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Investigating the Effects of Cognitive Style on the Small Gasoline Engines Content Knowledge of Undergraduate Students in a Flipped Introductory Agricultural Mechanics Course at Louisiana State University

Whitney L. Figland, Louisiana State University, wfigla2@lsu.edu

J. Joey Blackburn, St. Charles Community College, jblackburn@stchas.edu

Kristin S. Stair, Louisiana State University, kstair@lsu.edu

Michael F. Burnett, Louisiana State University, vocbur@lsu.edu

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Abstract

One of the greatest challenges that classroom teachers face has been fostering a learning environment that caters to the needs of diverse learners. Teachers have various teaching methodologies at their disposal, ranging from passive, teacher-centered to active, student-centered strategies. The flipped classroom approach allows for teachers to become the facilitator of learning activities and students to become actively engaged in the learning experience. This transition allows for more student-centered activities to occur in class that enhance students’ critical thinking and problem-solving skills. Team-based learning (TBL) is a modified version of flipped classroom that allows students to work collaboratively to solve complex problems. Content knowledge has long been considered an important prerequisite of higher cognitive functions such as critical thinking, problem solving, and reflective thinking. The purpose of this exploratory study was to explain the effect of cognitive style on the small gasoline engines content knowledge of undergraduate students enrolled in a flipped introductory agricultural mechanics course at Louisiana State University. To test the hypotheses, this study utilized descriptive statistics, including the mean and standard deviation, and independent t-tests. A Mann-Whitney U test was employed to determine the influence of cognitive style on content knowledge. Overall, no differences in content knowledge were found. It is recommended to replicate this study longitudinally to increase statistical power. For practice, educators should employ learning strategies that meet the needs of students with diverse cognitive styles.

Introduction and Literature Review

One of the greatest challenges classroom teachers face has been fostering a learning environment that caters to the needs of diverse learners. To achieve this, teachers have a variety of teaching methodologies at their disposal, ranging from passive, teacher-centered methods to active, student-centered strategies (Schunk, 2012). One relatively new means of active engagement has been through the utilization of flipped classrooms. Some of the first flipped classroom models can be seen emerging into secondary and post=secondary education in the late 1990s and early 2000s after the inception of No Child Left Behind (NCLB) (Frederickson et al., 2005; Strayer, 2007; U.S. Department of Education, 2001). Baker (2000) presented his early version of the “classroom flip” as a new method of teaching that was made possible by an increase in the need for new educational methodologies that better engage learners and the increase in instructional technology availability (p. 4). Similarly, Lage et al. (2000) developed the “inverted classroom” model to invert the classroom structure and better engage students during class (p. 32). In both models, it was suggested to move instructional lecture material out of the classroom and make it available online, thus using class time for the professor to serve as a guide to assist students while providing increased time for application and practice (Baker, 2000; Lage et al., 2000). Over the past two decades, the flipped classroom approach has gained increased attention in secondary and post-secondary education for its student-centered approach and increased emphasis on engagement (Barkley, 2015; McCubbins et al., 2018).

The flipped classroom model allows teachers to become the facilitator of learning activities and the students to become actively engaged in the learning process while still focusing on delivering course content (Connor et al., 2014). This transition can allow for more student-centered activities during class to enhance students’ critical thinking and problem-solving skills (Allen et al., 2011; Hanson, 2006). Additionally, active learning strategies promote a student-centered learning environment by creating opportunities for students to solve problems in a real-world context (Michealsen & Sweet, 2008; Sibley & Ostafichuk, 2015).

In recent years, a new type of flipped classroom has emerged as a version of a traditionally flipped classroom; team-based learning (TBL). TBL has emerged as a flipped classroom technique that allows students to work collaboratively to solve complex problems during class time (Michealsen & Sweet, 2008; Wallace et al., 2014). Similar to traditional flipped classroom models, TBL is a student-centered approach that shifts instruction away from a traditional lecture format to create a student-centered learning environment (Artz et al., 2016; Nieder et al., 2005). In a TBL-formatted course, students take on the responsibility of learning conceptual knowledge outside of class and spend more time applying that knowledge in class as a part of a team (Michaelsen et al., 2004). Essentially, TBL is formatted to provide students with opportunities to learn declarative and procedural knowledge to enhance critical thinking and problem-solving skills (Michaelsen & Sweet, 2008). One aspect of TBL that sets it apart from the traditional flipped classroom is its increased emphasis on accountability (Michaelson et al., 2004). An essential element of TBL is the administration of Individual Readiness Assurance Tests (IRATS) and Team Readiness Assurance Tests (TRATS) that serve as formative assessments after each module to ensure students have engaged with the material.

Despite the many possible applications of TBL to agricultural education, research supporting its use in agricultural education has been limited. McCubbins et al. (2016) conducted a study to examine student perceptions of TBL in an agricultural education capstone course. The findings suggested that students had a positive view of TBL and were highly satisfied with the student-centered learning environment (McCubbins et al., 2016). This study also indicated that working in teams positively impacted student motivation to learn in a collaborative setting (McCubbins et al., 2016). A similar study conducted by McCubbins et al. (2018) found that TBL in agricultural education courses supported the development of critical thinking, motivation to learn, and ability to effectively apply course concepts by undergraduate students. Focusing specifically on agricultural mechanics, a course typically heavily focused on problem solving, Figland et al. (2020a) reported that undergraduate students perceived that TBL supported the development of problem-solving skills and promoted positive collaboration between group members while increasing student self-efficacy in the content area.

The ability to increase critical thinking and problem-solving skills cannot be developed exclusively by integrating specific teaching methods. Instead, the education literature has supported the notion that the cognitive styles of students in classes and educational teams can influence the ability of students to problem solve effectively (Myers & Dyer, 2006; Parr & Edwards, 2004; Thomas, 1992; Torres & Cano, 1994; Torres & Cano, 1995; Witkin et al.,1977). Cognitive styles have typically been defined as an individual’s preferred way of organizing and retaining information to solve problems (Keefe, 1979; Kirton, 2003). The awareness of a student’s cognitive style can be an important factor in the success of their ability to solve problems (Jonassen, 2000; Witkin et al., 1977). In agricultural education, Blackburn et al. (2014) and Lamm et al. (2011) concluded that before educators can understand how to tailor lessons to teach critical thinking and problem-solving skills effectively, they must be aware of varying cognitive styles and understand how to relate those cognitive styles to successful problem solving and critical thinking development. To better understand how problem solving can be developed within agricultural education coursework, cognitive style, and innovative teaching methods can be utilized to develop students’ critical thinking ability (Figland et al., 2020b).

Theoretical Framework

Kirton’s (2003) adaptation-innovation theory (A-I theory) served as the theoretical foundation of this study to aid in furthering the understanding of how critical thinking ability can be tied to TBL teaching methodologies. A-I theory is grounded on the premise that all people are creative and can solve problems, regardless of their preferred cognitive style (Kirton, 2003). Per the theory, cognitive style is a person’s preferred way to think, learn, and solve problems (Kirton, 2003). An individual’s cognitive style is measured through Kirton’s adaption-innovation inventory (KAI). KAI scores that fall below the mean are considered more adaptive, while scores above the mean are more innovative. However, it is important to note that the scale is a continuum, and individuals are never purely adaptive or purely innovative (Kirton, 2003). In other words, two people can have scores below the mean, indicating they are more adaptive compared to the normal distribution of scores, but the individual with the higher score is considered more innovative than the other.

When comparing the more adaptive and innovative, several key distinctions exist in how these individuals prefer to learn and solve problems. More adaptive individuals prefer well-established problems and favor working within the current problem structure (Kirton et al., 1991). These individuals collaborate well with group members and generate ideas that favor consensus (Kirton, 2003). On the contrary, the more innovative prefer less structure to solve the problem and often challenge boundaries (Kirton, 2003; Lamm et al., 2012). More innovative individuals tend to stretch the boundaries of problems and generate ideas outside the current group structure (Kirton, 2003). Often, individuals falling more on the innovative side of the continuum tend to be novel and find different ways to solve problems. Whereas the more adaptive ones tend to be safer, more predictable, conforming, and less ambiguous when solving problems (Kirton, 1999, 2003).

Cognitive style is one’s preferred way of learning and engaging in problem solving tasks (Kirton, 2003). However, learners are often presented with situations in which they must learn or perform outside their preferred style. In these instances, individuals utilize coping behaviors to navigate the environment (Kirton, 2003). Often, this occurs in a setting where the person must work with individuals of diverse cognitive styles. Kirton (2003) described this as the Problem A and Problem B situations. For example, consider students assembled into a team to complete a group project. Problem A is the group assignment, while Problem B is how well the group can navigate their diverse cognitive styles to perform the task.

Little research has existed in agricultural education that investigates the effects of cognitive style on student learning outcomes in a flipped learning environment. A-I theory postulates that cognitive style is unrelated to cognitive capacity; however, little literature has been advanced in agricultural education examining this notion. Further, no literature was found that tested this hypothesis in a flipped classroom setting. As a result, the principal question that arose after reviewing the literature was: How does cognitive style effect the small gasoline engine content knowledge of undergraduate students enrolled in a flipped introductory agricultural mechanics course at Louisiana State University?

Purpose of the Study

The purpose of this exploratory study was to explain the effect of cognitive style on small gasoline engine content knowledge of undergraduate students enrolled in a flipped introductory agricultural mechanics course at Louisiana State University.

The following null hypotheses guided this study:

H01: There were no statistically significant differences in small gasoline engine content knowledge of undergraduate students in an introductory agricultural mechanics course based on cognitive style.

Methodology

Data associated with this study were collected as a part of a larger research project that investigated students’ abilities to solve small gasoline engine-related problems. Specifically, a one-group pretest-posttest pre-experimental design was employed to collect data for this research (Campbell & Stanley, 1963; Salkind, 2010). This design is used widely in educational research when all individuals are assigned to the experimental group and observed at two points (Campbell & Stanley, 1963; Salkind, 2010). The changes from the pre-test to the post-test determine the results from the intervention; however, in this design, there is no comparison group, making it almost impossible to determine if the change would have occurred only from the intervention and not from extraneous variables (Salkind, 2010). Extraneous variables must be considered and dismissed to make any generalizations between the interventions and change (Salkind, 2010).

Population/Sample

The population of this study was all students who enrolled in an introductory agricultural mechanics course at Louisiana State University during the spring semester of 2018 (n = 17) and spring semester of 2019 (n = 15). Overall, one student in the spring semester of 2018 did not complete enough course material to be included in the study; therefore, the participating sample totaled n = 31. Institutional Review Board (IRB) approval was sought and granted. Per IRB, students were notified of this research on the first day of class and were given the opportunity to opt out without penalty. All students were over 18 and elected to provide signed consent to participate in this research.

To test for homogeneity between semesters, independent sample t-tests were conducted on individual cognitive score, age, and students’ pre-course interest survey to determine if the groups were homologous. The t-test analysis found that there were not statistically significant differences between the 2018 and 2019 semesters and cognitive style (p = .109), age (p = .596), and pre-CIS (p = .062), respectively. To test for homogeneity, Levene’s test for equality of error variances was calculated and was not statistically significant; therefore, it was assumed that the variances were almost equal and the groups were similar.

Further, a Chi-Square test was employed to determine if differences existed between the two semesters based on gender (X2 = .313, df = 1, p = .576). Therefore, from the analysis, it is concluded that our population from both semesters was homologous, and subsequently, the data were merged for further data analysis.

While the course was offered through the Department of Agricultural and Extension Education and Evaluation at Louisiana State University, it was advertised throughout the college and university. Table one provides the personal and educational characteristics of students (n = 31) who enrolled in this course during the spring of 2018 or 2019. Overall, these students’ ages ranged from 18 to 24, with 19 (29.0%) and 21(29.0%) being the most reported ages. The majority (n = 17; 54.8%) of students were female, and sophomore (41.9%) was the most frequently reported academic classification.  In all, nine majors were represented in this course, with Agricultural and Extension Education being the most common (41.9%).

Instrumentation

Kirton’s adaptation-innovation inventory (KAI) was used to determine students’ cognitive styles (Kirton, 2003). This instrument consisted of 32 items that asked questions about the individuals’ preferred way to learn. The KAI scores range from 32 to 160 on a continuum from more adaptive to more innovative, with a theoretical mean of 96 (Kirton, 2003). However, the practical mean of the KAI is 95 (Kirton, 2003). Therefore, individuals who score 95 or below are considered more adaptive, while those who score 96 or above are considered more innovative. The instrument has been successfully utilized to determine the cognitive style of a wide variety of individuals from varying backgrounds (Kirton, 2003). Internal reliability of this instrument has been measured through multiple studies. Kirton (2003) reported that after analyzing data from six different population samples with over 2,500 respondents that internal reliability coefficients ranged from .84 − .89. Also, 25 other studies that utilized the KAI showed reliabilities between .83 and .91 (Kirton, 2003).

Due to the nature of this pre-experimental study, it was important to determine the students’ knowledge in small gasoline engine content before and after the intervention. The researcher developed a 30-item criterion-referenced test to test the individual’s knowledge. It should be noted that half of the questions on this test were developed by Blackburn (2013) and further modified to meet the needs of this study. The other 15 questions were developed by the researcher based on the Small Engine Care & Repair textbook written by London (2003), a Small Engines Equipment and Maintenance textbook written by Radcliff (2016), and the Briggs and Stratton PowerPortal website. The criterion-referenced test was formatted using a four-option multiple-choice template, including one correct answer and three distractors. Guidelines offered by Wiersma and Jurs (1990) were followed to ensure the reliability of the criterion-referenced test. Table two provides the factors considered as well as how each was addressed.

Course Structure and Procedures

On the first day of the small gasoline engines unit, the KAI and the 30-item pretest were administered to the students. Due to using TBL as the primary teaching strategy, the students were grouped purposively by cognitive style into teams in which they would remain for the duration of the unit. Teams were developed as heterogeneous, homogeneous adaptive, or homogenous innovative. The course layout was formatted based on Michealsen and Sweet’s (2008) recommendations.

In the small gasoline foci, five individual modules were constructed, including (a) small engine tool and part ID, (b) 4-cycle theory and fuel, (c) ignition and governor systems, (d) cooling/lubrication system, and (f) troubleshooting. After each module, students completed an IRAT to determine their content knowledge retained. After completing the IRAT, the students would join their assigned team and complete the TRAT. During the TRATs, students were allowed to collaborate with other members to come to an agreement on items they may have gotten incorrect. The goal of completing the IRAT before the TRAT was to ensure that all group members of the team contributed equally. At the end of the small gasoline engine unit, the 30-item criterion-referenced test was administered.

Data Analysis

Descriptive statistics were utilized to test this study’s hypotheses, including means and standard deviations and independent sample t-tests. Independent sample t-tests are utilized to compare the means of two independent groups and determine if they are statistically significant. In this study, the t-tests were utilized to determine if the groups from the 2018 and 2019 semesters were homologous and could be merged for further data analysis. Further, Mann-Whitney U tests were employed to determine if there was a statistically significant difference between content knowledge and cognitive style.

Findings

The overall mean of the pretest was 15.58 (51.9%).  The mean of the more adaptive students pretest was 15.48 (51.6%), while the more innovative averaged 15.88 (52.9%). Regarding the post-test, the overall mean was 23.39 (77.9%). The more adaptive students’ average score was 22.96 (76.5%), and the mean post-test score of the more innovative students was 24.63 (82.1%), as presented in Table 5.

A Mann-Whitney U test was employed to determine if a statistically significant difference in content knowledge existed based on cognitive style. This test (see Table 6)determined no statistically significant differences in content knowledge by cognitive style (p = .292) at the .05 level.

Conclusion and Limitations

Overall, the statistical analysis revealed that cognitive style did not affect the small gasoline engine content knowledge of students enrolled in an introductory agricultural mechanics course at Louisiana State University. Therefore, the researchers failed to reject the null hypothesis. This conclusion aligns with the A-I theory in that cognitive style does not relate to cognitive capacity. In other words, one’s preferred style or manner of learning and problem solving does not influence the ability to learn or performance. Similarly, this research aligns with the findings of prior research that investigated factors influencing content knowledge achievement (Blackburn, 2013, 2014; Pate et al., 2004). However, these prior studies did not include a pretest measure of small gasoline engine content knowledge; therefore, they failed to account for pretreatment differences in content knowledge. Further, research should be conducted to compare the TBL method of teaching small gasoline engine content with direct instruction. Due to the lack of a comparison group, it is not known whether students in these semesters would have performed better or worse than similar students taught in a more traditional format. This type of research could allow practitioners greater confidence that, at a minimum, they are not impeding students learning by employing TBL in their classrooms.

This study was conducted during two spring semesters to increase the sample size to enhance statistical power. However, due to enrollment sizes and data attrition, the overall sample was only 31 students. Small sample sizes are a detriment to most parametric statistical tools; however, these data were tested for normality in SPSS. However, due to the low sample size, the statistical power of this research was inherently low, which increased the chance of committing Type-II errors.

An additional limitation of this study was the lack of random selection of participants. Due to the nature of using student enrollment in a particular class, caution must be given when interpreting the findings, and it cannot be generalized past the sample reported in this research. The introductory agricultural mechanics course was required for students majoring in agricultural and extension education and has become an increasingly popular elective for other majors across the university. Students not required to complete this course may have a higher mechanical aptitude or prior knowledge and/or experiences in the content areas, which may influence their performance in the course.

Recommendations

To increase statistical power, it is recommended that this research be extended for a minimum of three more semesters. Depending on enrollments, this would increase the sample size to more than 75 students. A sample size of 75 to 100 would sufficiently increase power. Further, additional variables such as mechanical aptitude should be assessed to determine the impact on content knowledge. Additionally, content knowledge should be utilized as an independent variable to determine its role in students’ problem-solving ability in authentic learning environments. Additional research should determine the effect of these diverse cognitive teams on the ability to generate hypotheses and solve authentic problems. Content knowledge could also be employed in a multiple regression model to determine its impact when hypothesizing and solving contextual problems.

Practitioners should be informed that cognitive styles influence how students prefer to learn and solve problems (Kirton, 2003) but are not related to how well a student learns. Teachers should strive to create learning environments conducive to diverse learners to ensure all students have an opportunity to learn (Roberts et al., 2020). As teachers provide opportunities for diverse learning styles – auditory, kinesthetic, and visual – they should provide opportunities geared toward the more adaptive and innovative problem-solving styles. This would ensure one style preference is not constantly required to employ coping behaviors to succeed. Post-secondary educators should consider TBL if they are interested in flipping an agricultural mechanics course. Results from this study indicated that, based on cognitive style, all students can learn successfully. Further, the use of frequent IRATs and TRATs ensures a level of accountability not normally found in traditional flipped classes.

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How do Animal Science Standards Align: A Comparison of South Carolina Standards to AFNR Standards

Kayla N. Marsh, Oklahoma State University, Kayla.marsh@okstate.edu

Christopher J. Eck, Oklahoma State University, Chris.eck@okstate.edu

K. Dale Layfield, Clemson University, dlayfie@clemson.edu

PDF Available

Abstract

Content and performance standards were the basis on which school-based agricultural education (SBAE) teachers develop effective and relevant instruction. These standards prepare students for future agricultural careers and support the needs of the community. The purpose of this study was to determine the extent to which South Carolina SBAE standards align with the national AFNR standards for the animal science career pathway. This study implemented an existing data design, comparing the South Carolina animal science standards and the national AFNR animal science pathway standards through content analysis. Thirty-one percent of standards were written at or above the Applying level, as compared to 95% of the AFNR standards. The analysis of standards demonstrated the lack of rigor in current standards. Although this study highlights concerns with SBAE standards in South Carolina, additional research is needed to see how other states’ standards align with AFNR standards. It is further recommended that teacher educators develop preservice and in-service activities that will prepare SBAE teachers to plan activities and assignments at higher-order levels of thinking.

Introduction

“A standard is both a goal (what should be done) and a measure of progress toward that goal (how well it was done)” (Ravitch,1995, p.7). Standards help teachers design courses and develop objectives to deliver content and evaluate student learning (Nilson, 1998). Specifically, content and performance standards were the basis on which school-based agricultural education (SBAE) teachers, school districts, and state education departments rely. These standards develop effective and relevant instruction to prepare students for future agricultural careers and support the needs of the community (Molina, 2009; Swafford, 2018). To be effective, content standards need to be current to support effective SBAE teachers, build capacity for abstract learning, and prepare students for science, technology, engineering, and math (STEM) based agricultural careers (Swafford, 2018). Judson et al. (2020) defined the process of teachers adapting standards to meet the community’s needs, beliefs, culture, and values as the sensemaking of educational standards. This evidence suggested that strong state standards provide a needed structure to empower teachers while still giving the sensemaking freedom to implement and support student learning (Judson et al., 2020).

The push for national standards started in 1989 with policy goals focused on academic achievement and an increase of rigorous coursework for all students. They prompted the reform of learning expectations and assessment, which led to state and national debate over content, assessment, and evaluation in educational systems (Clune, 1993; Darling-Hammond, 1994; Ravitch, 1995). Many oppose the adoption of national standards for a multitude of reasons, including federal control of educational standards, weak or narrow standards due to political influence, controversial values imposed by the government, and diminishing of teachers’ creativity and ability to connect with students in the classroom because they were forced to teach to an assessment or examination (Ravitch, 1995). These concerns still exist, as well as evidence that strong educational standards indicate learning gains, equity for all students, and increased collaboration and communication of needs (Bloom, 1956; Judson et al., 2020; Ravitch, 1995). Sharing ideas between teachers and educational content developers (i.e., textbook writers, curriculum and software developers, and assessment companies) requires well-defined standards as a guide (Anderson, 2001; Darling-Hammond, 1994; Ravitch, 1995). The debate was further complicated by diverse types of standards that have been ill-defined and vaguely used, but each were essential when creating coherent educational expectations for students (Ravitch, 1995). Specifically, content standards are appropriate when discussing what students should learn, while performance standards relate to measuring the level at which it was learned (Ravitch, 1995). Interrelated but irrelevant without the other is the consistent relationship between content and performance standards, making the process of adopting and revising standards messy (Ravitch, 1995). Therefore, it has become best practice to address the complexity and develop content and performance standards that serve as a strong framework to support SBAE teachers, students, administrators, faculty, and content developers because vague non-measurable standards are an ineffective tool in supporting rigorous and relevant instruction and learning (Anderson, 2001; Judson et al., 2020; Ravitch, 1995; Swafford, 2017).

To support these efforts, the Agriculture, Food, and Natural Resources (AFNR) content and performance standards were developed and supported by the National Council for Agriculture Education (2015). AFNR standards provide a baseline to support SBAE career clusters that incorporate STEM integration for multiple agricultural career pathways (The Council, 2015; Swafford, 2018). The eight different SBAE career pathways align AFNR standards with the components of a comprehensive SBAE program for instruction, career and leadership development (FFA), and Supervised Agricultural Experiences (SAE) with the following national standards to ensure a robust framework of rigor and relevance for SBAE programs: Common Career and Technical Core (CCTC), Next Generation Science Standards (NGSS), Common Core Mathematics (CCSS), Common Core English Language Arts (ELA), National Standards for Financial Literacy and Green/Sustainability Knowledge and Skill Statements (The Council, 2015; see figure 1). Not only were the AFNR standards a thoroughly crafted framework for SBAE teachers, students, and support professionals for classroom instruction, but they were purposely constructed to support the comprehensive model for secondary agricultural education developed by Baker et al. (2012), which includes supervised agricultural experiences (SAE) and leadership and career development through the national FFA organization.

Figure 1
Comprehensive Model for SBAE (Baker et al., 2012)

“Adoption and use of these standards is voluntary; states and local entities are encouraged to adapt the standards to meet local needs” (The Council, 2015, p. 2), ultimately allowing SBAE teachers to prepare students for future STEM careers by providing rigorous and relevant instruction while also meeting the needs of the community and program (Baker et al., 2012; Judson et al., 2020; Ravitch, 1995; Swafford, 2018). According to Swafford (2018), at least one STEM component (i.e., science, technology, engineering, or math) was directly aligned with AFNR standards within each pathway, with science the most prevalent as it was found in six of the eight pathways. Therefore, comprehensive SBAE programs were supported by strong content and performance standards with increased levels of rigor and career preparation through the relationship between AFNR and STEM standards (Baker et al., 2012; Judson et al., 2020; Swafford, 2018).

Theoretical and Conceptual Framework

This study was undergirded by Bloom’s (1956) taxonomy, which established distinct levels of learning and engagement as a hierarchical structure representing six categories, ranging from basic learning objectives (i.e., knowledge of content) to higher-order learning (i.e., synthesis and evaluation; Bloom, 1956; Clemons & Smith, 2017). Bloom formed the basis for early work on the development of instructional objectives, standards, and learning goals for classes and curricula, providing a framework and shared vocabulary for teachers, school districts, and educational content developers (Anderson et al., 2001; Bloom, 1956; Krathwohl, 2002). Each of the six categories of Bloom’s Taxonomy has been defined and represented by an action verb that distinguishes the level of learning and retention taking place, as represented in Figure 2.

Figure 2
Bloom’s (1956) Cognitive Taxonomy

The rigor, relevance, and retention of the content and skills learned increase as we move to the pinnacle of the pyramid represented by the action verb create from the base represented by the action verb remember (Anderson et al., 2001; Bloom, 1956; Krathwohl, 2002). Remember represents cognitive tasks that are more concrete and less abstract, including memorization, recall, and labeling as learning activities. Understanding demonstrates concrete learning through cognitive activities of comparing, contrasting, and explaining. Applying is achieved by organizing, developing, or utilizing concrete concepts learned in a new and abstract situation. Analysis reflects when learning activities ask students to analyze content to make assumptions, conclusions, and simplifications. Evaluation is an abstract process of detailed parts or critical elements to criticize, defend or justify within the learning activity. Create is the abstract use of many dissimilar sources to build, invent, solve, or test within the learning activity (Anderson et al., 2001; Bloom, 1956; Krathwohl, 2002). According to Anderson et al. (2001), we should approach this taxonomy as a guide to communicating the cognitive rigor expected from content and performance standards to construct relevant and effective learning activities and content materials. While the action verb is our first indicator as to the level of rigor associated with a learned activity, the context in which the action verb was used in the standard will impact the level of rigor of the task (Anderson et al., 2001; Bloom, 1956; Krathwohl, 2002). For this study, the hierarchical structure was used to determine the cognitive level of animal science standards in South Carolina compared to that of the national AFNR standards.

Purpose of the Study

The purpose of this study was to determine the extent to which South Carolina SBAE standards align with the national AFNR standards for the animal science career pathway. Three research objectives guided this study: (1) What percentage of South Carolina SBAE standards align with the AFNR standards for animal science; (2) At what level of Bloom’s Cognitive Taxonomy are the South Carolina SBAE standards written; and (3) How does the level of rigor compare between the South Carolina SBAE standards and AFNR standards?

Methods and Procedures

This study implemented a non-experimental existing data design (Privitera, 2020), comparing the South Carolina animal science standards and the national AFNR animal science pathway standards through content analysis. A content analysis allows researchers to analyze written records that outline detailed content (Privitera, 2020), in this case, educational standards. The publicly available electronic documents served as the existing data (Privitera, 2020) being analyzed, which included South Carolina SBAE standards for the Animal Science Career Pathway (South Carolina Cooperative Extension, 2021) and the national AFNR Standards for Animal Science (The Council, 2015).

The research team evaluated the state and national standards to determine the alignment between South Carolina standards and national AFNR standards. The research team consisted of a graduate student with nine years of SBAE teaching experience and two faculty members in agricultural education with over 40 years of combined experience in teaching and preparing students to be effective SBAE teachers. The team aimed to answer the three proposed research objectives through collaborative content analysis. Bloom’s Taxonomy (1956) was the lens used to evaluate the state and national standards by the research team. Using the complete research team to analyze the existing data helps the researchers overcome the potential experimenter bias (Privitera, 2020).

Microsoft Excel was implemented to categorize, compare, and analyze animal science standards through the lens of Bloom’s taxonomy (1956). As the research team analyzed each South Carolina standard, the standard was categorized into one of the 20 performance indicators associated with the eight AFNR content standards for the animal systems career pathway (see Table 1).

Table 1
Agriculture, Food, and Natural Resources (AFNR) Animal Systems Pathway Content Standards

AFNR Standard AFNR Performance Indicator
AS.01. Analyze historic and current trends impacting the animal systems industry AS.01.01. Evaluate the development and implications of animal origin, domestication and distribution on production practices and the environment.
  AS.01.02. Assess and select animal production methods for use in animal systems based upon their effectiveness and impacts. 
  AS.01.03. Analyze and apply laws and sustainable practices to animal agriculture from a global perspective.   
AS.02. Utilize best-practice protocols based upon animal behaviors for animal husbandry and welfare.    AS.02.01. Demonstrate management techniques that ensure animal welfare.   
  AS.02.02. Analyze procedures to ensure that animal products are safe for consumption (e.g., use in food system, etc.).  
AS.03. Design and provide proper animal nutrition to achieve desired outcomes for performance, development, reproduction and/or economic production.      AS.03.01. Analyze the nutritional needs of animals.      
  AS.03.02. Analyze feed rations and assess if they meet the nutritional needs of animals.  
   AS.03.03. Utilize industry tools to make animal nutrition decisions.   
AS.04. Apply principles of animal reproduction to achieve desired outcomes for performance, development and/or economic production.   AS.04.01. Evaluate animals for breeding readiness and soundness.  
  AS.04.02. Apply scientific principles to select and care for breeding animals   
   AS.04.03. Apply scientific principles to breed animals   
AS.05. Evaluate environmental factors affecting animal performance and implement procedures for enhancing performance and animal health.   AS.05.01. Design animal housing, equipment and handling facilities for the major systems of animal production.  
  AS.05.02. Comply with government regulations and safety standards for facilities used in animal production  
 AS.06. Classify, evaluate, and select animals based on anatomical and physiological characteristics.     AS.06.01. Classify animals according to taxonomic classification systems and use (e.g. agricultural, companion, etc.).
   AS.06.02. Apply principles of comparative anatomy and physiology to uses within various animal systems.     
  AS.06.03. Select and train animals for specific purposes and maximum performance based on anatomy and physiology.    
AS.07. Apply principles of effective animal health care.    AS.07.01. Design programs to prevent animal diseases, parasites and other disorders and ensure animal welfare.   
  AS.07.02. Analyze biosecurity measures utilized to protect the welfare of animals on a local, state, national, and global level.    
AS.08. Analyze environmental factors associated with animal production.    AS.08.01. Design and implement methods to reduce the effects of animal production on the environment.   
  AS.08.02. Evaluate the effects of environmental conditions on animals and create plans to ensure favorable environments for animals.   

To address the second research objective, the research team evaluated each South Carolina standard and categorized the taxonomical level (i.e., remember, understand, apply, analyze, evaluate, or create) at which the standard aimed to represent. The percentage of standards at each taxonomical level was then compared to address the final research objective using Microsoft Excel.

Results

Research Objective 1: What Percentage of South Carolina SBAE Standards Align with the AFNR Standards for Animal Science

The first objective sought to identify the percentage of South Carolina SBAE standards aligning with the AFNR standards for animal science. The South Carolina animal science pathway included 19 courses and 150 standards that were analyzed in comparison to the AFNR animal science pathway, which consists of eight standards and 20 performance standards. Ninety-five percent of the AFNR standards were written at or above Bloom’s applying level of taxonomy; in comparison, only 39% of South Carolina standards were written at a comparable level. The majority (57%) of South Carolina standards fell in the lowest taxonomy levels, including 12% at remembering and 45% at the understanding level. Additionally, 14% of the South Carolina standards were written at the applying level, 5% at the analyzing level, 3% at the evaluating level, and 20% at the creating level. Although 20% of South Carolina standards were representative of creating based on the action verbs used, 17 of the 31 (11%) used “Discuss” as the verb, when really it was being used to represent explain, which suggests that the South Carolina SBAE standards belonged to the t (Anderson et al., 2001; Bloom, 1956; Krathwohl, 2002). Sixty-eight percent of South Carolina SBAE standards were at or below the understand level compared to five percent of the AFNR Standards for the animal science pathways after the verb meaning adjustment (see Table 2).

Table 2
Comparison of State SBAE Standards and AFNR Standards at Each Level of Bloom’s Taxonomy

StandardIIIIIIIVVVI
AFNR
    Standard
0%5%35%30%20%10%
South Carolina 
     SBAE
     Standard
     with Adjusted
     Verb Meaning
  12%      56%  14%      5%  3%  9%

Research Objective 2: At what Level of Bloom’s Cognitive Taxonomy are the South Carolina SBAE Standards Written

The second objective explored South Carolina SBAE standards for animal science to be analyzed using Bloom’s taxonomy shown in Figure 1 (i.e., remember, understand, apply, analyze, evaluate, and create). The South Carolina standards align to remember (12%) and understand (56%) levels of rigor, which were limited to basic cognition tasks representing knowledge (Anderson et al., 2001). In addition, the wording of South Carolina SBAE standards and action verbs indicated the intended level of rigor at basic knowledge levels of remember and understand. Eleven percent of standards used the action verb discuss to represent lower cognitive tasks.

Furthermore, South Carolina SBAE content and program standard’s strength and value were hard to measure due to the limited number of standards per each of the 19 courses in the animal science pathway. Courses within the South Carolina SBAE animal science pathway ranged from 46 to zero standards, with an average of eight and a median of six. Additionally, five of the 19 South Carolina SBAE animal science pathway courses had no animal science standards. Table 3 compares the number of standards at each of the six levels of Bloom’s (1956) taxonomy with each of the 19 courses in the animal science career pathway in South Carolina.

Table 3
Comparison of South Carolina SBAE Course Specific Standards at Each Level of Bloom’s Taxonomy                                                                                               

 South Carolina SBAE courseIIIIIIIVVVITotal Standards per course
5624 – Agricultural Science
     and Technology
2400006
5691 – Agricultural and
     Biosystems Science
0720009
5620 – Agricultural Science
     and Technology for the
     Workplace
0000011
5600 – AgriBusiness and
     Marketing             
0000000
5614 – Agricultural Crop
     Production and
     Management
0301105
5660 – Agricultural
     Mechanics
     and Technology
0000000
5663 – Aquaculture3140008
5692 – Biosystems Mechanics
     and Engineering
0000000
5679 – Equine Science212210219
5657 – Food Processing0100001
5646 – Cattle Production06121111
5647 – Farm Animal
     Production
0320027
5612 – Small Animal Care630220646
5613 – Introduction to
     Veterinary Science
55100213
5627 – Soil and Water
     Conservation
1030004
5630 – Soil and Soilless
     Research
0000000
5603 – Animal Science04213010
5621 – Equipment Operations
     and Maintenance
0000000
5608/5609a – Animal Science
     for the Workplace I and II
08200010

Note. aCourse codes 5608 and 5609 represent the same course that is to be taken concurrently within an academic year. For the purpose of our standard analysis, they have been counted as a single and complete course.

Research Objective 3: How does the Level of Rigor Compare Between the South Carolina SBAE Standards and AFNR Standards

The final objective compared the level of rigor between the South Carolina SBAE standards and AFNR standards for the animal science pathway. Ninety-five percent of AFNR standards for the Animal Systems Career Pathway have expected student learning outcomes at or above the applying level, whereas 31% of South Carolina SBAE Animal Science standards were found in corresponding levels of Bloom’s Taxonomy.

Conclusions, Recommendations, and Discussion

Thirty-one percent of South Carolina animal science standards were written at or above the applying level of Bloom’s Taxonomy compared to 95% of the AFNR standards. The analysis of standards demonstrated the lack of rigor in current South Carolina standards, as they were primarily written at or below the understanding level. Comparatively, the AFNR standards were written at or above the applying level of Bloom’s Taxonomy, allowing students to integrate the new knowledge in the future, draw conclusions, and produce their own products. Unfortunately, the South Carolina standards asked students to memorize or recall basic information or describe the material, with students very rarely (less than 31%) getting to the application level. Furthermore, the South Carolina SBAE standard’s strength and value are hard to determine due to the apparent lack of consistent standards or expected quality of written standards in the animal science pathway. The number of standards spanned from zero to 46, with an average of eight standards per course. Additionally, five of the 19 animal science courses had no animal science standards, which represented a vague attempt at a rigorous and relevant framework for supporting SBAE students, teachers, school districts, content developers, and community needs (Molina, 2009; Ravitch, 1995; Swafford, 2018). The concept of vague standards was further exacerbated by unclear and misaligned action verbs with the expected student learning activity, where discuss was used at the level of create to represent higher-order learning activities that were truly explaining basic knowledge at the understanding level (Bloom, 1956; Clemons and Smith, 2017; Judson et al., 2020).

The movement from teacher-led learning activities to student-led learning creates higher-order learning activities that allow students to use and process information abstractly (Baker et al., 2012; Judson et al., 2020; Swafford, 2018). Upon further evaluation of South Carolina SBAE standards, they should be considered incomplete, according to Ravitch (1995), since complete standards must include content and performance standards. Content standards describe what was taught, and performance standards describe the depth and use of that learning (Ravitch, 1995). The two types of standards were connected, and South Carolina standards currently lacked both. Despite the current South Carolina SBAE standards weak level of rigor and clarity in both content and performance standards, standards remain essential for effective teaching (Nilson, 1998), furthering the need to evaluate and revise these standards to provide relevant and purposeful standards for SBAE teachers across the state (Kraftwohl, 2002; Ravitch, 1995).

Perhaps this misguided attempt was purposeful to allow teachers creative freedom in their SBAE program content and teaching, but the current South Carolina standards burden SBAE teachers with the search for relevant frameworks to align content due to its incomplete, weak, and confusing nature. Ravitch (1995) found that teachers and administrators who argue against national content and performance standards actively seek curriculum, textbooks, industry certification, or mandated exams to align their course content. SBAE teachers need and deserve the support provided by clear, consistent, and measurable content and performance standards (Judson et al., 2020; Ravitch, 1995). Further demonstrating that a strong and clear framework of standards can support all involved, but vague, unclear, and unmeasurable standards have little value for teachers and students when it comes to designing lessons that promote abstract learning for STEM integration. This lack of alignment limits the ability to meet the rigor and relevance needed to support SBAE teachers in preparing students for future STEM-based agricultural careers (Baker et al., 2012; Judson et al., 2020; Swafford, 2018).

Developing strong, clear, and realistic content and performance standards can be a messy and complex process, but it is essential to support the success of our SBAE students, teachers, programs, and communities (Judson et al., 2020; Molina, 2009; Ravitch, 1995). Perhaps South Carolina should consider adopting or cross-walking the AFNR standards to support their SBAE programs, as reevaluating and updating the state-level standards will allow teachers an opportunity to increase further the rigor and relevance of SBAE programs across the state. To accomplish this task, it is recommended that a team of SBAE teachers, state agricultural education staff, and faculty be developed. Further research should investigate the level of rigor taught in SBAE classes across South Carolina, comparing the rigor established in the state standards with what has been taught in classrooms. Although this study highlighted concerns with SBAE standards in South Carolina, additional research is needed to determine how other states’ SBAE standards align with AFNR standards. SBAE standards provide a structure for teachers, but the impact of these standards on student performance and outcomes remains unknown, although Swafford (2018) connected the implementation of cross-walked AFNR standards in SBAE teacher preparation programs to increased preparation and STEM integration.

Preservice teacher preparation programs should consider preparing SBAE teacher aspirants to recognize and utilize rigorous and relevant higher-order learning standards. Ultimately allowing them to understand and be better prepared to adapt and find support when standards do not provide enough support, such as those identified in this study. Additionally, SBAE teacher aspirants should be familiar with AFNR standards, as they are aligned with the complete SBAE program (i.e., classroom/laboratory instruction, FFA, and SAE), which serves as a valuable resource. SBAE teacher preparation faculty should consider the current standards in their state and how professional development opportunities cross-walking AFNR standards could benefit the rigor and relevance of SBAE teachers and programs across their state.

Parallel to the recommendations for preservice programs expanding instruction on higher-order learning standards, readiness to teach specific agricultural and natural resources content at higher levels could be an equally challenging issue. In a study by Snider et al. (2021), preservice teachers were surveyed to assess their self-perceived competence to teach different topics in the AFNR standards. Students were found to have a “need for competence enhancement in the Power, Structural, and Technical Systems and the Biotechnology Systems Pathways,” (Snider et al., 2021, p. 44). Other areas preservice teachers indicated gaps in were Agribusiness Systems and Food Products and Processing Systems. In contrast, preservice teachers indicated greater competence in the Natural Resources Systems, Plant Systems, and Animal Systems pathways. Snider et al. discussed that pathways such as Animal Systems were an established curriculum in their state and that preservice teachers sought out skill development opportunities in these pathways. Does self-efficacy of specific AFNR pathways influence the level that state standards were written? 

The Agribusiness Systems career pathway has been noted to have great inservice need for years (Radhakrishna & Bruening, 1994; Joerger & Andreasen, 2000; Layfield & Dobbins, 2002). Further, preservice agricultural education programs have called for increased coursework offerings in agribusiness recently (DiBenedetto et al., 2018; Snider et al., 2021). Might these needs have impacted the lack of alignment between the state and AFNR standards for the Agribusiness and Marketing courses, as shown in Table 3? It is recommended that future research in self-efficacy of AFNR skills areas have any influence on those writing standards for state and national curricula.  

Whether the state program adopts the AFNR standards or chooses to revise its current work, this does not guarantee that the new/revised standards will be taught at the higher levels. Ulmer and Torres (2007) found that SBAE teachers exhibit lower-order (knowledge and comprehension) teaching 83% of the time. The same study found that this is not isolated to agriculture teachers, as science teachers were at the lower levels 84% of the time. Similarly, Cano and Metzger (1995) also found that horticulture teachers were at the lower levels 84% of the time. All of these researchers recommended that SBAE teachers were engaged in professional development that would assist them in developing student activities and assignments that encourage higher-order thinking skills. It is recommended that teacher educators develop purposeful professional development that will prepare SBAE teachers to plan activities and assignments at higher-order thinking levels.

Future research should consider the replication of this study on a state-by-state basis as deemed necessary. Additionally, a mixed method approach could be beneficial to assess teachers’ current level of self-efficacy to implement STEM-based higher-order instruction in SBAE, aligning with Bloom’s (1956) cognitive taxonomy. This study could also establish a repository of resources, materials, and curriculum currently being utilized as a framework to deliver STEM-based higher order instruction, helping prepare future SBAE teachers. Researchers should also consider exploring teachers’ content needs, current curriculum resources, and their perspectives on content and performance standards through qualitative interviews. Finally, as state-level changes are made related to SBAE, teachers’ perceptions of current standards should be considered to support and improve the adoption of new state standards.

References

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Technical Professional Development Needs of Agricultural Education Teachers in the Southeastern United States by Career Pathway

D. Barry Croom, University of Georgia, dbcroom@uga.edu

Ashley M. Yopp, Florida Department of Education, ashley.yopp@fldoe.org

Don Edgar, New Mexico State University, dedgar@nmsu.edu

Richie Roberts, Louisiana State University, roberts3@lsu.edu

Carla Jagger, University of Florida, carlajagger@ufl.edu

Chris Clemons, Auburn University, cac0132@auburn.edu

Jason McKibben, Auburn University, jdm0184@auburn.edu

O.P. McCubbins, Mississippi State University, am4942@msstate.edu

Jill Wagner, Mississippi Department of Education, am4942@msstate.edu

PDF Available

Abstract

Determining the professional development needs of teachers framed through the national career pathways of agricultural education has become imperative for modern classrooms. Participants in this study were from six Southeastern U.S. states. Most were female educators, with the largest group having teaching experience between 11-20 years. Participants indicated their professional development needs regarding technical content in the seven agricultural education career pathways. Based on the findings, the researchers concluded that participants needed professional development in plant science, followed closely by animal systems. The least beneficial area for professional development was power, structural and technical systems, and food products and processing systems. No differences existed between male and female teachers regarding their technical professional development needs except within the power, structural, and technical pathway. Teachers with less than 10 years of teaching experience reported a greater need for professional development in animal science than their more experienced counterparts. Finally, participants in rural school systems were more likely to desire professional development on natural resources.

Introduction and Review of Literature

Teachers with a high level of content knowledge are better equipped to help their students succeed academically and can be more effective as educators (National Research Council, 2010). The content knowledge held by teachers has been shown to have a statically significant effect on student learning. When content knowledge is of sufficient depth and quality, the impact on student learning has also been positive (Ambrose et al., 2010). As teachers employ high-quality pedagogical strategies, their content knowledge helps students improve knowledge retention and learning transfer (National Research Council, 2010). In agricultural education, teachers need content knowledge of sufficient depth and breadth to meet the current and future demands of the agricultural industry (Solomonson & Roberts, 2022).

Facilitating Understanding

Teachers with quality content knowledge can help students understand the material more deeply and meaningfully. They can explain concepts clearly, provide relevant examples, and confidently answer questions (Driel, 2021; Gess-Newsome et al., 2019). On this point, Harris and Hofer (2011) found that teachers with more content knowledge were more strategic in selecting learning tasks, created more student-oriented learning activities, and were more deliberate in planning lessons. Pursuing this further, Marzano (2017) proposed that teachers with a high level of content knowledge were more capable of helping students detect errors in their reasoning and successfully solve problems in the real world. Teachers often use content knowledge to guide students to examine how new technical content differs from their existing assumptions. This strategy deepens their understanding of key concepts (Dean & Marzano, 2012; Walshaw, 2012). Ambrose (2010) suggested that content knowledge and intellectual proficiency were key drivers in a teacher’s ability to successfully use technical content to facilitate students’ learning in the classroom. 

Adaptability

Adaptability refers to the ability of teachers to modify their teaching strategies to meet the needs of their students. Teachers with content knowledge can be more adaptable in their teaching. They can adjust their teaching strategies and methods to suit the needs of their students and make adjustments when necessary (Bolkan & Goodboy, 2009). Edgar (2012) postulated that the more content knowledge a teacher possesses, the more likely the teacher would employ varying means to teach the content.

Building Credibility

Building credibility as a teacher has become essential to creating a positive and effective learning environment. Teachers with content knowledge are more credible to their students, parents, and colleagues. The rich source of content knowledge that teachers can draw upon in the classroom has become the source of most of this credibility (Forde & McMahon, 2019). They can speak with authority on their subject matter and inspire confidence in their teaching (Bolkan & Goodboy, 2009; Finn et al., 2009).

Effective planning

Teachers with content knowledge can also create more effective lesson plans and assessments and deploy more effective teaching strategies (Orlich et al., 2012; Senthamarai, 2018). For example, they can design activities and assessments that accurately measure student learning and identify the essential concepts students need to learn (Hume et al., 2019). Previous research has suggested that teacher preparation programs must focus more on understanding how teachers acquire technical content knowledge and support their ability to communicate such to their students (Darling-Hammond et al., 2017; Levine, 2008). For this study, technical knowledge referred to the lesson elements designed to provide students with instruction, practice, and review of information regarding the agricultural sciences.

Agricultural Education Teacher Professional Development Systems

Agricultural education teachers who were traditionally certified often receive technical content training during their initial teacher preparation phase. Formal teacher preparation traditionally begins during college coursework (Croom, 2009). During this period, the preservice teachers are inducted into teaching through training and development (Talbert et al., 2022). However, concerns arise about the ability of novice teachers to deliver content-rich lessons (Roberts et al., 2020a, 2020b). Induction follows the competency-building stage, where technical content skill development continues. This phase is where most professional and skill development occurs (Croom, 2009; Fessler & Christensen, 1992).

Professional development usually involves teachers attending professional development sessions based on their perceived technical content deficiencies (Smalley et al., 2019) because teachers sense their need to address technical content deficiencies through continuous professional development (Easterly & Myers, 2019). Despite this desire to develop technical skills, previous research has found a significant gap in agricultural mechanics skill development and other technical agriculture concepts (Easterly & Myers, 2019; Yopp et al., 2020).

Conceptual Framework

Darling-Hammond et al. (2017) proposed that teacher professional development proceeds through seven elements (see Table 1). Effective professional development employs strategies that deepen a teacher’s technical content knowledge. However, this is not enough. Teachers also need sustained professional development activities of sufficient duration that demonstrate how to teach technical content. Darling-Hammond et al. (2017) further proposed that teachers were best served by professional development provided in a social environment, with teachers collaborating and exploring effective instructional models under expert coaches’ guidance. Teachers needed to reflect on their performance to internalize new content knowledge and the strategies for teaching it (Darling-Hammond et al., 2017). This model for professional development begins with developing technical content knowledge (Darling-Hammond et al., 2017). The research team focused on this element of the model because we contended that professional development was grounded in content skill development applied through effective teaching strategies.

Table 1
Elements of Effective Professional Development adapted from Darling-Hammond et al. (2017)

The connection between professional development in the content taught is that both are needed to support effective teaching practices. Teachers who have a strong understanding of the content they are teaching and who have the skills and knowledge needed to teach that content effectively will be better equipped to meet the needs of their students and support their learning (Ambrose et al., 2010; Darling-Hammond et al., 2017). Additionally, ongoing professional development and content training can help teachers stay up-to-date with the latest research-based practices, teaching strategies, and techniques, which can further improve their teaching practices over time (Darling-Hammond et al., 2002).

The agricultural education curriculum covers a range of grade levels and a wide range of technical content. It provides students with knowledge as the content transitions from more basic to advanced skill development through pathway progression. As a result, secondary agricultural education teachers must provide essential knowledge and experiences through advanced instruction in animal science, agricultural engineering, plant and soil science, forestry, natural resources, food processing, and agricultural business management (Talbert et al., 2022). Therefore, secondary students must have the skills to navigate complex problems regarding agriculture, food, and natural resources using good reasoning skills (Figland et al., 2020). Table 2 illustrates the seven areas of agricultural sciences as identified by Advance CTE (2018) and describes the primary learning attribute guiding the learning activities.


Table 2

Agriculture, Food & Natural Resources Career Pathways adapted from Advance CTE (2021)

Purpose and Objectives

This study aimed to investigate the professional development needs of teachers in the Southeast United States regarding the national career pathways for secondary agricultural education. After describing the demographics of teachers who participated in the study, the objectives were to:

  1. Determine the professional development needs of teachers in the Southeastern region of the United States in each of the seven career pathways described by Advance CTE, and
  2. Compare the professional development needs of teachers by gender, years of teaching experience, and community setting.

Methods

This descriptive study sought to determine teacher perceptions regarding professional development needs as framed by the seven career pathways in the agricultural education curriculum. We distributed an instrument Yopp et al. (2020) developed to the target population of agricultural science teachers in six Southeastern states. We used each state’s directory of agricultural science teachers provided by state agricultural education authorities to define the target population.

We developed the questionnaire to address each research objective, including demographic questions. We included 54 Likert-scale items based on seven career pathways developed by Advance CTE (2018): Power and Technical Systems (16 items), Plant Systems (8 items), Natural Resources (4 items), Food Products and Processing (7 items), Environmental Service Systems (5 items), Animal Systems (7 items), and Agribusiness Systems (7 items). We asked participants to rate each item based on its perceived benefit level using this scale: 1 = not beneficial to 5 = essential. We entered data into SPSS® version 24.0 to calculate means and standard deviations. We conducted further analysis through t-tests to determine the significance between variables of interest.

A panel of agricultural teachers with expert knowledge of Advance CTE career pathways examined the questionnaire for content and face validity. Using methods proposed by Creswell and Creswell (2017), we pilot-tested the questionnaire with a sample of 14 pre-service agricultural education teachers using the test re-test method. These test measures yielded Cronbach’s alpha coefficients ranging from .83 to .91 (.70 or higher acceptable range). Our post-hoc reliability analysis of the instrument yielded an overall valid measure (α = .86).

Guided by Dillman et al. (2014) tailored design method, researchers administered the instrument to prospective participants via email using each state’s unique agricultural education teacher listserv. The research team sent an initial invitation to participate in the study. We followed this with a second message to engage participants through an opt-in email directing them to a Qualtrics hyperlink specific to their respective instrument by state. Lastly, the researchers sent two follow-up reminder emails to non-respondents over four weeks. Previous instrument implementation (Yopp et al., 2020) yielded Cronbach’s alpha coefficients ranging from .83 to .91 (Creswell & Clark, 2017). Post-hoc analysis of the instrument based on the population of interest revealed an overall α = .81.

Due to the nature of school-based agricultural education (SBAE) and participants’ ability to respond in a timely manner, early and late responders were evaluated to determine whether response differences occurred (Lindner et al., 2001). Analysis revealed no differences (p = .45) in the population of interest. The final response rate gained was 52.24 %. We anticipated this because decreased response rates to web-based instruments have been reported, especially in recent decades, with the influx of messaging in professional environments. Baruch (1999) noted that rates have declined from approximately 65% to 48% when using electronic survey methods. On this issue, Fraze et al. (2003) found that SBAE teachers responded less frequently to electronic surveys, possibly due to overloaded work schedules.

Findings

Female participants outnumbered male participants in this study, and most participants were still in their first 10 years of teaching. Most participants received formal training to become teachers through a traditional undergraduate program in agricultural education. Many teachers (n = 107) earned their teacher certification through an alternative certification program. The majority of teachers in this study taught in rural schools. Urban agricultural educators made up the smallest percentage of participants in this study. Table 3 provides a detailed representation of the socio-demographic characteristics of participants.

Table 3
Socio-demographic Characteristics of Participants

Objective One: Professional Development Needs in the Seven Career Pathways

Based on data gathered from SBAE teachers and guided by the career pathway to frame the professional development needs, we found that the essential area was that of Plant Systems (M = 4.17, S.D. = .78) and closely followed by Animal Systems (M = 4.14, S.D. = .98). The career pathway with the least beneficial area for professional development was Power, Structural & Technical Systems (M = 3.26, S.D. = 1.02) with Food Products & Processing Systems (M = 3.46, S.D. = 1.02) having a similar response by respondents. The two lowest career pathways also displayed the most variation of answers, as identified by participants. Table 4 shows the professional development needs of agriculture teachers based on career pathways in agricultural education.

Table 4
Professional Development Needs of Agriculture Education Teachers Based on Career Pathways

Note. 1 indicates a scale used from 1 = Not beneficial to 5 = Essential with 3 = No opinion

Objective Two: Professional Development Needs of Teachers by Gender, Years of Teaching Experience, and Community Setting.

The research team collected data on the professional development needs of participants aligned with career pathways and disaggregated based on gender. Two pathway areas had statistically significant differences based on gender. We found significant differences between genders within the Power Technology (p = .000) and Natural Resources (p = .005) pathways. The remaining pathways did not reveal significant differences based on gender. Table 5 displays the needs for professional development in career pathways by gender.

Table 5
Needs for Professional Development in Career Pathways based on Gender

Note. 1 indicates a scale used from 1 = Not beneficial to 5 = Essential with 3 = No opinion

The research team gathered data on the professional development needs of participants aligned with career pathways and analyzed it based on years of experience. The Animal Systems pathway has significant differences based on experience (p = .005). Although the means reported were similar (4.14 and 4.13), the associated standard deviations were dissimilar (1.07 and 0.86), resulting in statistically significant differences between the groups regarding experience. The remaining pathways did not have substantial differences based on experience level. Table 6 details participants’ professional development needs based on years of teaching experience.

Table 6
Needs for Professional Development in Career Pathways Based on Experience

Note. 1 indicates a scale used from 1 = Not beneficial to 5 = Essential with 3 = No opinion

Participants reported their professional development needs regarding career pathways based on the impact of the community setting. The Natural Resources pathway (p =. 049) indicated significant differences based on the community setting. Table 7 displays the needs for professional development based on the community type.

Table 7
Needs for Professional Development in Career Pathways Based on the Community Type

Note. 1 indicates a scale used from 1 = Not beneficial to 5 = Essential with 3 = No opinion

Conclusions & Implications

This study aimed to investigate the professional development needs of teachers in the national career pathways in agricultural education. The divisions of gender and years of experience do not represent a generalizable representation of each state regarding the professional development needs of agriculture teachers. Participants in this study were from six states in the Southeastern United States. Most respondents were female, with the largest group having teaching experience between 11-20 years. Respondents were experienced and prepared mainly for their teaching career through traditional means.

Participants were asked to indicate their professional development needs regarding technical content in the seven career pathways. Based on the findings, we concluded that professional development was most needed in the specialized content area of plant science, followed closely by animal systems. Meanwhile, we also conclude that the least beneficial areas for professional development were Power, Structural & Technical Systems, and Food Products & Processing Systems. Concerning Power, Structural & Technical Systems, the findings are inconsistent with the results of similar studies (Easterly & Myers, 2019; Smalley et al., 2019) that have reported a significant gap in teacher preparation in this area. However, we conclude from our findings that teachers do not perceive technical training in Power, Structural & Technical Systems to be a significant need.

Further conclusions evoked through this research population werethat no differences exist between male and female teachers regarding their technical in-service training needs, with two exceptions. More males than females found the need for training in natural resources and power and technical systems. Further, teachers with less than 10 years of teaching experience need more training in animal science than their more experienced counterparts. This is consistent with the teacher development model developed by Fessler and Christensen (1992). The only significant difference among respondents for this research objective was that rural teachers rated natural resources training higher than their urban counterparts. We found that teachers in rural schools were more likely to require training on natural resources. This could result from rural teachers’ access to more natural resources and, therefore, more opportunities to teach this content area than a teacher in an urban setting.

Recommendations for Future Research

Based on the conclusions from this study, this study should be replicated in other regions of the United States to gain a clearer picture of the professional development needs of agricultural education teachers. Agriculture operations vary across the United States due to climate, arable land, geography, and access to infrastructure that supports markets and transportation. The teachers in one region may have different professional needs from those in another. This study should be replicated in the future to determine if teacher training needs have changed. The agriculture industry uses human ingenuity and innovation to power new and better methods for producing food, fiber, and natural resources. Consequently, agricultural educators must be well-equipped to educate students using innovative technology.

This study found differences between male and female teachers in power, structural and technical systems, and natural resources. Additional research in this area may help determine why these differences exist. Furthermore, we noted differences between new and experienced teachers concerning animal science. This begs the question as to whether Inservice training needs should be customized based upon the years of experience. Researchers should conduct follow-up studies to determine if this would benefit teachers.

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Does Experiential Learning Improve Student Performance in an Introductory Animal Science Course?

Eric D. Rubenstein, University of Georgia, erubenstein@uga.edu

Savannah R. White, University of Georgia, savannah.r.white@gcpsk12.org

James D. Scott, University of Georgia, jamesd.scott@uga.edu

C. Robert Dove, University of Georgia, crdove@uga.edu

T. Dean Pringle, University of Florida, td.pringle@ufl.edu

PDF Available

Abstract

At postsecondary educational institutions, the learning process has lecture at the focal point of most courses, for-going experience, and hands-on learning for the more efficient lecture-based model of teaching. A consensus exists among educators that motivation and student engagement can be difficult but remain a crucial part of planning and teaching. Hands-on experiences can be used to motivate students and allow them to gain problem-solving and critical-thinking skills. Therefore, the purpose of this study was to investigate the influence experiential learning had on students enrolled in a large lecture introductory animal science course at the University of Georgia. This quasi-experimental study divided the students enrolled in the course into two groups to determine if experiential learning had a positive influence on the students learning. The experiential learning activities were designed to replace a two-hour study session held each week during the semester. Student performance was measured by the scores on the course summative assessments. The first quiz scores were analyzed by group to determine if a difference was found between the groups. There was no significant difference (p = 0.60) found between the two groups on the first quiz. The researchers found that no significant differences were found between the groups of students on questions related to the four content areas. Therefore, the researchers concluded that experiential learning may not have a positive impact on all learning experiences for students. Therefore, more research should examine the utilization of experiential learning in the teaching of introductory content material to college students.

Introduction and Review of Literature

Kolb explained learning as, “the process whereby knowledge is created through the transformation of experience” (Kolb, 1984, p. 41). Within postsecondary educational institutions, lecture is frequently utilized to foster and facilitate learning in the classroom, indicating the lack of direct experience and hands-on learning in favor of the more efficient lecture-based model of teaching. Further, removing experience-based learning leaves a gap in the development of underclass students at a postsecondary level. According to Kolb (1984), a gain in knowledge is the result of transforming information learned from an experience, implying that learning cannot occur through presentation alone; transformation of experience with the material is required for true knowledge acquisition. Healey and Jenkins (2007) implemented experiential learning in geography in higher education. In their article, the authors outlined the strengths that Kolb’s conceptual frame has for postsecondary institutions. Among the strengths was the benefit of implementing experiential learning into an entire degree program but starting with one course or class session can be equally beneficial for students (Healey & Jenkins, 2007). Students come to a classroom with different learning styles and adaptive natures, but Mainemelis et al (2002) notate that both internal factors (e.g., learning styles) and external factors lead to the acquisition of knowledge and formation of intelligence. Mainemelis et al (2002) also postulated that “intelligence is thus the result of the dialectic integration of internal cognitive organization, reflective abstraction, and external adaptation, active involvement in experience” (p. 7). John Dewey (1938) was the first academic to connect education with experience but warns against the concept that not all experiences are education, which was later explained by Kolb (1984) in his experiential learning model. Dewey (1938) acknowledges that students already have experiences in classrooms, but those experiences lack the depth and character to be learning experiences. To better understand the learning experiences of students in a lecture-based college introduction to animal science course, researchers sought to examine the impact that the integration of experiential learning lessons have on student comprehension of basic animal science topics in comparison to traditional lecture.

A consensus exists among educators that motivation and student engagement can be difficult but remain a crucial part of lesson planning and teaching. Hands-on experiences can be used to motivate students, leading to a gain in problem-solving and critical thinking skills, often acquired through experiential learning activities (Rhykerd et al., 2006), as well as improving student achievement (Stor-Hunt, 1996), the necessary skills to succeed (Barron et al., 2017), and attitudes towards learning (Johnson et al., 1997). In examining how experiential learning can be used to motivate students and the development of problem-solving skills, Rhykerd et al (2006) implemented a hands-on contest with crop production and marketing to help students without an agriculture background gain real-life experience that they can apply to their future careers. The researchers created the contest based on pedagogical research centered around the idea that comprehension can be increased through activities applying real-world situations and critical thinking concepts (Rhykerd et al., 2006). Upon analysis, researchers noted these activities and exercises led to a positive impact on student knowledge development (Rhykerd et al., 2006). Furthermore, in examining the impact of hands-on experiences on student achievement in a middle school science course, Stor-Hunt (1996) determined that students involved in hands-on activities more frequently scored relatively higher on science exams. Additionally, not only does the integration of experiential learning impact student achievement and knowledge development, but these experiences also improve student confidence and self-efficacy (Barron et al., 2017). Veterinary students undergoing their final year of coursework were exposed to real-life appointments, in which they were required to discuss diagnosis and treatment with clients. Researchers concluded a significant increase in confidence and communication skills through the integration of these experiences (Barron et al., 2017). As mentioned, prior research indicated that the integration of hands-on learning also improved student attitudes toward learning. Johnson et al. (1997) concluded that including hands-on learning activities in the classroom was effective in developing positive student attitudes toward academic subjects, and increasing these activities can influence student outcomes in agricultural and science education.

While hands-on experiences are often utilized more frequently in laboratory experiences, circumstances exist in which hands-on, experience-based lessons are removed from courses and replaced with more lecture-based instruction. Therefore, it is important to re-evaluate the use and efficacy of experiential learning in comparison to traditional lecture-based instruction. Furthermore, within agricultural education, the importance of integrating experiential learning opportunities for students is ever important. Osborne (1993) elaborated on the distinct change toward science-based methods in agricultural education through agriscience. He stressed the importance of the incorporation of science into the agriculture industry. Osborne (1993) stated, “our job is not to duplicate science instruction offered by science departments. Our job is to teach science differently, focusing on applications of science in all facets of the broad agricultural industry” (p. 3). A shift towards agriscience and using scientific methods and principles in agriculture education requires a focus on active learning through hands-on activities. Additionally, Shoulders and Myers (2013) concluded that guiding students through experiential learning can enhance their learning in lab settings, increase science literacy, and lead to higher-level thinking, even though laboratory settings have been previously associated with only the development of psychomotor skills. However, Shoulders and Myers (2013) determined that most educators were not engaging their students in experiential learning, leading to a lack of development and acquisition of relevant knowledge. Further research within agricultural education and experiential learning indicated that students who had the experiential learning treatment scored higher on domain-specific creativity and practical use of knowledge, but students who did and did not receive the treatment scored similar on analytical knowledge (Baker & Robinson, 2016). Based on the results, Baker and Robinson (2016) suggested incorporating experiential learning and traditional lecture-based instruction, stating, “combination produces successful student intelligence most effectively” (p. 139). Baker and Robinson (2017) continued their research in an experiential learning approach in an agriculture classroom regarding student motivation, to which the researchers determined that instruction type does not alter student motivation and learning style plays a role in motivation. In the recommendations, the researchers re-emphasized the need for varied instruction to reach students in all learning styles, as well as adequate planning and delivery (Baker & Robinson, 2017).

Although research has indicated the use of experiential learning is important for student development and the acquisition of skills and competencies to be successful, a lack of research examining the integration of experiential learning in college agricultural and animal science courses is limited. A level of accountability existed in incorporating experiential learning into college-level courses (Caulfield & Woods, 2013). Studies have shown positive outcomes of experiential learning through internships (Esters & Retallick, 2013), study abroad (Ingraham & Peterson, 2004), and work-study programs (Ambrose & Poklop, 2015). However, few exist surrounding the implementation of experiential lessons into large, introductory science courses in a university setting. Healy and Jenkins (2000) recommended that research in geography education should examine whether post-secondary students in the twenty-first century identify as having a predominant learning style in the incorporation of experiential learning in a university setting. Additionally, Coker et al. (2017) suggested examining the impact of experiential learning in situations where students are randomly assigned to groups of varying information, as an attempt to eliminate any biases of self-selection, student demographics, and other common traits and characteristics. Therefore, this study aimed to bridge the gap in the literature by integrating experiential education lessons into a large introductory animal science course and examining the impacts on student academic achievement on course tests following the experiential education lesson.

Conceptual Framework

This study was guided by the conceptual framework of experiential learning theory as defined by Kolb (1984), and further elaborated upon by Kolb and Kolb (2005). The process of experiential learning has a perspective that “emphasizes the central role that experience plays in the learning process” (Kolb, 1984, p. 20). Experiential learning is used to solidify the learning experience through four stages as seen in Figure 1: concrete experience, reflective observation, abstract conceptualization, and active experimentation (Kolb, 1984). True learning occurs when individuals have the chance to both the experience, as well as the reflection and transformation of the knowledge (Kolb, 1984). Furthermore, Kolb and Kolb (2005) clarify that experiential learning is not a technique taught to students or a mindless reflection on experience, but rather a philosophy of education. The transformation can be seen in classrooms when students are tested on the knowledge created in experiences. Experiences can be created in classrooms through hands-on activities that are coupled with other teaching methods to help students with varied learning styles. To further explain the factors within experiential learning, Kolb (1984) outlines six characteristics of experiential learning. Learning is:

  1. Described best as a process, not an outcome
  2. Continuously grounded in experience
  3. Requires the resolution of internal conflicts with external stimuli
  4. A process of adapting to external stimuli
  5. Interactions between the person and the environment
  6. The process of creating knowledge

            Two characteristics of Kolb and Kolb’s (2005) description of the Experiential Learning Theory are significant for this study, the facets that learning is conceived by the process of creating knowledge and learning results from interactions between the person and their environment. Additionally, Kolb (1984) posits that learning is best described by the process of creating knowledge and is a continuous process grounded in the experiences of the learner. Kolb (1984) states, “the emphasis on the process of learning as opposed to the behavioral outcomes distinguishes experiential learning from the idealist approaches of traditional education” (p. 26). In examining the application of experiential learning theory in collegiate-level courses, Healey and Jenkins (2007) applaud the theory for being easy to well-developed, and understandable and for its generalizability over single classes or entire degree programs. Additionally, agriculture classrooms and laboratories have used experiential learning as a foundational component for numerous years, as educators have continually utilized varied aspects of the theory and many of the applications to educate students.

Figure 1

Kolb’s (1984) Experiential Learning Model

Purpose and Objectives

The purpose of this study was to investigate the influence experiential learning had on students enrolled in a large lecture introductory animal science course at the University of Georgia.  The National Research Agenda called for research to investigate learning to ensure that graduates are prepared for the 21st-century workforce (Roberts et al., 2016).  This study was guided by the following research objective and hypothesis:

  • Describe the effect of experiential learning activities on student comprehension of content taught in an introductory animal science course.
  • Ho: Students who participated in experiential learning activities will have an equal mean score on the course summative assessments compared to those who did not participate in the experiential learning activities.
  • Ha: Students who participated in experiential learning activities will have a higher mean score on the course summative assessments compared to those who did not participate in experiential learning activities. 

Methods and Procedures

This study was conducted utilizing a quasi-experimental design to ensure that all students in the course were granted the same opportunities and to reduce any effects from this population not being randomized (Campbell & Stanley, 1963). According to Campbell and Stanley (1963), quasi-experimental design studies should utilize a crossover method to ensure that multiple data points are collected from each student in the population. Therefore, the researchers broke the course into four sections and alternated the utilization of experiential learning activities for each of the two groups (Table 1).

Table 1

Experimental Treatments by Group

Content AreaGroupTreatment
ReproductionAExperiential
 BControl
NutritionAControl
 BExperiential
GeneticsAExperiential
 BControl
MeatsAControl
 BExperiential

Course Description

Within the Department of Animal and Dairy Science at the University of Georgia, all students are required to complete an introductory animal science course. However, the laboratory component of the Introductory to Animal Science course was removed from the course nine years ago to help alleviate teaching overloads and budgetary constraints. Therefore, the introductory animal science course has been taught as a standalone lecture-based course, structured to teach the basic animal science material all students need to comprehend before taking more advanced courses. The faculty who have taught the course have extensive experience in teaching laboratory classes and have attempted to enhance their classroom instruction in this course to provide students with a better learning environment.  The class meets three times a week for a 50-minute lecture and students were offered a once-a-week study session that could last up to two hours.

Study Design

To ensure variability among the two groups, students were randomly assigned to one of the two groups, denoted as either A or B. Group assignment was determined during the beginning of the semester, prior to any instruction of course material. Thus, one experimental treatment was designed for this study, where students were either in a control group or an experiential learning group for each of the content areas. The group that received experiential learning lessons were taught utilizing hands-on lessons twice during the unit. The laboratory activities were designed through the lens of Kolb’s experiential learning model, in which the labs were structured to ensure students were given the opportunity to engage in each stage of the model. Students were provided with varied hands-on activities and review sections during the session, which was scheduled during the specified time block for traditional review. Each of the activities were planned to take 105-minutes, to ensure that there was time for questions and further explanation for students without exceeding the 120-minute class period. Activities were taught by faculty in the Department of Animal and Dairy Science alongside faculty from the Department of Agricultural Leadership, Education and Communication, with assistance from the teaching assistants for the course, to ensure that students received instruction in a consistent format for fidelity of experimental treatment. Researchers and faculty developed each laboratory activity to correlate with what was being taught in lecture and would be included on the summative assessments. Activities included the deconstruction of a hog carcass in meat science, the dissection and labeling of male and female reproductive tracts in the reproduction unit, examining breed outcomes of puppies and mice during the genetics unit, and the dissection and evaluation of microbial presence in monogastric and ruminant tracts during the digestion unit. In each lab, students were provided the opportunity to first observe each activity demonstrated by the instructors, upon which they then were able to ask questions and build upon what was learned in the lecture. Students were then able to complete the activity in groups, applying the concepts of what was learned in lecture and the demonstration to their own experience and experimentation, completing the cycle of experiential learning. Instructors provided assistance to students throughout the lab as needed, allowing for the opportunity to develop an understanding of the content and apply what was learned to their experiment.

The traditional review session also took place during the 120-minute period, considered to be the control group, in which the students met with the course teaching assistants to review content during a study session. This review was led by student questions to create buy-in from the students attending. To ensure that students were attending the correct session and for fidelity in the treatments, attendance was taken during each meeting to verify the group assignment and ensure that upon data analysis, student grades were sorted appropriately. If, for any circumstance, students missed an experimental treatment, they were removed from the study. Additionally, students were provided the opportunity to remove themselves from the study altogether, and these students were continually offered the opportunity to attend the traditional review session.    

Data Collection and Analysis

Data were collected through four summative course assessments given throughout the semester during specified exam hours, and a final summative exam given at the conclusion of the semester. Exams were created by faculty in the animal science department and were examined prior to each exam to ensure that content was relative to the experiential learning lessons and review sessions that were taught throughout the semester. The exams were also designed to be in correlation with the objectives of the overall course, which were written according to the understand classification within Blooms Taxonomy rather than the analyze or evaluate classifications (Krathwohl, 2002). The exams and objectives were designed in this way to ensure that students in an introductory course were provided with the opportunity to develop the knowledge and skills necessary to complete advanced classes in their major. The summative assessments were given during designated test sessions that were either two hours in length for a unit exam or three hours in length for the final exam. All assessments presented to students were identical in design and students were asked to indicate whether they were in Group A or B prior to completing the exam. This was done to ensure that there were no external influences on student performance or data analysis. Assessments included a variety of multiple choice, true/false, and short answer questions directly related to the content that was taught during the lecture-based component of the course.

Upon completion of the exams, scores were tabulated and sorted by student and group. Content experts and researchers reviewed each exam for total exam score, as well as the total number of questions that were deemed correct and directly related to what was taught in the course and later reviewed or expanded upon with experiential learning lessons. The total number of content related scores that were deemed correct ranged from 10 to 65 questions, depending on the additional content that was taught during the course, which was anywhere from the additional 90 questions to 35 questions. For the final exam, researchers and content experts separated the exam into content areas, which included 16 nutrition questions, 18 reproduction questions, 16 genetics questions, and 11 meat science questions. After scores were tabulated and entered into spreadsheets, data were then analyzed using SPSS version 25 with an a priori level of .05.  

Results

Prior to the study, quiz scores from the first quiz given in the course were analyzed by group to determine if a difference was found between the groups. There was no significant difference (p = 0.60) found between the two groups on the first quiz. Additionally, as previously stated, due to this being an introductory course, students entered the course with either no prior knowledge or limited knowledge from high school curricula. Therefore, because the quiz scores were determined to have no significant difference, the groups were deemed similar and the study groups were deemed appropriate for this study.

After completion of each exam, and tabulation of scores, researchers examined mean scores for each of the content areas within the summative assessments. Mean scores between the groups varied in regard to the difference between the scores, with the largest difference being between the groups within the reproduction content area. The mean score of the treatment group was 40.33 (SD = 4.21) and the mean score for the control group was 39.33 (SD = 3.55). Table 2 displays the mean scores for content area based upon group assignments.

Table 2

Student Assessments Mean and Standard Deviations for Each Content Area

Content AreaGroupnMean (SD)
ReproductionExperiential3940.33 (4.21)
 Control4239.33 (3.55)
NutritionExperiential4242.43 (4.46)
 Control3943.13 (4.62)
GeneticsExperiential3937.77 (3.67)
 Control4237.17 (3.99)
MeatsExperiential4213.52 (2.71)
 Control3914.05 (2.84)

To further examine the data, an independent sample t-test was run to determine if significant differences existed between the control and experimental groups for each content area. The independent samples t-test showed that no significant differences existed between the control and experimental groups on the four content questions. Further examination was conducted at the question level and found that only four total questions were found to have a significant difference at the .05 level. Table 3 displays the results of the independent samples t-test for each content area.

Table 3

Independent Samples t-test – Mean Scores on Each Content Area Between Groups

Content AreaFtdfp
Reproduction.711.1574.59.25
Nutrition.13.6978.05.49
Genetics.08.7178.99.48
Meats.41.8677.84.40

Upon completion of individual summative assessment analysis, researchers then examined final exam scores. Exam questions were divided into each content area, and then mean questions correct and standard deviation were calculated per group (Table 4).

Table 4

Mean Questions Correct and Standard Deviation for Final Exam

Content AreaGroupnMean (SD)
ReproductionExperiential (A)3912.67 (3.35)
 Control (B)4212.74 (3.12)
NutritionExperiential (B)4212.12 (2.33)
 Control (A)3912.05 (2.53)
GeneticsExperiential (A)3912.82 (1.67)
 Control (B)4212.28 (2.08)
MeatsExperiential (B)428.48 (2.71)
 Control (A)397.95 (2.84)

After examining the overall mean and standard deviation per group by content specific questions deemed correct on the final exam, researchers then analyzed the data, using an independent samples t-test. This was done to determine if there were any significant differences between the two groups, in which the results of this analysis revealed there was no significant differences within any content area (Table 5).

Table 5

Independent Samples t-test – Mean Scores on Each Content Area Between Groups

Content AreaFtdfp
Reproduction.002.0979.46
Nutrition.040.1379.45
Genetics1.081.2779.10
Meats.410.8679.19

Conclusions

Based on the results of the study, the researchers fail to reject the null hypothesis, as there were no statistically significant differences in assessment scores between the group that received experiential learning activities in the laboratory session and the group that did not. Although the researchers determined there were no statistically significant differences in the teaching methods used for the lecture and review group, and the lecture and experimental group, the nature of the course was to create a baseline of knowledge for students to continue in their degree program where further experiential learning activities were used more frequently.

As noted, faculty within the animal science department at the University of Georgia designed the overall course utilizing lower levels of Bloom’s Taxonomy (Krathwohl, 2002), utilizing lecture-based instruction to provide students with the opportunity to develop the knowledge and skills to be successful in more complex courses in students’ program of study. However, within the implementation of this study, researchers and faculty integrated hands-on experiential components in the overall design of the course, to provide students the opportunity to develop knowledge at the analysis and evaluation classification (Krathwohl, 2002). While the researchers sought to determine whether or not experiential learning impacted student performance and success (Barron et al., 2017; Stor-Hunt, 1996), the development of skills and knowledge (Rhykerd et al., 2006), and attitudes towards learning animal science content (Johnson et al., 1997), researchers determined that the experiential learning sessions were not implemented appropriately. Because of this, the discrepancies between the exam questions and the knowledge presented in the laboratory sessions should be noted for future studies and additional implementation of experiential learning in an introductory animal science course.

Among the students in the course, whether participation occurred in laboratory sessions or the traditional review session, there was no statistically significant difference in knowledge comprehension between the control and experimental groups. However, there was evidence that a few individual questions may reflect a benefit in hands-on experiences for some content areas, as the results from the nutrition, genetics, and meat science assessments revealed a higher average of questions correct from these activities. Additionally, it is evident that some experiential learning activities provide students with the opportunity to develop more content related knowledge and improve scores on summative assessments. Although researchers noted an increase in student assessment scores, it can be concluded that in this study, experiential learning does not always impact student success and knowledge gain.

Experiential learning is a beneficial teaching method that uses hands-on experiences to create knowledge and provide all students with the opportunity to develop skills and confidence to succeed in the classroom and beyond (Mainemelis et al., 2002). As previously stated, the results of this study did not indicate significance in student performance between groups, however, it should be noted that the use of experiential learning activities in laboratory sessions alongside lecture provides students with further opportunities to acquire the necessary knowledge and skills. Further, the instructors of the course utilized their personal experiences within the animal science field to provide real-world examples for students to imagine the practicality of the content being taught.  Therefore, the researchers conclude that true engaging lecture can be an effective tool in college classes (Estepp et al., 2014). 

Recommendations for Practice and Research

From the results of this study, researchers identified recommendations for future studies, which include replicating the study with modifications to the study design and data collection and replicating the study with modifications to the lessons taught in lab alongside guided directions for teaching assistants and instructors, to minimize the external influences on student knowledge development and skill acquisition. Additionally, researchers recommend future studies examining the performance of students on summative assessments when content and assessments are structured around hands-on learning experiences. Researchers also noted the importance of longitudinal research within the use of experiential learning laboratories on student performance, and recommend that in additional study replication, students enrolled and participate in the introductory course with experiential learning laboratories are observed throughout other animal science courses for performance.

The researchers also determined the need for recommendations for practitioners in college-level animal science courses, including the use of hands-on laboratory sessions to accompany traditional lecture-based instruction and review in introductory courses.

References

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Barron, D., Khosa, D., & Jones-Bitton, A. (2017). Experiential learning in primary care: Impact on veterinary students’ communication confidence. Journal of Experiential Education, 40(4), 349-365. https://doi.org/10.1177/1053825917710038

Campbell, D. T., & Stanley, J. C. (1963). Experimental and quasi-experimental designs for research on teaching. Houghton Mifflin.

Dewey, J. (1938). Experience and education. Touchstone

Estepp, C. M., Shelnutt, K. P., & Roberts, T. G. (2014). A comparison of student and professor perceptions of teacher immediacy behaviors in large agricultural classrooms. NACTA Journal, 66(2), 155-162. https://www.jstor.org/stable/pdf/nactajournal.58.2.155.pdf

Healey, M. & Jenkins, A. (2007). Kolb’s experiential learning theory and its application in geography in higher education. Journal of Geography, 99(5), 185-195. https://doi.org/10.1080/00221340008978967

Johnson, D. M., Wardlow, G. W., & Franklin, T. D. (1997). Hands-on activities versus worksheets in reinforcing physical science principles: Effects on student achievement and attitude. Journal of Agricultural Education, 38(3), 9-17. https://doi.org/10.5032/jae.1997.03009

Kolb, A. Y. & Kolb, D. A. (2005). Learning styles and learning spaces: Enhancing experiential learning in higher education. Academy of Management Learning and Education, 4(2), 193-212. https://doi.org/10.5465/amle.2005.17268566

Kolb, D. A. (1988). Experiential learning: Experience as the source of learning and development. Prentice-Hall Inc.

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Stor-Hunt, P. M. (1996). An analysis of frequency of hands-on experience and science achievement. Journal of Research in Science Teaching, 33(1), 101-109. https://doi.org/10.1002/(SICI)1098-2736(199601)33:1<101::AID-TEA6>3.0.CO;2-Zopen_in_new

Investigating Science Efficacy Before and After a Professional Development Program focused on Genetics, Muscle Biology, Microbiology, and Nutrition

Jesse Bower, Fresno State, jessebower@csufresno.edu

Bryan A.  Reiling, University of Nebraska-Lincoln, breiling2@unl.edu

Nathan W. Conner, University of Nebraska-Lincoln, nconner2@unl.edu

Christopher T. Stripling, University of Tennessee, cstripli@utk.edu

Matthew S. Kreifels, University of Nebraska-Lincoln, matt.kreifels@unl.edu

Mark A. Balschweid, University of Nebraska-Lincoln, mbalschweid2@unl.edu

PDF Available

Abstract

This study investigated teachers’ levels of Personal Science Teaching Efficacy (PSTE) and Science Teaching Outcome Expectancy (STOE) using the Science Teaching Efficacy Beliefs Instrument (STEBI). The population included 10 teachers completing an Increasing Scientific Literacy through Inquiry-Based Professional Development in Genetics, Muscle Biology, Microbiology, and Nutrition. Assessments were made at two points. First, the participants were assessed by using a pretest followed up by a posttest 12 months later after implementing the new curriculum. The teachers experienced gains during the professional development on both their personal science teaching efficacy and their science teaching outcome expectancy. However, the mean differences were not statistically significant. Results of this study indicate that the Increasing Scientific Literacy through Inquiry-Based Professional Development may be used as a tool to increase PSTE and STOE in agricultural educators and science teachers.

Introduction/Theoretical Framework

In the 2020-2021 school year, the Nebraska student-centered assessment in the area of science indicates that only 50% of high school students meet the science expectation (Nebraska Department of Education, 2022). The lack of science proficiency is not surprising given the statistics from 2017 indicating students’ proficiency gradually decreases between 5th grade, 8th grade, and 11th grade (Nebraska Department of Education, 2017). In 2017, 28% of 5th graders were below proficient, 32% of 8th graders were below proficient, and 39% of 11th graders were below proficient (Nebraska Department of Education, 2017). Proficiency scores indicate that science efficacy needs to be addressed at all grade levels, but specifically at the high school level. Based on research and theory, it is determined that outcome expectancy (OE) and science efficacy (SE) are complementary factors in determining the success of teachers in a science-based classroom. (Stripling & Roberts, 2013)

Teacher self-efficacy relates to progressive teaching behaviors and positive student outcomes. Therefore, the social cognitive theory serves as the theoretical framework for this study. The social cognitive theory identifies the capabilities of humans, and their purposeful intentions, that can and will affect their course of action (Bandura, 1977, 1997). This process is called triadic reciprocal causation and was developed by Albert Bandura (1977, 1997). Triadic reciprocal causation suggests three interrelated factors that mutually impact people: environmental, behavioral, and personal factors (Bandura, 1977, 1997). These three factors determine what a person believes about themselves and aide in their decision-making process (Bandura, 1977, 1997). Triadic reciprocal causation advocates that no one single factor determines a person’s behavior, instead, it is the combination of all three factors (Bandura, 1977, 1997). When determining OE and SE, behavior could be predicted (Bandura, 1997) and efficacy beliefs help dictate motivation (Maehr & Pintrich, 1997; Pintrich & Schunk, 1996). Self-efficacy theory helps outline what motivates a person (Graham & Weiner, 1996), and so, the theory can be applied to any behavioral task and predict what will take place.

In the teacher efficacy belief literature, two dimensions of teacher self-efficacy, including Teaching Efficacy (Outcome Expectancy) and Personal Teaching Efficacy (Self- Efficacy), have been defined and utilized in subsequent studies. Several studies suggest that teacher efficacy beliefs may account for individual differences in teacher effectiveness (Armor et al., 1976; Berman & McLaughlin, 1977; Brookover et al., 1978; Brophy & Evertson, 1981). Student achievement has also been shown to be significantly related to teacher efficacy beliefs (Ashton & Webb, 1983). The measurement of Personal Teaching Efficacy has been used to predict teacher behavior with accuracy (Ashton et al., 1983).

Teachers’ content knowledge affects student learning (Ballou & Podgursky, 1999; Ma, 1999; Podgursky, 2005); therefore, science teachers are expected to be highly qualified in the subject area in which they teach. Not only do teachers need to have a high level of comprehension in the content area, but they also need to display passion and enthusiasm. Additionally, standardized tests, only prove that students can memorize and focus on the content because the performance goals measured only address low levels of learning (Meece et al., 2006).

Teacher self-efficacy has also been connected to beginner agriculture teachers’ pledge to the teaching career (Knobloch & Whittington, 2003). Teaching efficacy is a more specific type of self-efficacy (Stripling & Roberts, 2013; Stripling et al., 2008), and is a teacher’s belief in their competence to facilitate the learning environment and produce desired learning results (Guskey & Passaro, 1994; Soodak & Podell, 1996). Beginning teachers who are more efficacious tend to have a greater obligation to teaching than those who are not as efficacious and consequently are more motivated to remain in the teaching profession (Whittington et al., 2003). In fact, beginner teachers could have an exaggerated sense of self-efficacy because of their student teaching experience (Knobloch, 2006).

This professional development program utilized inquiry-based learning as the main instructional approach. There have been numerous studies that show inquiry-based learning is an effective method for teaching science (Keys & Bryan, 2001). Inquiry-based learning requires students to manage their own learning and their success will be based on their engagement in the lesson through active listening and problem solving. Inquiry-based learning opportunities provide the foundation for students to make observations, pose questions, compare evidence, predict outcomes, and communicate research results (National Research Council, 2000).

Purpose/Objectives

The purpose of this study was to determine the teachers’ level of science efficacy in the agricultural education and science classrooms and compare the results as the teachers progressed through the yearlong professional development. The modified science teaching efficacy scale (based on Enochs & Riggs, 1990) consists of both personal science teaching efficacy (PSTE) and science teaching outcome expectancy (STOE).

Objectives include:

  1. Investigate secondary life science teachers’ personal science teaching efficacy (PSTE) within the sciences before and after the Increasing Scientific Literacy through Inquiry-Based Professional Development in Genetics, Muscle Biology, Microbiology, and Nutrition.
  • Investigate secondary life science teachers’ science teaching outcome expectancy (STOE) before and after the Increasing Scientific Literacy through Inquiry-Based Professional Development in Genetics, Muscle Biology, Microbiology, and Nutrition.

Two null hypotheses were used to guide this inquiry:

H01: There is no significant difference in the personal science teaching efficacy (PSTE) of life science teachers before and after the Increasing Scientific Literacy through Inquiry-Based

Professional Development in Genetics, Muscle Biology, Microbiology, and Nutrition treatment.

H02: There is no significant difference in the science teaching outcome expectancy (STOE) of life science teachers before and after the Increasing Scientific Literacy through Inquiry-Based

Professional Development in Genetics, Muscle Biology, Microbiology, and Nutrition treatment.

Methods/Procedures

Professional Development

This professional development (PD) program provided an opportunity for high school agricultural education teachers and science teachers to participate in a 12-month long PD. Applicants were encouraged to join the program with both a science and agriculture teacher from their school. The purpose of this was to bridge the gap between agriculture and science disciplines. After applications were submitted, there were not enough paring entries from all the same schools, so science and agriculture teachers were coupled from different schools (N = 10). For this study, the participants will be referred to as life science teachers. Applicants were recruited in the Spring of 2017. The project was divided into three phases.

Phase I

The PD program began in summer 2017 with a one-day workshop that took place at three different locations throughout Nebraska. The workshop introduced information centered around how students learn, more specifically, experiential learning, short-term and long-term memory, Bloom’s taxonomy, and learning styles. From there, the inquiry-based learning teaching method was introduced. All learning activities that were developed and used in this PD incorporated inquiry-based learning and allowed teachers to experience learning activities as students.

Basic scientific disciplines including biology, chemistry, and mathematics are interrelated in the growth and development of living beings.  For this reason, scientific units of study that focused on the Scientific Principles of Food Animal Systems were developed. The following units were included:

  1. Genetics
  2. Growth & Development / Chemistry of Muscle Biology

3)   Microbiology of Food Safety

4)   Physiology and Chemistry of Nutrition

Each unit provided basic content knowledge, hands-on inquiry-based learning activities, and student reflection instruments.  Content knowledge included educational videos and PowerPoint slides that could be used to introduce high school students to the topic and provided the scientific basis of the topic and related activities. Instructional materials also included a listing of necessary supplies and equipment, ordering information, and easy-to-follow instructions.  For those secondary life science educators that participated in the PD, selected supplies that would not normally be present in a typical high school science laboratory were provided to facilitate the small-group student learning activities. 

Finally, through inquiry-based learning, it is imperative that high school students be asked to reflect upon what they’ve just learned; to evaluate the results and to project how those results might relate to new situations or scenarios (Kolb, 1984).  To facilitate this final component of inquiry-based learning, instruments were developed to encourage high school students to reflect upon what they just learned and how that new knowledge may be applied to different situations in the future. Scientific principles related to genetics, muscle biology, microbiology, and nutrition were used to demonstrate a hands-on, inquiry-based learning pedagogy. 

Phase II

The program continued throughout the 2017-2018 academic year. Conference calls through Zoom, a video conferencing platform, took place in August and December of 2017, and April of 2018. The calls were used to discuss how life science teachers were implementing the prescribed learning activities that focused on genetics, muscle biology, microbiology, and nutrition.

Phase III

Life science teachers were placed in small teams and asked to develop additional inquiry-based learning activities that were presented during the final PD session in June of 2018. Each team was assigned a specific unit (genetics, muscle biology, microbiology, or nutrition) to focus their efforts.  The overall purpose of this activity was to help life science teachers learn how to develop their own inquiry-based learning activities and share their activities with a broader audience.

Data Collection

Quantitative methods were used to determine the change in teachers’ science teaching efficacy by using a modified science teaching efficacy scale (based on Enochs & Riggs, 1990). The instrument used for data collection was created by Enochs and Riggs (1990) to measure the self-efficacy of science teachers, called the Science Teaching Efficacy Belief Instrument (STEBI). Additionally, the data collected for this study was part of a larger data set.

The STEBI consisted of 23 questions scaled from 1 (strongly disagree) to 5 (strongly agree). Terminology was adjusted by researchers to accommodate for high school teachers instead of preservice elementary science teachers. Example questions from Enochs and Riggs (1990) include “I will continually find better ways to teach science,” “The inadequacy of a student’s science background can be overcome by good teaching,” “The low science achievement of some students cannot generally be blamed on their teachers,” and “When a low achieving child progresses in science, it is usually due to extra attention given by the teacher.”

The STEBI (Enochs & Riggs, 1990) is comprised of two scales that measure the constructs personal science teaching efficacy (PSTE) and science teaching outcome expectancy (STOE).

All items use a 5-point rating scale (1 = strongly disagree to 5 = strongly agree). The following item was modified from Enochs and Riggs (1990) by removing the word elementary: “I understand science concepts well enough to be effective in teaching elementary science.”

Additionally, Enochs & Riggs (1990) stated reliability analysis produced Cronbach’s alpha coefficients of .90 for PSTE and .76 for STOE. Post-hoc reliabilities for PSTE and STOE were .799 and .732, respectively. These measures of internal-consistency are acceptable given the nature of the constructs and present reliabilities on comparable measures (Ary et al., 2014).

Data Analysis

Data were analyzed using IBM SPSS version 20. Descriptive statistics (i.e., frequencies, percentages, and means) were used to describe the science teaching efficacy data. Additionally, based on Haynes and Stripling (2014) and Dossett et al. (2019), low, moderate, and high self-efficacy was defined as 1.00 to 2.33, 2.34 to 3.67, and 3.68 to 5, respectively. Data was summarized using descriptive statistics (i.e., frequencies, percentages, and means). Paired samples t-tests were utilized to determine if a significant difference existed in science teaching efficacy and outcome expectancy (OE).

The STEBI contains 23 items in the survey and 13 are designed to address science teachers’ level of belief that they can teach science (Personal Science Teaching Efficacy or PSTE) and 10 assess the respondents’ belief that their teaching will have a positive effect on the students they are teaching (Science Teaching Outcome Expectancy or STOE). Paired t-tests were run on the pre and post survey scores for the PD. The PSTE and STOE section, scores were analyzed separately. Therefore, all analyses of group mean differences were done as two tailed tests.

Results/Findings

The first and second objectives were to investigate the level of PSTE/STOE of the professional development participants before and after the PD. During the first phase of the study teachers reported before the PD, they had a mean personal science teaching efficacy (PSTE) score of 3.83 (SD = .27) and an outcome expectancy (OE) of 3.35 (SD = 0.48). The second phase conducted after the 12-month PD teachers reported an increase in both areas with a mean PSTE of 3.95 (SD = 0.33) and an OE of 3.47 (SD = 0.47).

Means and analysis results for the surveys are presented in Table 1 and Table 2. Analysis of surveys from the PD indicated no significant pre/post shifts on PSTE or STOE scores, however there were small actual mean differences.

Table 1

Personal Science Teaching Efficacy Scores 

LowModerateHigh
MSDf%f%f%
Pretest3.830.2700.0330.0770.0
Posttest3.950.4800.0110.0990.0
Note. 1.00 to 2.33 = low efficacy, 2.34 to 3.67 = moderate efficacy, 3.68 to 5 = high efficacy.

Table 2

Science Teaching Outcome Expectancy Scores 

  LowModerateHigh
 MSDf%f%f%
Pretest3.350.4800.0660.0440.0
Posttest3.480.4700.0660.0440.0
Note. 1.00 to 2.33 = low efficacy, 2.34 to 3.67 = moderate efficacy, 3.68 to 5 = high efficacy.

The mean differences between the pre and post teaching efficacy scores for PSTE and STOE are in Table 3. Analysis revealed a .11-point increase in PSTE, a .13-point increase in the STOE. However, the mean differences were not statistically significant. Thus, the null hypotheses were not rejected.

Table 3

Summary of Paired Samples t tests

 Mean differenceSDSEtp
PSTE posttest – pretest.11.20.061.79.11
STOE posttest – pretest.13.51.16.79.45

Conclusions/Recommendations/
Implications

The purpose of administering the modified STEBI (based on Enochs & Riggs, 1990) was to investigate teachers’ level of science efficacy in the agricultural education and science classrooms and compare the results as the teachers progressed through the professional development.Personal science teaching efficacy (PSTE) slightly increased from pre and posttest and science teacher outcome expectancy (STOE) also changed during the PD.

Analysis revealed a .11-point increase in PSTE, and a .13-point increase in STOE. However, the mean differences were not statistically significant. Thus, the null hypotheses were not rejected. Results of this study indicate that the Increasing Scientific Literacy through Inquiry-Based Professional Development program may be used as a tool to increase PSTE and STOE in life science teachers. Professional development opportunities focused on teaching science through inquiry-based learning could be a way to increase science efficacy (SE) and outcome expectancy (OE) over time. If professional development workshops could continually increase SE and OE, the SE and OE could be used to help determine teacher success in a science-based classroom, thus aligning with Stripling and Roberts’ (2013) assertion that OE and SE can be used to determine teacher success. Teacher educators should purposefully design teacher professional development programs to allow teachers to practice their science teaching skills, thus providing an opportunity for the teacher to increase their SE and OE. To align with Kolb (1984), the professional development should be designed to have purposeful reflection activities that allows the teachers to critically examine their ability and confidence when teaching science concepts.

We found life science teachers in this study to be moderately efficacious in their ability to teach science concepts before and after the conclusion of the PD. However, 20% of the life science teachers in this study moved from moderate to high efficacy with PSTE. According to Bandura (1997), self-efficacy influences behavior. Thus, theoretically, being highly efficacious in PSTE should positively impact the teaching of contextualized science in school-based agricultural education and science programs; on the other hand, being moderately efficacious may negatively impact the teaching of contextualized science. Additionally, educating life science teachers in technical science content aligns with Ballou and Podgursky, 1999, Ma, 1999, and Podgursky, 2005 assertion that teachers content knowledge impacts student learning. Therefore, we recommend the continuation of professional development programming that aims to increase technical content knowledge. Providing in-depth technical content knowledge should allow the teachers to increase their confidence because they will have a better understanding of the technical content and will feel more comfortable teaching the technical content in the classroom. It is important to note that the small sample size limits the generalizability of the findings.

Future research should be conducted to determine why approximately an equal number of teachers are moderately or highly efficacious in PSTE and determine if moderate self-efficacy negatively impacts the teaching of contextualized science. In regard to science teaching outcome expectancy, a majority of the life science teachers were moderately efficacious in STOE. Theoretically, being moderately efficacious in STOE may negatively impact the teaching of contextualized science. The said research will also aid the planning of professional development for agricultural education and science teachers and can be used to guide experiences offered in agricultural and science teacher education programs.

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Implications of Pandemic Responses for Extension Education and Outreach

Samuel Quinney, Clemson Extension, squinne@clemson.edu
Grace Greene, Clemson University, mgg2@g.clemson.edu
Christopher J. Eck, Oklahoma State University, chris.eck@okstate.edu
K. Dale Layfield, Clemson University, dlayfie@clemson.edu
Thomas Dobbins, Clemson University, tdbnns@clemson.edu

PDF Available

Abstract

As part of daily tasks of Cooperative Extension, agents handle public issues by offering programming by approved methods to inform the public. Within the context of this study, a mixed-methods approach was established to determine the factors impacting behaviors associated with Clemson Extension, programming efforts, and roles during the COVID-19 pandemic. Understanding the attitudes and perceptions of Extension educators and key stakeholders (i.e., advisory committee members), researchers, faculty, and Extension educators can be better prepared to face future challenging while continuing to meet the public demand. This exploratory, mixed methods inquiry investigated the perceptions of current Clemson Extension agents across South Carolina and Extension advisory committee members related to the ongoing COVID-19 pandemic and Extensions response. To meet the needs of this mixed methods approach, qualitative interviews were conducted with Extension agents and a survey questionnaire was utilized to collect pertinent data from Extension advisory committee members. Through this study, strengths and challenges for South Carolina Cooperative Extension Agents during the COVID-19 pandemic were learned, providing a framework in the event of similar challenges in the future. Adaptability is key moving forward for Extension, as it allows Extension agents to meet the needs in their communities, serve their primary stakeholder groups, and improve overall perceptions of what they offer. Extension professionals should consider the findings as a starting point to evaluate the current state of Extension programming and how to best move forward to address pertinent agricultural issues.

Introduction/Theoretical Framework

“The pace of innovation in the agriculture-related, health, and human sciences demands that knowledge rapidly reaches the people who depend on it for their livelihoods” (USDA-NIFA, 2021, para. 1). Specifically, the Clemson Cooperative Extension (2021) service aims to “improve the quality of life of all South Carolinians by providing unbiased, research-based information through an array of public outreach programs in youth development; agribusiness; agriculture; food, nutrition and health; and natural resources” (para. 1). The normal day to day operations of Clemson Extension was brought to a halt on March 18th, 2020, after the World Health Organization (2020) declared the Novel Coronavirus or COVID-19, a global pandemic on March 11, 2020.

As part of daily tasks of Cooperative Extension, agents handle public issues by offering programming by approved methods to inform the public (Dale & Hahn, 1994; Patton & Blaine, 2001). Most issues originate as private concerns and become public when outside agencies become involved and widespread support or opposition is gained. This is often related to an identifiable problem, whereas others may arise from misinformation or inaccurate perceptions (Patton & Blaine, 2001). These contentious issues often create situations in which public input and education can be keys to solving the problem; however, due to the highly charged nature of such issues, many leaders tend to avoid them (Jolley, 2007; Patton & Blaine, 2001; Rittel & Webber, 1973). Clemson extension has always made it a priority to provide relevant programming to address these public issues.

During today’s societal changes of the COVID 19 Pandemic, agricultural communities have faced challenges. According to the United States Department of Agriculture (USDA) Economic Research Service (ERS) (2021), the total number of cash receipts by commodity has remained steady, with some commodities increasing between the years 2020 and 2021. Animals and animal products increased just under $8.6 billion, and crops increased just over $11.8 billion via cash receipts reported by the USDA-ERS (2021). Some of these increases in consumer purchases have come through governmental policies, which increased American agriculture commodity purchases from foreign countries under the US and China trade deal. China will purchase and import $40 billion dollars’ worth of American agriculture products including meat goods (McCarthy, 2020), others came from a decrease in store availability, though no nationwide shortages have been reported (USDA, 2021). Though the total cash receipts have improved nationally, local agriculture producers face a distinct set of issues. Such issues include a misinformed public, slaughterhouse backups, and a lack of land availability. However, the agricultural cash receipts have yet to be reported for South Carolina according to the USDA-ERS (2021).

Clemson Extension was not alone, as schools, businesses and government agencies across the U.S. adapted to limit in-person contact (CDC, 2020). Extension agents had to cancel some scheduled programming and events and shift what they could to virtual platforms, such as Zoom, which has been identified as easy-to-use and engaging (Robinson & Poling, 2017). With the pandemic catching most off-guard, little account was taken into the perceptions, attitudes, and beliefs of Clemson Extension agents and advisory groups. To frame the evaluation of these concerns, the theory of planned behavior (Ajzen, 1991) was implemented (see Figure 1).

Figure 1

Ajzen’s (1991) Theory of Planned Behavior Model

The theory of planned behavior (Ajzen, 1991) “provides a useful conceptual framework for dealing with the complexities of human social behavior” (p. 206), as it provides a frame to outline the predictability of an individual’s future plans and behaviors (Ajzen, 1991). The theory of planned behavior has further been implemented (Murphrey et al., 2016) to evaluate one’s perceptions and/or intentions related to formal and informal training (i.e., Extension programming). Within the context of this study, a mixed-methods approach was established to determine the factors (i.e., attitude toward the behavior, subjective norms, and perceived behavioral control) impacting behaviors associated with Clemson Extension. Specifically, programming efforts (i.e., attitudes), roles (i.e., norms), issues (i.e., attitude and perceived control), and solutions (i.e., intentions) were addressed to establish best practices learned from the COVID-19 pandemic. Understanding the attitudes and perceptions of Extension educators and key stakeholders (i.e., advisory committee members) allows researchers, faculty, and Extension educators to be better prepared to face future challenges while continuing to meet the current public demand.

Purpose and Research Objectives

During today’s societal changes, Clemson Extension has expanded its role to provide education to the public through virtual and other non-contact options. Therefore, this study aimed to determine the perceptions of Clemson Extension agents and the prevalent issues faced within the agriculture community in the South Carolina by interviewing Extension agents and surveying Clemson Extension advisory committee members. Four research questions were developed to guide this study:

  1. Describe the current perceptions of Clemson Extension agents amidst the COVID-19 pandemic.
  2. Identify the greatest issues facing agriculture in South Carolina according to advisory committee members during the COVID-19 pandemic?
  3. Determine current and potential solutions from Clemson Extension to address the issues faced during the COVID-19 pandemic.
  4. Create a list of preferred programs and program delivery methods for future Extension programming.

Methods

This exploratory, mixed methods inquiry investigated the perceptions of current Clemson Extension agents across South Carolina (N = 154) and Extension advisory committee members (N = 64) related to the COVID-19 pandemic and Extensions response. To meet the needs of this mixed methods approach, qualitative interviews were conducted with Extension agents (n = 6) and a survey questionnaire was utilized to collect pertinent data from Extension advisory committee members.

Qualitative Inquiry Procedures

As with most qualitative inquiries, this study sought to provide rich information from the Extension agents as they adapt with the changing dynamics of the pandemic. A purposive sampling strategy was implemented to reach data saturation amongst the variety of agents across the state. This sampling method included soliciting participation from agents from all five regions and 10 program teams, resulting in interviews with six agents representing five program teams and all five regions spanning 15 counties, as some agents work in multiple counties. For proper tracking of data, each participating agent was provided a pseudo name that is outlined in Table 1.

Table 1

Clemson Extension Agents Who Participated in the Study (n = 6)

Pseudo Name Sex Region Program Team 
Shawn Male Region 4 Horticulture 
Abigail Female Region 1 4-H Youth Development 
Violet Female Region 5 Livestock & Forages 
Leonard Male Region 3 Forestry & Wildlife 
Keith Male Region 4 Agronomic Crops 
Taylor Male Region 2 Horticulture 

To address the overarching research objective of the qualitative inquiry, a flexible interview protocol was established spanning four topic areas, including: 1) Accessibility and program impacts; 2) Responding in a time of crisis; 3) Remote instruction and distance education; and 4) Economic and communication concerns early in the COVID-19 pandemic. Each topic area included probing questions to help facilitate conversation, helping to uncover the specific paradigm being studied. Glesne (2016) identifies the specific paradigm or reality being evaluated within this study as an ontology, as the study aimed to discover and individuals’ beliefs associated with their current reality, further connecting to the theory base (Ajzen, 1991) as we try to uncover future intentions. The interview protocol was checked for face and content validity (Salkind, 2012) by two faculty members with teaching and research experience in Extension education and research methodology. All six interviews were conducted by an undergraduate student minoring in Extension education following the interview protocol for consistency. Additionally, a fieldwork notebook was compiled by the interviewer to document the interview experiences through observation notes, interview notes, and reflexive thoughts (Glesne, 2016).

The interviews were conducted using Zoom due to the ongoing COVID-19 pandemic and University regulations. The interviews were recorded and transcribed using features embedded in the Zoom platform, which were then compared against one another for accuracy. In addition to the interview recordings and transcriptions, interviewer notes were used for triangulation of data. To further increase the trustworthiness of the study, the research team followed the recommendations of Privitera (2017) to establish credibility, transferability, dependability, and confirmability within the study. Creditability was addressed through coding member checks across the research team to reduce bias (Creswell & Poth, 2018) along with triangulation of data and saturation of emerging categories (Privitera, 2020). To enhance transferability the researchers described the participants (including pseudonyms), detailed the interview and data analysis process, and highlighted the perspectives of the participants. Procedural explanations and data triangulation furthered the dependability of the research (Creswell & Poth, 2018; Privitera, 2020), and a reflexivity statement was included to describe any inherent biases associated with then phenomenon (Privitera, 2020).

Confirmability refers to the objectivity of the findings and the ability to interpret the narrative of the experience of participants to determine the essence of the phenomena instead of the researcher’s bias (Creswell & Poth, 2018; Privitera, 2020). A reflexivity statement describes the researchers previous understanding of the phenom

To analyze the interview transcripts through a qualitative lens, this study implemented the constant comparative method (Glasser & Strauss, 1967), which permits the data to speak for itself, allowing themes to emerge. The first round of coding used open-coding sources, allowing themes to emerge through the process (Creswell & Poth, 2018). Axial coding was followed for second-round coding, where the relationships between open codes resulted in overarching categories (Creswell & Poth, 2018; Glasser & Strauss, 1967). Round three of coding was selective coding, where the researchers determined the core variables from the qualitative interviews.

The purposive sampling provides a limiting factor as only six Clemson Extension agents were interviewed for the purpose of this study. Therefore, the findings of this study are limited to the views of the participants and not necessarily that of all agents in the state, but the findings of the study can be used to inform practice, guide future research, and potentially offer state-wide implementations based on needs. The research team recommends caution when looking to generalize the data, although the data has transferable qualities if the readers deem the population and situations identified as germane to their inquiry.

Within a qualitative inquiry, Palaganas et al. (2017) recommends for researchers to acknowledge any inherent bias and reveal their identify to offer reflexivity. The research team consisted of two faculty members in agricultural education at Clemson, a current Extension educator, and an undergraduate student pursuing a minor in extension education. The faculty members have more than 30 years of experience combined in agricultural and extension education. We recognize our bias toward Extension because of our faculty roles and have attempted to harness that bias through a consistent interview protocol, interviewer, and extensive field notes.

Survey Research Procedures

This non-experimental descriptive survey research component aimed to reach Clemson Extension advisory committee members (N = 64) in Abbeville, Anderson, Greenville, Oconee, and Pickens counties in South Carolina. The counties selected to participate in the survey were selected for their vast differences, including suburban, rural agriculture/homesteads, small towns, and large cities. The populations of the participating counties were Greenville – 507,003; Anderson – 198,064; Pickens – 124,029; Oconee – 77,528, and Abbeville – 24,627 (United States Census Bureau, 2021).

The questions addressed in this study were designed to assess how the Clemson Cooperative Extension Service adapted during the COVID 19 pandemic. Survey questions were divided into three categories, 1) Agricultural issues, 2) Extension programming, and 3) Participant demographics. The agricultural issues category elicited open ended responses to determine the greatest issues facing agriculture and what Clemson Extension is and can do to help the issues. The second category aimed to determine the preferred program delivery methods and primary program teams of interest. The researcher-developed survey was reviewed for face and content validity by Agricultural Education faculty and Clemson Extension professionals.

Of the 64 advisory members who received the survey via email, 27 responded, resulting in a 42.2% response rate. Participants were 55.6% male and 44.4% female and ranged in age from 29 to 73 years old, with agricultural involvement varying from pre-production/production agriculture to agricultural consumers (see Table 2) across the five counties. Data was analyzed using SPSS Version 27 to address the proposed research questions.

Table 2

Personal and Professional Demographics of Extension Advisory Committee Members in South Carolina (n = 27).

Demographics   f %
Gender Male 15 55.6
  Female 12 44.4
  Prefer not to respond 0 0.0
Age 21 to 30 1 3.7
  31 to 40 5 18.5
  41 to 50 3 11.1
  51 to 60 8 29.6
  61 to 70 4 14.8
  70 or older 6 22.2
  Did not respond 0 0.0
 Current Role in Agriculture Pre-Production  7.4 
Production1452.9
Consumer1037.03
 Did not respond 1 3.7

Findings

Research Question 1: Describe the current perceptions of Clemson Extension agents amidst the COVID-19 pandemic.

The emerging codes, themes, and categories were used to explain the perceptions of Clemson Extension agents related to the ongoing COVID-19 pandemic. Four overarching categories emerged from the findings.

Category 1: Extension is Adaptable

 Keith stated, “we’re used to getting things thrown in our lap, everybody in the world or everybody in the country says, you have any questions call your county extension agent,” which reinforced this concept. When considering the COVID-19 pandemic, Keith went on to say, “as far as agronomy agents and a lot of the horticulture agents, we’ve never quit visiting farmers, when they call, we go.” The changes caused by the pandemic looked different across the state, depending on the needs of community, which was encompassed through the thoughts of Extension professionals “adapting every single day and the pandemic just made it a big step, as opposed to little steps. We just had to figure out a way to continue to do what we’re already doing, just in a different format” (Leonard). Other interviews built upon these same lines of thought to demonstrate the overall adaptability of Clemson Extension.

Category 2: Need for Training and Resources

The greatest need indicated across the interviews was specific training and resources to help Extension professionals and constituents navigate the pandemic. Keith simply stated that “everybody’s been putting out fires and handling their own problems … and I think some help and some guidance with all our delivery programs would be great.” Abigail further identified “a big chunk of people who are probably [her] age and younger and then a couple of older ones who … are more traditional, who need some help.” The participants identified specific training needs for agents across the state related to Zoom, virtual programming, and mental health of both adults and youth, “because as the times change, new stuff comes up.” Additional resources were also discussed by participants as many Extension professionals “live out in the middle of nowhere and Internet does not come to [their] house” (Shawn), requiring them to work of a limited data hot spot, when the data is gone, they are without internet. Participants also expressed a need for computers “that can handle Zoom,” so they can utilize Zoom features and provide essential programming to constituents. The final resource need is for the community members Extension professionals aim to reach, as many farmers and ranchers struggle to engage using technology, which Leonard explained that “it’s not necessarily that they can’t do it, a lot of them just don’t have the ability. Your rural areas just don’t have computers.”

Category 3: Community Perceptions

Perceptions of the communities Extension professionals serve was expressed by Violet as, “we’ve been at this so long, I wonder about our relevance… I’m still making farm visits, but a lot of people think we’re closed.” Similarly, Taylor struggled “going from what we normally do and being the face of the public and the face of the university to everything [moving] online, was tough. The biggest struggle was getting over the hill of convincing yourself that this is the way it’s going to be and then having to convince clientele that this is the way it’s going to be for a little while.” The change in delivery was difficult for all involved and many are concerned with the impact of the pandemic on the relationship between the Extension professional and the clientele moving forward. Which, Violet expressed as her “greatest concern, is how to bring those people back and have them trust us again and know that we’re still working, we’re still here and we still deserve to be paid, that sort of thing. I’ve heard all those things so that’s probably what I’m worried about the most.”

Category 4: Reluctancy to New Methods

Violet explained that “certainly the Zoom capabilities are good, but there’s been some reluctance to use them from our older crowd, and, unfortunately most farmers are 65 and older.” She went on to express the hardships as “it’s been a little bit hard to pull them [older farmers] in and get them to really feel connected. They like our meetings for the information side of it, but also the community feel, and I think you do lose a little bit of that with the virtual sense or virtual realm.” In contrast, Taylor found a positive side to the new methods as “we’re reaching a lot more people, especially on our side of the team that probably wouldn’t normally come to a meeting because they can just jump on a computer now.” But he also went on to explain the reluctance as “a majority of our clientele is older, the Zoom thing is tough for them, the technology piece is tough… We picked up a lot of clients… but we probably have some frustrated clients because of it.”

Research Question 2: Identify the greatest issues facing agriculture in South Carolina according to advisory committee members during the COVID-19 pandemic?

The second research question focused on determining the greatest issue(s) currently facing the agricultural industry in South Carolina. Of the 27 respondents, two primary issues arose, the cost/lack of agricultural inputs and outputs, and the need for local produce and meat products. Table 3 outlines underlying issues that make up those broader categories.

Table 3

Greatest Issues Facing South Carolina Agriculture (n = 27)

CategorySpecific Issues
Cost/Lack of Agricultural Inputs and OutputsLand, Seed, Feed, Fertilizer, Chemicals; Slaughter Facilities
 Increased Cost due to Urban Sprawl; Market Fluctuations
Need for Local Produce and Meat productsCOVID Restrictions; Farmers Market and Open-Air Markets Closed

Research Question 3: Determine current and potential solutions from Clemson Extension to address the issues during the COVID-19 pandemic.

The third research question addressed the current and potential solutions Clemson Extension is currently providing or could provide to address issues in agriculture. Table 4 outlines the current solutions being offered, although 14.8% of respondents felt that nothing was currently available. The two current solutions include agricultural education and agricultural land loss prevention. Specifically, agricultural education represents the Making It Grow programming offered through South Carolina Educational Television (SCETV), information provided by the Home Garden Information Center (HGIC), 4-H youth development programming, and Extension programs/Education. The second solution to currently assist agriculturalists is the agricultural land loss prevention program focused on agricultural land easements offered through the USDA-NRCS office.

Table 4

Solutions Available for Current Agricultural Issues (n = 27)

Current SolutionsSpecific Program/Offering
Agricultural EducationMaking it Grow
 HGIC
 4-H Youth Programming
 Extension Programs/Education
Agricultural Land Loss PreventionAgricultural Land Easements-NRCS

In addition to current programs, respondents’ ideas for potential solutions were of interest to the research team. Respondents identified two categories of solutions, the first being to publicize Extension programs and services better, so the public have a better understanding of what Extension does and what is being offered. The second solution was an increase in agricultural education, specifically targeting small farms and farming for-profit programs, additionally youth education opportunities, along with specific education programming highlighting the historical importance of agricultural land and keeping that land in agricultural production. Much of this was connected to 56% of respondents identifying COVID-19 as having a specific impact on agriculture in the state. Specifically, one of the greatest concerns was the impact of virtual programming during the COVID-19 pandemic, as many individuals did not have access to virtual programming due to lack of technology or internet. A potential option that was presented was being sure to offer recorded (asynchronous) programming options versus the live (synchronous) options currently available.

Research Question 4: Create a list of preferred programs and program delivery methods for future Extension programming.

The final objective aimed to establish the preferred program delivery methods for future extension programming, along with current and future program interests. Table 6 outlines the preferred information delivery method of respondents.

Table 6

Preferred Information Delivery Method (n = 27)

Delivery Methodf%
Email933.3
Office Visits622.2
No Preference622.2
Farm Visits13.7
Phone13.7
Text Updates13.7
Fact Sheets13.7
Postal Mail13.7
Social Media13.7

In addition, 55.6% of participants said they would be willing to participate in future virtual programming if offered, while 22.2% of participants said they would not participate, and the remaining 22.2% were unsure. To further understand programmatic interests, participants were asked to identify which of the Clemson Extension Program teams had provided the most information during the pandemic, Table 7 outlines their responses.

Table 7

Programmatic Teams Offering the Most Programming During COVID 19

Program Teamf%
4-H725.9
Unknown622.2
Forestry and Wildlife414.8
Agricultural Education311.1
Horticulture311.1
Food Systems and Safety27.4
Livestock and Forages13.7
Rural Health and Nutrition13.7

Although 4-H was reported as the program team providing the most programming during the pandemic, participants expressed the most interest in more programming from the forestry and wildlife team (33.3%), followed by the agricultural education and livestock and forages teams, both with 26% of the respondents interested. The agribusiness team (22.2%) and the horticulture team (18.5%) rounded out the top five. The remaining program areas had less than 14% of participants interested.

Conclusions, Implications, and Recommendations

Through this study, strengths and challenges for South Carolina Cooperative Extension Agents during the COVID-19 pandemic were learned, providing a framework in the event of similar challenges in the future. As identified in the category one finding, “Extension is Adaptable,” discussed how agents continued to meet their constituent’s needs, but through use of many creative means. a benefit that will aide Cooperative Extension Agents is the ability to adapt quickly. This ability to adapt would support those aspects in the category two findings which identified a need for training/in-service of Cooperative Extension Agents and their constituents. Category three, “Community Perceptions,” is reflective of the anxiety and uncertainty that was commonly experienced during the pandemic. Shifts in time and locations of workplace during the pandemic created a variety of uninformed interpretations of staff labor and confusion among the clientele base. Category four, “Reluctancy to New Methods” was commonly thought to be a challenge, but during the pandemic, it became widely know that there are gaps in technological competencies. Altough Extension agents had negative perceptions about certain components of their ability to provide appropriate education and outreach to constituent groups, their overall intentions were positive leading to actionable behaviors (Ajzen, 1991) that made an impact in their communities and states.

According to the advisory committee members in this study, there are two primary issues (i.e., attitudes; Ajzen, 1991) facing agriculture (i.e., cost or lack of agricultural inputs and outputs and the need for local produce and meat products) in South Carolina. The first issue can be contributed to the availability of land due to urban sprawl as well as all input costs having significantly increased in spring 2021. Additionally, slaughter facilities have been waitlisted for the last year due to high demand for American meat products. The area of concern can be considered together with the first due to slaughterhouses being backed up, local meat producers are unable to get their product finished out and packed for sale. Open air markets and farmers have been under the mercy of local and federal government’s restrictions, which have limited or cancelled all opportunities for local produce to be made available (L. Keasler, personal communication, 2021). Although these issues are of concern, Extension has the opportunity to address some of them by providing timely and accurate information to those who need it most. This allows the agents to control what they can through communication, reducing the negative perception and informing stakeholders if the subjective norms (Ajzen, 1991) currently impacting agricultural production.

Extension can work with local producers to ensure that they are in contact with their local and state representatives to be made aware of the issues that American agriculturalists are facing in today’s environment. Extension can also provide more agricultural education to the general consumer to assist our agricultural producers in informing the community what issues they face to maintain their livelihood. Some things cannot be controlled, such as market fluctuations and processing facilities operation. However, agents can make public representatives aware of the issues, asking them to push these issues in front of our elected legislative bodies to enact change through governmental policies. According to Anderson and Salkehatchie counties Cattlemen’s Association members and meat producers (personal communication, January 12, 2021), the availability of funds to build more USDA certified handling facilities would increase the speed at which products can be made available to markets, as well as increase jobs in areas where these facilities are housed. Perhaps, inputs such as fertilizers and herbicides can be regulated by government to avoid price gouging when they are needed the most, making the big companies richer and the hard-working farmers pockets tighter to continue to make a living in production agriculture.

Local fruit and vegetable producers face a slightly different issue in that they are at the mercy of local, state, and federal mandates, only operating at full capacity when they are told it is safe to do so (L. Keasler, personal communication, 2021). Similarly, Extension is subject to these same mercies, although we have seemed to reach a new normal, the findings of this study can be beneficial for Clemson Extension and similar Extension agencies in other states.

The implications support the Theory of Planned Behavior (Ajzen, 1991), as agents recognized that they could adapt to meet the needs of their constituents during time of many unknowns and countless challenges demonstrates how favorable attitudes and intentions result in adaptable behaviors. These behaviors include the awareness of need for additional training and to seek resources to meet needs. Paradoxically, the resistance of many constituents to accept alternative programming methods presented opposing behaviors from the agents, creating additional challenges. Regardless, adaptability is key moving forward for Extension, as it allows Extension agents to meet the needs in their communities, serve their primary stakeholder groups, and improve overall perceptions of what they offer. Although it should be noted that many of the factors impacting Extension during the COVID-19 pandemic were outside of the Extension agents’ control, ultimately impacting the perceived behavioral control the agents had on situations (Ajzen, 1991).

Considering recommendations for Extension professionals, a need exists to better publicize programs and services offered from the county offices to increase awareness and community participation. This can be done through local news organizations such as newspapers, radio stations, social media, and news channels. Although the pandemic has provided its share of challenges, the increased availability for virtual programming has some benefits, such as being able to reach a broader audience across the state who previously never participated in Extension programming. Moving forward it is recommended that Extension consider ways to offer programming in-person and virtually to continue to expand the diversity of people being reach for programming. Perhaps, with a collaborative effort Clemson Extension could make a greater impact on the future of agriculture across the state, as agriculture makes an impact on everyone’s daily life. Extension professionals should consider the findings as a starting point to evaluate the current state of Extension programming and how to best move forward to address pertinent agricultural issues.

Realizing the conclusions and implications addressed in this study, it is recommended that Cooperative Extension Services consider the following actions:

  1. Initiate an assessment of State Cooperative Extension Service staff to develop a comprehensive guide on best management practices in the event of future events of the magnitude experienced from the COVID-19 pandemic;
  2. Develop a series of in-service offerings on communications tools for delivery of online programming, provided at different skills levels;
  3. Coordinate with agencies that provide professional development in awareness of mental health issues and recommended practices and resources available, and
  4. Establish a review team of IT experts for the Cooperative Extension Service that will develop a standard protocol to assure that technologies (laptops, scanners, etc.) needed for online delivery and required Internet access will be available for staff to successfully complete their programming remotely as needed.

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