Category

Quantitative

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

Baker, M. A. & Robinson, J. S. (2016). The effects of Kolb’s experiential learning model on successful intelligence in secondary agriculture students. Journal of Agricultural Education, 57(3), 129-144. https://doi.org/10.2032/jae.2016.03129

Baker, M. A. & Robison, J. S. (2017). The effects of an experiential approach to learning on student motivation. Journal of Agricultural Education, 58(3), 150-167. https://doi.org/10.5032/jae.2017.03150

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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.

Krathwohl, D. R. (2002). A revision of Bloom’s taxonomy: An overview. Theory into Practice, 41(4), 212–218. https://doi.org/10.1207/s15430421tip4104_2

Mainemelis, C. Boyarzis, R. E., & Kolb, D. A. (2002). Learning styles and adaptive flexibility: Testing experiential learning theory. Management Learning, 33(1), 5-33. https://journals.sagepub.com/doi/pdf/10.1177/1350507602331001

Osborne, E. (1993). Rediscovering our niche. The Agricultural Education Magazine, 66(4), 3-12. https://www.naae.org/profdevelopment/magazine/archive_issues/Volume66/v66i4.pdf

Rhykerd, R. L., Tudor, K. W., Wiegand, B. R., Kingman, D. M., & Morrish, D. G. (2006). Enhancing experiential learning through a hands-on crop production and marketing contest. North American Colleges and Teachers of Agriculture, 60(4), 25-30.

Roberts, T. G. (2006). A philosophical examination of experiential learning theory for agricultural educators. Journal of Agricultural Education, 47(1), 17-29. https://doi.org/10.5032/jae.2006.01017

Roberts, T. G., Harder, A., & Brashears, M. T. (Eds). (2016). American Association for Agricultural Education national research agenda: 2016-2020. Gainesville, FL: Department of Agricultural Education and Communication.

Shoulders, C. W. & Myers, B. E. (2013). Teachers’ use of experiential learning stages in agricultural laboratories. Journal of Agricultural Education, 54(3), 100-115. https://doi.org/10.5032/jae.2013.03100

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

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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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