THE SIGNIFICANCE OF AGRICULTURE TO FUTURE GENERATIONS IS
UNPARALLELED
INTRODUCTION
The United Nations projects the global population to swell to 9.75 billion people by
2050, and to proliferate to 11.2 billion by 2100 (United Nations, 2015). This increase in
population will demand greater food production in the next 50 years than the previous
10,000 years combined (Borlaug, 2000). Agricultural production practices, such as
concentrated animal feeding operations (CAFO), pesticide and fertilizer usage, and
environmental issues, such as water usage, erosion, and non-point source pollution are
increasingly coming under strong review and criticism (Horrigan, Lawrence, & Walker,
2002). Other issues including antibiotic use in animals, animal safety, as well as the heated
debates over genetically modified organisms (GMOs) have been misrepresented in the
media and supported by special interest groups (Leising, Heald, Hubert, & Yamamoto,
1998). The non-agricultural population has little to no understanding or comprehension of
the complexities of sustaining a viable agricultural system (Doerfert, 2011, p. 8). Doerfert
(2011) found that agricultural literacy is an area often unseen and rarely discussed outside
specific agricultural disciplines. Society does not view agriculture as being important, yet it
is important that society be properly educated on issues in order to reach well-informed
decisions and render prudent choices that impact the world around them (Kovar & Ball,
2013, p. 168).
The population of the United States, once a predominately agrarian society, has been
transformed into an urban society. This is supported by the fact that only 1 percent of our
population provided food, fuel, and fiber for Americans and peoples around the world in
2012, down 3.1 percent from 2007 (United States Department of Agriculture, 2015). The
United States Environmental Protection Agency (EPA) concurred in their report that less
than 2% of the U.S. population lived on farms and less than 1% claim farming as an
occupation (United States Environmental Protection Agency, 2015). This trend toward
urbanization has contributed to the decline of an agriculturally literate population (Kovar &
Ball, 2013; Ryan & Lockaby, 1996; Pope, 1990). While advancements in technology and its
adoption into agricultural production systems has increased efficiency, the distance between
the farming and consumer populations have broadened (Birkenholz, Harris, & Pry, 1994, p.
1). The United States Department of Agriculture (USDA) reports that one farmer in the
United States can feed 155 people. The American farmer today can realize a 262 %
increased yield in food production requiring 2% fewer farmer inputs (labor, seed, fertilizer,
etc.) compared to farmers in 1950 (American Farm Bureau Federation, 2015).
These statistics, while impressive in the production capabilities of a single American
farmer, who are few in number and aging, suggest a bleak future for agriculture. According
to the 2012 Census of Agriculture, the last year for which data is available, the USDA
figures indicated the average age of the American farmer is 58.3 years (United States
Department of Agriculture, 2015). This figure up 1.2 years since 2007 and up 3 years since
2002 (National Sustainable Agriculture Coalition, 2014). This trend should be disturbing.
Added to this, the number of total farmers is decreasing at a rapid rate according to the 2012
Census of Agriculture, indicating fewer people are choosing agriculture as a career option.
Considering that the human population increases exponentially and food production
increases linearly, there is an urgent need for an agriculturally and scientifically literate
populace (Pimentel & Pimentel, 2008).
As the population of agriculturally literate individuals declines, society’s perception
of agriculture changes. The term “agriculture” has long been associated with farming or
ranching (Terry, Herring, & Larke, 1992). Kovar & Ball (2013) noted that masses of
agriculturally literate individuals are needed to address the onslaughts of emotional
negativity channelled through various media outlets. The public often understands and
assimilates information, on which it bases its decisions and choices, through the
professionals who are training the next generation of leaders and policy-makers, namely,
educators (Elliot, 1999).
One strategy for addressing the concern with “agricultural literacy” occurred in
1988. The National Research Council’s Committee on Agricultural Education in Secondary
Schools suggested “ beginning in kindergarten and continuing through twelfth grade, all
students should receive some systematic instruction about agriculture” (National Research
Council, 1988, p. 2).
However, the definition of literacy is only the foundation that needs to be
established. (Geier, Bonnet, & Bleam, 2013). Increases in the current knowledge and
technology base have created a significant shift in what educators view as a “literate”
student. There are many more forms of literacy than what was traditionally associated with
the term including digital literacy, computer literacy, media literacy, information literacy,
technology literacy, political literacy, cultural literacy, multicultural literacy and visual
literacy according to the National Writing Project’s website, Digital Is (National Writing
Project, 2014). Project 2061, a long-term research and development initiative of the
American Association for the Advancement of Science (AAAS), through its Benchmarks for
Science Literacy, has focused on science education for American students to become literate
in science, technology, engineering, and mathematics (STEM) courses beginning by the end
of grades 2, 5, 8, and 12 (American Association for the Advancement of Science, 2015).
To be agriculturally literate, the National Research Council (NRC) originally
envisioned that an agriculturally literate person “understand the food and fiber system, its
history and its current economic, social and environmental significance to all Americans”
(National Research Council, 1988, p. 8-9). Further, the NRC suggested the definition to
encompass “some knowledge of food and fiber production, processing, and domestic and
international marketing” (NRC, 1988, p. 9).
The Food and Fiber Systems Literacy Framework (FFSL) was a comprehensive
curriculum developed by Leising (1998), to address the NRC’s concern for students from
Kindergarten to 12th grade to become agriculturally literate citizens. As Leising pointed out,
nearly ninety percent of the population was two or three generations removed from direct
contact with agriculture. Youth know little about agricultural production, processing,
marketing, distribution, regulation or research (Leising, Heald, Hubert, & Yamamoto, 1998).
Today, youth are farther removed from agriculture and are more ambivalent regarding their
food chain connections.
The FFSL was intended as a road map for infusing Food and Fiber Systems
knowledge into core academic subjects and across grade levels (Leising, et al.1998). Sample
instructional materials help teachers understand the Food and Fiber Systems standards and
benchmarks by discovering how existing instruction connects to agriculture. Drake (1990)
noted that the success of any program about agriculture intended for children depended on
the ability of the teacher.
Leising stated the FFSL summarizes what America’s youth should know about the
Food and Fiber Systems to be agriculturally literate by the time they graduate from high
school.
In 2001-2002, the United States Department of Agriculture (USDA) contracted with
the Department of Agricultural Education, Communications and 4-H Youth Development at
Oklahoma State University to study the impact of student agricultural literacy in selected
Agriculture in the Classroom (AITC) trained teacher classrooms in Arizona, Montana,
Oklahoma, and Utah (Leising, Pense, & Portillo, 2001).
Statement of the Problem
Illinois ranks fourth in the nation for agricultural productivity (United States
Department of Agriculture, 2015), yet the agricultural literacy of its elementary students is
unknown. At the time of this writing, the researcher could find no evidence that Illinois
elementary school students in K-5th grades have been tested statewide to determine
agricultural literacy. Without an assessment of students’ level of agricultural literacy, it will
be impossible to plan, develop, and progress in the delivery of a successful agricultural
literacy program.
Purpose of the Study
The purpose of this study was to assess the agricultural knowledge of selected
Illinois classrooms of public elementary school students in kindergarten through fifth grades
that employ Agriculture in the Classroom (AITC) methods and materials. In order to
determine the agricultural literacy rate of elementary school students, the researcher used the
original instruments based on kindergarten through fifth grade standards and benchmarks of
the Food and Fiber Systems Literacy Framework.
Objectives of the Study
1. Develop a demographic profile of schools that participated in the study.
2. Assess differences using posttest mean scores between AITC treatment group
and control group in student knowledge about agriculture, before and after AITC
instruction, for each grade grouping (K-1, 2-3, 4-5).
3. Assess differences in posttest mean scores between AITC treatment groups and
control groups in student knowledge about agriculture, before and after AITC
instruction, using the five thematic areas of the Food and Fiber Systems Literacy
(FSSL) Framework for each grade grouping (K-1, 2-3, 4-5).
4. Assess theme posttest mean score gains between treatment and control groups in
student knowledge about agriculture, before and after AITC instruction, for each
grade grouping (K-1, 2-3, 4-5).
5. Develop a profile of student knowledge about agriculture, before and after AITC
instruction based on pre- and posttest mean scores, for each grade grouping (K-1,
2-3, 4-5) by the five thematic areas of the Food and Fibers Literacy (FSSL)
Framework.
6. Develop a demographic profile of students that will participate in this study.
Scope of the Study
The scope of this study encompassed classrooms of public elementary students in K-
5th grade (N = 500) in Illinois; a total of thirty Illinois schools were selected.
Assumptions
The assumptions reported in the Final Report 2001-2003 AITC Report (Leising,
Pense, & Portillo, 2001) were comparable to this study, and are stated as follows:
1. The instrument to be used will elicit accurate responses.
2. The respondents will fully understand the questions they will be asked.
3. The respondents will provide honest expressions of their knowledge.
Limitations
The limitations reported in the Final Report 2001-2003 AITC Report, Leising et al
(2001), were comparable to this study, and are stated as follows:
1. Results cannot be generalized beyond the public elementary school students included
in this study.
2. Sizes of public elementary schools may vary – some schools included in the study
may be larger or smaller than most similar schools.
3. Access to some public elementary schools may be limited due to stringent screening
of research proposals.
4. Administrators in some public elementary schools may refuse access due to a
compressed curriculum and excessive mandated testing.
5. Access to some public elementary schools may be revoked due to changes in school
administration.
6. Administrators in some public elementary schools may fail to respond to request for
permission to conduct research.
7. Previous agricultural knowledge and interventions may exist or may have previously
existed in some classrooms.
8. No other tests based upon an agricultural literacy framework, beyond the FSSL,
currently exist for measuring concurrent validity.
9. There is no state-approved agricultural literacy curriculum for elementary school
students.
10. Ethnic differences were not considered.
Definition of Terms
Agriculture – Agriculture is the production of agricultural commodities; including food,
fiber, wood products, horticultural crops, and other plant and animal products. The term also
includes the financing, processing, marketing and distribution of agricultural products; farm
production supply and service industries; health nutrition and food consumption; the use and
conservation of land and water resources; development and maintenance of recreational
resources; and related economic, sociological, political, environmental and cultural
characteristics of the food and fiber systems (Wallace, 1995).
Agriculture, Food, Fiber and Natural Resources (AFFNR) Systems - a term used
synonymously with food and fiber systems.
Agricultural Literacy - possessing knowledge and understanding of food and fiber systems.
An individual possessing such knowledge would be able to synthesize, analyze, and
communicate basic information about agriculture (Frick, Kahler & Miller, 1991). Today’s
definition has reflected current societal changes to be “a society with an understanding of
agriculture and current economic, social, and environmental impacts [that] could lessen
current challenges facing agriculture through good decision making along with the necessary
support” (Kovar & Ball, 2013). Further, The American Farm Bureau Foundation for
Agriculture in Pillars of Agricultural Literacy define agricultural literacy as knowledge of
“all of the industries and processes involved in the production and delivery of food, fiber,
and fuel that humans need to survive and thrive” (American Farm Bureau Foundation for
Agriculture, 2014). Finally, the National Agriculture in the Classroom in Agricultural
Literacy Logic Model has defined an agriculturally literate person as one who “understands
and can communicate the source and value of agriculture as it affects our quality of life”
(Spielmaker, Pastor, & Stewardson, 2013).
Agricultural Literacy Framework — a systematic, multi-disciplinary, educational approach
that promotes, fosters, and disseminates agricultural knowledge (Powell, Agnew, & Trexler,
2008).
Agriculture in the Classroom (AITC) – organized by the United States Department of
Agriculture in 1981, AITC is a state-run organization addressing the agricultural education
needs of the state’s students through partnerships of agriculture, business, education,
government and dedicated volunteers to supplement and enhance the teacher's existing
curriculum in a flexible educational program (Illinois Agriculture in the Classroom, 2015).
Benchmark – statement identifying expected or anticipated skill or understanding relating to
Food and Fiber Systems at various developmental levels. It may be declarative, procedural,
or contextual in the type of knowledge it describes (Leising, Igo, Heald, Hubert, &
Yamamoto, 1998).
Conversational Literacy in Agriculture, Food, Fiber and Natural Resources (AFFNR) – a
term used synonymously with agricultural literacy.
Food and Fiber Systems – a term used synonymously with the term agriculture (Igo, 1998).
Food and Fiber Systems Literacy – a term used synonymously with the term agricultural
literacy (Igo, 1998).
Food and Fiber Systems Literacy Framework – a curriculum model delineating what a
person should know to be agriculturally literate. The Framework is divided into five
thematic areas relating to agriculture: Understanding Agriculture; History, Geography and
Culture; Science, Technology and Environment; Business and Economics; and Food,
Nutrition and Health. It includes a narrative explanation of the concepts and information that
an agriculturally literate person would understand. The Framework also includes
gradegrouped standards with accompanying benchmarks (Igo, 1998).
Standard – describes what a student should know or be able to do relating to Food and Fiber
Systems knowledge or understanding (Igo, 1998).
Thematic Area – one of five related topics, which comprise the overall subject of agriculture.
CHAPTER 2
REVIEW OF LITERATURE
The purpose of this chapter was to present a review of the relevant literature for this
research study. This review of literature was divided into the following sections: (1)
Introduction; (2) Agricultural Literacy Defined; (3) Research in Agricultural Literacy; (4)
Agricultural Education Programs Contributing to Agricultural Literacy; (5) Agricultural
Literacy Materials; (6) Agricultural Literacy Programs Outside the United States; (7)
Agricultural Literacy Curricula Materials; (8) Learning Theories in Education; (9)
Frameworks in Agricultural Literacy Education; (10) Agricultural Literacy Models; (11)
Educational Measurement in Agricultural Education; and (12) Summary.
Introduction
Agriculture, the first science, impacts the food, health, stability, and economic well
being of a nation and it’s inhabitants, yet it is poorly understood by the general public and
especially, youth (Tisdale, 1991; Russell, McCracken, & Miller, 1990; Mayer & Mayer,
1974). With the migration from rural communities to urban areas, beginning with the
economic panic of 1873, the first global depression brought about by industrialization, and
continuing through the Dust Bowl, and the Great Depression, greater numbers of the
population have distanced themselves from their agricultural roots to a predominately urban
society (Blanke, 2016).
Supporting this distancing is the fact that only 1 percent of our population provided
food, fuel, and fiber for Americans and peoples around the world in 2012, a figure down 3.1
percent from 2007 (United States Department of Agriculture, 2015). In 1988, the National
Research Council found many people to be two to three generations removed from farms
and farming (National Research Council, 1988). Today, youth are further removed.
With this removal from our agricultural roots, the knowledge base about agriculture
has dissolved for the vast majority of Americans over that time. Today’s population is ill
equipped to make well-informed decisions regarding the role agriculture plays in their lives
(Mayer & Mayer, 1974; National Research Council, 1988; Tisdale, 1991). Additionally, the
non-agricultural population has little to no understanding of the complexities involved with
sustaining a viable agriculture system (Doerfert D. L., 2011). Further, this loss of
understanding regarding agriculture’s complexities allows the poorly informed majority to
impact policy decisions that may affect the agricultural industry’s ability to function
efficiently and effectively in an increasingly competetive world market (National Research
Council, 1988). Misconceptions about the importance of the role of agriculture in today’s
global market comes as no surprise. While communicating clear and concise agricultural
information is necessary, the public often understands and assimilates information, on which
it bases its decisions and choices, through the professionals who are training the next
generation of leaders and policy-makers, namely, educators (Elliot, 1999).
The National Research Agenda for the American Association of Agricultural
Education (AAAE) outlined, under Research Priority One, an emphasis on understanding
agriculture in a modern world through the need for an agriculturally literate society
(Doerfert, 2011). Agricultural literacy education, beginning in kindergarten through adult
levels, has been advocated for over 45 years (Russell, McCracken, & Miller, 1990; National
Research Council, 1988; Swan & Donaldson, 1970).
Elementary students’ misconceptions regarding agriculture can be corrected when
students are taught about agriculture and its role (Swan & Donaldson, 1970). In support of
this concept, the National Research Council’s Committee on Agricultural Education in
Secondary Schools suggested “ beginning in kindergarten and continuing through twelfth
grade, all students should receive some systematic instruction about agriculture” (National
Research Council, 1988, p. 2).
The field of agriculture is considered by Mayer & Mayer (1974) to be the model
science, but is viewed by others, as a system. However it is labeled, agriculture is a complex
field of study encompassing biology, economics, environment, sociology, politics,
technology, and international trade and relations (Moore, 1987). Moreover, agriculture has
become intensely specialized so that even those engaged in agriculture may know or
understand little about the intricacies of inputs and resources needed outside their scope
(Martin, 2015).
This review of literature addresses those topics related to agricultural literacy;
namely, recognized definitions of agricultural literacy, programs, curricular materials,
research, related educational theories, frameworks and educational measurements.
Agricultural Literacy Defined
In 1988, the National Research Council, defined an agriculturally literate person as
having:
…an understanding of the food and fiber system that would include its history and
its current economic, and social, and environmental significance to all Americans.
The definition is purposely broad, and encompasses some knowledge of food and
fiber production, processing, and domestic and international marketing. As a
complement to instruction in other academic subjects, it also includes enough
knowledge of nutrition to make informed personal choices about diet and health.
Agriculturally literate people would have the practical knowledge needed to care for
their outdoor environments, which include lawns, gardens, recreational areas, and
parks (National Research Council, 1988, p. 9).
A few years later, based on a survey of agricultural educators at land-grant
universities, agricultural literacy was re-defined. The resulting definition stated:
“Agricultural literacy can be defined as possessing knowledge and understanding of
our food and fiber system. An individual possessing such knowledge would be able
to synthesize, analyze, and communicate basic information about agriculture. Basic
agricultural information includes the production of plant and animal products, the
economic impact of agriculture, its societal significance, agriculture’s important
relationship with natural resources and the environment, the marketing of
agricultural products, the processing of agricultural products, public agricultural
policies, the global significance of agriculture, and the distribution of agricultural
products” (Frick, Kahler, & Miller, 1991, p. 52).
Over the years, scholars have moved away from a knowledge-based understanding of
agriculture to defining agricultural literacy in terms of “conversational knowledge, critical
analysis, and value-based judgment” (Powell, Agnew, & Trexler, 2008, p.). Trexler (2000,
pg. 5) further clarified conversational literacy as “ the policies and values we hold as we
define the depth and breath of conversational literacy” in the American lexicon. Further, in
an empirical study, literacy development was found to be built around “culturally based
beliefs, values, and attitudes” leading to “the ability to make judgments based on culturally
based norms” and asserted that “agriculture is a culture unto itself” which is reflected in
today’s society engagement with agriculture (Meischen & Trexler, 2003, p. 43).
In April 2013, researchers, practitioners, and government officials met in
Washington, D.C. to develop a National Agricultural Literacy Logic Model (Spielmaker,
Pastor, & Stewardson, 2014, p. 1). In support, the model defined an agriculturally literate
person as “a person who understands and can communicate the source and value of
agriculture as it affects our quality of life” (National Agriculture in the Classroom, 2014, p.
1).
Research in Agricultural Literacy
The National Research Council found that too many Americans are uninformed
about the social and economic impact agriculture plays in the United States (NRC, 1998). To
address this concern, the agricultural education community focused its research into literacy
programs, curricular materials, and agricultural knowledge at all age levels to refine its
literacy efforts. Successive research projects led to content standards and a literacy
framework to aid in planning, executing, and assessing agricultural literacy research and
instruction.
Overview of Agricultural Literacy Programs
Agricultural instruction is not a recent innovation. Proponents of instruction in the
field of agriculture date back to Socrates and Aristotle, as well as educational reformers like
Froebel, Pestalozzi, Rousseau, and Comenius. Socrates, Pestalozzi, and Comenius all
believed that peoples should learn about plant, animals, and the ways in which humans use
them, early in life (Snowden & Shoemake, 1973). In 1749, Benjamin Franklin, founder of
the American Philosophical Society, proposed that children be educated in agricultural
instruction and early on published many essays on agricultural topics (Mercier, 2015;
Snowden & Shoemake, 1973). The well-known agriculturalist, Thomas Jefferson in writing
to George Washington, on August 14, 1787, stated, “Agriculture … is our wisest pursuit,
because it will in the end contribute most to real wealth, good morals & happiness” (Thomas
Jefferson Foundation, 2016, p. 1). Human development theories formulated by Freud,
Erikson, and Piaget suggest that children between the ages of six to eleven years develop
opinions and ideas that last throughout their lifetime. They also determined that this is the
same age range in which children should learn about their environment and society (Davis,
1983).
Hillison (1998) noted in the early parts of the 1900s, agriculture was utilized as a
method for teaching science through a study of nature. Most of the states in the original
American colonies had their own scientific societies focused specifically on agriculture
(Mercier, 2015). Agriculture was considered an excellent delivery system for additional
instruction at the elementary school level as reasoned by educational philosophers such as
Froebel and Pestalozzi (Hillison, 1998). Where 18th century agricultural education was a
means of providing farmers with the basic skills they needed to prosper on their farms, 19th
and early 20th centuries observed that traditional agricultural education was focused on
increasing production to sustain a growing and increasingly urban and industrial population
(Mercier, 2015).
Agricultural Education Organizational Programs Contributing to Agricultural
Literacy
Agricultural literacy programs existed prior to the 1988 National Research Council’s
call for such a program in schools across the country.
4-H (Head, Heart, Hands, and Health)
In the late 1890s, vast numbers of young people were moving to the cities by the lure
of the potential labor market. The economic prosperity for future generations of rural
children was bleak. With visionaries like Liberty Hyde Bailey, who promoted the concept of
linking youth to nature and rural environments (Bailey, 1909, p. 309); O. J. Kerns, Illinois
Agricultural Experiment Station, who founded Farmers’ Institutes to introduce farm and
home topics and classes for rural youth; and Will B. Otwell, who offered premiums to boys
for highest corn yields, the need has existed for the promotion of the field of agriculture (4-
H, 2015, p. 1).
A. B. Graham, a school principal in Ohio, promoted vocational agriculture
instruction in schools through clubs with officers, projects, meetings and record
requirements. This was considered the founding of 4-H (4-H, 2015, p.1).
According to their website, 4-H is the nation’s largest positive youth development
and youth mentoring organization in the U.S. today working through the Cooperative
Extension System and the United States Department of Agriculture (USDA). This
organization works in partnership with 110 universities; programs are research-backed and
available through 4-H clubs, camps, afterschool and school enrichment programs in every
county and parish in the U.S. (4-H, 2015, p.1). Additionally, independent 4-H Clubs are
found around the globe in over 50 countires including Canada, Mexico, Africa, parts of
Central and South America, Great Britian, Eastern Europe, Scandinavia, China, India,
Japan, Australia, New Zealand, and Indonesia (http://www.4-h.org/about/global-network/).
The 4-H organizations recognizes that young people are the drivers of future change
with more than one billion between the age of 12 and 24 (4-H, 2015, p. 3). The United
Nations projects the global population to swell to 9.75 billion people by 2050, and to 11.2
billion by 2100 (United Nations, 2015). This increase in humanity will demand greater food
production in the next 50 years than the previous 10,000 years combined (Borlaug, 2000).
These young people are the future farmers who will need to do the job. Interestingly, more
than 3.5 million girls and young women are involved in 4-H (4-H, 2015, p. 3).
The National FFA (FFA)
In 1928, 33 students from 18 states met in Kansas City, MO, to form the Future
Farmers of America (FFA) (National FFA Organization, 2015, p. 1). According to their
website, FFA’s mission was to prepare future generations for the challenges of feeding a
growing population. The early founders and supporters taught that agriculture is more than
planting and harvesting – it's a science, it's a business and it's an art (National FFA
Organization, 2015 p. 1).
In 1935, under the guidance of G. W. Owens and J. R. Thomas, teacher-educators in
agricultural education at Virginia State College, and Dr. H.O. Sargent, a federal agricultural
education official, a national organization for African-American boys interested in
agriculture formed in Tuskegee, Alabama, called the New Farmers of America (National
FFA Organization, 2015, p. 2). By 1965, the NFA and FFA consolidated in recognition of
shared missions for agricultural education.
According to its website, FFA’s vision is “students whose lives are impacted by FFA
and agricultural education will achieve academic and personal growth, strengthen American
agriculture and provide leadership to build healthy local communities, a strong nation and a
sustainable world” (National FFA Organization, 2015, p. 1).
Tenney (1977) noted the National Future Farmers of America (FFA) Food for
America program, implemented in 1975, and engaged high school agriculture students to
share their agricultural knowledge with elementary school students. Their goal was to
educate the younger students’ understanding of the food and fiber chain from producer to
consumer, a forerunner of the agricultural literacy movement. Other FFA chapter’s operated
children’s barnyards and provided agricultural information to students in elementary schools
(Tenney, 1977). Building Our American Communities (BOAC), a program initiated in 1971
to provide a vehicle for FFA members to make a direct contribution to their communities,
also engaged in agricultural literacy efforts (Future Farmers of America, 1985).
Agriculture in the Classroom (AITC)
In 1981, the United States Department of Agriculture established an initiative
focused on agricultural literacy called Agriculture in the Classroom (AITC) (Linder, 1990).
The goal for all students to become agriculturally literate is not achieved by a single method.
To be successful in this endeavor, the formation of partnerships combining intellectual,
financial, material, and human resources are needed. Agriculture in the Classroom partners
with various entities to accomplish this goal; including traditional agricultural high school
programs, Farm Bureau, and industry organizations (Landeen, 2000).
The partnerships formed between education and profession was deliberate. In 1982,
the USDA held a meeting in Washington, D.C. to discuss the need for agricultural literacy
with representatives from agriculture, government, and education sectors. The
representatives determined that the USDA would serve as a coordinator and communications
link among the states, while allowing each state AITC program, autonomy.
A model plan was developed to provide guidance for each state’s beginning efforts (United
States Department of Agriculture, 1982).
Two of the first states to forge ahead with the AITC programs were California and
Illinois. In both states, the Farm Bureau (FB) was instrumental is establishing and
continuing the success of the current programs. The Farm Bureau Foundations in the
respective states called upon agricultural educators, agricultural extension agents, and other
consultants to utilize their expertise to guide in the development of lessons to be shared with
schools (Law, 1990; Landeen, 2000).
California.
California Ag in the Classroom (CFAITC) has been educating students about
agriculture since 1986. In 2011, the California State Legislature recognized the CFAITC for
its 25 years of service in promoting agricultural literacy to over 10 million California
students through AITC programs and resources, which were used in 46% of all California
schools (California Foundation for Agriculture in the Classroom, 2016).
Esparto, California high school agriculture teachers utilize a “Mentor Teacher”
program to promote agricultural literacy district-wide by spending time and energy outside
the traditional program. “Mentor students” were trained as aides or teacher’s assistants
instructing elementary students under the supervision of the “mentor teacher” or the
elementary classroom teacher (Schulte, Barnes, & Landeen, 1990, p. 11-12).
Illinois.
For many years in Illinois, the Illinois Farm Bureau was the state contact for Ag in
the Classroom. In the fall, 2005, the Illinois Farm Bureau Agriculture in the Classroom
program merged with Partners for Agricultural Literacy to form Illinois Agriculture in the
Classroom. This merge combined the efforts of the Illinois Farm Bureau, Facilitating the
Coordination of Agricultural Education (FCAE), University of Illinois Extension,
Association of Illinois Soil and Water Conservation Districts, various Illinois commodity
organizations and others (National Agriculture in the Classroom, 2014).
In their 2014-2015 achievements, Illinois AITC (IAITC) noted: there are active
programs in all 102 Illinois counties, spending $2,198,986 at the local level; reaching
549,370 students directly through county programs; and training 576 teachers across the
state through the Summer Agricultural Institutes (SAI) (Illinois Agriculture in the
Classroom, 2016).
Texas.
Texas utilized Ag Science Fairs and Extension educators as avenues for agricultural
literacy aimed at children (Blackburn, 1999). Also, promoting agricultural literacy,
commodity groups contribute to the development and dissemination of educational materials
promoting their individual products (Igo, 1998). These efforts by commodity groups are also
found in other states as well.
Brown & Stewart (1993) noted that teaching a six-week module about agriculture not
only increased agricultural knowledge, but also positively impacted middle school student
attitudes about agriculture.
National Agriculture in the Classroom Programs (NAITC)
By 1990, thirty-two states (64%) reported agricultural literacy programs in at least
one grade level (Hall D. E., 1991). State programs are organized and staffed differently
throughout the nation. State programs may be housed within departments of agriculture,
agricultural organizations, universities, or private nonprofit foundations. Most state
programs have formed educational nonprofit organizations, which have the benefit of a
taxdeductible status. Every state in the nation has some form of agricultural literacy program
in place. In 2014, the National Agriculture in the Classroom Organization (NAITCO) and
member states reached 171,000 teachers and 5,299,566 students (National Agriculture in the
Classroom, 2014).
In 2010, through a grant funded by National Institute of Food and Agriculture
(NIFA), the National Agriculture in the Classroom in cooperation with University of
Minnesota under project director, J. G. Leising, the developer of the FFSL, developed a
National Agricultural Literacy Curriculum Matrix. The Matrix, as it is called, is an online,
searchable, and standards-based curriculum map for K-12 teachers and contextualizes
national education standards in science, social studies, and nutrition education with
instructional resources linked to the Common Core Standards. The website allows educators
to print lessons and activities or store them in a personal online “My Binder” associated with
the Matrix (National Agriculture in the Classroom, 2014).
In 2012, the National Agriculture in the Classroom (NAITC) organization’s
executive committee became responsible for working as a volunteer network of state
contacts elected by their NAITC members in providing guidance to strengthen state
programs. The NAITC organization encourages and supports state programs and their staff.
NAITC challenges and encourages state AITC program leadership to adopt minimum
standards and expectations for official NAITC State Contacts (National Agriculture in the
Classroom, 2014).
The USDA sponsored an extensive evaluation of AITC using a census survey of each
state’s AITC director. AITC respondents were from all 50 American states, Guam and the
Virgin Islands (Curtis, Hellerich, Hipsley, Smith, & Traxler, 1988; Meischen & Trexler,
2003). The study found the apparent success and strength of AITC comes from its grassroots
organization, and the fact that educators are an important part of the movement.
Since 1981, AITC has focused its efforts toward connecting agriculture with education, and
is regarded as a flexible educational program designed to supplement and enhance the
teacher’s existing curriculum (National Agriculture in the Classroom, 2014; Curtis, et
al.,1988).
Summer Agriculture Institutes (SAI) Program
An agricultural literacy program for K-12th grade teachers called Summer
Agricultural Institute was implemented by Oregon State University using teacher curricula,
including agriculture as the context for instruction (Balschweid, Thompson, & Cole, 1998).
In Illinois, Summer Agricultural Institute, is designed for educators who wish to expand
their curriculum to include topics related to agriculture-the world’s food and fiber system.
The course focuses on how to integrate available resources and hands-on activities about
agriculture and the environment into an existing classroom curriculum. Educators can earn
professional development credits or college credit for attending. Scholarships are often
provided to educators to cover or defray the cost through the local county Farm Bureau.
Agricultural Literacy Materials
AITC Materials
Educators are able to receive agricultural literacy materials from the local County Ag
Literacy Coordinator or the local Farm Bureau offices, free of charge or available online, in
the form of Ag Mags (a four page agriculture based magazine), mAGic (multidisciplinary
AGricultural integrated curriculum) kits, Agri-Learning (agriculture and learning linked
together in the study food, plants, and animals) kits, books, SMART board lessons and
activities, Terra Nova, interest Make-n-Takes and other activities. In Illinois, educators have
access to all the above-mentioned materials as well as technology lessons in QR Codes,
Augmented Reality app (Aurasama), and Kahoot! (a free game-based learning platform)
through the Illinois Agriculture in the Classroom website under “Teacher Resources”
(http://www.agintheclassroom.org/TeacherResources/).
Project Food, Land & People, Inc. (FLP) Materials
Other agencies have also tackled the issue of agricultural literacy. Project Food, Land
& People, Inc. (FLP), a nonprofit educational organization, provides materials that have
proven effective for integrating an agricultural curriculum in science and social studies
classes (Cardwell, 1999). Established in 1989, a group of 50 professionals concerned about
students, educators and citizens understanding the crucial relationships between agriculture,
natural resources, and people of the world, developed a collection of related lessons for Pre-
K-12th grades. Project FLP’s science and social sciences based curriculum, Resources for
Learning, consists of 55 hands-on lessons ranging from environmental science and
stewardship to human populations and land use issues. Lessons are available for purchase on
their website, http://www.foodlandpeople.org/ordering/.
Agricultural Literacy Programs Outside the United States
Few programs outside the United States address the issue of agricultural literacy as
rigorously as the proponents in this country, yet interest and concern for agricultural literacy
programs are growing. Some global studies focused attention on adult training programs
rather than children’s programs. However, this suggests there is a greater need for
agricultural literacy education and instruction to begin at the elementary school levels.
Great Britain
A recent study of students across England commissioned by the Year of Food and
Farming found a profound decline in children’s contact with the countryside. In fact, one in
five children, or nearly one million children, have no contact with the land or any idea of
where their food comes from (Department for Environment, Food and Rural Affairs (Defra);
Department of Health; Department for Children, Schools and Families (DCSF), 2007).
Defra found between 2000 and 2005 overnight visits to England’s countryside
declined by 38% (Sigman, 2007). Sigman (2007) also found an increasing number of
“concrete kids” who view life on a computer or TV instead of being outdoors or much less
in the countryside.
Taiwan
Straybirds, launched by the Taiwan Council of Agriculture (COA) in 2006, is
considered the most important agricultural trainee program aimed at young people in
Taiwan (Wang & Huang, 2010). Inspired by the popular 1901 German movement, die
Wandervögel, the program encourages young people living in urban areas to move to more
rural areas with natural environments and pursue more independent lifestyles (Mohler,
1972). Facing both an aging agricultural work force and agricultural labor shortages,
Straybirds offers a solution faced by Taiwan and other countries facing farm labor shortages
(Wang & Huang, 2010). Straybirds provides informal government-organized agricultural
training courses designed to enhance agricultural literacy and disseminate the value of a
rural lifestyle (Hele, 2005; Liu & Ho, 2004; Deeds, 1991; Russell, McCracken, & Miller,
1990).
In 2011, following on the heels of the success of Straybirds, the Council of
Agriculture in Taiwan introduced The Farmer’s Academy, a virtual academic network
established to cultivate the next generation of farmers. The launch of Agriculture 3.0 offered
cloud-computing solutions for transferring agricultural knowledge and has brought stability
and growth to the nation’s agricultural sector (Council of Agriculture, 2012).
Australia
In a recent study, American agricultural education student teacher researchers spent
ten weeks in New South Wales, Australia in an international student teacher program. The
study found that culture, stereotypes, language, teaching methods, student performance, and
community unification can be impacted through an international exchange of ideas and
teaching methods (Bunch, Stephens, & Hart, 2011).
Poland
Polish researchers have found that there is an urgent need for a continual transfer of
knowledge to the farmers in that region with the most significant role being played by
school education, as well as training and workshops (Zuzek & Wielewska, 2015).
France
Montpellier, France has seen agriculture “reinterpreted” inside cities (Torreggiani,
Dall'Ara, & Tasinari, 2012). “Shared garden”, or collective garden concept in France, found
their beginnings in the North American community garden movement (Pashchenko &
Consales, 2010). The study found that collective gardens provided meaningful
environmental and agricultural education elements to urban life and help reconnect urban
life to agriculture (Scheromm, 2015).
Spain
As in France, allotment gardens, managed and cared for by single gardeners or their
families, and allotment gardens or “community gardens”, to use the American vernacular,
are found in Spain. The study found 95.5 percent of the interviewed partiticpants stated that
urban gardens had the most impact on their well-being through learning and education
(Camps-Calvet, Langemeyer, Calvet-Mir, & Gomez-Baggethun, 2016).
European Modules and Mobility in Agricultural Education (EMMA)
The primary aim of the EMMA project is to conduct educational activities by
providing opportunities for both experienced teachers and student teachers to work together
in international teams and develop educational outputs related to agriculture and agricultural
education. Two one-week courses were held for experts who produced the training tool of
the European Modules for student teachers. This tool was used during the training period at
the one-month mobility sessions at each partner institution across the European Union
(Czech University of Life Sciences, 2009). This program is similar to the one-week Summer
Agriculture Institutes (SAI) held annually across the United States.
These global studies suggest the importance agricultural literacy and training is a
growing and vital concern in embracing knowledge of and about agriculture as an important
component in today’s societies, promoting social cohesion, quality of life, healthy lifestyles
and food choices in various parts of the world.
Agricultural Literacy Curricula Materials
The NRC (1988) report noted that few systematic efforts existed to include
agricultural literacy to students of any age. Students may have received some instruction
about agriculture, but the report noted, “the material tends to be fragmented, frequently
outdated, usually only farm oriented, and often negative or condescending in tone” (NRC,
1988, p. 9). At that time, assessment of agricultural literacy instructional material was in its
infancy.
A precedent setting study utilizing a Delphi technique established a working
definition of agricultural literacy classifying eleven broad agricultural subject areas that
could be utilized to develop a framework for expanding agricultural curricula (Frick, et al.,
1992). The eleven subject areas addressed in agricultural literacy are:
1. Agriculture’s important relationship with the environment
2. Processing of agricultural products
3. Public agricultural policies
4. Agriculture’s important relationship with natural resources
5. Production of animal products
6. Societal significance of agriculture
7. Production of plant products
8. Economic impact of agriculture
9. Marketing of agricultural products
10. Distribution of agricultural products
11. Global significance of agriculture (p.54)
Frick’s work was the foundation for many subsequent research studies in agricultural
literacy.
A later study reported an agricultural literacy framework developed using a modified
Delphi technique and validated by panelists representing a broad spectrum of agriculture and
education interests in California (Leising & Zilbert, 1994). A tri-state study of K-8th grade
students (Igo, Leising, & Frick, 1999) found it was possible to increase student agricultural
knowledge by utilizing instruction based on the Food and Fiber Systems Literacy
Framework (FFSL) standards and benchmarks. Further, the researchers found it possible to
infuse agricultural education into core academics using the FFSL’s five thematic areas,
standards, and benchmarks as guides for instruction and use.
With this call for agricultural literacy instruction, Pals (1998a) found Idaho teachers
typically incorporated agriculturally related materials into the science core subjects. Further,
the researcher found respondents were interested in attending agricultural workshops for
science credit and were interested in receiving lists of suggested resource materials to
provide agricultural instruction according to the Idaho AITC program. In a related study,
Pals (1998b) evaluated the Idaho AITC Curriculum Guide. Only 11 units in the guide were
being taught yearly by each of the 128 teachers who utilized the guide. The teachers
indicated science, health and nutrition, and social studies topics were frequently presented.
However, the effective use of materials did not necessarily predicate prior agricultural
knowledge.
In Ohio, a survey of 750 randomly selected fourth grade teachers verified the
AgVenture Magazine was an effective instructional aid in teaching students about agriculture
(Swortzel, 1997). Teachers reported positive perceptions about the magazine stating it was
used primarily in social studies classes approximately nine hours per year.
Perry (1998) surveyed 1,048 Oregon state teachers and queried them regarding 19
identified curricula commonly used for agriculture and natural resources education. Over
80% of the respondents acknowledged Future Farmers of America (FFA) and 4-H as the
most commonly known programs, even in urban areas. The SOLV (Stop Oregon Litter &
Vandalism) program was known by 50% of the survey respondents. More than 30% of the
teachers responding to the survey knew of Project WILD, a wildlife-focused conservation
education program for K-12 educators and their students (Project WILD, 2016), Project
Learning Tree, an environmental education program for Pre-K-12 educators and their
students (Project Learning Tree, 2010), and Salmon Watch. Perry (1998) found that K-5
teachers and science teachers best knew Project WILD and Project Learning Tree, while
Salmon Watch was best known by middle and high school teachers.
Lesser-known curriculums, GREEN (Global Rivers Environmental Education
Network) and The Wonders of Wetlands, were known to 10% of surveyed teachers. The
Summer Ag Institute (SAI) was known to 13% of respondents, and rural teachers were two
to three times more familiar with this program than urban teachers. The study further
revealed that science teachers and teachers from rural areas tended to be more aware of
agricultural and natural resources curricula.
Facing educational accountability demands and increased student performance,
teachers often select curricula that will best prepare students for success on standards-based
achievement tests (Bellah & Dyer, 2006). Teachers are more concerned with what to teach in
order to meet the standards and assume positions as “gatekeepers” in selecting and
delivering subject matter to students (Barab & Luehmann, 2003).
There is not a lack of available curriculum resources to assist teachers in integrating
agricultural concepts and providing contextual experiences for students. The challenge is
how to shape these components into a deliverable, student-centered package (Bellah &
Dyer, 2006).
Assessment of Knowledge About Agriculture
Kovar and Ball (2013) undertook a synthesis of two decades of publications
regarding agricultural literacy research since the publication of Understanding
Agriculture—New Directions for Education (1988). The researchers sought to determine
where agricultural literacy was published, which populations were targeted, the purpose of
the research, and the finding of the agricultural literacy studies between 1988 and 2011. A
total of 49 studies were identified – 17 studies in the Journal of Agricultural Education,
seven studies in the North American Colleges and Teachers of Agriculture (NACTA), three
studies in the Journal of Extension, 18 studies in national or regional American Association
for Agricultural Education (AAAE) conference proceedings, and four miscellaneous studies.
Elementary teachers and students were the most frequently targeted populations. The
purposes of the identified studies were coded into three specific areas: (a) assess agricultural
literacy; (b) test the effectiveness of an agricultural literacy program; and (c) develop a
framework or guide to assist educators.
Kovar and Ball (2013) found while the programs were successful in increasing
agricultural literacy, many of the assessed populations were found to be agriculturally
illiterate. The researchers noted further research is warranted to explain areas of deficiency
in agricultural literacy (Kovar & Ball, Two Decades of Agricultural Literacy Research: A
Synthesis of the Literature, 2013).
K-8 Student Assessment of Knowledge About Agriculture.
The earliest study focusing on elementary and middle school students’ knowledge
about agriculture, or agricultural literacy, found that less than 30% of the 2000 Kansas
student respondents could correctly answer basic agricultural questions (Horn & Vining,
1986).
Perritt and Morton (1990) reported that youth in urban and suburban areas had little
exposure to agriculture. Local FFA members presented a five-day curriculum to 120 fourth
graders in Nacogdoches, Texas, using agricultural examples to assist the teacher. Three
months following instruction, a quiz was given to the participating students with 89% of the
fourth graders passing the quiz. The researchers concluded that presenting a positive
association with agriculture to the public sector was a challenge for agricultural educators
(Perritt & Morton, 1990, p. 15).
Williams and White (1991, p. 9) found student knowledge about agriculture of all
fifth, eighth, and eleventh grade levels in rural Oklahoma County was deemed a “low” level
of literacy, a score below 50 was considered low. Students in this study had an overall mean
score of 32.62. While the scores were not surprising, it was disturbing in a state where
agriculture was the second largest industry in terms of income generated. The study also
compared students who participated in agricultural organizations, specifically 4-H and FFA.
Students in fifth and eighth grades had higher scores than non-participating students
(Williams & White, 1991, p. 10).
Brown and Stewart (1993) assessed Missouri middle school students’ knowledge
about agriculture and attitudes regarding the subject. Results from the pre- and posttests
indicated there was a change in agricultural knowledge and attitude toward agriculture after
students received instruction about agriculture. However, the length of time students
received agricultural instruction (6 to 18 weeks) did not affect a change in their agricultural
knowledge or attitude toward agriculture.
Herren and Oakley (1995) evaluated Georgia’s Ag in the Classroom curriculum,
which began in 1987. The researchers found that second and fourth grade students receiving
AITC instruction demonstrated significantly greater increase in agricultural knowledge
scores over the control group. Students of teachers with little or no farm experience
exhibited significant differences in their scores as a result of the AITC program.
Additionally, data revealed the AITC program was effective whether students lived in urban
or rural environments; thus, agricultural literacy was an issue regardless of locale.
In another study, Swortzel (1996) studied Ohio fourth grade students’ knowledge
about animal agriculture. Utilizing the AgVenture Magazine, the researcher integrated animal
agriculture instruction into the curriculum over a period of four weeks. Using a
preexperimental pre-posttest design, he found students scored an average of 9.6 points
higher on the posttest than the control group. Contrary to the study conducted by Herren and
Oakley (1995), students living in urban areas had higher gains between pretest and posttest
scores.
Known as the “cheeseburger” study, Trexler (1997) concluded that participants who
lived solely in urban environments did not consider where the food they consumed came
from, but only considered it on the basis of hunger and the need for food. The participant
who lived in closest vicinity to where food was produced was more aware of the living
things, like cattle, that became his/her food. Trexler also discovered that school-based
understandings in science regarding the agri-food system varied widely from well
developed, to partial, to non-existent. These findings are very similar to those of Sigman
(2007) regarding the ambivalence of “concrete” children to where they food comes from.
Additionally, Trexler (1997) found that elementary students with limited exposure to
production agriculture believed farms were small (the size of two football fields) with one
farmer growing multiple varieties of crops in adjacent rows. Tevis (1996) agreed that
“stereotypes about agriculture remain a stumbling block” (p. 64) characterizing the
perception problem facing American agriculture.
DeWerff (1989) suggested that learning about agriculture should begin at younger
ages. The researcher found students see agriculture in a narrow sense, i.e. a farmer, a cow, a
pig, etc., along with other sterotypes (p.15). Additionally, DeWerff noted the problem is
further complicated by the successful productivity of the American farmer with less land
needed for agriculture allowing for the growth of residential areas. “It is a small wonder that
few Americans have an accurate understanding of modern agriculture” (p.14).
A recent study found elementary students understand where their food comes from,
namely farms, but few understand details about the agri-food system and often have
misconceptions that may hinder acquisitions of new schema (Hess & Trexler, 2011).
The first study of its kind in the field of agricultural education, Igo, Leising and Frick
(1999) assessed K-8 student knowledge about agriculture before and after receiving
instruction based on the completed and validated Food and Fiber Systems Literacy (FFSL)
Framework (Leising, et al., 1998). Based on the five themes of the Framework with
standards and benchmarks for each theme, the researchers developed a series of lessons and
instructional activities for teachers to utilize as examples for incorporating agricultural
concepts into their classroom curricula. Teacher training contained two phases, and students
were pretested prior to a treatment being administered. The results of this three-state
quasiexperimental study indicated the pre-posttest data increased agricultural knowledge
significantly. Additionally, a positive relationship was found between the number of teacher-
reported connections to the FFSL and increases in student agricultural knowledge
(Igo, Leising & Frick, 1999).
In a related study, Leising, Pense and Igo (2001) utilized a quasi-experimental
nonequivalent control group design to compare differences between treatment and control
groups by grade grouping, FFSL Framework themes, and teacher-reported instructional
connections to the FFSL in a three-states, specifically, Nebraska, Oklahoma, and Montana.
Nebraska, the control group, exhibited greater student agricultural knowledge than the
Oklahoma/Montanta treatment group on the pretest, but no significance was observed
between the mean scores for any of the four grade groupings. However, the
Oklahoma/Montana treatment group revealed a significant increase in student agricultural
knowledge in three of the four grade groupings through integrated lessons based on FFSL
standards and benchmarks.
The FFSL Framework was organized around five thematic themes: Understanding
Agriculture; Histoey, Culture, and Geography; Science and the Environment; Business and
Economics; and, Food, Nutrition and Health (Leising, et al., 1998). In this study, three
thematic themes produced the greatest statistically significant differences in the treatment
group: Understanding Agriculture; History, Culture, and Geography; and Science and
Environment. This difference was apparent in the 2-3, 4-5, and 6-8 grade groupings. The
treatment group for grade groupings 2-3 and 4-5 were statistically different in Business and
Economics; and in grade groupings 1-2 and 2-3, Food, Nutrition, and Health was
significantly different. In the control group, there was no statistical differences between the
pretest and posttest scores for any grade grouping in the first two thematic areas:
Understanding Agriculture; and History, Culture, and Geography. However, the control
group did yield a statistical difference in a single grade grouping for the remaining three
thematic areas: Science and Environment (2-3 grade grouping); Business and Economics (23
grade grouping); and Food, Nutrition, and Health (K-1 grade grouping) (Leising, Pense, &
Igo, 2001).
Researchers found that unlike the previous year of the study, there was no
statistically significant correlation between test score differences and the number of
instructional connections led by teachers in the treatment group sites (Leising, Pense, & Igo,
2001).
Secondary School Student Assessment of Knowledge About Agriculture.
In a study conducted by Kovar and Ball (2013), the researchers found that in the last
two decades, between 1988-2011, there were five studies focused on high school students.
The studies on high school students in these early studies used instruments developed
around agricultural areas found to be important for agricultural literacy, but did not involve
the development of an instrument for 9-12 grades to assess agricultural literacy.
Pense (2002), in collaboration with others, developed a validated instrument based
on grades 9-12 benchmarks of the FFSL Framework of standards and benchmarks for
assessing agricultural literacy of this population of students in general education and
agricultural education classes. The instrument used to assess student agricultural knowledge
in K-8 grades was used as a model in the instrument development process for 9-12 grades
(Pense, 2002). Pense (2002) found general education students in rural schools to have the
lowest mean agricultural knowledge scores when compared to their urban and suburban
counterparts. Additionally, the agricultural education students overall mean scores on the
agricultural knowledge test did not differ significantly from the general education students’
mean scores. However, the suburban school groups had the highest mean scores while the
rural school groups scored the lowest.
Using the 1990 Frick study as a foundation, Frick, Birkenholz, Gardner, and
Machtmes (1995) found rural high students were most knowledgable in natural resources
concepts and least knowledgable in agricultural plants. The urban inner-city high school
students were also found to be most knowledgable in natural resources and least
knowledgable regarding agricultural policies. The study reported that urban inner-city high
school students had overall lower mean knowledge scores as well as overall less positive
perceptions toward agriculture than rural high school students (Frick, et al., 1995).
In a related study, Frick, et al. (1995) used the instrument developed in the 1990
Frick study to assess the agricultural knowledge, perception related to agriculture, and
demographic information of 550 mid-western 4-H students. The respondents were most
knowledgable about natural resources concepts and marketing of agricultural products. Their
lowest mean score knowledge came in the plant concept areas. 4-H members were found to
have the most positive perception mean scores for natural resources and animal science
concept areas. The least positive perception score was agricultural policy concept area. The
study found 4-H members had high overall mean levels of knowledge of agriculture for all
concepts areas, but scores varied widely (Frick, et al., 1995).
According to a study by Frick and Wilson (1996), Montana’s Native American high
school students had overall moderate to high levels of knowledge about agriculture. The
instrument developed by Frick (1990) was utilized to assess knowledge and perception of
argiculture in seven content areas. The Native American students perception toward
agriculture was positive, but a wide variance of perception within the seven concept areas
was found (Frick & Wilson, 1996).
Kovar and Ball (2013) noted that changes in the agriculture industry, including the
financial crisis of the 1980s , the rise of corporate farming, as well as the changes in
technology and farming trends, such organic farming and ethanol production to precision
agriculture and environmental stewardship warrants a new framework to assess agricultural
literacy.
Teacher and Adult Assessment of Knowledge About Agriculture.
Kovar and Ball (2013) noted that teachers were identified in ten studies from 1988 to
2011. Of this number four studies were of elementary school teachers, two studies focused
on high school teachers, and an additional four studies examined K-12 school teachers.
Another six studies examined non-educator adults, including parents, officials,
administrators, or other community leaders. These studies typically examined knowledge
and perceptions about the field of agriculture. This is vital as education and, more
importantly, the educators were determined to be the tool that would both establish and
promote the growth of concepts to insure that citizens would learn how to be responsible
citizens and secure the United States as a nation for future generations (Gelbrich, 1999).
Terry (1990, p. 9) stated “The role of the teacher in teaching students about
agriculture cannot be understated. In most programs of agricultural literacy that have been
proposed, the regular classroom teacher would be responsible for delivering the material to
the students”.
In the Texas public school system, science and social studies were typically
introduced in the fourth grade. (Terry, Herring, & Larke, 1992). In this study, researchers
surveyed fourth grade teachers to determine their knowledge and perceptions levels of
agriculture. Additionally, the researchers sought to examine the extent to which teachers
used resources in their everyday curricula that were agricultural in nature. The study
determined that teachers have innacurrate perceptions and limited knowledge about
agriculture. The researches concluded that efforts were needed to improve teacher
perceptions and increase teacher technological knowledge about agriculture.
In a related study of Missouri secondary teachers, Harris and Birkenholz (1993)
found educators to be knowledgable about agriculture and to have positive attitudes toward
agriculture. The researchers found teachers more knowledgable about agriculture were more
likely to include agricultural examples in their lessons (Harris & Birkenholz, 1993).
Cox (1994) developed a five-part mail survey to ascertain fourth grade educators
perceptions, knowledge, concepts taught, and assistance used to integrate agricultural related
concepts into their classrooms. The researcher found respondents did not associate
agriculture with science, but identified agriculture as the production of animals, plants, and
food. Ten questions related to plant growth and development, ecology and environment,
nutrition and food sources, and entomology were answered incorrectly by the majority of
teachers. Plant science activities were the most widely completed units of instruction.
Primarily, teachers relied on textbooks and periodicals for agricultural information. The
study concluded increased education and marketing to educators should accentuate the
relationship of agriculture to the various fields of science (Cox, 1994).
Based on the eleven concept areas of agricultural literacy proposed by Frick, Kahler,
and Miller (1991), science educators in Arizona middle and high schools were found to be
illiterate. Wallace noted that science teachers most understood environmental issues and
their relationship to agriculture (Wallace, 1995).
Balschweid, et. al (1998) debuted an agricultural literacy program aimed at Oregon’s
non-agricultural K-12 teachers through Oregon State University. In verifying the
effectiveness of the program, the researchers noted teachers in the program used agriculture
extensively as a context for instruction. Barriers to implementation of agricultural
information into the curriculum were not due to negative attitudes or lack of knowledge
regarding agriculture, but were time constraints and inadequate supplies and materials
(Balschweid, Thompson, & Cole, 1998).
Wilhelm, Terry, and Weeks (1998) utilized a mailed questionnaire to K-6 teachers
coded into two groups of those having attended an Oklahoma AITC SAI and those who had
not to deermine whether AITC influenced the inclusion of agriculture in their instruction.
The teachers who attended a SAI were found to include more agriculture related topics than
those who did not attend. Additionally, SAI teachers reportedly used more AITC materials
significantly more and incorporated agriculture lessons into the core areas of language arts
and information skills than their non-attending counterparts. The researchers not only
recommended the continuance of AITC SAI, but also recommended additional methods of
intensive teacher development be provided to allow a larger number of teachers to attend
(Wilhelm, Terry, & Weeks, 1998).
In a 2003 study, Knobloch and Ball, examined teachers’ and agricultural literacy
coordinators’ beliefs related to the integration of agriculture into instruction. The study
found beliefs act as a powerful filter in how teachers intrepret new phenoma (Pajares, 1992).
Teachers participating in an Illinois SAI for teachers interpret their profesional development
experiences through beliefs they hold about teaching, learning, educational standards,
integration and agriculture (Knobloch & Ball, 2003). Knobloch and Ball (2003) found
beliefs play a vital role in how teachers interpret new knowledge and experiences and the
value the teachers place upon new knowledge and experiences.
The teachers participating in this study taught English, reading, math, social science,
and science to first through fifth graders. The study estimated that only 3% of the
elementary teachers in Illinois have participated in a SAI (Knobloch & Ball, 2003). The
study revealed that food, consumer, and general agricultural topics were taught about once a
year. Teachers appeared to need more professional development opportunities to develop
activities, identify resources, and integrate agricultural topics to the Illinois Learning
Standards to explain ag-related topics to students (Knobloch & Ball, 2003).
Barriers to integration of agricultural topics into the daily curriculum included lack
of time, need for instructional resources, in-service education, and assistance for
incorporation into daily instruction (Knobloch & Ball, 2003). These barriers to inclusion of
agricultural topics are similar to those reported by Wilhelm, Terry, and Weeks (1998) as well
as Balschweid, Thompson, and Cole (1998).
Agricultural literacy is a current issue, not only in American society, but globally.
Knowledge and understanding of agriculture is necessary as the global population expands
compounding issues of feeding the world, while establishing and maintaining a sustainable,
viable agriculture system (Kovar & Ball, Two Decades of Agricultural Literacy Research: A
Synthesis of the Literature, 2013).
Learning Theories in Education
There are numerous theories related to human learning which have evolved over
time.
As with other areas of research, different theories have arisen as researchers have
concentrated on different types of learning. Some research has focused on skill acquisition
such as learning to read, write and, yes, type (Anderson, 1981; Bryan & Harter, 1897;
LaBerge & Samuels, 1974; NRC 2000). Other researchers have focused on understanding
learning and how learning effects schema formation and transfer (Anderson & Pearson,
1984, Judd, 1908; NRC, 2000; Wertheimer, 1959). Still other researchers investigate the
emergence of new ideas through “bumping up against the world” and through interactions
with other people (Carey, 2000; Karmiloff-Smith & Inhelder, 1974; Papert, 1980; Vygotsky,
1978).
Learning theorists have examined different settings for where learning can occur,
such as preschools, traditional schools, experimental laboratories, informal gathering
venues, and home and workplace settings. In the past 30 years, research has moved out of a
“lab only” setting to more complex surroundings like classrooms, schools, and districts
(Brown A. L., 1992; Collins, 1992; Linn, Davis, & Bell, 2004; Resnick, 1987).
In Learning Theories and Education: Toward a Decade of Synergy, researchers
focused on several key traditions of thinking that may influence and change how future
educators and scientists are trained. The researchers focused on three major areas of
research, specifically: (1) implicit learning and the brain; (2) informal learning; and (3)
formal learning. Typically, these areas worked independently of one another. However,
when researchers in these fields attempted to apply the findings directly to education, the
results were disappointing (Bransford, et al., 2005).
Bransford, et al. (2005) found that successful efforts to understand and drive human
learning required a simultaneous emphasis of informal and formal learning and implicit
ways in which learning occurs regardless of the environments. Utilizing these traditions may
create a more vigorous understanding of learning that can inform the learning environments
that allow students to succeed in the quickly changing world of the twenty-first century
(Darling-Hammond & Bransford, 2005; Vaill, 1996).
Implicit Learning
Implicit learning refers to information that is acquired effortlessly and often without
conscious recollection of the learned information or having acquired it (Reber, 1967; Graf &
Schacter, 1985). Bransford, et al. (2005) interest in implicit learning revealed the view that:
(a) implicit learning takes place in both informal and formal educational settings, (b)
implicit learning involves skill learning which plays a vital role in other types of learning,
and (c) implicit learning plays an essential role in learning about language and people across
the lifespan.
Implicit learning arises in many areas; it influences social attitudes and stereotypes
regarding gender and race (Greenwald et al., 2002), motor response time tasks (Nissen &
Bullemer, 1987), syntactic language learning (Reber, 1976), phonetic language learning
(Kuhl, 2004), and young children’s imitative learning of their culture, behaviors, customs,
and rituals of their social groups (Meltzoff, 1988; Tomasello, 1999).
Bransford et al. (2005) noted that our lifelong learning about language and people
begins before kindergarten, and in some cases important foundations are established in the
first year of life. In these areas, parents are the first "teachers" and much is absorbed through
spontaneous and unstructured play.
Brain-Based Learning
Modern neuroscience research notes learning in an alive, awake brain, reveals the
impact of experiential learning before it can be observed in behavior (Bransford, et al.,
2005). Brain studies link neural underpinnings to behavioral function, helping us understand
learning and may alter what we do in classrooms. Bransford, et al. (2005) found that future
research needs to combine educators and neuroscientists to study learning across settings
and will take a great deal of collaborative work.
Neurobiological studies, however, do provide crucial knowledge that cannot be
obtained through behavioral studies. There are three justifications for adding cognitive
neuroscience to tools for developing a science of learning.
First, science of learning will involve understanding not only when learning occurs,
but also understanding how and why it occurs. The how and why of learning are exposed if
we discover it’s neural underpinnings and identify the internal mechanisms that govern
learning across ages and settings (Bransford, et al., 2005).
Second, neural learning often precedes behavior (Tremblay, 1999), offering a chance
for scientists and educators to reflect on what it means to “know” and “learn”.
Third, better categorization of behaviors should allow the educational strategies and
policies that affect learning to be usefully grouped in ways not obvious absent the study of
brain function (Bransford, et al., 2005).
In education, teaching should be multifaceted in order to engage students to express
visual, tactile, emotional, and auditory responses and may require the reshaping of learning
organizations to exhibit the complexities found in life (Caine & Caine, 1990, p. 69). Caine
and Caine (1989) noted this requires three interactive elements: relaxed alertness,
immersion, and active processing.
Relaxed alertness occurs when the brain’s preference for challenge and its search for
meaning requiring a delicate balancing act are met (Caine & Caine, 1990, p. 69).
Teachers should promote the immersion of their students in appropriate experiences
because all learning is experiential (Caine & Caine, 1990, p. 69). The researchers noted that
teachers can make their classrooms “real-world communities”, where the students are given
responsibilities for handling ceremonies and supervisory functions.
Active processing allows students to take charge of learning through questioning and
genuine reflection in a way that is personally meaningful (Caine & Caine, 1990, p. 69).
Caine and Caine (1990, p. 69) noted that this allows students to recognize and deal with
their own biases and attitudes and develop thinking skills and logic as they create
connections to what they are learning.
Informal Learning
Informal learning can be learning that occur in homes, on playgrounds, among peers,
and in other situations where a designed and planned educational agenda is not
authoritatively sustained over time (Bransford, et al., 2005, p. 25).
Seventy-nine percent of a child’s waking activities, during their school age years, are
spent in non-school pursuits—interacting with family and friends, playing games,
consuming commercial media, and so on (NRC, 2000).
Informal learning research seeks to study how people learn in “their” informal
settings with sustained attention paid to “indigenous meanings and local phenomena”
(Emerson, 2001, p. 136).
Educators need to better understand the specific resources that young people bring to
school from their informal activities as well as how school-based knowledge is utilized to
further informal learning (Bransford, et al., 2005, p. 41).
Formal Learning
Formal learning in education is a cyclic process of research, design, and evaluation
of current educational programs to create the most effective learning environments in
in which to help students learn.
From a learning perspective, formal learning is also important to understand the
social and cognitive processes that support the kinds of competencies educators want
students to develop (Bransford, et al., 2005, p. 43).
Bransford, et al (2005, p. 50) noted that central to the goal of helping students
achieve important learning outcomes is to clarify what success looks like (Wiggins &
McTighe, 1997). This is important both for issues of summative assessment (seeing how
students perform at the end of some course or program of study) and formative assessment
(creating measures that provide feedback to students and teachers) plus opportunities for
revision that speed learning progress over time (NRC, 2001; Darling-Hammond &
Bransford, 2005).
However, a number of researchers suggest that typically used assessments provide
useful yet incomplete pictures of the kinds of skills, knowledge, and attitudes needed for
success in the twenty first century (Bransford, et al., 2005, p. 51). And the debate continues.
Learning Theories Related to Agricultural Education
Authentic Learning
Newmann and Associates (1996) through a five year, federally funded study,
provided valuable insight to conditions under which innovations in a school's organization
contribute to achievement. They recommended standards for reaching student intellectual
quality and offered evidence of how these standards work.
Authentic learning occurs through tasks, activities, and assessments that result in
achievement, which is significant and meaningful, according to Newmann and Wehlage
(1993). Newmann and Wehlage (1993) relied on three criteria consistent with proposals to
Wisconsin’s Center on Organization and Restructuring of Schools, namely: (1) students
construct meaning and produce knowledge; (2) students use disciplined inquiry to construct
meaning; and (3) students aim their work toward production of discourse, products, and
performances that have meaning or value beyond success in school.
Driscoll (1994) noted that authentic learning is a constructivist approach to learning
based on common assumptions of constructivism: (a) complex, challenging learning
environments and authentic tasks; (b) learning through shared responsibility and social
negotiation, (c) multiple representations of the content; (d) understanding that knowledge is
constructed; and (e) student-centered instructions.
Newmann and Wehlage (1993) found the challenge is not simply to adopt
groundbreaking teaching techniques or seek new venues for learning, but to assess the extent
to which any given activity, regardless of where it occurs, engages students to use their
minds well.
Five standards of authentic instruction were developed to address these concerns (see
Figure 1). Newmann and Wehlage (1993) reported that these five standards to estimate
levels of authentic instruction were being used in social studies and mathematics in
elementary, middle, and high schools. Their purpose was not to evaluate schools or teachers,
but to learn how authentic instruction and student achievement are facilitated by
restructuring and organization of schools, content of programs, quality of leadership, and the
school and community culture.
Five Standards of Authentic Instruction
1. Higher-Order Thinking
lower-order thinking only 1...2...3...4...5 higher order thinking is central
2. Depth of Knowledge
knowledge is shallow 1...2...3...4...5 knowledge is deep
3. Connectedness to the World Beyond the Classroom no connection
1...2...3...4...5 connected
4. Substantive Conversation
no substantive conversation 1...2...3...4...5 high-level substantive conversation
5. Social Support for Student Achievement negative social support
1...2...3...4...5 positive social support
Figure 1: Five Standards of Authentic Instruction Source:
Newmann & Wehlage (1993).
Further, Woolfolk (2001) found authentic tasks have connections to real-life
problems and situations students encounter outside the classroom. Ormrod (2000)
emphasized that an authentic activity promoted problem solving, critical thinking,
synthesized knowledge, and application of skills in real-life contexts.
Inquiry-based Learning
Inquiry-based learning or problem-based learning (PBL) and instruction historically
have held a prominent role in agricultural education classrooms across the United States,
especially in school-based agricultural education (SBAE) (Wells, Matthews, Caudle,
Lunceford, & Clement, 2015; Parr & Edwards, 2004).
There is a need for SBAE programs to move beyond curricula that emphasizes
memorization toward advanced concepts that challenge students and require knowledge in
academic subjects (Edwards, 2004). SBAE programs are situated so that teaching and
learning strategies emphasize the development of the individual and offer a broader variety
of learning experiences that suit a wide spectrum of student interests and learning styles
(Phipps et al., 2008; Edwards, 2004) (see Table 1).
According to Merriam-Webster, inquiry is a request for information; the act of asking
questions in order to gather or collection information; or an official effort to collect and
examine information about something (Merriam-Webster, Inc., 2015). Whether the word is
spelled using the American I or the English E, the meaning is the same, inquiry based on
question(s) asked by a learner or investigator. However, the field of science education has its
own concept of the meaning of the word (Martin-Hauser, 2002; Minstrell
& van Zee, 2000).
Table 1. Typical Student Inquiry-Based Classrooms
Traditional Approach
Inquiry-based Approach
Listen-to-learn method of
learning
Learning is question-oriented with real and
authentic goals
Little interaction, individual
work
Peer interaction, team work
Assessments in the form of
tests and term papers
Shared end product with an audience
Limited knowledge imparted
by the teacher
Ability to dig deeper into a topic
Mastery of content
Development of skills and questioning along with
mastery of content
Receivers of information
Pursuers of information
Mastery of content
Development of habits of the mind
Students are passive recipients
of knowledge
Students are actively involved in learning and
construction of knowledge
Moderate to low interest
High interest
Textbook dictated learning
Student focused learning
Evaluation at the end
Ongoing assessment
Source:
http://courseweb.lis.illinois.edu/~dafagan2/LIS506LEB/best_practices/traditional_vs_IL
Inquiry has been viewed as a teaching strategy and a set of student skills, such as individual
process skills (Barman, 2002). Another study found alternative definitions of inquiry: habit
of mind (encouraging inquisitiveness), teaching strategies for motivating learning, and
hands-on and minds-in, manipulating materials to study particular phenomena, and
stimulating questions from students (Martin-Hauser, 2002; Minstrell & van Zee, 2000).
Minstrell (2000, pg. 473) found an inquiry was complete when something that was
not previously known is known. When research fails to find an answer, the inquiry, or more
simply the question, should yield a greater understanding of factors involved in finding the
solution. Students nurtured to seek information will continue to do so even when a class is
done for the day (Newcomb & Trefz, 1987).
A former science teacher, John Dewey, recommended the inclusion of inquiry into K-
12 science curriculums (Dewey, 1910). Dewey noted that the educational establishment of
his day was unwilling to embrace the incorporation of science into their educational system.
In part, this unwillingness may have resulted from the rigid scientific methods, which
consisted of six steps: sensing perplexing problems, clarifying the problem, formulating a
tentative hypothesis, testing the hypothesis, revising with rigorous testing, and acting on the
solution (Dewey, 1910). Dewey encouraged K-12 science teachers to use inquiry as a
teaching strategy where the student is actively involved, and the teacher is a facilitator and
guide. Students should be encouraged to address problems they want to know and apply it to
the observable phenomena (Dewey, 1916).
Dewey modified the earlier scientific goal of relative thinking: presentation of the
problem, formation of a hypothesis, collecting data during the experiment, and formulating a
conclusion. Problems must be related to the students’ experiences and within their
intellectual capacity; for the students need to be active learners in searching for answers,
Dewey noted (Dewey, 1938).
In 1960, Joseph Schwab described two types of inquiry: stable (growing body of
knowledge) and fluid (invention of new conceptual structures that revolutionize science)
(Schwab, 1960). Schwab (1960) encouraged teachers to use laboratories to aid students in
their study of scientific concepts. He recommended science be taught using an inquiry
format.
Project Synthesis.
Project Synthesis, a compilation of three major National Science Foundation (NSF)
projects, found the greatest emphasis was placed on academic preparation (Harms & Yager,
1981). Inquiry was one of the five areas of Project Synthesis and was approached from two
dimensions: teachers and students, and strategy used to help students learn science (Welch,
Klopfer, Aikenhead, & Robinson, 1981). Welch et al. (1981) found teachers do not use
inquiry and identified the following reasons: limited teacher preparation, including
management; lack of time, limited materials available; lack of support; emphasis on content
only; and difficult to teach. Later research identified three main reasons for avoidance of
inquiry: state documents emphasizing content, easier to access content, and textbooks’
emphasis of science as a body of knowledge (Eltinge & Roberts, 1993).
Project 2061.
Project 2061, a long-term effort of the American Association for the Advancement of
Science (AAAS) to reform K-12th grade science, identified what all students should know
and be able to do when they graduate the 12th grade (American Association for the
Advancement of Science, 2016). Science for All Americans (SFAA), their first document,
broadly defined scientific literacy (Rutherford & Ahlgren, 1989). Benchmarks for Scientific
Literacy organized the topics into K-2, 3-4, 5-8, and 9-12 grade groupings (American
Association for the Advancement of Science , 1993). Project 2061 established goals for
teaching inquiry in SFAA chapter titled, “Habits of the Mind”: start with questions about
nature, actively engage students, concentrate on collection and use of evidence, provide
historical perspective, insist on clear expression, use a team approach, do not separate
knowledge from finding out, deemphasize memorization of technical vocabulary.
Science educators have multiple interpretations of inquiry. This has led to confusion
between educators, students and parents. The National Research Council (NRC) released
Inquiry and the National Science Education Standards to clarify what inquiry means
(National Research Council, 2000). Simply put, every inquiry must engage the students in a
scientifically oriented question of interest to the student; otherwise, students will not be
engaged.
The National Science Education Standards (NRC, 1996) recommended professional
development programs for K-12 teachers of science need to model inquiry in the offerings.
Sessions should provide participants the opportunity to become comfortable with
experiencing inquiry before implementing inquiry in the classroom. Further, model inquiry
units and lessons should be demonstrated along with classroom visitations, videos, and
vignettes with discussion afterwards. Consultative assistance should be available teachers
implementing inquiry lessons (National Research Council, 1996).
Calls for increased student achievement have led to innovative and challenging
teaching and learning methods within all classrooms (Pearson, et al., 2010; Stone III, Alfeld,
& Pearson, 2008). Teaching methods should learning through hands-on applications that
reinforce academic content and aid students’ natural inclinations and abilities to learn useful
content (Phipps, Osborne, Dyer, & Ball, 2008; Stone, et al., 2008).
Experiential Learning
Experiential learning can be defined as “a philosophy and methodology in which
educators purposefully engage with students in direct experience and focused reflection in
order to increase knowledge, develop skills, and clarify values” (Association for
Experiential Education, 2016, para. 2). Often referred to as “learning through doing”,
experiential learning can be defined by the following maxims:
I hear and I forget, I see and I remember, I do and I understand.
Confucius, 450 BC
Tell me and I forget, Teach me and I remember, Involve me and I will learn.
Benjamin Franklin, 1750
There is an intimate and necessary relation between the process of actual experience and
education. All learning is experiential, but all experiences are not educational.
John Dewey, 1938
The groundwork for “learning through doing” theories were provided through
educational psychologists such as John Dewey (1859-1952), Carl Rogers (1902-1987), and
David Kolb (b. 1939). While each made significant contributions to understanding
experiential learning, the key element remains the student, and the knowledge gained
(learned) as a result of personally being involved in the process.
“Learning is the process whereby knowledge is created through the transformation of
experience” (Kolb, 1984, p. 38). Kolb represented this process in the four stage learning
cycle in which a learner “touches all the bases” (see Figure 2).
Experiential education is typically associated with secondary and post seconday
education, not elementary education. However, the following research suggests otherwise.
Legend says that King Alfred planted school gardens so boys could have agricultural
training, and is mentioned as the beginning of Oxford University (Dadisman, 1921, p.16).
Dadisman (1921) noted that gardens were used as an instructional tool throughout Europe.
He also noted that in 1564 the Jesuits that argued that learning should be related to living
things and that materials for education are not always found in books, but from the external
world, including the usual occupations of men (Dadisman, 1921, p. 16).
Faced with a growing concern for childhood obesity, certain cancers, and other
chronic diseases, the use of school gardens as a learning approach to enhance nutritional
education to students is gaining ground considering fewer than half of boys and girls age
418 years old consume more than 5 servings of fruits and vegetables on a daily basis
(American Institute for CancerResearch, 2007; Guenther, Dodd, Reedy, & Krebs-Smith,
2006; Van Duyn & Pivonka, 2000).
Parmer, et al. (2009) found that second grade students who received nutrition
education instruction and participated in the school garden scored significantly higher in
their nutrition knowledge, fruit and vegetable preference, and vegetable choice and
consumption than students who received nutrition education instruction only or the control
group. Another garden-based nutrition education study with sixth grade students indicated a
significant increase in the consumption of fruits and vegetables by the treatment group after
participating in the study (McAleese & Rankin, 2007).
In a review of the impact of garden-based nutrition intervention programs examining
peer-reviewed studies conducted between 1990 and 2007, researchers found five studies
Figure 2: Kolb's Learning Cycle Experiential Learning
Source: http://www.simplypsychology.org/learning-kolb.html took place on school grounds
and were integrated into the school curriculum, three studies were conducted as an afterschool
program, and three additional studies were conducted within the community (Robinson-
O'Brien, Story, & Heim, 2009).
In a Temple, Texas study, third, fouth and fifth grade students participated in a school
gardening program which resulted in significantly higher science achievement scores than
the control group (Klemmer, Waliczek, & Zajicek, 2015).
According to Knobloch (2003), agricultural educators should based their instruction
on an experiential model that is grounded on the four tenets of experiential learning in
agricultural education: learning through doing (Dewey, 1938); learning by doing (Knapp,
cited in Lever, 1952); learning through projects (Stimson, 1919); and learning through
solving problems (Lancelot, 1944), stating that these are aligned with Newmann and
Associates authentic learning standards and more likely to provide a sound framework for
learning.
As these studies suggest, experiential learning helps students broaden and enrich
their educational experience through a solid foundation of learning.
Frameworks in Agricultural Literacy Education
To address the need for educating an “agriculturally literate” populace, Nunnery
(1996) noted that building of a literacy framework for understanding agriculture’s viewpoint
and perspective was necessary. In 1994, Leising and Zilbert addressed agricultural literacy
similarly and developed a systematic curriculum framework identifying what students
should know or should be able to do. In the initial framework, 39 panelists along with more
than 160 specialists in eight agricultural related groups were involved to validate the Food
and Fibers Systems Literacy Framework (FFSL), which determined and explained what an
agriculturally literate student should understand (Leising & Zilbert, Validation of the
California agriculture literacy framework, 1994). The FFSL, composed of a series of
standards in five thematic areas, demarcated the components necessary for understanding
how the food and fiber systems related to daily life. The standards, broken down into
gradegrouped benchmarks (K-1, 2-3, 4-5, 6-8, 9-12), provided the FFSL with a well-
organized means of addressing agricultural literacy in the context about agriculture.
Igo, Leising and Frick (1999) addressed student literacy through program assessment
focused on K-8th grade teachers and students in elementary and middle schools located in
Montana and Oklahoma. Instruments used for measuring student knowledge were based on
the FFSL Framework for themes and standards at the grade-level benchmarks. At the time of
this study, revisions to the FFSL had been undertaken, but not nationally disseminated
(University of Minnesota, 2012). Therefore, this is currently the only instrument for
assessing agricultural knowledge.
At the time of this writing, there are two agricultural literacy frameworks: Food and
Fiber Systems Literacy Framework (Igo, Leising, Frick, Hubert, & Malcolm, 1999), and
Project Food, Land and People (http://www.foodlandpeople.org).
Food and Fiber Systems Literacy Framework (FFSL)
The Food and Fiber Systems Literacy Framework is composed of a series of
standards in five thematic areas, each delineates the components necessary for
understanding how the food and fiber systems relates to daily life. The standards are broken
down into grade-grouped benchmarks (K-1, 2-3, 4-5, 6-8, 9-12). The standards and
benchmarks are designed to infuse food and fiber systems, or agricultural education, into
core academic subjects through existing connections through classroom learning activities
(Igo, et. al, 1999) (See Appendix C-Food and Fiber Literacy Framework-Themes and
Standards and Appendix D-Food and Fiber Systems Literacy Framework-Standards and
Benchmarks). This Framework has been used by teachers, state agricultural education
leaders, directors of curriculum and others in over 30 states since 1998 (University of
Minnesota, 2012).
In 2010, the National Institute of Food and Agriculture (NIFA) sponsored Grant
Number 2010-38858-21831 (Proposal Number 2010-04609) to revise and reinvent the FFSL
Framework. The project had two phases: Phase I-Develop a National Ag in the Classroom
Curriculum Advisory Committee composed of two state contacts from each region of the U.
S.; and to review current FFSL and advise project director, Dr. James G. Leising, of essential
elements of a new Agricultural Literacy Map. Phase II-Developed the Agricultural Literacy
Map of major activities, assemble content experts to review themes and benchmarks of
existing FFSL to determine importance, relevancy, and supplication, and identify new
content for inclusion; to cross-reference of Map to Common Core State
Standards; and to develop field testing and dissemination strategies. The AITC Advisory
Committee recommended that a project, connecting lesson plans to the Agricultural Literacy
map be conducted prior to field-testing of the Map. However, the field-testing strategy was
not addressed (University of Minnesota, 2012).
Project Food, Land & People, Inc. (FLP)
The Project Food, Land and People is a conceptual framework of six comprehensive
ideas from agricultural awareness to responsible food, land, and people decision-making for
today and the future. The framework is further divided into subdivisions, which identifies
topics and concepts used by teachers and educators to create instructional lessons (Project
Food, Land & People, 2012).
Agricultural Literacy Models
Additionally there are two agricultural literacy models: Pillars of Agricultural
Literacy (American Farm Bureau Foundation, 2015) and National Agricultural Literacy
Outcomes (National Agricultural Literacy Outcomes, 2014).
Pillars of Agricultural Literacy
The American Farm Bureau Foundation for Agriculture has defined an agriculturally
literate person as one who “understands the relationships between agriculture and the
environment, food, fiber and energy, animals, lifestyle, the economy and technology”.
Through its Pillars of Agricultural Literacy, the American Farm Bureau Foundation strives
to cultivate and build awareness, understanding, and a positive public perception of
agricultural literacy in any person, no matter their age or experience (American Farm
Bureau Foundation, 2015) (http://www.agfoundation.org/).
National Agricultural Literacy Curriculum Matrix
The National Agricultural Literacy Outcomes (NALOs), a synthesis of influential
research and the above mentioned agricultural literacy frameworks, resulted in the
development of five critical thematic areas focused on the newer agricultural literacy
definition, namely, a “person who understands and can communicate the source and value of
agriculture as it affects the quality of life” (National Agricultural Literacy Outcomes,
2014) (http://www.agclassroom.org/teacher/matrix/).
Educational Measurement in Agricultural Education
There are several types of assessments used to measure student learning in
agricultural education. These include, but are not limited to, standards-based assessment,
criterion-based assessment, and authentic assessment.
Standards-Based Assessment
Standards-based assessments, or norm-referenced assessments, are effective ways to
measure student learning. Assessments give educators a variety of strategies for assessing
whether students are meeting local, state, and national content standards. In this age of
accountability, assessments have become a valuable resource for augmenting and
documenting student learning (Lambert, 2007).
In the last 20-30 years, assessment has become one of the newest “buzz” words in
education. During this time, mountains of printed materials, hundreds of conferences,
iterations of federal and state policies, and school-based reform initiatives have been
generated, all in the name of assessment (Lambert, 2007, p. 1). Wilson observed in
Consilience: The Unity of Knowledge (1998), “We are drowning in information while
starving for wisdom” (Wilson, 1998, p. 269).
Lambert (2007) found that to design effective programs, professional dialogue and
respected research designs need to drive “best practices” through careful thought and clear
conceptual wisdom. These programs should not occur haphazardly, but require
uncompromised commitment to student learning to refine the practices. A thoughtful,
organized plan for teaching from concept introduction to student demonstration of learning
will form a firm foundation (Lambert, 2007).
Effective program design must include curriculum, instruction, and assignment
design components. Assessment with curriculum and instruction must result in an effective
tripartite whole. Theoretical and conceptual criterions provide practical framework to
establish processes for planning and implementing standards-based assessment (Lambert,
2007).
Lambert (2007) found that assessment models could vary considerably from
adherents to a particular policy requirement to conformists to normative assessment
practices and dominant standards of educational research. However, this does not lead to
educating students to learn the things that matter most, but pursues “results” thus, missing
the point of individual learning. Assessment is a two-edged sword. If the policy path is
chosen disregarding its affects toward learning, the initiatives are disappointing. If the need
for assessment models from the standpoint of learning is chosen, the models are likely to
follow those of the past (Worthen, 1993).
One of the most disturbing problems found in Pre-K-12th grades is the widening gap
between assessment theory and practice (Nettles, 1995). Nettles (1995) found that standards-
based assessment practices often used a “mix and match” approach. This has created a tug-
of-war between conceptual and theoretical practices, yet it is the fundamental duty of
professional educators to strike a balance between the quality of the programs and the
demand for accountability (Lambert, 2007, p. 5).
Education is about power. Lambert (2007, p. 5) noted that assessment of student
learning is a three-prong power play: power of a teacher to influence student learning,
personal power a student gains through the acquisition of knowledge, and power of
persuasion and influence a teacher’s pedagogical options have in crafting the voyage of
learning and the liberty learning provides.
If the history of assessment has taught the educational system anything, it appears
that excessive emphasis is placed on standardized testing rather than student learning.
Currently, limited time exists in an educator’s instructional day to focus on any more than
“teaching to the test” ensuring students can “test well” (Lambert, 2007, p. 10).
Criterion-Based Assessment
Criterion-based assessment is designed to measure a student’s performance based
on mastery of a specific set of skills at the time of assessment. A good example is a driving
test. Whereas, norm-referenced assessment measures a student’s performance in comparison
to other same age students taking the same assessment and is scoring is based on a bell
curve, meaning only half of those tested scored above the 50th percentile. An example is the
SAT, which compares the abilities of one high school student to another.
Assessments based on student performance can be used to provide feedback and
inform future teaching and learning needs (Green, 2002).
Authentic Assessment
Assessment can be considered authentic when student performances on worthy
intellectual tasks are examined. By contrast, traditional assessment relies on indirect or
proxy “items” or simplistic substitutes from which potentially valid inferences can be
concluded about a student’s performance based on the challenges of the particular
assessment (Wiggins, 1990).
Wiggins (1990) found authentic assessments required students to be effective
performers with acquired knowledge. Traditional assessment tends to show whether the
student can recall what was learned or “regurgitate” the learning.
Authentic assessments present students with a full array of tasks that mirror real-life
situations rather than being limited to paper and pencil or one-answer questions. They also
allow students to demonstrate justifiable answers or performances that conventional testing
only allows a student to write or select correct responses (Wiggins, 1990).
Wiggins (1990) noted that authentic assessment achieves validity and reliability by
emphasizing and standardizing appropriate criteria for scoring in contrast to traditional
testing’s “one” right answer approach.
Authentic assessment provides parents and community members with understandable
evidence concerning students’ performance and is more discernible to laypersons. Wiggins
(1990) noted that as researcher, Lauren Resnik said, “What you assess is what you get; if
you don’t test it, you won’t get it”.
Summary
This review of literature in this chapter has provided contextual information
regarding agricultural literacy in the United States and globally: it’s origins, developments,
and current status. The review has examined definitions of agricultural literacy from
conceptual to the currently accepted definition, agricultural literacy programs in the United
States and globally, research in agricultural literacy, educational and learning standards,
frameworks and literacy models for the development and assessment of agricultural literacy,
and educational measurement in agricultural education.
Additionally, the review of literature did not reveal any statewide studies utilizing the
FFSL Framework and criterion-referenced instruments to determine the agricultural literacy
of Illinois elementary students. As a result, it was determined that research was needed to
access the agricultural knowledge of Illinois elementary school students; to understand their
level of agricultural literacy, and to determine strengths and weaknesses of agricultural
knowledge for this group of students using the five thematic areas of food and fiber
identified in the FFSL Framework.
CHAPTER 3
METHODOLOGY
Introduction
Agricultural literacy is a field that is extremely important and has far-reaching
implications and consequences beyond the agricultural sector. However, agricultural literacy
is an area often unseen and rarely discussed outside specific agricultural disciplines
(Doerfert, 2011). Kovar and Ball (2013) found an agriculturally literate individual would
make sound decisions regarding agricultural policy, production agriculture, and accurately
disseminate information pertaining to other pressing issues related to agriculture. The
nonagricultural population has little to no understanding or comprehension of the
complexities involved in sustaining a viable agricultural system and is agriculturally
illiterate due to urbanization and the advancement of technologies in agriculture (Doerfert,
2011; Leising et al., 2000).
Purpose of the Study
The purpose of this study was to assess the agricultural knowledge of selected
Illinois classrooms of public elementary school students in kindergarten through fifth
grades, and determine if gaps exist in the current elementary educational curriculum
regarding instructional topics that would lead to agricultural literacy. To accomplish this, this
study utilized instruments based on the Food and Fiber Systems Literacy Framework
standards and benchmarks for data collected on the agricultural knowledge of Illinois public
elementary school students. The methods and procedures used in developing and conducting
this research study are described in this chapter.
Objectives of the Study
The study aimed to assess the agricultural knowledge of selected Illinois classrooms
of public elementary school students in kindergarten through fifth grades that employ
Agriculture in the Classroom (AITC) methods and materials. The specific research
objectives were:
1. Develop a demographic profile of schools that participated in the study.
2. Assess differences using sum score means between AITC treatment group
and control group in student knowledge about agriculture, before and after AITC
instruction, for each grade grouping (K-1, 2-3, 4-5).
3. Assess differences in sum score means between AITC treatment groups and
control groups in student knowledge about agriculture, before and after AITC
instruction, using the five thematic areas of the Food and Fiber Systems Literacy
(FSSL) Framework between schools for each grade grouping (K-1, 2-3, 4-5.
4. Assess theme score mean gains between treatment and control groups in
student knowledge about agriculture, before and after AITC instruction, for each
grade grouping (K-1, 2-3, 4-5).
5. Develop a profile of student knowledge about agriculture, before and after
AITC instruction based on pre- and posttest mean scores, for each grade grouping
(K-1, 23, 4-5) by the five thematic areas of the Food and Fibers Literacy (FSSL)
Framework.
6. Develop a demographic profile of students that participated in this study.
Institutional Approval-Human Subject Committee (HSC) Federal
regulations and Southern Illinois University Carbondale policy require review and approval
of all research studies that involve human subjects before investigators can conduct their
research. The Southern Illinois University Carbondale Office of Sponsored Projects
Administration (OPSA), through the Human Subject Committee (HSC), reviews all
research involving human subjects. In compliance with the aforementioned policy, this
study received proper review and was granted permission to proceed. The
Human Subjects Committee assigned the protocol number 15281 (See Appendix A-Human
Subjects Committee Approval Notification). Written administrative consent from each
principal for each school site was required by the HSC, and an appropriate form was
developed to meet this requirement (See Appendix B-Administrative Consent Form).
Research Design
This study utilized a quasi-experimental nonequivalent control group, using a pretest
and a posttest, as described by Cook and Campbell (1979). Quasi-experimental designs are
used where non-randomization of treatment groups are allowed (Ary, Jacobs, & Sorenson,
2010). Some suggest pretests may influence results (Blakstad, 2008). However, this is one of
the more frequently used designs in social sciences to measure the degree of change
occurring as a result of a treatment or intervention (Shuttleworth, 2009). Cook and Campbell
(1979) noted while not a true experimental design by name, quasi-experimental designs
could sometimes provide a more natural, generalizable environment that better establishes
effectiveness (as opposed to efficacy, typically associated with medical research).
Treatment and control groups were selected in each participating FCAE District
within Illinois. The treatment group was comprised of classrooms (K-5) in schools that
utilize AITC Literacy Coordinators, training, and/or materials in the academic year
20152016. The control group was comprised of classrooms (K-5) in schools that did not
utilize AITC Literacy Coordinators, training, and/or materials in the academic year 2015-
2016. The control groups were selected from schools that were similar in size and
geographic location to the treatment groups. A pretest and posttest were administered to
students to measure their knowledge about agriculture.
Population
The population of this study included a cross-section of selected public elementary
school classrooms across the state of Illinois during the 2015-2016 academic school year. As
random sampling was not feasible based on unique characteristics of each school and the
availability of subjects in intact groups, this study employed a purposive sample (Lund
Research Ltd., 2012; Wiersma, 1995).
One form of purposive sampling technique, or homogeneous sampling, contains
units, which are similar in terms of age and background (Black, 2010). Worthen, Sanders
and Fitzpatrick (1997, p. 359) employ the term “judgment sampling”, the strength of which
is found in describing a subgroup, which permits a better understanding of the program as a
whole. This non-probability sampling approach is based on particular characteristics or
judgments, which will best enable the research questions to be answered; these are specific
to the characteristics of a particular group and is not to be considered a weakness
(Explorable, 2016; Lund Research Ltd., 2012). In this study, the researcher selected the
schools based on the knowledge and professional judgment of the Illinois County AITC
Literacy Coordinators who participated, and not based solely on the researcher’s knowledge
or judgment.
Illinois is a very vertical state (north/south), 390 miles long and 210 miles wide.
While the state’s 57, 918 square miles ranks 25th in land size, it’s over 12 million residents
places it fifth in terms of total population.
To obtain a cross-section of a diverse population, the purposive sample included
public elementary school classrooms located in counties within the five Facilitating
Coordination in Ag Education (FCAE) districts (see Figure 3).
The counties were selected randomly from each FCAE District, which consisted of
87 counties (see Table 2). The Agricultural Literacy Coordinators for each selected county,
within each FCAE District, were contacted regarding participation in the study. The
participating County Agricultural Literacy Coordinator identified four or more public
elementary schools (K-5th grades): two or more public elementary schools identified
incorporated the Agriculture in the Classroom (AITC) instructional program, training and/or
use of AITC related materials for the academic school year 2015-2016, and two or more
public elementary schools had no exposure to or did not use the AITC instructional program,
training and/or use of AITC related materials for the academic school year 20152016 (see
Table 3).
The target population was 500 students, similar in number per state, to the original
study conducted by Leising, et al. in 2003. The population included students in schools
whose student population varied from 81 to 148 students. Intact groups of students reflected
diverse academic ability, both genders, and all present ethnicities were included in the
Figure 3: Facilitating Coordination in Agricultural Education Districts
Source: Illinois Association of Vocational Agriculture Teachers (2016)
Table 2. Facilitating Coordination in Agricultural Education (FCAE) Districts by Counties
FCAE District
Counties Within District
Number of Counties
1
Boone, Bureau, Carroll, Henderson, Henry, Jo
Davies, Knox, Lee, Livingston, McLean, Ogle,
Peoria, Rock Island, Stark, Stephenson,
Tazewell, Warren, White, Winnebago,
Woodford
20
2
Cook, DeKalb, DuPage, Grundy, Kane,
Kankakee, Kendall, Lake, LaSalle, Marshall,
Mason, Menard, McHenry, Putman,
Whiteside, Will
16
3
Fulton, Greene, Hancock, Jersey, Logan,
Macoupin, Madison, McDonough, Pike,
Sangamon, Schuyler, Scott
12
4
Coles, Crawford, DeWitt, Douglas, Edgar,
Effingham, Fayette, Ford, Iroquois, Jasper,
Macon, Montgomery, Moultrie, Piatt, Shelby,
Vermillion
16
5
Alexander, Franklin, Gallatin, Hamilton,
Hardin, Jackson, Jefferson, Johnson, Marion,
Massac, Monroe, Perry, Pope, Pulaski,
Randolph, Richland, Saline, St. Clair, Union,
Wabash, Washington, Wayne, Williamson
23
Total
87
Source: Illinois Agriculture in the Classroom, County Coordinator List, 2015.
Table 3. Potential Counties and Schools Identified by FCAE Districts
FCAE
District
Potential Counties Identified
Number of Potential Schools
Identified
1
McLean
4
2
Cook, McLean, DeKalb
8
3
Carthage
2
4
Fayette
2
5
Franklin, Jackson, Union, Williamson
15
Total
31
population. The final population was 430 students rather than the targeted population of 500
students (see Table 4).
To obtain an adequate cross-section of students, different strategies were utilized
according to organizational differences at each school. School district reorganization in
Illinois began in the mid-1990s as a method of consolidating resources and personnel (Hall
& Arnold, 1993). Some school districts did not implement the program until the beginning
of the 2013-2014 academic school year due to the need for established infrastructure to
house the incoming students. Other districts were in transition at time of the writing of this
study per conversations with local area teachers. This school district reorganization resulted
in some districts transitioning to attendance centers, which only included K-2nd grades or
3rd-5th grades.
Therefore, additional schools were selected to compensate for this change and to
adequately reflect the agricultural knowledge of K-5th grade students in Illinois following
the initial selection guidelines.
In early September 2015, the researcher contacted all Illinois County Agricultural
Literacy Coordinators in all five FCAE Districts to identify treatment and control schools in
their respective areas for potential participation this study. Responses were received
throughout the month.
In early October 2015, the identified schools received a letter of introduction to the
researcher and the research study, an administrator’s permission form, a parental consent
form (HSC requirement), a student consent form (HSC requirement), and a sample of the
testing instruments. A follow-up email and phone call followed approximately one week
later to confirm participation. If the identified potential school failed to respond, or denied
Table 4. Summary of Schools and Students Composing the Study Population by FCAE
Districts
Pretest
FCAE District
County
School
K
1st
2nd
3rd
4th
5th
Total Students Tested
1
*
*
*
*
*
*
*
*
*
2
*
*
*
*
*
*
*
*
*
3
*
*
*
*
*
*
*
*
*
4
Fayette
1
21
27
23
31
20
26
148
5
Total
Union
1
11
14
13
11
16
16
81
2
32
41
36
42
36
42
229
* Denotes districts with no participating school
Posttest
FCAE District
County
School
K
1st
2nd
3rd
4th
5th
Total Students Tested
1
*
*
*
*
*
*
*
*
*
2
DeKalb
1
17
17
16
16
22
22
110
3
Carthage
1
10
13
14
25
14
15
91
4
Fayette
1
21
27
23
**
20
26
125
5
Total
Union
1
10
14
13
11
16
16
80
4
58
71
43
83
72
79
406
* Denotes districts with no participating school
**Denotes school failed to return posttests
permission to conduct the study, the researcher contacted the local County Agricultural
Literacy Coordinator for additional potential schools. If additional potential schools failed to
respond or denied permission to conduct the study, the researcher continued the study with
the participating schools.
Pretest instruments, separated by grade levels, including testing instructions to the
teachers along with direct contact information for the researcher, were sent to the
participating schools by late October to mid November 2015. All pretests were completed
and returned to the researcher by early to mid December 2015. Posttest instruments,
separated by grade levels, including testing instructions to the teachers along with direct
contact information for the researcher, were sent to the participating schools in late March to
early April. All posttests were completed and returned to the researcher by late April to mid
May 2016. Testing time varied with each grade level from 30 minutes to 40 minutes and
were conducted in a single classroom period, rather than spread the testing out over several
days as allowed by the instructions to the teachers.
Four schools, identified by the Agricultural Literacy Coordinator in FCAE District 1,
granted permission through their Regional Office to conduct this research study. However,
when the researcher contacted the school principals to determine number of classrooms and
student population, the Regional Office revoked permission, stating the study was going to
require “too much time” for testing (see Limitations, Chapter 1).
One school identified in FCAE District 2, also granted permission for the study.
Again, when requesting the number of classrooms and student population, the researcher
was told the principal, who initially granted permission, was out on medical leave. The
interim principal revoked permission without offering a reason.
One school identified in FCAE District 4 was removed from the study, as it was the
only parochial school willing to participate in the study.
Two schools identified in FCAE District 5 were removed from the study, as the
schools initially were identified as control schools, but had received AITC instruction in at
least one of their grade levels and classrooms.
Instrumentation
A review of the literature indicated previous studies utilized a variety of data
collection instruments. Some researchers elected to create a new instrument to achieve
research objectives (Doerfert D. , 2003). Other researchers developed an instrument based
on the 11 agricultural literacy objectives identified by Frick, et al. (Frick, Kahler, & Miller,
1990). Doerfert (2003) noted that a select number of researchers chose to utilize instruments
developed by another researcher(s).
The researcher chose to utilize the original instruments, developed and tested by
Leising and Igo, based on the K-5th grade benchmarks of the FFSL Framework of standards
and benchmarks for agricultural literacy (Leising, Igo, Heald, Hubert, & Yamamoto,
1998)(see Appendix D). At the time of this study, no other instrument had been developed,
tested, or was available to assess agricultural literacy knowledge of students in K-5.
Reliability of Testing Instruments
Reliability of testing instruments can be determined by utilizing Cronbach Alpha or
Kuder-Richardson 20 (KR 20). However, Wiersma & Jurs (1990) found these methods are
appropriate only for norm-referenced tests or standardized tests, which are designed to
measure the differences between individuals by spreading out the scores on a “bell curve”.
The test questions are designed to accentuate the performance differences among the test
takers, not to determine if students achieved specified learning standards, learned certain
materials, or acquired specific skills or knowledge (Abbott, 2014).
Abbott (2014) noted tests that measure performance against a fixed set of criteria or
standards are called criterion-referenced tests. These tests are based on the number of correct
answers provided by students with scores expressed as a percentage of the total possible
number of correct answers. Common Core State Standards are criterion-referenced exams
that along with the federal policy, No Child Left Behind, are intended to measure school
performance (Abbott, 2014). TerraNova Common Core is an avenue for teachers to
“benchmark” learning progress and determine if students are on track to perform well on
Common Core-based assessments, which Illinois adopted in 2010, and implemented in
2013-2014 academic year (Abbott, 2014; Illinois State Board of Education, 2016).
The instruments used in this study were criterion-referenced with five thematic areas
focused on agriculture, less homogenous, and were previously piloted tested with groups of
students not included in the initial study (Leising, Pense, & Portillo, 2003). Leising, et al.
(2003) determined the internal consistency using Guttman’s Split-Halves reliability
coefficients, to be 0.7763 for kindergarten through first grade, 0.9469 for second through
third grade, and 0.7892 for fourth through fifth grade.
Data Collection
In order to obtain the broadest cross-section of elementary public school students in
Illinois, classroom test sites were purposively selected from the five FCAE Districts by
randomly selected county Agriculture Literacy Coordinators and roughly represented by the
FCAE Districts. One to six schools in each district were selected for this study resulting in a
total of 31 potential study sites.
The instrument, for each appropriate grade, (See Appendix E-Food and Fibers
Systems Literacy Tests) was administered at each site by the researcher, County Agricultural
Literacy Coordinator, or the teacher. Teachers were instructed to offer assistance as needed
in the opinion of the tester. This included reading aloud the testing instrument to younger
students. The term, “food and fiber systems,” was allowed to be changed to “farming”. The
teachers and Agriculture Literacy Coordinators were informed as to the numbering system
for the testing instruments. To ensure anonymity, each instrument was given a six-digit
number in an effort to separate test scores, FCAE Districts, school identities, grade levels, as
well as the identities of individual students.
Demographic information of each school was based on documents the schools
submitted for state and federal funding as well as qualitative observations of the researcher
or AITC Agriculture Literacy Coordinators.
Data Analysis
Each student was assigned a six-digit code number that was pre-stamped by the
researcher on each grade appropriate instrument. The first digit represented the test, i.e.
pretest or posttest. The second digit represented one of the five FCAE Districts. The third
digit represented the assigned school number. The fourth digit represented the assigned
grade level, Kindergarten to 5th grade. The last two digits represented the student. The
identities of the students were not connected to the student numbers on the instruments, but
were used to ensure that each student was scored separately and participated in both pretest
and posttest, and was grouped according to grade level and school.
Upon completion and retrieval of the pretest instruments, tests were scored by hand
and coded into a Microsoft Excel spreadsheet (Microsoft Excel for Mac 2011, Version
14.6.0) for analysis purposes. A data file was created for import to JMP Pro Version 13.0.0
and was used to perform all statistical procedures and analysis of pretest and posttest group
data in conjunction with the stated purpose and objectives of this study.
Qualitative methods were used to gather and report demographic information
regarding the schools included in this study. School documents and qualitative observations
of the researcher or AITC Agriculture Literacy Coordinators provided important data about
each site.
Descriptive statistics were utilized to report demographic characteristics of the
respondent students. The JMP Pro Version 13.0.0 were used to calculate frequencies and
percentages of study respondents by age, gender, and grade. Descriptive statistics were also
utilized to describe and summarize observations, specifically; percentages, means, and
standard deviations.
Due to the stated potential limitations of this study (see Limitations, Chapter 1), i.e.
school administrators failed to respond to the requests of the researcher; school
administrators revoked previously granted permission to conduct the research study; school
administration changes; and/or stringent review policies regarding outside research studies,
the researcher found it necessary to alter the original design of the study. This changed
resulted in the implementation of the Solomon Four-Group Design.
Statistical Treatment Using Solomon Four-Group Design
Over 65 years ago, Solomon introduced a new form of experimental design referred
to as the Solomon four-group design (Solomon, 1949). Campbell and Stanley described the
Solomon four-group design (Campbell & Stanley, 1963) as a one-treatment experimental
design. They found that the pre- and posttest control group designs and the posttest-only
control group designs were adequate to assess the effect of the treatment and were immune
to threats of internal validity. However, the researchers found the Solomon four-group
design was the only design able to assess the presence of pretest sensitization or test
reactivity (Huck & Chuang, 1977). Huck and Sandler (1973, p.54) noted that “exposure to
the pretest increases … the Ss’ sensitivity to the experimental treatment” and prevented
generalizations between the pretested group and the unpretested group. Therefore, the
Solomon four-group design added a higher degree of external validity in addition to the
internal validity leading Helmstadter (1970, p. 110) to conclude it (i.e., the Solomon 4-group
design) was the most desirable of all basic experimental designs.
However, the Solomon four-group design is underused. According to Braver and
Braver (1988, p. 150), there are four reasons that may contribute to the underuse. First, the
assumption that the Solomon four-group design requires twice the number of groups used by
the other two designs thus implying that twice the number of subjects is needed. Braver and
Braver (1988) found by cutting the size of each group in half, the total sample size retained
was comparable to the sample size of the other designs. Further, they found the strategy
resulted in adequate statistical power, which was greater than that of the posttestonly control
group design.
Second, researchers may have little to no interest in the area of pretest sensitization
effects, for which Solomon four-group design has the strongest advantage to detect. Braver
and Braver (1988) noted that pretest sensitization is an artifact that could limit the
generalizability of the effect for which researcher’s interests are directed or a researcher’s
belief that pretest sensitization does not exist in their research area. Additionally, they noted
this belief indicates that pretest sensitization artifacts rarely occur, which is supported by
literature reviews (Bracht & Glass, 1968; Lana, 1959; Lana, 1969; Rosnow, 1971; Solomon,
1949). Braver and Braver (1988) stated that the artifact should be considered an effect that
could potentially threaten the external validity of a research finding unless the use of the
Solomon design has ruled this out.
Third, conclusions may be more complicated using the Solomon design due to the
number of comparisons it allows (Oliver & Berger, 1980). This intricacy may dissuade
researchers from using Solomon. With increased negativity to allowing outside testing in
schools such as the researcher encountered firsthand, if Solomon could demonstrate that a
pretest was unnnecessary and did not drive the outcome, school administrators may be more
amemanble to allowing outside testing in their schools or school districts in which only a
posttest would be administered.
Fourth, and considered the most important reason by Braver and Braver (1988) is
uncertainty concerning the appropriate statistical treatment of Solomon. Braver and Braver
that Solomon examines more contengiencies and has greater statistical power (i.e., the
ability to (1988) agreed with the analysis of Campbell and Stanley (1963) and Huck and
Sandler (1973) that Solomon examines more contengiencies and has greater statistical power
(i.e., the ability to detect significance).
For purposes of this study, the researcher investigated does the possibility of a pretest
sensitization, or test reactivity effect, or whether X drives the outcome measure only when a
pretest measure is administered. (Campbell & Stanley, 1963). If this were the case,
O2 would be higher than O4, but O5 would not be higher than O6 as seen in Table 5. (Braver
& Braver, 1988). Evidence indicating pretest sensitization, or test reactivity effect, would be
detected by an interaction. The researcher evaluated a 2 x 2 between-groups analysis of
variance (ANOVA) on the four posttests, as indicated in Table 5.
An Analysis of Varaiance (ANOVA) of the posttest scores of the four participating
schools indicated no test reactivity effect was found in this study. Prob > F was reported at
0.91 with a F ratio of 0.24 (see Appendix J). This suggested that the pretest did not drive the
posttest, but the treatment drove the posttest. The researcher kept the pretest scores for the
purposes of comparing this study to the orginal study by Leising, Pense and Portillo entitled,
“The Impact of Selected Agriculture in the Classroom Teachers on Student Agricultural
Literacy” (Leising, Pense, & Portillo, 2001). No meta-analysis data was available for
comparison other than originally published results. Additionally, the researcher dropped the
pretest scores and examined the posttest only scores for each grade level as opposed to grade
groupings.
Table 5. Three One-Treatment Condition Experimental Design
Design
Group
Pretest
Treatment
Posttest
Solomon four-group
1
O1
X
O2
2
O3
O4
3
X
O5
4
O6
Pre- and posttest control group
1
O1
X
O2
2
O3
O4
Posttest-only control group
1
X
O5
2
O6
Note: O = outcome measure;
X = treatment measure
Source: Braver and Braver, 1988.
CHAPTER 4
DATA ANALYSIS AND FINDINGS
The objective of this chapter was to present the research findings in graphic and
narrative formats. Upon completion of the analysis, the researcher presented the data to
address the purpose and objectives of this study.
Introduction
The purpose of this study is to assess the agricultural knowledge of selected Illinois
classrooms of public elementary school students in kindergarten through fifth grades, and
determine if gaps exist in the current K-12 educational curriculum regarding instructional
topics that would lead to agricultural literacy. To accomplish this, the study utilized
instruments based on the Food and Fiber Systems Literacy (FFSL) Framework standards
and benchmarks for collecting data on the agricultural knowledge of Illinois public
elementary school students.
Study Design
A quasi-experimental nonequivalent control group, using a pretest and a posttest, was
utilized to study the agricultural knowledge of selected Illinois kindergarten through fifth
grade students. A population of 430 students at four schools in four locations was included
in the study. Data was collected during the 2015-2016 school year.
The schools, Brownstown Elementary, with 148 students; Lick Creek Elementary
School, had 81 students; Nauvoo Elementary School, had 91 students; and Hiawatha
Elementary School, with 110 students. Classroom size varied from 11-23 students. The
classroom teachers at each site administered the instruments.
Analysis by Study Objectives
Objective 1: Describe the demographic profile of schools that participated in the study.
Descriptions of Research Sites
Qualitative data from documents, observations of Agricultural Literacy Coordinators,
and discussion with faculty and administrators helped to develop a demographic profile of
each site.
School 1.
Brownstown Elementary School (FCAE District 4) is located in Brownstown,
Fayette County, and is situated in the south central part of the state. It is part of the
Brownstown Consolidated School District 201. The PK- 6 student population totaled 229.
The ethnic composition of Brownstown Elementary School students was 95.6% White,
0.9% Black, 2.2% Hispanic, 0.9% Pacific Islander, and 0.4% two or more races. Lowincome
students comprised 64.6% of the student body and were eligible to receive free or reduced-
price lunches, lived in substitute care, or whose families received public aid. Another 3.5%
reported being homeless. Additionally, 18.8% of students received special education
services. Student mobility rates of 34.6% represented students who transfer in or out of the
school between the first school day of October and the last school day of the year, not
including graduates. Approximately $5,438 instructional expenditure per pupil was allocated
and included only the activities directly dealing with the teaching of students or the
interaction between teachers and students. Total revenue was $4.2 million, of which
$354,442 was federal funds. The single driving factor in school funding is local property
taxes, which yielded $941,292 to the district.
Attendance rate was 96% with an average class size of 17. There was a 15:1 student
to teacher ratio at Brownstown Elementary School. The FTE (Full-Time Equivalent) teacher
population was 27. The ethnic composition of Brownstown Elementary School teachers was
100% white, of which 81.5% was female and 18.5% was male (Illinois State
Board of Education, 2016).
School 2.
Lick Creek Elementary School (FCAE District 5) is located in Lick Creek, Union
County, and is situated in the far southern part of the state. It is part of the Lick Creek
Consolidated School District 16. The PK- 8 student population totaled 124. The ethnic
composition of Lick Creek Elementary School students was 95.2% White, 1.6% Black,
2.2%, and 3.2% two or more races. Low-income students comprised 37.9% of the student
body and were eligible to receive free or reduced-price lunches, lived in substitute care, or
whose families received public aid. Another 4.8% reported being homeless. Additionally,
8.1% of students received special education services. Student mobility rates of 5.5%
represented students who transfer in or out of the school between the first school day of
October and the last school day of the year, not including graduates. Approximately $5,151
instructional expenditure per pupil was allocated and included only the activities directly
dealing with the teaching of students or the interaction between teachers and students. Total
revenue was $1.1 million, of which $100,380 was federal funds. Local property taxes which
yielded $295,983 to the district.
Attendance rate was 95% with an average class size of 12. There was a 12:1 student
to teacher ratio at Lick Creek Elementary School. The FTE (Full-Time Equivalent) teacher
population was 11. The ethnic composition of Lick Creek Elementary School teachers was
100% white, of which 87.3% was female and 12.7% was male (Illinois State Board of
Education, 2016).
School 3.
Nauvoo Elementary School (FCAE District 3) is located in Nauvoo, Hancock
County, and is situated in the northwestern central part of the state boarding Missouri. It is
part of the Nauvoo-Colusa Consolidated School District 325. The PK- 8 student population
totaled 127. The ethnic composition of Nauvoo Elementary School students was 94.5%
White, 1.6% Hispanic, and 3.9% two or more races. Low-income students comprise 63.8%
of the student body and were eligible to receive free or reduced-price lunches, live in
substitute care, or whose families received public aid. Another 3.1% reported being
homeless. Additionally, 17.3% of students received special education services. Student
mobility rates were 41.5% representing students who transfer in or out of the school between
the first school day of October and the last school day of the year, not including graduates.
Approximately $5,309 instructional spending per pupil was allocated and included only the
activities directly dealing with the teaching of students or the interaction between teachers
and students. Total revenue was $3.2 million, of which $218,552 was federal funds. Local
property taxes contributed $2,090,374 to the district.
Attendance rate was 94% with an average class size of 14. There was a 12:1 student
to teacher ratio at Nauvoo Elementary School. The FTE (Full Time Equivalent) teacher
population was 23. The ethnic composition of Nauvoo Elementary School teachers was
100% white, of which 95.6% was female and 4.4% was male (Illinois State Board of
Education, 2016).
School 4.
Hiawatha Elementary School (FCAE District 2) is located in Kirkland, DeKalb
County, and is situated in the far northern part of the state. It is part of the Hiawatha
Consolidated School District 426. The PK- 8 student population totaled 421. The ethnic
composition of Hiawatha Elementary School students was 84.8% White, 0.2% black, 10.7%
Hispanic, 0.7% Asian, and 3.6% two or more races. Low-income students comprise 53.2%
of the student body and were eligible to receive free or reduced-price lunches, live in
substitute care, or whose families received public aid. Another 7.8% reported being
homeless with 2.1% demonstrating limited English proficiency. Additionally, 13.3% of
students received special education services. Approximately $5,409 instructional spending
per pupil was allocated and included only the activities directly dealing with the teaching of
students or the interaction between teachers and students. Total revenue was $6.1 million, of
which $484,316 was federal funds. Local property taxes added $3,917,616 to the district.
Attendance rate is 95%. Average class size is 20.6 with state average of 21.2. There
was an 18.5:1 student to teacher ratio at Hiawatha Elementary School. The FTE (Full Time
Equivalent) teacher population was 36. The ethnic composition of Hiawatha Elementary
School teachers was 100% white, of which 70.8% was female and 29.2% was male (Illinois
State Board of Education, 2016).
Objective 2: Compare differences using sum score means between AITC treatment group
and control group in student knowledge about agriculture, before and after AITC
instruction, for each grade grouping (K-1, 2-3, 4-5).
Data in Table 6 summarized the AITC treatment and control groups by pretests and
posttest mean scores. Data indicated a kindergarten through first grade pretest mean score of
38.66 for the treatment group and 34.54 for the control with standard deviations of 6.87 and
8.16, respectively. Data also indicated a kindergarten through first grade posttest mean score
of 39.72 for the treatment group and 38.76 for the control group with standard deviations of
6.72 and 6.66, respectively. Additionally, the differences for the kindergarten through first
grade posttest and pretest mean scores were 1.06 for the treatment group and 3.22 for the
control group.
Data indicated a second through third grade pretest mean score of 73.89 for the
treatment group and 71.96 for the control with standard deviations of 9.93 and 12.84,
respectively. Data also indicated a second through third grade posttest mean score of 77.30
for the treatment group and 76.29 for the control group with standard deviations of 10.39
and 9.80 respectively. In addition, the differences for the second through third grade posttest
and pretest mean scores were 3.41 for the treatment group and 4.33 for the control group.
Data indicated a fourth through fifth grade pretest mean score of 22.87 for the
treatment group and 24.59 for the control with standard deviations of 4.60 and 4.19
respectively. Data also indicated a fourth through fifth grade posttest mean score of 30.70
for the treatment group and 24.34 for the control group with standard deviations of 4.13 and
5.56 respectively. In addition, the differences for the fourth through fifth grade posttest and
pretest mean scores were 7.83 for the treatment group and (0.25) for the control group.
Objective 3: Compare differences in sum score means between AITC treatment groups and
control groups in student knowledge about agriculture, before and after AITC instruction,
using the five thematic areas of the Food and Fiber Systems Literacy (FSSL) Framework
between schools for each grade grouping (K-1, 2-3, 4-5). (see Table 7).
90
6 Summary of Grade Grouping for AITC Treatment and Control Pretest and Posttest
Mean Scores
Treatment Control
Grade Grouping n M SD % Correct n M SD % Correct
K-1
Pretest 47 38.66 6.87 75.80 24 34.54 8.16 67.73
Posttest 47 39.72 6.72 77.89 24 38.76 6.66 72.55
Difference 1.06 3.22
2-3
Pretest 54 73.89 9.93 71.74 24 71.96 12.84 69.86
Posttest 23 77.30 10.39 75.05 24 76.29 9.80 74.07
Difference 3.41 4.33
4-5
Pretest 46 22.87 4.60 49.72 32 24.59 4.19 53.46
Posttest 46 30.70 4.13 66.73 32 24.34 5.56 52.91
Difference 7.83 (0.25)
91
Table .
The kindergarten through first grade post mean scores by treatment and theme
indicated the treatment group answered 77.89 percent of the questions correctly and the
control group answered 72.55 percent correctly. The treatment and control groups were most
knowledgeable about Theme 5 (Food, Nutrition and Health) followed by Theme 4 (Business
and Economics), with the treatment group being more knowledgeable about Theme 1
(Understanding Food and Fiber Systems), while the control group was more knowledgeable
about Theme 3 (Science, Technology and Environment). The treatment and control groups
were least knowledgeable about Theme 2 (History, Geography and Culture).
The second through third grade post mean scores by treatment and theme indicated the
treatment group answered 75.05 percent of the questions correctly and the control group
answered 74.07 percent correctly. The treatment group was most knowledgeable about
Theme 3 (Science, Technology and Environment) followed by Theme 1 (Understanding Food
and Fiber Systems) and Theme 5 (Food, Nutrition and Health). The control group was most
knowledgeable about Theme 1 (Understanding Food and Fiber Systems) followed by
Theme 3 (Science, Technology and Environment) and Theme 4 (Business and Economics).
The treatment and control groups were least knowledgeable about Theme 2 (History,
Geography and Culture).
92
The fourth through fifth grade post mean scores by treatment and theme indicated the
treatment group answered 66.73 percent of the questions correctly and the control group
answered 52.91 percent correctly. The treatment group was most knowledgeable about
Theme 2 (History, Geography and Culture) followed by Theme 3 (Science, Technology and
Environment) and Theme 5 (Food, Nutrition and Health). The control groups were most
knowledgeable about Theme 3 (Science, Technology and Environment) followed by Theme 7
Summary of K-5 Mean Pretest and Posttest Scores by AITC Treatment and Control for Themes
Pretest
Posttest
Group
n
M
SD
% Correct
n
M
SD
% Correct
K-1
Treatment
47
47
Theme 1
12.06
3.53
50.00
12.19
3.33
44.44
Theme 2
6.74
1.97
44.44
7.13
1.76
44.44
Theme 3
7.34
1.62
44.44
8.17
1.44
33.33
Theme 4
3.19
0.74
60.00
3.40
0.84
40.00
Theme 5
9.32
0.86
80.00
8.83
1.53
60.00
K-1 Control
24
24
Theme 1
11.33
4.51
27.78
12.48
3.80
72.22
Theme 2
6.04
1.90
33.33
7.08
1.53
69.30
Theme 3
6.21
2.40
44.44
7.64
1.75
66.67
Theme 4
8.79
0.96
60.00
2.72
0.79
20.00
Theme 5
2.17
1.02
80.00
8.84
0.94
80.00
2-3
Treatment
54
23
Theme 1
22.33
2.85
78.57
22.91
2.79
82.14
Theme 2
15.04
3.43
63.16
17.22
2.41
78.95
Theme 3
15.22
3.01
95.00
16.26
4.16
85.00
Theme 4
9.20
2.96
68.42
10.35
2.85
63.16
93
Table .
Theme 5
12.09
3.20
70.59
10.57
3.33
88.24
2-3 Control
24
24
Theme 1
21.79
2.32
71.43
23.29
2.12
78.57
Theme 2
14.13
3.48
42.11
13.50
3.43
84.21
Theme 3
13.88
4.67
70.00
14.88
3.89
80.00
Theme 4
11.25
3.73
57.89
12.96
1.78
68.42
Theme 5
10.92
3.54
52.94
11.67
2.65
82.35
4-5
Treatment
46
46
Theme 1
0.26
1.95
35.71
10.76
1.40
78.57
Theme 2
0.24
2.34
53.33
7.83
2.49
40.00
Theme 3
8.39
1.31
52.26
5.17
1.00
83.33
Theme 4
6.22
1.27
42.86
5.11
1.25
57.14
Theme 5
3.57
0.96
50.00
1.83
0.90
75.00
4-5 Control
32
32
Theme 1
9.06
1.58
64.29
8.84
2.02
71.43
Theme 2
6.06
1.93
40.00
6.38
2.46
60.00
Theme 3
3.84
1.46
96.09
3.94
1.74
50.00
Theme 4
4.09
0.96
42.86
3.66
0.97
57.14
Theme 5
1.53
1.11
38.25
1.53
1.02
75.00
Note: Theme 1 (Understanding Food and Fiber Systems); Theme 2 (History, Geography and
Culture); Theme 3 (Science, Technology and Environment); Theme 4 (Business and
Economics); Theme 5 (Food, Nutrition and Health)
1 (Understanding Food and Fiber Systems) and Theme 4 (Business and Economics). The
treatment was least knowledgeable about Theme 4 (Business and Economics) and Theme 5
(Food, Nutrition and Health). The control group was least knowledgeable about Theme 2
(History, Geography and Culture) followed by Theme 5 (Food, Nutrition and Health).
Objective 4: Compare theme score mean gains between treatment and control groups in
94
student knowledge about agriculture, before and after AITC instruction, for each grade
grouping (K-1, 2-3, 4-5) (see Table 8).
Students’ mean and percent correct scores by thematic area of the FFSL Framework
allowed the researcher to verify the level of agricultural knowledge demonstrated by the
students receiving AITC instruction and those who did not receive AITC instruction. This did
not allow for the determination of students’ acquisition of agricultural knowledge. To reflect
the students’ acquisition of agricultural knowledge, the difference between the mean posttest
and the pretest score was calculated as the gain score.
The kindergarten through first grade posttest and pretest mean score differences by
treatment and themes reflected increase of 1.07 and 3.62 for the treatment and control
groups with standard deviation of 0.18 for the treatment group and a decrease of 1.98 for the
control group. The treatment and control groups’ highest knowledge increases were in
Theme 3 (Science, Technology and Environment) followed by Theme 2 (History,
Geography and Culture) and Theme 1 (Understanding Food and Fiber Systems). The
treatment group indicated an increase in knowledge about Theme 4 (Business and
Economics) while the control groups reflected a decrease. The control group had an increase
for Theme 5 (Food, Nutrition and Health) and the treatment group showed a decrease.
8 Comparison of Mean Gain Scores Between AITC Treatment and Control Groups by
Themes
Group n M SD
T C T C T C
K-1 Treatment/Control
Overall gain
47
24
1.07
3.62
0.18
(1.98)
Theme 1 (Understanding Food and Fiber Systems)
0.13
1.15
(0.20)
(0.71)
Theme 2 (History, Geography and Culture)
0.39
1.04
(0.21)
(0.37)
95
Table .
Theme 3 (Science, Technology and Environment)
0.83
1.43
(0.18)
(0.65)
Theme 4 (Business and Economics)
0.21
-6.07
0.10
(0.17)
Theme 5 (Food, Nutrition and Health)
(0.49)
6.67
0.67
(0.08)
2-3 Treatment/Control
Overall gain
54
23
3.43
4.33
0.09
(3.87)
Theme 1 (Understanding Food and Fiber Systems)
0.58
1.50
(0.06)
(0.20)
Theme 2 (History, Geography and Culture)
2.18
(0.63)
(1.02)
(0.05)
Theme 3 (Science, Technology and Environment)
1.04
1.00
1.15
(0.78)
Theme 4 (Business and Economics)
1.15
1.71
(0.11)
(1.95)
Theme 5 (Food, Nutrition and Health)
-1.52
0.75
0.13
(0.89)
4-5 Treatment/Control
Overall gain
46
32
13.02
(0.23)
(0.79)
1.17
Theme 1 (Understanding Food and Fiber Systems)
10.50
(0.22)
(0.55)
0.44
Theme 2 (History, Geography and Culture)
7.59
0.32
0.15
0.53
Theme 3 (Science, Technology and Environment)
(3.22)
0.10
(0.31)
0.28
Theme 4 (Business and Economics)
0.11
(0.43)
(0.02)
0.01
Theme 5 (Food, Nutrition and Health)
(1.74)
0.00
(0.06)
(0.09)
The second through third grade posttest and pretest mean score differences by
treatment and themes indicated increases of 3.43 and 4.33 for the treatment and control
96
groups, respectively. The standard deviation of 0.09 for the treatment group and a decrease
of 3.87 for the control group were reflected. The treatment group was most knowledgeable
about Theme 2 (History, Geography and Culture) while the control group indicated a
decrease. The control group was most knowledgeable about Theme 1 (Understanding Food
and Fiber Systems) while the treatment group reflected a smaller increase. The treatment and
control groups reflected similar knowledge gains in Theme 4 (Business and Economics).
The control group was more knowledgeable about Theme 5 (Food, Nutrition and Health)
with the treatment group exhibiting a decrease.
The fourth through fifth grade posttest and pretest mean score differences by
treatment and themes reflected increase of 13.02 for the treatment and a 0.23 decrease in the
control group with standard deviation decrease of 0.79 for the treatment group and a increase
of 1.17 for the control group.
The treatment group was most knowledgeable about Theme 1 (Understanding Food
and Fiber Systems) and Theme 2 (History, Geography and Culture) followed by a slight
increase in Theme 4 (Business and Economics). The treatment group indicated decreases in
Theme 3 (Science, Technology and Environment) and Theme 5 (Food Nutrition and
Health). The control group reflected slight increases in Theme 2 (History, Geography and
Culture) and Theme 3 (Science, Technology and Environment). No gain was indicated for
Theme 5 (Food Nutrition and Health). Decreases in agricultural knowledge were found for
Theme 4 (Business and Economics) and Theme 1 (Understanding Food and Fiber Systems).
97
Objective 5: Develop a profile of student knowledge about agriculture, before and after
AITC instruction based on pre- and posttest mean scores, for each grade grouping (K-1, 23,
4-5) by the five thematic areas of the Food and Fibers Literacy (FSSL) Framework (see
Table 9).
The K-1 group demonstrated equal knowledge for both treatment and control groups
about Theme 5 (Food, Nutrition and Health) in both pre- and posttests. While treatment and
control groups indicated the similar knowledge about Theme 4 (Business and Economics) in
the pretests, this knowledge dropped to fourth and fifth places in the posttests with Theme 1
(Understanding the Food and Fiber Systems) moving to the second most knowledgeable
theme in the posttests. Theme 2 (History, Geography and Culture) for treatment and control
groups posttests exhibited a third place knowledge while Theme 3 (Science, Technology and
Environment) remained the least knowledgeable area for the treatment group in both pre-and
posttests.
The 2-3 groups demonstrated the least knowledge about Theme 2 (History,
Geography and Culture) for the both treatment and control groups in the pretests with
Theme 4 (Business and Economics) becoming the least knowledgeable for the both
treatment and control groups in the posttests. The treatment group was most knowledgeable
about Theme 3 (Science, Technology and Environment) in the pretests and most
knowledgeable about Theme 5 (Food, Nutrition and Health) in the posttests. The control
group was most knowledgeable about Theme 1 (Understanding the Food and Fiber Systems)
in the pretests and most knowledgeable about Theme 2 (History, Geography and Culture) in
the posttests.
98
Table 9. Profile of Student Knowledge about Agriculture, Before and After AITC
Instruction, for Each Grade Grouping by Theme (1-Most Knowledgeable to 5-Least
Knowledgeable)
K-1 2-3 4-5
Pretest Posttest Pretest Posttest Pretest, Posttest
Treatment, Control
T, C
T, C
T, C
T, C
T, C
T, C
Theme 1
3,5
2,2
2,1
3,4
5,2
2,2
Theme 2
4,4
3,3
5,5
4,1
1,4
5,3
Theme 3
5,3
5,4
1,2
2,3
2,1
1,5
Theme 4
2,2
4,5
4,3
5,5
4,3
4,4
Theme 5
1,1
1,1
3,4
1,2
3,5
3,1
Note: Theme 1 (Understanding Food and Fiber Systems); Theme 2 (History, Geography and
Culture); Theme 3 (Science, Technology and Environment); Theme 4 (Business and
Economics); Theme 5 (Food, Nutrition and Health) and 1-Most Knowledgeable, 5-Least
Knowledgeable
99
For the 4-5 groups, the treatment group indicated the most knowledge about Theme
2 (History, Geography and Culture) in the pretests, and Theme 3 (Science, Technology and
Environment) in the posttests. The control group was most knowledgeable about Theme 3
(Science, Technology and Environment) in the pretests, and most knowledgeable about
Theme 5 (Food, Nutrition and Health) in the posttests. The treatment group demonstrated
the least knowledge about Theme 1 (Understanding the Food and Fiber Systems) in the
pretests and Theme 2 (History, Geography and Culture) in the posttests. The control group
showed limited knowledge about Theme 5 (Food, Nutrition and Health) in the pretests and
Theme 3 (Science, Technology and Environment) in the posttests.
Objective 6: Develop a demographic profile of students that participated in this study.
Results of Student Demographic Questionnaire
Section One of the instrument included four questions identifying aspects of student
demographic information: including age, gender, ethnicity, and the number of years the
student received Agriculture in the Classroom (AITC) instruction. Frequencies and
percentages were calculated for each identified gender. The students were generally
distributed evenly by gender, however, in Schools 1, 3, and 4, the number of males was 3.3
to 14.5% higher than females. Only School 2 demonstrated a 3.3% higher female to male
count (see Table 10).
Solomon Four-Group Design Analysis
An analysis of variance of the data using the Solomon Four-Group design analysis,
found no indication of pretest sensitization, or test reactivity effect, was present in this study
(see Appendix H).
100
This finding is supported by the comparison of mean scores based on the
administration of a pretest administration or no pretest administration (See Figure 4).
Table 10. Distribution of Study Participants by Frequency and Gender
Male
Female
School Number
n
%
n
%
Total n
1
77
53.9
70
46
147
2
38
47.2
43
52.7
81
3
47
51.6
44
48.3
91
4
63
57.3
47
42.7
110
Total
225
204
429
101
Figure 4: Mean Score Based on Administering Pretest or No Pretest
Where 1 row excluded
Each error bar is constructed using 1 standard error from the mean.
Me
a
n Score Based On Administering Pretest or No Pretest
Pretest
N
Y
0
10
20
30
40
50
60
Mean
102
As a result of this finding, the researcher reexamined only the posttest mean scores,
by individual grade levels, i.e. K, 1, 2, 3, 4, and 5 as opposed to grade groupings of K-1, 2-3
and 4-5. A one-way analysis of variance (ANOVA) between subjects was conducted to
compare the effect of the posttest mean scores by grade and test type, i.e. treatment or
control. The grade effect resulted in lost degrees of freedom and was examined separately.
There was a significant effect on the posttest mean scores at p < 0.05 for type condition;
control [F(5,5) = 9.98, p = 0.0123) and treatment [F(5,5) = 100.471, p < .0001].
Additionally, a one-way analysis of variance examined compare posttest mean scores by
grade. The comparison was significant at p < 0.05 for grade effect [F(5,17) = 36.67, p <
.0001].
The researcher also examined a potential theme effect. The one-way analyses for
theme where p < 0.05 resulted in the following findings: Theme 1 [F(5, 17) = 38.08, p =
<.0001]; Theme 2 [F(5, 17) = 70.77, p < .0001]; Theme 3 [F(5, 17) = 91.87, p < .0001];
Theme 4 [F(5, 17) = 75.07, p < .0001]; and Theme 5 was not significant. (see Appendix H –
Analysis of Variance Tables).
Summary of Findings
1. A Solomon Four-Group analysis indicated that pretest sensitization, or test reactivity
effect, was not present in the four-school posttest examination. This suggested the
pretest did not drive the posttest, but the treatment drove the posttest.
2. Elementary school students participating in this study demonstrated that agricultural
literacy knowledge was increased for all groups except the 4-5 grade control group,
103
which indicated a 0.25 decrease in agricultural literacy knowledge where pre-and
posttests were administered.
3. A Solomon Four-Group analysis indicated that pretest sensitization, or test reactivity
effect, was not present in the four-school posttest examination. This suggested the
pretest did not drive the posttest, but the treatment drove the posttest.
4. Elementary school students participating in this study demonstrated that agricultural
literacy knowledge was increased for all groups except the 4-5 grade control group,
which indicated a 0.25 decrease in agricultural literacy knowledge where pre-and
posttests were administered.
5. Given the findings in Number 1, the pretest mean scores were dropped and the
posttest only mean scores for each classroom, as opposed to grade group, were
analyzed.
6. Student demographic profiles for this study indicated a slightly greater male to
female ratio, 225 to 204 respectively.
7. Schools varied in student enrollment for this study with numbers from 81 to 148.
Class size varied from 11 to 23 students per grade.
8. School demographics showed low-income student population varied from 37.9% in
School 2 to 64.6 % in School 1.
9. School demographics indicated students receiving special education services varied
from 8.1% in School 2 to 18.8% in School 1.
10. Instructional spending per pupil ranged from $5,151 for School 2 to $5,438 for
School 1, and included only the activities directly dealing with the teaching of
students or the interaction between teachers and students.
104
11. Property tax contributions to school districts ranged from $295,983 for School 2 to
$3,917,616 for School 4.
12. The fourth through fifth grade treatment group achieved the highest mean score gain
with fourth through fifth grade control group earning the lowest mean score gain of
all grade groupings. Second through third grade treatment and control groups
exhibited the highest means score gains of all grade groupings. Kindergarten through
first grade treatment and control groupings indicated positive mean score gains.
13. The fourth through fifth grade treatment grouping scored the highest mean scores in
the Understanding Food and Fiber Systems theme and in the History, Geography and
Culture theme and the lowest in the Science, Technology and Environment theme.
The fourth through fifth control group indicated negative mean score gains in all
themes except History, Geography and Culture, which scored a slight mean score
gain.
14. The second through third grade treatment grouping indicated the highest mean core
gain in History, Geography and Culture theme followed by Business and Economics
theme and Science, Technology and Environment theme. A slight increase in mean
score gain was scored in Understanding Food and Fiber Systems theme. The Food,
Nutrition and Health theme indicated negative mean score gain.
15. The kindergarten through first grade treatment group had slight increased mean
score gains in Science, Technology and Environment theme, followed by History,
Geography and Culture theme, Business and Economics theme and Understanding
Food and Fiber Systems theme. Food, Nutrition and Health indicated a negative
mean score gain. The kindergarten through first grade control group indicated the
highest mean score gain in Food Nutrition and Health theme followed by Science,
105
Technology and Environment theme, Understanding Food and Fiber Systems theme,
and History, Geography and Culture theme scoring similarly. The Business and
Economics theme had the highest negative mean score gain of all grade groupings.
16. This study was compared to findings in a previous four state agricultural literacy
study conducted by Leising, Pense, and Portillo, from June 15, 2001 through
September 14, 2003, entitled, “The Impact of Selected Agriculture in the Classroom
Teachers on Student Agricultural Literacy”. Only published data was available for
comparisons. In comparing this study to the previous study, the researcher found
students in Illinois public elementary schools demonstrated positive mean gain
scores for both treatment and control groups (K-1 and 2-3), except for 4-5 control
group, which indicated a slight 0.25 decrease in agricultural literacy knowledge.
While the differences in mean gain scores was not as sizeable as the Leising et al.
study, the researcher contributes the smaller mean score gains to the fact that Illinois
was one of the earliest adopters of the Agriculture in the Classroom instructional
program. Therefore, Illinois public elementary students had potential access to
agricultural literacy materials possibly earlier than public elementary students who
participated in the previous study.
17. Relating the Illinois public elementary students’ agricultural knowledge by themes
with the Leising et al. study, the K-1 group were most knowledgeable about
agricultural topics regarding Theme 5 (Food, Nutrition and Health) as was found in
the previous study, followed by Theme 1 (Understanding the Food and Fiber
Systems). The students in the Leising et al. study were similarly knowledgeable
about Theme 4 (Business and Economics) and Theme 2 (History, Geography and
Culture) as were the students in the this study.
106
18. The 2-3 treatment and control groups in the Leising et al. study were most
knowledgeable about Theme 1 (Understanding the Food and Fiber Systems). The
treatment group followed with Theme 2 (History, Geography and Culture) and
Theme 3 (Science, Technology and Environment). The treatment group was least
knowledgeable about agricultural topics regarding Theme 4 (Business and
Economics) as was the 2-3 treatment and control groups in this study. The treatment
group in this study was most knowledgeable about Theme 3 (Science, Technology
and Environment) in the pretest and Theme 5 (Food, Nutrition and Health) in the
posttests. Similarly, the pretest control group in this study was knowledgeable about
agricultural topics involving Theme 1 (Understanding the Food and Fiber Systems)
as was the control group in the Leising et al. study. However, the posttest control
group in this study was more knowledgeable regarding Theme 2 (History,
Geography and Culture) than the control group in the previous study, which was the
least knowledgeable.
19. The 4-5 treatment group in this study was most knowledgeable about agricultural
topics involving the Theme 2 (History, Geography and Culture) in the pretests and
Theme 3 (Science, Technology and Environment) in the posttests. The treatment
group demonstrated the least agricultural knowledge about Theme 1 (Understanding
the Food and Fiber Systems) in the pretests and Theme 2 (History, Geography and
Culture) in the posttests. The control pretest group was most knowledgeable about
Theme 3 (Food, Nutrition and Health) and least knowledgeable regarding
agricultural topics in Theme 3 (Science, Technology and Environment) in the
posttest. In the Lesing et al. study, both treatment and control groups were most
107
knowledgeable regarding Theme 2 (History, Geography and Culture) as was this
study’s treatment pretest group and least knowledgeable about agricultural topics
regarding Theme 4 (Business and Economics).
108
CHAPTER 5
CONCLUSIONS, RECOMMENDATIONS, AND IMPLICATIONS
Summary
Purpose
The purpose of this study was to assess the agricultural knowledge of selected
Illinois classrooms of public elementary school students in kindergarten through fifth
grades, and determine if gaps exist in the current K-12 educational curriculum regarding
instructional topics that would lead to agricultural literacy. To accomplish this, the study
utilized the original instruments based on the Food and Fiber Systems Literacy (FFSL)
Framework standards and benchmarks for collecting data on the agricultural knowledge of
Illinois public elementary school students.
Objectives
To accomplish the purpose of the study, the research project was focused on the
following research objectives:
1. Develop a demographic profile of schools that participated in the study.
2. Assess differences using sum mean scores between AITC treatment groups and
control groups in student knowledge about agriculture, before and after AITC
instruction, for each grade grouping (K-1, 2-3, 4-5).
3. Assess differences in sum mean scores between AITC treatment groups and
control groups in student knowledge about agriculture, before and after AITC
instruction, using the five thematic areas of the Food and Fiber Systems Literacy
(FSSL) Framework between schools for each grade grouping (K-1, 2-3, 4-5).
109
4. Assess theme mean score gains between treatment and control groups in student
knowledge about agriculture, before and after AITC instruction, for each grade
grouping (K-1, 2-3, 4-5).
5. Develop a profile of student knowledge about agriculture, before and after AITC
instruction based on pre- and posttest mean scores, for each grade grouping (K-1,
2-3, 4-5) by the five thematic areas of the Food and Fibers Literacy (FSSL)
Framework.
6. Develop a demographic profile of students who participated in this study.
Study Design and Procedure
This study utilized a quasi-experimental nonequivalent control group, using a pretest
and a posttest, as described by Cook and Campbell (1979). Quasi-experimental designs are
used where non-randomization of treatment groups are allowed (Ary, Jacobs, & Sorenson,
2010). Some suggest pretests may influence results (Blakstad, 2008). However, this is one of
the more frequently used designs in social sciences to measure the degree of change
occurring as a result of a treatment or intervention (Shuttleworth, 2009). Cook and Campbell
(1979) noted while not a true experimental design by name, quasi-experimental designs
could sometimes provide a more natural, generalizable environment that better establishes
effectiveness (as opposed to efficacy, typically associated with medical research).
Treatment and control groups were selected in each participating FCAE District
within Illinois. The treatment group was comprised of classrooms (K-5) in schools that
utilize AITC Literacy Coordinators, training, and/or materials in the academic year
20152016. The control group was comprised of classrooms (K-5) in schools that did not
utilize AITC Literacy Coordinators, training, and/or materials in the academic year 2015-
110
2016. The control groups were selected from schools that were similar in size and
geographic location to the treatment groups. A pretest and posttest were administered to
students to measure their knowledge about agriculture.
Population
The population of this study included a cross-section of selected public elementary
school classrooms across the state of Illinois during the 2015-2016 academic school year. As
random sampling was not feasible based on unique characteristics of each school and the
availability of subjects in intact groups, this study employed a purposive sample (Lund
Research Ltd., 2012; Wiersma, 1995).
One form of purposive sampling technique, or homogeneous sampling, contains
units, which are similar in terms of age and background (Black, 2010). Worthen, Sanders
and Fitzpatrick (1997, p. 359) employ the term “judgment sampling”, the strength of which
is found in describing a subgroup, which permits a better understanding of the program as a
whole. This non-probability sampling approach is based on particular characteristics or
judgments, which will best enable the research questions to be answered; these are specific
to the characteristics of a particular group and is not to be considered a weakness
(Explorable, 2016; Lund Research Ltd., 2012). In this study, the researcher selected the
schools based on the knowledge and professional judgment of the Illinois County AITC
Literacy Coordinators who participated, and not based solely on the researcher’s knowledge
or judgment.
The target population was 500 students, similar in number per state, to the original
study conducted by Leising, et al. in 2003. The population includes students in schools
whose student population varied from 81 to 148 students. Classroom sizes varied from 11 to
111
23. Intact groups of students reflecting diverse academic ability, both genders, and all
present ethnicities were included in the population. The final population was 430 students
rather than the targeted population of 500 students.
Instrumentation
A review of the literature indicated previous studies utilized a variety of data
collection instruments. Some researchers elected to create a new instrument to achieve
research objectives (Doerfert D. , 2003). Other researchers developed an instrument based
on the 11 agricultural literacy objectives identified by Frick, et al. (Frick, Kahler, & Miller,
1990). Doerfert (2003) noted that a select number of researchers chose to utilize instruments
developed by another researcher(s).
The researcher of this study chose to utilize the original instruments, developed and
tested by Leising and Igo, based on the K-5th grade benchmarks of the FFSL Framework of
standards and benchmarks for agricultural literacy (Leising, Igo, Heald, Hubert, &
Yamamoto, 1998) (See Appendix E- Food and Fiber Systems Literacy Tests for students in
grades K-5). At the time of this study, no other instrument had been developed, tested, or
was available to assess agricultural literacy knowledge of students in K-5.
Data Collection
In order to obtain the broadest cross-section of elementary public school students in
Illinois, classroom test sites were purposively selected from the five FCAE Districts by
randomly selected county Agriculture Literacy Coordinators and roughly represented by the
FCAE Districts. One to six schools in each district were selected for this study resulting in a
total of 31 potential study sites.
112
The instrument, for each appropriate grade level, was administered at each site by the
same teacher (See Appendix E-Food and Fibers Systems Literacy Tests). To ensure
anonymity, each instrument was given a six-digit number in an effort to separate test scores,
FCAE Districts, school identities, grade levels, as well as the identities of individual
students.
Demographic information of each school was based on documents the schools
submitted for state and federal funding as well as qualitative observations of the researcher
or AITC Agriculture Literacy Coordinators.
Data Analysis
Each student’s six-digit code number was pre-stamped by the researcher on each
grade appropriate instrument. The identities of the students were not connected to the
student numbers on the instruments, but were used to ensure that each student was scored
separately and participated in both pretest and posttest, and was grouped according to grade
level and school. The researcher kept a record of the students’ names and students’
identification numbers. This list was destroyed after completion of data collection to ensure
anonymity.
Upon completion and retrieval of the pretest instruments, tests were scored by hand
and coded into a Microsoft Excel spreadsheet (Microsoft Excel for Mac 2011, Version
14.6.0) for analysis purposes. A data file was created for import to JMP Pro Version 13.0.0
and was used to perform all statistical procedures and analysis of pretest and posttest group
data in conjunction with the stated purpose and objectives of this study.
Descriptive statistics were utilized to report demographic characteristics of the
respondent students. The JMP Pro Version 13.0.0 was used to calculate frequencies and
113
percentages of study respondents by age, gender, and grade. Descriptive statistics were also
utilized to describe and summarize observations; specifically, percentages, means, and
standard deviations.
Statistical Treatment Using Solomon Four-Group Design
Over 65 years ago, Solomon introduced a new form of experimental design referred
to as the Solomon four-group design (Solomon, 1949). Campbell and Stanley described the
Solomon four-group design (Campbell & Stanley, 1963) as a one-treatment experimental
design. However, the researchers found the Solomon four-group design was the only design
able to assess the presence of pretest sensitization or test reactivity (Huck & Chuang, 1977).
Huck and Sandler (1973, p.54) noted that “exposure to the pretest increases … the Ss’
sensitivity to the experimental treatment” and prevented generalizations between the
pretested group and the unpretested group. Therefore, the Solomon four-group design added
a higher degree of external validity in addition to the internal validity leading Helmstadter
(1970, p. 110) to conclude it (i.e., the Solomon 4-group design) was the most desirable of all
basic experimental designs.
Conclusions may be more complicated using the Solomon design due to the number
of comparisons it allows (Oliver & Berger, 1980). This intricacy may dissuade researchers
from using Solomon. With increased negativity toward allowing outside testing in schools,
such as the researcher encountered firsthand, if Solomon could demonstrate that a pretest
was unnnecessary and did not drive the outcome, school administrators may be more
amemanble to allowing outside testing in their schools or school districts in which only a
posttest would be administered.
114
Major Findings
A statistical analysis using the Solomon Four-Group Design found pretest
sensitization, or test reactivity effect, was not present in this study. This finding is significant
in that it could persuade school administrators to allow outside research studies access to
their educational systems, as only a single posttest would be required. This was the single
greatest barrier in this study--the time requirements school administrators perceived to be
too burdensome to allow for pre- and posttesting of their student population. Without this
obstacle, future research studies may gain access into educational systems more readily.
Illinois public elementary students who participated in this study demonstrated they
possess varying levels of knowledge about agriculture using the Food and Fibers Systems
Literacy with regards to the five thematic areas of the FFSL. All grade groups (K-1, 2-3, 45)
for both treatment and control groups indicated positive gains in overall agricultural
knowledge with the exception of the 4-5 control group, which showed a slight degrease in
their knowledge about agricultural topics.
The kindergarten through first grade treatment and control groups were most
knowledgeable about agricultural topics related to Theme 5 (Food, Nutrition and Health),
and were least knowledgeable about agricultural topics regarding Theme 2 (History,
Geography and Culture).
The second through third grade treatment group was most knowledgeable about
agricultural topics associated with Theme 3 (Science, Technology and Environment) while
the control group was most knowledgeable about agricultural topics as related to Theme 1
(Understanding the Food and Fibers System). Both treatment and control groups
demonstrated limited agricultural knowledge regarding Theme 2 (History, Geography and
Culture).
115
The fourth through fifth grade treatment group was most knowledgeable with
agricultural topics relating to Theme 2 (History, Geography and Culture) with the control
group most knowledgeable regarding Theme 3 (Science, Technology and Environment).
Both groups demonstrated the least agricultural knowledge relating to Theme 4 (Business
and Economics) and Theme 5 (Food, Nutrition and Health).
Findings by Objectives
Objective 1: Develop a demographic profile of schools that participated in the study.
The schools, which participated in the study, reflected the diversity of the very
vertical (north/south) state of Illinois. Student enrollment varied from 81 to 148, which are
similar with other schools in their regions of the state whether a rural school or a suburban
school.
School demographics indicated low-income student population varied from 37.9% to
64.6 %. Additionally, schools with students receiving special education services varied from
8.1% to 18.8%.
Instructional spending per pupil ranged from $5,151 to $5,438, and included only the
activities directly dealing with the teaching of students or the interaction between teachers
and students. Property tax contributions to school districts, a major source of local school
funding, ranged from $295,983 for to $3,917,616.
Objective 2: Assess differences in posttest mean scores between AITC treatment group and
control group in student knowledge about agriculture, before and after AITC instruction, for
each grade grouping (K-1, 2-3, 4-5).
The fourth through fifth grade treatment group achieved the highest mean score gain
with fourth through fifth grade control group earning the lowest mean score gain of all grade
116
groupings. Second through third grade treatment and control groups exhibited the highest
mean score gains of all grade groupings. Kindergarten through first grade treatment and
control groupings indicated positive mean score gains.
Objective 3: Assess differences in posttest mean scores between AITC treatment groups and
control groups in student knowledge about agriculture, before and after AITC instruction,
using the five thematic areas of the Food and Fiber Systems Literacy (FSSL) Framework
between schools for each grade grouping (K-1, 2-3, 4-5).
The kindergarten through first grade post mean scores by treatment and theme
indicated the treatment group answered 77.89 percent of the questions correctly and the
control group answered 72.55 percent correctly. The treatment and control groups were most
knowledgeable about Theme 5 (Food, Nutrition and Health) followed by Theme 4 (Business
and Economics), with the treatment group being more knowledgeable about Theme 1
(Understanding Food and Fiber Systems), while the control group was more knowledgeable
about Theme 3 (Science, Technology and Environment). The treatment and control groups
were least knowledgeable about Theme 2 (History, Geography and Culture).
The second through third grade post mean scores by treatment and theme indicated
the treatment group answered 75.05 percent of the questions correctly and the control group
answered 74.07 percent correctly. The treatment group was most knowledgeable about
Theme 3 (Science, Technology and Environment) followed by Theme 1 (Understanding
Food and Fiber Systems) and Theme 5 (Food, Nutrition and Health). The control group was
most knowledgeable about Theme 1 (Understanding Food and Fiber Systems) followed by
Theme 3 (Science, Technology and Environment) and Theme 4 (Business and Economics).
The treatment and control groups were least knowledgeable about Theme 2 (History,
117
Geography and Culture).
The fourth through fifth grade post mean scores by treatment and theme indicated the
treatment group answered 66.73 percent of the questions correctly and the control group
answered 52.91 percent correctly. The treatment group was most knowledgeable about
Theme 2 (History, Geography and Culture) followed by Theme 3 (Science, Technology and
Environment) and Theme 5 (Food, Nutrition and Health). The control groups were most
knowledgeable about Theme 3 (Science, Technology and Environment) followed by Theme
1 (Understanding Food and Fiber Systems) and Theme 4 (Business and Economics). The
treatment was least knowledgeable about Theme 4 (Business and Economics) and Theme 5
(Food, Nutrition and Health). The control group was least knowledgeable about Theme 2
(History, Geography and Culture) followed by Theme 5 (Food, Nutrition and Health).
Objective 4: Compare theme posttest mean score gains between treatment and control
groups in student knowledge about agriculture, before and after AITC instruction, for each
grade grouping (K-1, 2-3, 4-5).
The fourth through fifth grade treatment grouping scored the highest mean scores in
the Understanding Food and Fiber Systems theme and in the History, Geography and
Culture theme, and the lowest in the Science, Technology and Environment theme. The
fourth through fifth control group indicated negative mean score difference, or loss rather
than gain, in all themes except History, Geography and Culture, which scored a slight mean
score gain.
The second through third grade treatment grouping indicated the highest mean score
gain in the History, Geography and Culture theme, followed by the Business and Economics
theme and Science, Technology and Environment theme. A slight increase in mean score
118
gain was achieved in Understanding Food and Fiber Systems theme. The Food, Nutrition
and Health theme indicated a negative mean score difference, or a loss rather than gain.
The kindergarten through first grade treatment group had slight increased mean score
gains in the Science, Technology and Environment theme, followed by the History,
Geography and Culture theme, Business and Economics theme and Understanding Food and
Fiber Systems theme. Food, Nutrition and Health indicated a negative mean score
difference. The kindergarten through first grade control group indicated the highest mean
score gain in the Food Nutrition and Health theme followed by the Science, Technology and
Environment theme, Understanding Food and Fiber Systems theme, and History, Geography
and Culture theme. The Business and Economics theme had the highest negative mean score
difference of all grade groupings.
Objective 5: Develop a demographic profile of students that participated in this study.
Student demographic profiles for this study indicated a slightly greater male to
female ratio, 225 to 204, respectively, with three schools indicating the number of males was
3.3 to 14.5% higher than females. One school demonstrated a 3.3% higher female to male
count.
Racial demographics indicated the following: White (84.8% to 95.6%),
AfricanAmerican or Black (2.2%), Hispanic (10.7%), Asian (0.7%), Pacific Islander (0.9%),
and multi-racial (two or more races) (0.4% to 3.9%).
Conclusions
The conclusions in this study were not generalized beyond the 430-selected K-5th
grade students in the four Illinois elementary schools who participated in this study. The
major findings presented in this study support the following conclusions:
119
1. Based upon the demographic data collected, it was found that students
attending the four schools varied in population and property tax contributions to the
respective school districts. However, instructional spending per student was not too
different. The ethnic composition of the student population at each school was similar. Male
to female ratio favored male students slightly over female students.
2. Both AITC treatment and control group students possessed some agricultural
knowledge regarding the five thematic areas of the Food and Fiber Systems Literacy (FSSL)
Framework.
3. Both groups, the AITC treatment group and the control group, showed
increased mean score gains about agricultural knowledge for all grade groups (K-1, 2-3, 4-
5) with the exception of the fourth through fifth control group.
4. Student agricultural knowledge scores across all grade groupings differed
between pretest and posttest scores in three of the Food and Fiber Systems Literacy
Framework themes: Business and Economics; History, Geography and Culture; and Science,
Technology and Environment.
5. Most students in the study displayed similar levels of knowledge for the
theme, Understanding the Food and Fiber Systems, a foundational subject area in the Food
and
Fiber Systems Literacy Curriculum Framework.
6. The overall agricultural knowledge of K-5 grade school students at the four
Illinois elementary schools that participated in this study demonstrated that they do possess
varying levels of agricultural literacy, as defined by the FFSL Framework.
120
Recommendations
The following recommendations were based upon the researcher’s perceptions while
conducting this study, examination of the major findings of the study, conversations with
educators before and during the study, and the conclusions of the overall research project.
1. This study utilized an instrument based upon the Food and Fibers Systems
Literacy standards and benchmarks for grades K-5. It was previously piloted tested at
schools with students not associated with this study.
A. The five themes, as well as the standards and benchmarks, provide a
diagnostic tool for adoption and incorporation of an instructional program into
current curriculum. Teachers, as well as curriculum specialists, can use the
instrument to identify current gaps in their students’ knowledge about agriculture
and it’s related fields.
B. At the time of this study, no instrument, other than the FFSL
framework instrument, had been developed to assess the agricultural literacy of K-5
students. An updated instrument, especially one that aligns agricultural literacy with
the Common Core Standards (CCS) and the Next Generation Science Standards
(NGSS) is, in the opinion of this researcher, critically needed. If an instrument were
so designed, adoption and implementation into current school curricula by teachers
would be more feasible.
C. The redesign of the original testing instrument is critically needed.
With the schools’ adoption of computer technology, i.e. iPads, tablets, etc., into the
classroom, an interactive testing instrument, with use of color and sound, may reveal
121
the strengths and weaknesses of the current agricultural literacy program more
objectively.
D. With rapid changes in the fields of agriculture, science, technology,
environment, and culture, etc., a flexible system for updating, deleting, and changing
outdated facts and figures in a redesigned testing instrument needs to implemented to
remain relevant with the latest technologies and, thus allow for more accurate
measurements of student knowledge about current agricultural topics and trends.
2. Illinois, one of the earliest state adopters of the Agriculture in the Classroom
program has, at the time of this study, made advances toward aligning their agricultural
literacy classroom materials, especially the Ag Mags, to meet the Common Core Standards
and Next Generation Science Standards as adopted by the state.
A. The Minnesota Agriculture in the Classroom Program created an Ag
Mag Jr for students in K-2, the only one of its kind in the nation at the writing of this
study. Adoption, nationwide, of a publication such as this would create an
opportunity for younger audiences to learn about the importance of agriculture in
their daily lives with their families and siblings.
3. Students in this study demonstrated that they possessed some agricultural
knowledge. However, the areas in which they had the least knowledge were Business and
Economics; History, Geography and Culture; and Science, Technology and Environment.
Further research may be necessary to determine why students are deficient in these areas and
provide suggestions to correct this deficiency.
A. Creating summer agricultural youth camps, similar to those held by 4-
H, could expand students’ knowledge and interest about the field of agriculture.
122
4. Agricultural literacy may be viewed as unimportant, when in fact, the field of
agriculture touches the lives of every man, woman, and child in ways many educators,
parents, and students do not comprehend. As such, agricultural topics should receive greater
recognition and adoption into current STEM or STEAM literacy programs.
5. Teachers from local area schools, who spoke with the researcher, stated that
they would be more likely and more willing to incorporate agricultural literacy into their
current school curriculums if grade-level appropriate materials aligned with the Common
Core
Standards and Next Generation Science Standards, including lesson plans, activities, and/or
links to web-based materials, were available to them, preferably in a binder form with
copyready lessons. Simply put, they indicated that they do not have time or adequate
knowledge of the field of agriculture to search for or assemble appropriate materials while
meeting the standards to which they are expected to instruct students.
6. A methodology and delivery system, such as one suggested by local teachers,
should be developed that would infuse agricultural-based lessons into current curriculums.
Implications
Based on the findings of this study, the adoption and inclusion of agricultural literacy
in elementary schools may be too narrow in scope. A review and expansion of agricultural
education curriculums, programs, and currently available materials, Summer Ag
Institutes for teachers, and cooperative extension programs and materials is needed. A
review of literature in this study found programs aimed at educating adults, not only in this
county, but also in other regions of the globe, which in the opinion of the researcher, is a
123
motivator to broaden efforts to educate the younger population on the importance agriculture
plays in their daily lives.
From the observations and interactions of the researcher with students and educators
who participated in the study, as well as those outside of the study, younger elementary
students, specifically K-1, more readily absorb and retain information, especially if
presented to them in an engaging approach. This may be a contributing factor as to why the
K-1 group scored higher on some themes than their 4-5 counterparts. On the other hand,
students, specifically 4-5 group, are often being “taught to the test”, i.e. standardized tests,
and have limited classroom time available to participate in activities and lessons not readily
seen as contributing to increasing test scores. School administrators, facing pressure at the
state and local levels, are focused on increasing school scores often to the detriment of
agricultural-based activities.
Additionally, as an analysis of the Solomon Four-Group design demonstrated pretest
sensitization, or test reactivity, did not drive the outcome of the study. The treatment,
agriculturally based lessons and activities, was the driving force of the outcome, i.e. the
posttest scores. Given this finding, school administrators may be more open to future
agricultural literacy testing if a posttest only is required.
With most Americans being three to four, or more, generations removed from their
farming roots, agricultural educators, industry, and university and extension educators may
aid the expansion of agricultural knowledge to other educators across other disciplines
resulting in broader adoptions of agriculture as a context for teaching other subject matter.
This may promote increased agricultural literacy starting with our youngest citizens, and
over time, will spread agricultural literacy knowledge to the adult populace. Therefore, it is
124
imperative that current and future student citizenry become agriculturally literate in order to
lead, influence, and shape the future of agriculture and the world.
Agricultural literacy has been studied for over 30 years. During this period,
programs, materials and curriculum have been designed to promote agricultural literacy,
especially for K-8. New learning standards require agricultural literacy programs to evaluate
and modify their methods, materials, and strategies to meet the changing need of educators
and students alike.
Further dialogue among agricultural educators, agricultural literacy specialists,
curriculum and instruction specialists, and STEM and STEAM educators is clearly needed
to understand and address the societal necessity for understanding the importance of
agricultural literacy.
“If we estimate dignity by immediate usefulness,
agriculture is undoubtedly the first and noblest science.”
Samuel Johnson
