvement. Figure 1 shows the first three survey questions as a respondent's Internet browser would display them. An email that hyperlinked the survey was sent on September 16, and the survey remained open for data collection for approximately 1 month. In addition, a reminder email was sent on October 13.

Figure 1.
Partial On-Line Survey

Results and Discussion

The survey measured kinds of information described by Taylor-Powell and Renner (2000), including participant reactions (e.g., usefulness and influence of the advisory), teaching and facilitation (e.g., suggestions for improving the advisory), outcomes (e.g., perceived changes in knowledge and IPM practices), and future programming (e.g., asking what information would be useful in next year's advisory). This information may be useful for evaluating programs, especially for assessing some short- and medium-term outcomes as described by the University of Wisconsin Extension's "Logic Model" (2004).

Short-term outcome assessments included measuring the participants' awareness and opinions of the advisory and their perceived knowledge gained (e.g., improving their understanding of agricultural pest problems). Medium-term outcomes included decision-making assessment (e.g., how the advisory aided in choice of pesticide products, rates, and timing). This process may serve as a simple, cost-effective model for documenting impact of many kinds of Extension programs.

Results of the Survey

There were 119 responses to our survey (34.4% response rate). Eighty-seven percent of respondents had accessed the Virginia Ag Pest Advisory during the season. Sixty-eight percent of respondents who accessed the advisory did so once a week. Twenty percent viewed it less than once a week, and 8% accessed it more than once a week.

A majority of the respondents found the advisory to be useful (Table 1). On a Likert scale of 1 (not useful) to 5 (very useful), the mean was 4.0 (SD = 0.88). In addition, most respondents reported that the advisory influenced their (or their clients') pest management practices (Table 2). On a Likert scale of 1 = did not influence and 5 = greatly influenced, the mean response was 3.3 (SD = 0.93).

Based on responses to a list of other questions in the survey (Table 3), the Virginia Ag Pest Advisory clearly had a strong impact on educating clientele on agricultural pest problems and pesticide use. For instance, comments by respondents included: "[the advisory was] excellent for alerting farmers for possible insect problems" and "[the advisory] aided me in providing Extension updates about insect monitoring and treatment recommendations."

Suggestions from the Survey

Suggestions from the survey respondents for improving the information contained in the advisory included:

• Including more information on other crops (wheat; grape) and home gardening

• Expanding the advisory coverage area (include information from: northeast and southeast United States; South Carolina and North Carolina; northern Virginia; southwest Virginia)

• Provide digital photographs, audio, and links to other Web sites for more information on pests

• Provide a quick way to identify insects

• Provide color maps showing movement and prevalence of pests and make pest forecasts

• Increase the content of the advisory (provide more information on: daily blacklight trap catches; soybean aphid thresholds and how soybean aphids affect the plant; corn borer damage in corn and cotton; weeds and herbicides; seed treatments; vegetable pests; ornamental pests)

Suggestions from the survey respondents for improving the delivery of the advisory included:

• Send out emails more often during peak times of the growing season
• Distribute pest information via cell phone messages or by calling a toll-free number
• Include the full text of each advisory in the email in case someone has a slow Internet connection
• Make accessing the information easier
• Deliver the advisory on Fridays

Our Thoughts on the Survey Suggestions

Additional authors would help to improve the advisory by increasing crop and pest expertise and would also increase the coverage area. Photographs, audio, and image files would be a welcome addition and would help to keep the advisory graphically appealing, but large file sizes will slow down Internet connection speed and make it more difficult for people to print the advisory. A solution may be to include "extras" in an attachment--authors currently may attach one file to each of their posts--thus keeping the main screen simple and uncluttered.

Forty-eight of 58 respondents thought that email delivery of the advisory was an adequate notification system. Monday email deliveries were satisfactory for most people; however, four respondents said that they would prefer Friday email deliveries because they read more articles over the weekend or that it made it easier to schedule their work plans for the following week.

Emails provide fast, practical, convenient delivery; however, problems do arise. Some people had emails blocked by anti-spam software--in one case, this required the Web site administrator to go to the client's email host and certify that the message was not spam. Also, one may have to adjust his or her email filters so that messages from the sender are not blocked.

Having no file attachments, emails should take a minimum amount of time to receive and open. However, users with slow Internet service may become frustrated by waiting for pages to load and may miss some useful articles. For example, one user commented that "when I have to click on something and wait I often decide to just delete and go." Therefore, some would benefit from having a hard-copy printout, phone message, or other method of delivery, and Extension should work with these people to achieve desired results.

Conclusions

The Virginia Ag Pest Advisory is a useful information dissemination tool that simplifies the process of collecting input from IPM specialists and distributing the information in a timely manner. Growers, Extension and agricultural industry personnel, and others will benefit from the advisory's rapid dissemination of information; it's "anytime, anyplace" availability; and knowing that the information is reliable because it comes directly from specialists.

The on-line survey was user-friendly, easy to create, and inexpensive. It served as a model for providing useful numerical program impact data. Additionally, it provided written responses by survey participants that will help improve the system and would easily fit into a program assessment report. We hope to expand, enhance, and optimize the use of the advisory to support our clientele and to promote on-line surveys for improving Extension programs and reporting impact data to Extension administrators.

Acknowledgments

Ron Stinner, Steve Toth, and the staff of the Southern Region IPM Center in Raleigh, NC are thanked for their assistance in developing the Virginia Ag Pest Advisory. We also acknowledge Lex Bruce (Virginia Cooperative Extension, Blacksburg, VA) for his assistance with the survey.

References

Logic Model. University of Wisconsin Extension, Madison, WI. Retrieved November 29, 2004 from: http://www.uwex.edu/ces/pdande/evaluation/evallogicmodel.html

Mayadas, F. (1997). Asynchronous learning networks: a Sloan Foundation perspective. Journal of Asynchronous Learning Networks, 1 (1). Available at:

http://www.sloan-c.org/publications/jaln/v1n1/v1n1_mayadas.asp

Muske, G., Goetting, M., & Vukonich, M. (2001). The World Wide Web: A training tool for family resource management educators. Journal of Extension [On-line], 39(4). Available at: http://www.joe.org/joe/2001august/a3.html

Tennessen, D.J., PonTell, S., Romine, V., & Motheral, S.W. (1997). Opportunities for Cooperative Extension and local communities in the information age. Journal of Extension [On-line], 35(5). Available at: http://www.joe.org/joe/1997october/comm1.html

Taylor-Powell, E., & Renner, M. (2000). Collecting evaluation data: End-of-session questionnaires. University of Wisconsin Extension, Madison, WI. Available at: http://cecommerce.uwex.edu/pdfs/G3658_11.PDF

Determinants of Irrigation Farmers' Crop Choice and Acreage Allocation Decisions: Opportunities for Extension Service Delivery

Jeffrey D. Mullen
Assistant Professor
jmullen@agecon.uga.edu

Cesar Escalante
Assistant Professor
cescalante@agecon.uga.edu

Gerrit Hoogenboom
Professor
gerrit@griffin.uga.edu

Yingzhuo Yu
Research Assistant
yyu@agecon.uga.edu

University of Georgia
Athens, Georgia

Introduction

In the information and outreach market that was once dominated by Extension programs from land-grant universities, rapid technological advancements have created opportunities for other private data providers to compete with university Extension services in offering fast, convenient, open access information (Ilvento, 1997). At the same time, urbanization and industrialization trends have restructured most of the country's rural communities. As we look across the modern rural landscape, we see more mechanized farm operations, the consolidation of smaller farm businesses, and the adoption of technologies designed to produce highly specialized products (USDA, 1999). In this new landscape, the clientele of agricultural Extension services have redefined their information needs, with more specialized producers leaning more toward alternative sources of public information (Ilvento, 1997; King & Boehlje, 2000).

Surveys conducted over the years show a gradual decline in farmers' demand for university outreach services (Ford & Baab, 1989; Ortmann, Patrick, Musser, & Doster, 1991). To spur university Extension programs to recapture their market share and reputation as a reliable source of relevant information, King and Boehlje (2000) issued a challenge for these institutions to identify "newly defined niches of technology-mediated outreach (intended) for broader audience segments."

More recent studies have confirmed that ample opportunities still exist for university Extension programs. More than 50% of the farmer respondents to a survey in Michigan in 1999 emphasized the need for outreach programs in marketing, business management, and farm economics, in addition to traditional Extension topics such as pesticide use and plant genetics (Suvedi, Lapinski, & Campo, 2000). Three years earlier, programs related to farm economics did not receive high significance ratings.

Lavis and Blackburn (1990) analyzed Extension clientele satisfaction and found that, while older farmers were generally more satisfied with the delivery of Extension services, much of the demand for such services actually came from younger, full-time farmers operating larger farm businesses that require more specialized information. These younger farmers also tended to be more educated. These results are not outdated, as the same trends are still evident in a more recent study of diffusion-adoption stages and the use of information technology by farmers (Hall, Dunkelberger, Ferreira, Prevatt, & Martin, 2003). Most of the respondents in the Hall survey who were classified as technology innovators were younger, more educated operators of larger beef and peanut farms in the Southeast region. Age and education are also correlated with early adoption of information technology.

This article presents the results of a survey of Georgia irrigators that focused on the determinants of farmers' crop choice and crop acreage allocation decisions. The purpose of the survey was to identify opportunities for the delivery of university Extension services. The survey also addressed farmer interest in open-access information and decision support programs delivered by the University of Georgia via the Internet. The results of the survey should be beneficial to Extension programs in determining priority areas of involvement.

Data

Irrigation permits were required in Georgia beginning in 1988, although voluntary permits were encouraged prior to that date. By 2001, more than 21,000 irrigation permits had been issued by the Department of Natural Resources. Many farms have obtained multiple permits. By screening the permit database for multiple entries based on phone numbers, farm corporations, address, and name, one can identify 8,677 unique permit holders. Of the unique permits, 8,279 had listed phone numbers. From those 8,279 permits, a random sample of 195 farmers in Georgia was drawn for the survey. The sample was stratified to ensure proportional representation among groundwater and surface water users.

The database from which the sample was drawn represents the best information available concerning irrigation permits in Georgia. It includes all permits issued. Some of the permits within the database, however, are not exercised by the permit holder.

Attempts were made to contact the farmers in the sample by telephone in June of 2004. Of the 195 farmers in the sample, 37% (72 farmers) completed the survey. Another 8% (16 farmers) had retired from farming. The remaining 55% were either unavailable (69 farmers) or refused to complete the survey (38 farmers).

The questionnaire focused on the factors farmers consider when making two key decisions about use of their irrigated acres: which crops to plant and the number of irrigated acres to allocate to each crop. The questions were structured to limit the possibility of misinterpreting the results.

While the overall response rate was lower than had been hoped, of those who were contacted that were not retired, the survey response rate was 65%. No systematic pattern was identifiable among either the farmers we were unable to contact or the farmers who refused to answer the questionnaire. In his review of a number of comprehensive studies examining non-response in telephone surveys, Gary Langer finds that non-response has an insignificant impact on the quality of information received from the survey (Langer, 2003). For these reasons we feel the response rate is unlikely to have affected the results presented in this paper.

Crop Choice Decision

Farmers were asked to identify from a list all factors they consider in choosing the crops to plant in their farms' irrigated acreage. Respondents were also asked to identify any other factors they consider that were not listed. A follow-up question then requested them to identify the two most important factors that influence their planting decisions. Table 1 summarizes the most popular answers provided by the respondents.

More than 80% of the respondents identified rotational considerations as a factor in their decision of which crops to plant on their irrigated acres in any forthcoming season. This factor is also ranked ahead of all other factors in both the "most important" and "second most important" categories of the responses.

Economic considerations such as knowledge of futures prices and expected costs of production inputs were also important considerations, cited by over 60% of the respondents. Although input costs were identified by one more respondent than futures prices, futures prices were much more important to the planting decision than input costs.

Interestingly, while 20% to 35% cited weather forecasts and crop water requirements as among those factors influencing planting decisions, very few ranked these factors (especially weather) among the top two considerations.

These results suggest that farmers are making a multi-dimensional decision. The importance of rotational considerations indicates a long-run perspective that revolves around the agronomic consequences of crop choice. In addition, the importance of single-season economic factors like futures prices and input costs reflects a short-run perspective consistent with maximizing the season's net returns.

Crop Acreage Allocation Decision

The farmers were also asked to identify from a list all factors they consider when deciding how to allocate their irrigated acreage to the crops they intend to plant. They were also requested to list other factors they consider. Here, as well, the respondents were asked to identify the two most important factors considered. The most popular responses are summarized in Table 2.

Consistent with the crop choice results, concerns about the agronomic benefits of rotation, futures prices, and input costs are the three most commonly cited factors influencing the crop acreage allocation decision. Marketing concerns are rated highly, as knowledge of futures price levels is considered more important than anything else by 34% of the respondents. Rotation issues rank 2nd in the highest importance category and 1st^t in the 2nd most important category.

These results suggest that rotational considerations serve as a general guide to crop choice, but not as a strict constraint to planted acreage. In other words, farmers appear to be willing to forego some of the long-run benefits of rotational practices to capitalize on expected short-run economic conditions. Extension programs that assist farmers in quantifying the short-run benefits and costs versus the long-run benefits and costs of their acreage allocation decision should be of particular interest to this clientele.

Prospects for a University Decision Support Program

The survey was also designed to explore the feasibility of offering a decision support program that will be available through the University of Georgia Web site. The decision tool is envisioned to incorporate such factors as futures prices, input cost estimates, weather forecasts, crop water needs, and pest pressure predictions. This information will be routinely updated and available at a single location for easy access by farmers at the time planting and crop acreage allocation decisions are made.

Farmers were asked, "If a decision support program were available on the Internet through a University of Georgia website, would you consider using it?" Among the 72 respondents, 50 farmers comprising 69% of the survey participants said "yes", they would consider using the university's proposed online decision tool. Among the 22 who declined, the most popular reasons cited were lack of Internet access (8 farmers), lack of experience in Internet surfing (5 farmers), and inability to use Internet services (4 farmers).

Summary and Conclusions

This article presents survey results concerning the determinants of farmers' crop choice and acreage allocation decisions. What is evident from the results is that agronomy should remain an Extension priority area, as previous assessments of the demand for Extension services have established.

The more compelling result, however, is that while crop choice and acreage decisions are heavily influenced by rotational considerations, such considerations are not viewed as strict constraints. Farmers appear willing to adjust their acreage allocations away from agronomic recommendations under certain economic conditions. This suggests that Extension programs that provide economic as well as agronomic information will better serve the Extension clientele.

Finally, farmers appear to be very interested in accessing information relevant to their crop choice and acreage allocation decision on the Internet when that information is presented at a single Web site managed by the university. The survey did not address farmers' desire to substitute Internet-based programs for traditional information delivery methods. However, the survey did ask of those who were not interested in Internet-based information, why they felt that way. Two key factors were cited repeatedly: lack of computer literacy and lack of access to Internet resources. The lack of computer literacy also impedes the adoption of computer-based tools for formulating production and business plans. There are still some farmers who need to be guided through the computer adoption process in their farm business operations.

Meeting this important challenge will enable Extension programs to deliver relevant, reliable, timely information with greater efficiency. This, in turn, will assist farmers in making production decisions that are consistent with their own goals, and thereby enhance the welfare of the greater farming community.

References

Ford, S. A., & Baab, E. M. (1989). Farmer sources and uses of information. Agribusiness, 5(5), 465-476.

Hall, L., Dunkelberger, J., Ferreira, W., Prevatt, J. W., & Martin, N. R. (2003). Diffusion-adoption of personal computers and the Internet in farm business decisions: southeastern beef and peanut farmers. Journal of Extension [On-line], 41(3) Available at: http://www.joe.org/joe/2003june/a6.shtml

Ilvento, T.W. (1997). Expanding the role and function of the Cooperative Extension System in the university setting. Agricultural and Resource Economics Review, 26(2), 153-165.

King, D. A., & Boehlje, M. D. (2000). Extension: On the brink of extinction or distinction? Journal of Extension [On-line], 38(5) Available at: http://www.joe.org/joe/2000october/comm1.html

Langer, G. (2003). About response rates. Public Perspectives, May/June, 16-18.

Lavis, K. R., & Blackburn, D. J. (1990). Extension clientele satisfaction. Journal of Extension [On-line], 28(1). Available at: http://www.joe.org/joe/1990spring/rb4.html

Ortmann, G. F., Patrick, G. F., Musser, W. N. & Doster, D. H. (1993). Use of private consultants and other sources of information by large cornbelt farmers. Agribusiness, 9(4), 391-402.

Suvedi, M., Lapinski, M. K., & Campo, S. (2000). Farmers' perspectives of Michigan State University Extension: Trends and lessons from 1996 and 1999. Journal of Extension [On-line], 38(1) Available at: http://www.joe.org/joe/2000february/a4.html

U.S. Department of Agriculture. 1997 census of agriculture, Volume 1:Geographic Area Series, Part 51: United States Summary and State Data. AC97-A-51. March 1999.

An In-Depth Look at 4-H Enrollment and Retention

Amy Harder
4-H Youth Development, Leader Development & Outreach Agent
Colorado State University Cooperative Extension
Longmont, Colorado
aharder@coop.ext.colostate.edu

Alexa Lamm
4-H Coordinator
Colorado State University Cooperative Extension
Castle Rock, Colorado
alamm@douglas.co.us

Dennis Lamm
Agriculture Extension Education Director
Colorado State University
Fort Collins, Colorado
Dennis.Lamm@colostate.edu

Herbert Rose, III
Graduate
Colorado State University
Castle Rock, Colorado

Glen Rask
Associate Professor
Colorado State University
Fort Collins, Colorado
Glen.Rask@colostate.edu

Introduction

Here today, gone tomorrow--does this describe 4-H enrollment in your county? For many years, 4-H has struggled with the complex problems of membership recruitment and retention, especially with older youth.

In 1983, a study was conducted in West Virginia to determine the re-enrollment and dropout rates for first year 4-H club members, as well as factors affecting re-enrollment. Findings included that members who participated in 4-H activities more often had a higher rate of re-enrollment, as did members with supportive parents. Approximately 45% of new members became dropouts after the first year. In general, the older 4-H members were when they first enrolled in the program, the less likely they were to continue (Hartley, 1983).

Soon after the West Virginia study, agents in southeast Kansas found in their research that 40-50% of members were dropping after their first year, and an additional 20% dropped after the second year. A survey of first-year families indicated a lack of understanding of the 4-H program, never feeling welcome or part of the group, and conflicting time commitments were major contributors to the decision to drop 4-H (Astroth, 1985).

In 1991, Extension personnel in Louisiana again examined the puzzling issue of 4-H retention (Acosta & Holt, 1991). A needs assessment conducted by one rural parish in the state asked teens in seventh through twelfth grades to identify topics that they wanted to have more information about. By incorporating the topics of highest interests into their programming--careers, suicide, pregnancy, dating, teen years, fashion, and after high school--the parish saw a 21% increase in the senior retention rate after 2 years (Acosta & Holt, 1991).

While Louisiana was looking at ways to retain youth in their programs, Indiana was attempting to identify reasons why the program failed to address the needs of some youth. By conducting phone interviews with older youth (10-18 years of age) who had dropped out of 4-H, the researchers were able to isolate the single most frequent reason given for dropping 4-H: displeasure with 4-H clubs. The competing time demands of sports and jobs were also ranked highly by 4-H dropouts as reasons for leaving the program (Ritchie & Resler, 1993).

Today, Extension agents still recognize the findings from these studies as issues affecting retention rates in their own counties. Despite positive growth in overall 4-H participation in the last several years, membership in organized clubs has remained nearly static. In 1996, there were 6.30 million youth participating in 4-H; of those, 1.54 million were enrolled in 4-H clubs. In 2003, 7.0 million youth experienced some form of 4-H, but only 1.57 million of those youth were club members (National 4-H Enrollment Report, 2004).

A recent analysis of Colorado's ES 237 data offers some insight into understanding trends in traditional 4-H enrollment and retention in the twenty-first century. ES 237 data is gathered in each county and state annually and includes demographic information for all youth and leaders involved in the 4-H program. This information includes age, years in 4-H, ethnicity, and race. A thorough review of the findings resulted in the identification of several strategies to increase recruitment and retention of 4-H members.

Methods

The ES 237 data for Colorado from 2002 and 2003 was analyzed in an effort to more thoroughly understand 4-H enrollment and retention. The analysis was based upon a traditional club membership of 11,518 and 17,331 net records for 2002 and 2003, respectively. Duplicate records, incomplete data, and invalid ages were removed from the gross total membership reported for those years to arrive at the net totals.

Findings

The major findings from the analysis of ES 237 data are most easily understood in the context of four graphs: 4-H Member Population by Age, Estimated Net Dropout Rate by Age, Years in 4-H by Age—Intermediate Members, and Years in 4-H by Age—Senior Members (Figures 1-4).

4-H Member Population by Age

Figure 1.
4-H Member Population by Age

In Figure 1, members who were 11 years of age comprised the largest percentage of the 4-H population. The distribution of ages is suggestive of a bell curve, with the smallest percentages of the 4-H population occurring at ages 5-7 and 16-18.

Estimated Net Dropout Rate by Age

Figure 2.
Estimated Net Dropout Rate by Age

To determine the estimated net dropout rate by age, the number of members at each age was compared with the number of members at the age one year ahead. The ES 237 data from 2003 was used in these calculations.

This is not a direct value for the dropout rate, but serves as a model to determine what the dropout rate would be if conditions did not change. It also assumes that the individuals in the 2002 and 2003 data behaved the same. This is considered to be a good assumption due to the close match in population distribution for both years, but may not hold true for longer spans of time.

Negative percentages in Figure 2 indicate growth in the population, while positive percentages show that members are dropping out. 4-H had a negative net dropout rate for members 6-11, indicating more children enrolled in 4-H than left the program at those ages. At age 12, the net dropout rate crossed through zero (a static population) and never dropped below it again. From age 13 through age 18, 4-H increasingly lost more members than it recruited.

Years in 4-H by Age

In order to identify peak periods of enrollment as well as retention trends, the percentage of the population reporting "x" years in 4-H was plotted for each age group. An age group is defined as all the members reporting the same 4-H age. For purposes of simplicity, the graphs were separated into intermediate membership (Figure 3) and senior membership (Figure 4). The decision was made to exclude the junior membership because extrapolations about junior enrollment may be made from the intermediate and senior data.

Figure 3.
Years in 4-H by Age--Intermediate Membership

Figure 3 identifies several major enrollment trends in the intermediate membership (ages 11-13).

• A significant portion of each age group was comprised of first year members. It is worth noting that age group 11 had more first year members than the other groups. Those declined by approximately 5% for age group 12 and an additional 5% for age group 13.

• Valleys in the graph occurred for each age group after the first year, bottoming out at the second, third, and fourth years respective to age groups 11, 12, and 13.

• The population peaks for each group were as follows:
  • Age group 11 – 4 years in 4-H
  • Age group 12 – 5 years in 4-H
  • Age group 13 – 6 years in 4-H

• After the population peak, the population percentages dropped dramatically for each age group.

Figure 4.
Years in 4-H by Age--Senior Membership

Similar to Figure 3, Figure 4 also identifies enrollment trends, as well as retention trends. They are as follows/

• First year members were the smallest part of the population for age group 18.

• There was a small drop in the second year of membership for all groups except age group 18. Membership then remained relatively stable until a sharp increase to the population peak.

• The population peaks for each group were as follows:
  • Age group 14 – 7 years in 4-H
  • Age group 15 – 8 years in 4-H
  • Age group 16 – 9 years in 4-H
  • Age group 17 – 10 years in 4-H
  • Age group 18 – 11 years in 4-H

• The population peak for each age group coincided with youth enrolling at age 7.

• After the population peak, the percentages dropped dramatically for each group.

Discussion

4-H Member Population by Age (Figure 1)

Although only 2 years of data were examined in this research, the nearly identical nature of the 4-H Member Population by Age for both 2002 and 2003 suggests that this pattern may extend to the years surrounding it. The steady increase in member population until age 11 implies a strong interest in 4-H.

It has previously been noted that "at any given time, participation in 4-H, Scouts, and other youth organizations is skewed with 9 to 11 year olds comprising over half of the participants" (Heinsohn & Lewis, 1995). The interests of the parents may also factor into the high rates of enrollment seen from ages 8 – 11. Heinsohn & Lewis (1995) also note that for younger children, "parents move their children into group experiences€[and] determine the experiences and activities their children will have." High enrollment may also be indicative of recruiting efforts aimed at these ages.

A large jump in population occurs between the ages of 7 and 8, nearly doubling the number of members. Possibly, this can be accredited to the difference in opportunities offered to these age groups. In Colorado, youth may join 4-H as Cloverbuds between the ages of 5-7. Cloverbuds may join a club, but with limited participation--including no competitive events. It appears that many parents enroll their children when they can become members of Colorado's traditional program and not before then. This may be related to a desire to have their children compete, misconceptions about the Cloverbud program, or inadequate publicity for Cloverbuds.

Conversely, one observes that the steady decline in the member population begins at age 12 and continues on through age 18. This decline supports the perceptions by 4-H agents that senior members are difficult to retain in the program.

It has been suggested that the loss of senior members is not a poor reflection on 4-H, but rather a part of the natural development of adolescents. Unlike younger youth, adolescents are given more autonomy in choosing their activities and often opt to leave a program chosen by their parents in favor of one of their own choosing. Additionally, adolescence is commonly associated with exploration and experimentation, as well as a time to commit to refining specific interests and strengths (Heinsohn & Lewis, 1995). Continued involvement in 4-H may prevent an adolescent from having the desired time to explore new activities and contribute to an individual's decision to leave the program.

Estimated Net Dropout Rate by Age (Figure 2)

The Estimated Net Dropout Rate by Age reflects the patterns found in the 4-H Member Population by Age with one notable exception. In Figure 1, there is a steady increase in the member population through age 12. While Figure 2 does show a negative dropout rate for those ages, there is no consistency in the numbers. At age 6, the dropout rate is –54%, but that rate increases to –27% at age 7 and then decreases again to –79% at age 8. While the decrease from ages 7-8 has already been discussed and ties in with the large boost in enrollment at age 8, it remains unclear why the dropout rate does not consistently decline from ages 6-8, when the population is clearly rising. Certainly, 4-H in Colorado is not maintaining the same success in recruiting youth at age 7 as it is at ages 6 or 8.

Years in 4-H by Age (Figures 3 and 4)

Perhaps the most comprehensive view of enrollment and retention is obtained from Figures 3 and 4. Many parallel observations exist between the two graphs.

1. Older youth are less likely to join 4-H. This trend culminates with youth aged 18, with less than 5% of this group enrolling as new members.

2. There are less second year members in each age group than there are first year members. This pattern is supported by Astroth's (1985) and Hartley's (1983) studies that noted high percentages of first year families dropping the program.

3. For every age group, the population peak occurred according to the following formula: Age – Years in 4-H = 7. In other words, the majority of members at every age had enrolled in 4-H at age 7. However, more youth enroll at age 8 than any other age.

Clearly, 4-H is struggling to meet the needs of older youth. Not only do the data show that it is difficult to attract older members, there is a challenge in retaining them. However, many members who joined at an early age continue to re-enroll each year as they grow older. Identifying the reasons long-term members choose to continue with 4-H is a critical piece in understanding the puzzle of serving older youth.

Recommendations

Agents who are looking to improve their 4-H recruitment and retention efforts should consider the following recommendations.

Recruitment

1. To more evenly balance the 4-H population, strengthen recruitment efforts for audiences 12-18 years old. Working with the school districts to distribute 4-H information, holding an open house, or targeting advertising towards places teens often gather are all options.

2. In this research, enrolling at an early age in 4-H was related to an increased likelihood of remaining in 4-H as a senior member. To build a larger population of long-term members, increase parental awareness of the benefits of joining 4-H as a Cloverbud (ages 5-7). Opportunities to explore new activities and have group experiences in a safe environment are examples of benefits.

3. Agents commonly recognize that current members are the most effective recruiters for 4-H. Provide Clover memorabilia and promotional items to current members to share with their friends, have in their houses or on their cars.

Retention

1. Implement a new-family mentoring system to support first-year members. Previous research has shown this to be a positive step in preventing the high rate of dropouts that occurs between the first and second years (Astroth, 1985).

2. Conduct a needs assessment (similar to the one done in Louisiana) for the intermediate and senior levels of membership to modify and develop programs matching these groups' interests and desires.

3. Increase flexibility in the structure of the club program to allow older youth to explore outside interests while maintaining membership in 4-H.

4. Future research should examine the effects that joining 4-H as a Cloverbud (ages 5 to 7) has on retention.

References

Acosta, D. T.. & Holt, B. A. (1991). Give teens the programs they want . . . and need. Journal of Extension [On-line], 29(1). Available at: http://www.joe.org/joe/1991spring/a8.html

Astroth, K. A. (1985). The challenge of retaining 4-H members, Journal of Extension [On-line], 23(3). Available at: http://www.joe.org/joe/1985fall/sa4.html

Hartley, R. S. (1983). Keeping 4-H members. Journal of Extension

[On-line], 21(4). Available at: http://www.joe.org/joe/1983july/a4.html

Heinsohn, A. L. (1995). Why do teens drop out?: A developmental view. Journal of Extension [On-line], 33(1). Available at: http://www.joe.org/joe/1995february/comm1.html

National 4-H Enrollment Report (2004). United States Department of Agriculture. Available at: http://www.reeis.usda.gov

Ritchie, R. M., & Kenda M. Resler, K. M. (1993). Why youth drop out of 4-H. Journal of Extension [On-line], 31(1). Available at: http://www.joe.org/joe/1993spring/rb3.html

Adolescent Leadership Skill Development Through Residential 4-H Camp Counseling

Barry A. Garst
Extension Specialist, 4-H Youth Development
Staff Development, Camping, and 4-H Centers
Virginia Tech
Blacksburg, Virginia
bgarst@vt.edu

Jeremy Johnson
Prevention Counselor
James City County Community Services
Williamsburg, Virginia
JJohnson@james-city.va.us

Introduction

Camping is more than a location or a program, it includes what happens to youth during and after the camping experience; the affective, cognitive, behavioral, physical, social, and spiritual outcomes of 4-H camp participation (Garst & Bruce, 2003). Within Extension, camping is a 4-H delivery mode and can also be an important context for positive youth development (Garst, 2003). Indeed, 4-H camping may provide many of the essential elements of positive youth development (National 4-H Headquarters, 2001) including:

1. The presence of caring adults,
2. Physical and emotional safety,
3. Age-appropriate structure and limits,
4. Sense of belonging, and
5. Opportunities to build and master content and life skills.

In addition to affecting youth participants, 4-H camping participation also benefits the leaders and volunteers who work with youth (Purcell, 1998; Forsythe, Matysik, & Nelson, 2004). These volunteers are often teen counselors or teen leaders--youth who have accepted the responsibility for teaching, supervising, and caring for younger campers. With increasing emphasis on responsible youth program management, camp directors are expected to document the benefits or outcomes of their camping programs, which includes the benefits or outcomes of teen counseling programs. Research suggests that camping participation helps teenagers to develop leadership and life skills (Thomas, 1996; Purcell, 1998). In addition, residential youth camping provides an excellent context for the development of leadership, communication, and interpersonal skills (Thomas, 1996).

The camp context is also important. Research suggests that the residential nature of camp may have implications for adolescent development (Garst, Scheider, & Baker, 2001). Because residential camping occurs in a novel, equalizing context, many of the socio-economic and cultural barriers that identify teenagers in home or community settings may not be as prevalent in residential camp settings. Thus, teen counselors may be able to explore or demonstrate aspects of their personality that they might not demonstrate outside of camp due to the social influences of peers.

Although collecting evaluation data from teen counselors is important, an equally important consideration is to target the method of data collection to teens' development level. Teen counselors want and expect the opportunity to verbalize their opinions, feelings, and attitudes (Chester, 2002). It is important, therefore, for camp directors to take the time to learn about the "lived experience" as it is created, described, and expressed by teen counselors at camp.

The purpose of the study reported here was to explore how participation in residential camping, in a teen leadership role, affected the development of leadership and other life skills. The secondary purpose was to identify how camp teen counselors positively affected the youth they supervised and with whom they interacted.

Sample

During the summer of 2002, Virginia 4-H conducted 10-12 weeks of residential youth camp at six separate camping facilities. Approximately 12,000 youth ages 9-13 participated as campers. Teen leadership opportunities were provided for youth ages 14-18. The population for this study (n=1,126) was comprised of all adolescent teen counselors (ages 14-18) who attended residential camp in a leadership capacity at one of the six camping facilities.

To select a sample of participants for this study, one week of camp was randomly selected for each of the facilities. All of the adolescent teen counselors who participants in camp during the selected week at the respective sites received parental and participant consent forms prior to camp (n=131). The teen counselors (n=68) who returned their consent forms comprised the sample used in this study. They were asked to participate in a group discussion about their camp experiences as a teen counselor.

Methods

We used focus groups to provide the teen counselors with the opportunity to discuss, explore, and describe their camping experiences. Krueger (1994) recommended focus groups because they place participants in natural, real-life situations and allow for the dynamics of group interaction, which often reduce inhibitions that might be present during an interview. The focus groups were conducted on-site while the camping program was in session, in meeting rooms that were quiet and located away from camp activities. A total of 11 focus group discussions were conducted (approximately two per site), with group size ranging from 4 to 8 participants.

The primary researcher served as the "facilitator," and a camp staff member served as the "recorder." Recorders received training in focus groups and recording responses prior to the focus groups. The facilitator used an open-ended interview script as guiding questions to provide general structure for the discussion, and responses were recorded by hand.

The primary purpose of the focus group discussions was to understand the camp counselor leadership experience as it was described and interpreted by teen participants. Focus group questions explored how teens became involved with camp, memorable experiences, development of skills, how teens might or might not be important for camp, and how the teen counselor leadership experience might be improved.

Data from the focus groups were transcribed, and then open and axial coding procedures were performed (Strauss & Corbin, 1990). Open coding consisted of fracturing transcribed data according to phrases that represented one thought. Axial coding was then used to identify relationships between the categories. Using the axial coding process, a preliminary list of categorical relationships emerged through a semantic comparison of coded categories.

Qualitative methods for assuring confirmability and trustworthiness were used. These methods included informed readers and a participant review. Informed readers, who were familiar with the camping program yet were not involved directly with this study, performed an audit of the data analysis process and results (Huberman & Miles, 1994). In addition, informed readers coded the data to assess the dependability of the analysis. A participant review process was used to provide study participants with the opportunity to examine and confirm both the results and conclusions.

Results

A total of 68 teen counselors participated in the focus group discussions. A majority of participants were female (65%), and the primary ethnic groups represented were White (80%) and African American (16%). The mean age for a participant was 15 years old. Previous experience as a teen leader in camp ranged from 1-4 years, and participants had an average of 2 years of previous experience as a teen counselor in camp. Participants represented 16 different counties/cities across six regions of Virginia, ranging from urban areas in Northern Virginia, Richmond, and Hampton Roads, to rural areas in central and southwest Virginia.

Data analysis of focus group responses revealed major themes related to (a) internal motives and external factors that impacted teen camp counselor participation, (b) increased understanding of children, (c) increased understanding of self, and (d) development of mentoring relationships with children. In addition, participants described how camp was very important in their lives (Figure 1).

Figure 1.
Conceptual Model of Adolescent Leadership Skill Development Associated with 4-H Camp Counseling

Many participants struggled with talking to their friends about the camp experience. Camp is not viewed as a "cool" thing to do by most participants' friends. Participants stated that friends viewed camp as stupid, childish, for nerds, corny, lame, cheesy, and boring. Furthermore, participants shared that these negative perceptions of camp are created by the fact that their friends do not understand the context, purpose, or value of camp.

Participants described how being a teen counselor at camp helped them to understand children. Specifically, participating in camp as a teen counselor helps teens to learn the developmental differences of youth, how to respect children as individuals, and the importance of recognizing how strategies that work with one child may not work with another child. Teen counselors also reported that they learned how to be patient and how to communicate with kids without yelling or abusing their authority.

Participants discussed a number of ways that being a teen counselor at 4-H camp helped them to learn more about themselves. Specifically, 4-H camp leadership helped teens to:

1. become more responsible for themselves and the youth under their supervision,
2. overcome shyness and become more confident talking in front of large groups,
3. communicate effectively to campers and to adults in camp, and how to manage and problem-solve stressful situations, and
4. manage and problem-solve stressful situations.

Participants identified a number of specific ways that they helped youth at camp. Helping youth campers typically involved talking, listening, sharing, and empathizing, as well as teaching campers specific skills during camp classes. In this way, teen counselors developed a mentoring relationship with youth campers.

Conclusions and Applications

The results of the study suggest that 4-H camp participation positively affected teen counselors by helping them to develop leadership-related knowledge, skills, and behaviors. The study supports the results of other studies of the impacts of the 4-H camp counseling experiences (Purcell, 1998; Forsythe, Matysik, & Nelson, 2004).

Teen counselors became more aware of the developmental needs and individual differences of youth campers and became more aware of themselves as leaders who were responsible for the welfare of children. Furthermore, teen counselors developed a mentoring relationship with young people. Based upon the results of this study, the following applications are suggested for camp directors who are responsible for developing and managing camp counselor recruitment and training.

• Recruitment materials for 4-H camp teen counselors should highlight the benefits of volunteerism and should describe how camp teen counselors can use camp volunteerism to develop their resumes and to make themselves more competitive for future employment. It would be appropriate to use the teens' self-descriptions of the camp experience as promotional materials.

• Recognizing that potential 4-H camp teen counselors may face peer pressure not to participate in camp, recruitment materials should be engaging and modern, and should describe the nature of camp volunteerism. Camp directors should candidly talk with their camp teen counselors about their friends' perceptions of camp and engage the teen counselors in a discussion regarding changes that could be made to make 4-H camp volunteerism more appealing to reluctant teenagers.

• One of the critical elements of positive youth development settings is the presence of caring adults. Although adolescents are developmentally classified as youth themselves, the results of this study suggest that at 4-H camp, teen counselors can function in the role of "caring adults" for youth ages 9-13, in that teen counselors listen, talk, encourage, support, and empathize with campers. Thus, teen counselors not only gain valuable leadership skills at camp, but also have the opportunity to use those skills to help youth campers, which creates a mentoring relationship.

• The process whereby teen counselors were involved in focus group discussions about their 4-H camp experience was important. Teen counselors learned that their opinions, feelings, and attitudes were important to camp administrators. The importance that teen counselors placed on being involved in the evaluation process and in being "listened to" is a reminder that teen counselors should be engaged and involved (e.g., partners) in the planning, implementation, and evaluation of camp programs and the training that they receive.

• It is important that teen counselors' contribution of care and mentoring to the 4-H camp community is recognized both publicly and privately, and that camp counselors are valued and honored for their contributions that help to make camp a positive youth development experience. Any steps that teen counselors take in their leadership development, every small step towards mastery, should be recognized, especially if it contributes toward their development.

References

Brannan, S., & Fullerton, A. (1999). Case studies reveal camper growth. Camping Magazine, January-February, 22-25.

Chenery, M. F. (1994). Explaining the value of camp. Camping Magazine, May- June, 20-25.

Chester, E. (2002). Connecting with generation why. Presentation at the 2002        National Association of Extension 4-H Agents Conference, October 28, Norfolk, Virginia.

Forsythe, K., Matysik, R., & Nelson, K. (2004). Impact of the 4-H camp counseling experience. Research Paper. Department of Youth Development. University of Wisconsin-Extension.

Garst, B. A. (2002). 2001-2002 Virginia 4-H camping report: A summary of participation, outputs, and outcomes. Blacksburg, VA: Virginia Tech, Virginia Cooperative Extension.

Garst, B. A. & Bruce, F. A. (2003). Identifying 4-H camping outcomes using a standardized evaluation process across multiple 4-H educational centers. Journal of Extension [On-line], 41(3). Available at: http://www.joe.org/joe/2003june/rb2.shtml

Garst, B.A. (2003). Benefits of camping: Youth development through 4-H camping. Virginia Cooperative Extension. Publication 388-102.

Gillett, D. P., Thomas, G. P., Skok, R. L., McLaughlin, T. F. (1991). The effects of wilderness camping and hiking on the self-concept and the environmental attitudes of knowledge of twelfth graders. Journal of Environmental Education, 21, 33-44.

Henderson, K. (2001). Camping gives kids a world of good. Parks and Recreation. November, 14-22.

Hopkins, D. & Putnum, R. (1993). Personal growth through adventure. London: David Fulton Publishing.

Huberman, A.M. & Miles, M.B. (1994). Data management and analysis methods. In N.K. Denzin & Y.S. Lincoln (Eds.), Handbook of qualitative research. Thousand Oaks, CA: Sage Publications,

Krueger, R. A. (1994). Focus groups: A practical guide for applied research, 2nd ed. Thousand Oaks, CA: Sage Publications.

National 4-H Headquarters. (2001). National 4-H impact assessment project. Cooperative State Research, Education, and Extension Service. U.S. Department of Agriculture.

Purcell, L.E. (1998). Does participation in the Georgia 4-H counselor program increase leadership life skill development? Paper presented at the 1998 NAE4-HA Conference, Boseman, MT.

Shepard, C. L., & Speelman, L. R. (1986). Affecting environmental attitudes through outdoor education. Journal of Environmental Education, 17, 20-23.

Thomas, H. (1996). Youth leadership: Teaching essential proficiencies at camp. Camping Magazine, March/April.

Thompson, V. (2000). CITs are campers in transition: Building a successful CIT program. Camping Magazine, July/August.

Thurber, C. A. (2001). Internal leadership development. Camping Magazine, November/December.

Organizational Values Perceived as Evident Among Ohio State University Extension Personnel

Jana Crossgrove
Masters of Science Graduate
The Ohio State University
Columbus, Ohio
crossgrove.2@osu.edu

Scott D. Scheer
Associate Professor and Extension Specialist
The Ohio State University
Columbus, Ohio
scheer.9@osu.edu

Nikki L. Conklin
Associate Director, Programs, and Associate Professor
The Ohio State University
Columbus, Ohio
conklin.1@osu.edu

Jo M. Jones
Associate Professor Emeritus
The Ohio State University
Columbus, Ohio
jones20@ag.osu.edu

R. Dale Safrit
Associate Professor and Extension Specialist
North Carolina State University
Raleigh, North Carolina
dale_safrit@ncsu.edu

Introduction

Present and future values are of enormous importance in adequately understanding and managing change within the core mission of any organization. Values that are put into action set a company or an organization apart from others by clarifying the organization's identity and serving as a guide to a prosperous future. The goal of many organizations is to put its values into practice, evident both within and outside the organization.

OSU Extension's mission is to "help people improve their lives through an educational process using scientific knowledge focused on identified issues and needs" (Ohio State University Extension Personnel Unit, 2000, p. 2). What started as a collaborative teaching effort for farmers, cooking lessons for women, and corn clubs for boys and girls has expanded into an organization that promotes change, problem solving, and the education of the public and individuals.

The values of an organization define "what the organization stands for and what is important to it as it fulfills its mission and works towards its vision" (Boone, Safrit, & Jones, 2002, p. 100). The enduring nature of values and value systems arises from the reality that they are neither completely stable nor unstable, but rather, are evolving continuously according to our changing physical, social, and emotional surroundings (Safrit, Conklin, & Jones, 2003).

An organization is not able to function without the commitment and loyalty of its workers. Employees are assets with valuable skills, pride, dedication, and needs that require satisfaction in the work place (Haas & Tamarkin, 1982). Personal satisfaction appears when there is congruency between professional beliefs and the values evident within the work environment. According to Hitt (1988), harmony between guiding organizational beliefs and daily actions of organizational members has a significant impact on the total performance of an organization.

Therefore, it is not only important to know an organization's values, but to what extent they are evident in the organization. In addition, a few studies have examined organizational values in state Extension systems: New Mexico (Seevers, 2000), Kansas (Lavergne & Rutherford, 2002), Florida (Williams, 1984), Ohio State (Safrit, Conklin, & Jones, 2001), Minnesota (Barker, 1994) and North Carolina (Safrit, 1990).

Purpose

The purpose of the study reported here was to determine the perceived evidence of organizational values and in comparison to the perceived organizational values of Ohio State University Extension program personnel. The data was based on research by Safrit, Conklin, and Jones (2001) that concentrated on the organizational values of OSU Extension program personnel. Through secondary data analysis, the evidence of perceived values in OSU Extension program personal was examined according to these research questions.

1. How are OSU Extension organizational values perceived as "extremely evident" in the organization?
2. How do organizational values of OSU Extension compare to the respondents' perceived evidence of such values?

Methods

The Organizational Values Questionnaire was developed by researchers (Safrit, Conklin, & Jones, 2001) to gather data from the target population of all OSU Extension program personnel operating actively at their position as of April 1, 2001. The data was entered and initially analyzed by Boomershine (2001). The census resulted in 595 participants with a 75% response rate.

The survey contained two sets of four-point Likert scales. For each statement, the individual was asked to rank the degree to which he/she valued the statement and to rank the degree to which the value was evident in the organization. Response categories ranged from 1 to 4, with 1 representing "not valued" or "not evident," and 4 representing "extremely valued," or "extremely evident."

A split-half test was conducted to measure and assure the reliability, which indicated a correlation coefficient of .82 in relation to the values within the data. A coefficient of .50 or greater is suitable for instruments that have not been used or tested previously for reliability (Nunnally, 1967). In 2001, a panel of Extension organization experts (the OSU Extension Executive Committee) reviewed the questionnaire and deemed it acceptable for face and content validity (Boomershine, 2001). The committee was composed of male and female individuals who held cabinet positions at the time of the review.

Results

The top and bottom five values perceived as "extremely evident" are given in Table 1. The percentages for organizational values perceived as "extremely evident" ranged from 50.4 % (unbiased delivery of information) to 6.3% (employee participation in educational program in a foreign country). The difference between the top and bottom values perceived as "extremely evident" was 44.1%. Out of 52 values, only one was perceived as "extremely evident" by over 50% of the sample. The "extremely evident" value was selected because it illustrates the differentiation between the values that are most desired in an organization and the values that are the most evident.

Table 2 compares the top 10 perceived organizational values as either "extremely evident" or "extremely valued" based each on their percentage rank. Findings show the "unbiased delivery of information" was the highest ranked "extremely evident" value (50.4%), whereas it was ranked seventh for "extremely valued" at (81.8%) with a difference of 31.4%.

The two highest organizational values ranked "extremely valued" were "honestly/integrity in our work" (91.2%) and "credibility with clientele" (91.0%). However, when compared to "extremely evident," the same values were perceived at 47.9% and 42.6% respectively. As a result, 43.3% was the difference in the "extremely valued" to "extremely evident" comparison for "honesty/integrity in our work" and 48.4% for "credibility with clientele."

Discussion and Conclusions

The findings of this investigation can be examined in relation to two other statewide studies, one in Kansas (Lavergne & Rutherford, 2002) the other New Mexico (Seevers, 2000). The top 10 "extremely evident" values in Kansas were compared to the same top 10 values "extremely evident" in the Ohio State study. The highest item for Kansas State, "maintaining the credibility of our organization," was established at 31.4%, whereas the highest percent valid for Ohio State, "unbiased delivery of information," was 50.4%. The lowest ranked value for Ohio State in its top 10, "credibility with clientele," was 42.6%, which is greater than any of the values for the top 10 in the Kansas state study.

In an investigation at New Mexico State University (Seevers, 2000) similar results were found. Their data was also presented in the "extremely evident" category, and the same top 10 organizational values were utilized. For the value "honesty/integrity in our work," NMSU employees ranked this organizational value first, but the ranking in perceived evidence was fourth, with 46.8%. According to data presented in the "extremely evident" category, the same organizational value ranks first, but the ranking in actual evidence of the value was third, with a 47.9% difference.

The evidence of values in an organization plays an intricate role in the overall formation and function of individuals within the structure of an organization. As an organization thrives on the current personnel structure, it is necessary to advance individuals to further increase the similarity of between "extremely valued" to "extremely evident" values. It continues to be important to compare the respondents' perceived evidence of values to the actual organizational values possessed by OSU Extension personnel. The perceived evidence explains what is truly happening within an organization or institution.

Knowing an organizational shortcoming is a daunting task. Organizational values affect the personal outlook of individuals within the organization, as well as organizational entities and their capability to attain specified group objectives. As a result of this investigation, recommendations include:

1. Continue to enhance the actual evidence of OSU Extension values, not only by its employees, but its' clients and stakeholders as well.

2. Compare the findings to the current vision and mission statement of OSU Extension. The discrepancies found between "values" and the "perceived evident values" should each be addressed separately and reviewed to develop strategies for closing the gap in the discrepancies.

3. Identify what steps and processes are necessary for values in OSU Extension to reach desired levels of "extremely evident" values.

Values are important to all organizations, groups, and individuals. It was critical to accurately understand, comprehend, and utilize the evidence of each value in order to gain the full knowledge and use of organizational values. While many individuals invest certain items with a strong conviction, not all perceived evidence demonstrates that we are doing what we say we value and walking the talk.

It is necessary to compare "what is valued" and "the evidence of these values" in order to keep an organization operating at the highest standards. The findings in this research provide a sense of direction for organizations to investigate and develop a strong, meaningful list of organizational values that are expressed and displayed in the work environment. The behavior and actions of individuals within an organization establish the foundation that will leave a lasting impression.

References

Barker, W.A. (1994). The identification of organizational values in the Minnesota Extension service. Unpublished doctoral dissertation, University of Minnesota St. Paul.

Boomershine, B. (2001). Organizational values of male and female Ohio State Extension program personnel. Unpublished master's thesis, The Ohio State University, Columbus.

Boone, E.J., Safrit, R.D., & Jones, J. (2002). Developing programs in adult education: A conceptual programming model (Second Edition). IL. Waveland Press, Inc.

Haas, H. G., & Tamarkin, B. (1982). The leader within: an empowering path of self-discovery. New York, NY: Free Press.

Hitt, W.D. (1988). The leader-manager: guidelines for action. Columbus, OH: Battelle.

Lavergne, C., & Rutherford, T. (2002, February). Identifying and clarifying Kansas State University research and Extension's organizational values. Paper presented to the Southern Association of Agricultural Scientists, Orlando, FL.

Nunnally, J.D. (1967). Ohio's plan: The modernization of agricultural education. Columbus, OH: Author. Ohio State University Extension Personnel Unit. (2000). Columbus, OH: Ohio State University.

Safrit, R. D. (1990). Values clarification in the strategic planning process of an adult education organization. Unpublished doctoral dissertation, North Carolina State University, Raleigh.

Safrit, R. D., Conklin, N. L., & Jones, J. M. (2001). Ohio State University Extension organizational values study data. Unpublished research data, Ohio State University: Columbus.

Safrit, R. D., Conklin, N. L., & Jones, J. M. (2003). A longitudinal study of the evolution of organizational values of Ohio State Extension Educators. Journal of Extension [On-line], 41(5). Available at: http://www.joe.org/joe/2003october/rb1.shtml

Seevers, B. S. (2000). Identifying and clarifying organizational values. Journal of Agriculture Education [On-line], 41(3). Article 21 of 32. Available at: http://pubs.aged.tamu.edu/jae/pdf/vol41/41-03-70.pdf

Williams, M. S. (1994). Professional values and the Florida Cooperative Extension Service: Developing a foundation for strategic planning. Unpublished doctoral dissertation, University of North Florida, Jacksonville.

Pennsylvania Community Watershed Organizations as Seen by Key Informants

Brian D. Lee
Assistant Professor
Department of Landscape Architecture
College of Agriculture
University of Kentucky
Lexington, Kentucky
blee@uky.edu

Introduction

In order to address water resource issues, people must consider water use at the geographic scales from local to international (Grumbine, 1994). Therefore, collaboration and coordination are essential to successful and efficient water resource management. Watershed and ecosystem management must reconcile the frequently competing goals of maintaining ecological integrity and sustaining human livelihood.

In several states, organizations known as "watershed councils" have formed. These organizations are community based, semi- to formally appointed associations of people with diverse interests and values. These organizations are often founded to help manage natural resources and improve/maintain watershed conditions across private and political property boundaries (Conway, Godwin, Cloughesy, & Nierenburg, 2003). However, there has been relatively little research about these Community Watershed Organizations (CWOs) (Griffin, 1999). The primary objective of the project described here was to identify needed and used organizational resources for a successful CWO.

In the study, a Pennsylvania community watershed organization was defined as a non-profit, voluntary, non-governmental organization, with or without paid staff, that works in a defined watershed at least partially in Pennsylvania with water-related issues as a theme for the organization's existence. This article summarizes essential findings from key informant (KI) interviews about Pennsylvania CWOs. These findings may or may not be applicable to other areas.

CWOs often monitor water quality, clear streams of litter, improve wildlife habitat, stock fish, and purchase land or conservation easements. However, all of the work does not have to revolve around on-the-ground accomplishments; CWOs can work for collaborative community change (Brown & Evans, 2004). Some authors contend that an ineffective collaborative group often cannot accomplish their long-term goals (Bunker & Rubin, 1995; Holman & Devane, 1999). Communities often view Extension as being most effective in providing research-based education that helps build their capacity to make practical decisions (Conway, 2003). Extension professionals can work with CWOs to improve the functional capacity of the CWOs collaborative efforts (Brown & Evans, 2004).

Importance of CWOs

One way of addressing community issues is to import technical expertise to provide the answer(s). In this approach, the community stakeholders are essentially not involved in developing a solution. The community is a recipient of a solution that they may or may not embrace. An alternative approach, where CWOs function as an internal change agent, can alter the fundamental relationship between the external experts and the community. The community can often provide insights on the problem definition and formulation of alternative solutions (Prokopy & Castelloe, 1999).

This approach builds on the reservoir of knowledge within the community that can be used in solving community issues together (Behr, Schaffer, Lamb, Miller, & Sadowske, 1998). The community is integral to the process, from issue formulation through resolution. CWOs can foster a local-learning and decision-making environment. By working as an internal change agent, a CWO could help form local decisions that affect not only water, but also other social and biological concerns (Prokopy & Castelloe, 1999).

Land and water management practices in both urban and rural areas need to be changed if watershed functions are to be enhanced (Conway, Godwin, Cloughesy, & Nierenburg, 2003). Community groups can function to establish and maintain forums of interaction in the community (Warner, Hinrichs, Schneyer, & Joyce, 1999). These forums of interaction could be an essential component for addressing non-point source water pollution. In this context, CWOs have the potential to provide a forum of interaction about non-point source water pollution and related watershed issues.

Methods

The interview was chosen as the data collection method because there were few studies published about CWOs and none specifically about Pennsylvania CWOs. The interview approach allowed for topic exploration as KIs raised them. Formal KI interviews were conducted during the summer of 2001. Initially, nine KIs were interviewed, and through chain referral sampling an additional 18 KIs were identified (Gall, Borg, & Gall, 1996; Welch, 1975; Biernacki & Waldorf, 1981). A total of 24 KIs were interviewed including leaders of 13 CWOs.

All KIs were asked open-ended questions concerning their perceptions about Pennsylvania CWOs (Krannich & Humphrey, 1986). The interviews were semi-structured and followed a funneling strategy from easy to harder questions. The initial KI interviews were conducted face-to-face, while the remaining were telephone interviews. Six of the nine original KIs were identified by the other original KIs at least once and as many as three times as people to interview.

Findings

To simplify the KI interview findings, this article addresses approximately the top 20% of response types for the nine questions asked. In cases where the quintile would split the number of response types that were reported an equal number of times, all responses were included. The top quintile was selected because it provides a more concise way of reporting the key findings. KIs were allowed to provide multiple responses to the questions.

Typical Pennsylvania CWO

The KIs were asked to describe the characteristics of the typical CWO that they were familiar with in Pennsylvania. The KIs gave 17 characteristics in total. The median number of responses by each KI was three. The number of KIs responding is reported in parentheses. The typical Pennsylvania CWO consists of:

1. A core group of people (12),
2. Volunteer-based (11),
3. Relatively young (6),
4. Need of money (6).

These characteristics are fairly typical of almost any volunteer organization. In contrast, 11 KIs said that there is not a typical organization and that they are all very different. This is potentially important for Extension. It suggests that a one-sized approach for programming may not fit the needs of all CWOs, although there may be commonality amongst other volunteer organizations.

Organizational Milestones

The KIs were asked to identify organizational development milestones. These were not considered must-do milestones. These milestones appeared to be common for the CWOs to work towards achieving. Twenty milestones were identified by the KIs. The median number of responses by the KIs was five. The milestones were:

1. Establishing an organizational mission (14),
2. Completion of the first on-the-ground project (14),
3. Establishing an organizational vision and goals (13),
4. First grant received (12),
5. Transition of the board to a purely advisor