All Posts By

James Scott

Teacher Disengagement in High Stakes Learning Environments: An Ugly Data Perspective

Ashley M. Yopp, University of Georgia, ayopp@uga.edu

Billy R. McKim, Texas A&M University, brmckim@tamu.edu

Yvonna S. Lincoln, Texas A&M University, ysl@tamu.edu

PDF Available

Abstract

A lack of engagement has been reported to contribute to an ever-widening gap between how students develop knowledge, skills, and abilities and how teachers provide instruction. At the onset of this study, the purpose was to understand how depth and sequence of experience influenced student engagement, yet an emergent etic perspective surfaced. Data were collected from hundreds of hours of student interviews and observations, student and teacher reflexive journals, and classroom dialogue. Results of this study included a personal autoethnographic narrative describing the complex and unforeseen realities of (dis)engagement experienced by teachers and students. At the conclusion, it was evident the scope of the study needed to be expanded to not only describe the influence of how depth and sequence of experience engaged and, in some cases, disengaged students and teachers alike, but also the role meaningful connection plays in teaching in high stakes learning environments.

Introduction

Engaged students are more motivated to learn but understanding how to engage students is a complex task (Coates, 2007). Teaching and learning are not mutually exclusive. The ability of a teacher to engage students is met with an unlimited number of extraneous variables and ever-changing policies that continuously disrupt their daily approach. Issues of student engagement become more difficult in high-stakes educational settings. According to the National Research Council (1999), the context and standards of high-stakes environments have unintended consequences that discourage teachers from improving instruction to engage students. Additionally, teachers exhibit more controlling behaviors and are less likely to use practices that support student engagement, including exploration and experimentation (Sheldon & Biddle, 1998; Bain, 2004).

The challenges of teaching today’s student require teachers to adapt to a new reality that is far from the classroom many educators experienced as students. Priority 4 of the American Association for Agricultural Education National Research Agenda (Edgar et al., 2016) included the need to understand “meaningful, engaged, learning opportunities is paramount to future learning environments,” signaling a “paradigm shift” in the way teachers prepare students for the 21st century (pg. 38). However, perceptions that foster ideas of “edutainment” and quick fixes to student engagement only create misrepresentations of the problems teachers are facing in their classrooms (Sorathia & Servidio, 2012). Teaching, without renewed perspective of learning, may create an ever-widening gap between how students develop knowledge, skills, and abilities and how teachers provide instruction. In adapting the learning environment to also “entertain” students, teachers are taking on additional responsibilities in the classroom; teachers’ past experiences and current social, emotional, and mental states can largely affect these additions. To understand engagement, holistic accounts of student and teacher experiences should be considered. Assessing both parties allows researchers to identify levels of engagement in relation to classroom culture and learning expectations.

The complex web of perspectives, approaches, and settings presents the need to understand student and teacher engagement at a basic level. Bain (2004) suggested “the best teaching cannot be found in particular practices… but in the attitudes of teachers, in their faith in students’ abilities to achieve, in their willingness to take students seriously, and let them assume control of their own learning” (p. 78-79). In line with the learning process, teachers must consider their inevitable impact on student learning – experiences, both positive and negative, will impact student learning as well as the overall classroom environment. Although research has contributed to varied components of teaching and learning individually, a collective and reciprocal understanding could illustrate possible opportunities for teachers and students to engage in any learning environment – including all five disciplinary areas of our profession (agricultural communications, agricultural leadership, school-based agricultural education, extension and outreach education, and agricultural education in university and post-secondary settings).

What is Student Engagement?

Engaged learning practices used to develop students into in-depth learners, instead of passive receptors, have been essential components of educational theory for years (Johnson et al., 2001; National Research Council, 2009). Drawing on constructivism, engaged learning requires students construct knowledge with their own experiences instead of accepting the experiences of an all-knowing teacher (Piaget, 1976). In higher education, Chickering and Gamson (1987) provided a set of principles to engage undergraduates in learning; principles include student-faculty interaction, student cooperation and reciprocity, and active learning.

Developing a specific definition of student engagement has become increasingly important as researchers and administrators work toward practices to improve student performance. Krause and Coates (2008) defined student engagement as “the extent to which students are engaging in activities that higher education research has shown to be linked with high-quality learning outcomes” (p. 493).  Similarly, Hu and Kuh (2001) defined engagement as “the quality of effort students themselves devote to educationally purposeful activities that contribute directly to desired outcomes” (p. 3). Harper and Quaye (2009) argued engagement was a more complex matter that required more than an understanding of time and effort. In their view, involvement without feeling engaged was simply compliance; students must feel an emotional connection to make meaning of their experience.

What are the Benefits of Engaging Students and Teachers?

Dewey (1938) defined the most powerful learning experiences as those that engaged the human mind in meaning-making. Dewey believed the most educative learning experiences allowed learners to solve problems and build understandings through interaction with the world around them. Although students were the primary concern of most researchers in the literature, Magolda (2005) contended they’re not the only ones to benefit from increased engagement in the learning process. The reciprocal environment constructed to engage learners fosters increased teacher engagement as well (Magolda, 2005). Although the literature is rarely focused on the benefits increased student engagement has on teachers (at any level), the benefits can be inferred. For example, increased faculty-student interaction resulted in greater job satisfaction (Bensimon & Dowd, 2009) and feelings of connectedness for faculty members (Kuh, 2009).

Although the benefits of incorporating student engagement practices are well documented in the literature, there is little to illustrate the consequences of disengagement beyond mere observation of what teachers may perceive as disengaged behaviors. Further, rarely have both student and teacher data been viewed simultaneously to understand the reciprocal nature of (dis)engagement in teaching and learning.

Purpose

This study is a snapshot of a larger study describing and comparing how and when experience engages students in the learning. Although this study was an unanticipated outcome the phenomena of teacher disengagement lends insight to challenges to teaching post-secondary courses in agriculture. Therefore, the purpose of this study was to illustrate or story the phenomena of teacher disengagement as an emergent etic perspective and consequence of implementing deep, prolonged instructional experiences in a post-secondary environment.

Research question: How can implementing deep, prolonged instructional experiences in a post-secondary environment affect student and teacher (dis)engagement?

Theoretical and Conceptual Framework

Shame Resilience Theory (SRT; Brown, 2006) provided structure to understand how individuals experience shame in high stakes environments. Brown’s theory, including the shame web depicted human interaction, specifically female in current research, can be explained best by understanding the variables associated with shame and the relationship between experiences with shame and performance standards. Initially, Social Cognitive Theory (SCT; Bandura, 1986) provided bounds for data collection; SCT allowed data to be categorized by the interaction between people, environment, and behavior. By viewing personal characteristics as reciprocally altered by behaviors and environments, researchers can view people as both creators and products of their experiences and understand the way individual thoughts and feelings affect the different ways people approach the world (Bandura, 1986). In providing detailed accounts of individuals’ personal experiences, researchers can view academic experiences with a more fluid set of expectations, including experiences with shame.

Originally, data collected during student and teacher reflections were framed using SCT (Bandura, 1986) in an attempt to categorize deep, prolonged instructional experiences in a post-secondary environment using personal and environmental determinants as stable concepts or variables. After analyzing the data, Shame Resilience Theory (Brown, 2006) proved to frame the data in a more descriptive and honest way, including additional variables for behaviors recorded in the original study. Admittedly, data from the original study proved more colorful when viewed in the context of SRT. The change from SCT (Bandura, 1986) to SRT (Brown, 2006) allowed for data to be analyzed in full context of the experience with greater understanding of the connection between variables associated with shame and performance expectations within a high stakes learning environment.

Method

This autoethnography was part of a larger study that spanned one calendar year—three academic semesters (spring, summer, and fall). Although the findings were focused on phenomena of teacher disengagement, the context of the course, activities, and students enrolled contributed to the findings. The larger inquiry included four cohorts with varying levels of deep, prolonged experience. Forty-two students (six male, 36 female), between 18 and 25 years of age, agreed to participate after enrolling in one of four sections of an undergraduate social science research methods course. Students represented four majors: agricultural leadership development, agricultural science, agricultural communications and journalism, and animal science.

When this study was conducted, I was a graduate student, and I co-taught the research course with my dissertation advisor and committee chair. Our students were involved as both participants and researchers. Specific learning objectives were aimed at developing students’ abilities to access information, think critically, and present and support reasoned arguments. However, students studied engagement by evaluating theories, collecting data from other populations, while also being introspective about their own engagement in the course.

Design

Although the larger study was an abductive, longitudinal, quasi-experiment the emergent etic perspective storied here was autoethnographic in nature. Autoethnography is a method of rigorous self-reflection and reflexivity that relies on the personal experiences of the researcher to describe and evaluate beliefs, practices, and experiences (Ellis & Bochner, 2006; Adams & Manning, 2015). By nature, “autoethnography is messy, uncertain, and emotional” (Adams et al., 2014, p. 19). The ability to use a research method to both accommodate for and acknowledge the difficult realities of social life helped make meaning of my experiences struggling within a larger hyper-structured research design.  

Sources of Data

Data were extracted from more than 200 hours of interviews, four cohorts, and six hours of class per week, additional research meetings, conversations, and informal interactions of unknown amounts of time, and six weeks of immersive field experience. Additionally, quantitative data were collected from four commercially available instruments and used as artifacts to further increase the credibility of findings through data triangulation (Lincoln & Guba, 1985). Although the findings presented in this study only include data from observations, reflexive journals, student-teacher dialogue, and countless hours of rigorous introspection, the influence other sources of data may have had on my interpretation cannot be untangled. 

The Human Instrument

Lincoln and Guba (1985) provided characteristics that “qualify the human being as the instrument of choice for naturalistic inquiry” (p. 193). Unlike most quantitative instruments, human beings are adaptable and “like a smart bomb, the human instrument can locate and strike a target without having been preprogrammed to do so” (Lincoln & Guba, 1985, pp. 193-194). As the primary instrument of data collection, I viewed this process from a nonlinear perspective, but had the flexibility to use quantitative artifacts as sources of data. Data, regardless of method or source, were used to mold, adapt, and continuously calibrate the human instrument.

Observations, Journals, & Dialogue

Observations were made before, during, and after each class and research meeting and during the entire field experience. As an active participant in the experience, I was able to capture interaction, be inductive, and observe behaviors beyond what students would divulge during an interview (Patton, 2015). Observations brought my own perceptions to light as well as the perceptions of students as recorded in their reflexive journals.

In addition to my own journal, the reciprocal nature of the larger study required my students keep reflexive journals to reflect critically on the “human as instrument” (Guba & Lincoln, 1981). Journals served as a reservoir for thoughts, feelings, observations, and field notes. Together, we chronicled the learning process while calibrating our instruments through self-discovery and interrogation (Lincoln et al., 2011). Journals provided insight to distinctive voices each of us brought to the classroom and led to a greater understanding of the multiple perspectives that framed the learning process (Alcoff & Potter, 2013).

Students engaged in a constant exchange of thoughts and ideas that served as both a source of data and method of learning. Specific attention was given to Socratic dialogue to help unlock implicit ways of thinking and insights not previously explored by the group (Given, 2008). Many times, our Socratic sessions would occur spontaneously outside of the bounds of class meetings and usually near a white board. Our concepts, models, and brainstorms were captured in photos to visually recall and interpret the experience along the way.

Trustworthiness of Findings

Lincoln and Guba (1985) outlined techniques for establishing trustworthiness to ensure findings are reached in a systematic and disciplined manner. Trustworthiness techniques mirror evaluation criteria found in quantitative research and provide increased “inspectability” of data and findings. I used multiple techniques to enhance trustworthiness of findings including prolonged engagement, persistent observation, triangulation, audit trail, peer-debriefing, member-checks, reflexivity, and thick, rich description. Extensive records (reflexive journals, sketchbooks, pictures of conceptual designs and models, and process and personal memos) were kept for confirmability and constant comparison of significant statements, codes, and emergent themes. A coding structure was used to ensure a detailed audit trail and is as follows:

Student data: Ex: 014_BR2_079

  1. Student participant code (01 – 042); 2) Source of data (BR = Black and Red journal, SB = Sketchbook); 3) Page number = (001 – 175)

Teacher data: Ex. FN_BR3_104

  1. Research activity (OBSV=Observation, FN = Fieldnote, RF = Reflection.); 2) Source of data (BR = Black and Red journal, SB = Sketchbook); 3) Page number = (001 – 175)
                           

Data Coding, Analysis, and Presentation

The task of understanding ethnographic data lies in the ability to condense mass amounts and sources of data (Merriam, 1998). I originally approached coding in a very inductive manner, using in vivo coding, descriptive codes, and deductive codes based on the framework of SCT (Miles et al., 2014). However, the use of SCT proved to hinder the analytic process when considering the reflexive nature of my own data. I continued with the coding process despite my frustrations; I inductively analyzed and coded data, developed additional codes to describe unexpected elements that emerged, and placed each into a matrix where they were continuously sorted into primary, secondary, and tertiary themes. It was not until much later that I discovered the process of analyzing data was not an exact science. Therefore, data were then viewed as analytic memos where I recorded additional elements of how the coding process took shape (Saldaña, 2016). The resulting findings were presented with student data alongside my own using verisimilitude—a literary strategy that captures the researchers’ thinking processes and attempts to realistically convey the intricacies of the experience with thick, rich description—thereby, enabling readers to reconstruct the experience for themselves (Creswell, 2009; Lincoln & Guba, 1985).

With consideration for my relationship to the data and the difficulty experienced during analysis, SRT (Brown, 2006) was introduced as an alternative to SCT and data were analyzed for evidence of emotive response, specifically shame. Shame data, in the context of high stakes learning environments, must be considered when studying unintended consequences of student-teacher (dis)engagement. In Shame Resilience Theory: A Grounded Theory Study on Women and Shame, Brown identified five main concerns of shame: what are the participants describing, what do they care about, what are they worried about, what are the participants trying to do, and what explains the different behaviors, thoughts, and actions (Brown, 2006, p. 44).

Findings

Words are Hard

Native Language 

I began this process in search of a way to make learning research more engaging. After considering various methods of classroom engagement, my teaching partner and I decided to forgo traditional teaching methods by avoiding the use of research terminology in class. Instead, we used common language so students might discover terms on their own and attach those words to experiences as they came about. For me, it was pretty easy to adhere to our native language because as a graduate student, research terminology was new to my everyday vocabulary. However, my partner had been using research jargon for eight years and the transition was difficult. Words are Hard quickly became a classroom hashtag and constant reminder to communicate in a way our students understand. 

Research as a Second Language 

The hashtag, #wordsarehard, became a fun “game” for our students. Our open and transparent process left very few things unsaid in our classroom, and students quickly caught on to the struggle we were experiencing with words. For students, myself included, research was a second language and “unlocking” new words was exciting… at first. For example, after observing other [University] students at various locations on campus, our students began to describe the various behaviors, environments, and personal characteristics they had observed. As one student wrote in his journal, “[Teacher] gets so excited when we figure things out. I need to Google Social Cognitive Theory” (07_BR1_014). My journal entry echoed their observation that day. FN_BR1_029: It’s working! It’s really working! #wordsarehard #proudteacher. I was motivated to provide them with experiences and attach terminology after they understood meaning. It seemed crazy, but research was becoming our second language and after years of learning terms just to pass a test, we were interested in how they became a permanent part of our vocabulary. 

Language Acquisition through Experience 

As time passed, words including “sample,” “instrument,” and “analysis” started to creep into our classroom discussions. Instead of discussing what might occur during an observation, interview, or face-to-face survey, students experienced issues first-hand and shared their successes and failures with our class. The chance to rifle through their experiences made it easier to share new terminology as we evaluated the process of understanding people. Although students seemed to be refreshed (or maybe just relieved) by the lack of terminology, a few also expressed a bit of confusion and annoyance with the process. One student was hesitant to speak up in class, but wrote “How is observing some people at the [student center] relevant to any kind of actual research” (013_BR1_018). Another student wrote, “Just give [the terms] to me. I know how to do research! I’m tired of waiting around for you to give me information” (06_BR1_027). I wanted to understand their point of view but was irritated with their impatience. After returning to interview and preliminary data, I saw the shared connection. Both students were double majors in animal science and predisposed to research in the basic sciences. In a way, they were ahead of the rest of the class (and always would be), but reflections provided more insight as each progressed. One wrote, “Observations seemed like useless collections of information. I now see it was the beginning of understanding a larger process” (013_BR1_018). 

Native Language Attrition 

Much to my surprise, as students gained efficacy with research terminology, I did too. Soon, my normal contributions to office banter were replaced with “what’s your unit of analysis,” and “what if we used a different conceptual framework?” I noted this transition after reflecting on time back home with friends. FN_BR3_062: When will I realize that not every lunch requires #researchtalk? I’m blabbering. THEY DO NOT CARE. Obnoxious! I found it only got worse as time went on. Research permeated my every interaction from my first cup of coffee in the morning to the text messages I sent before bed. Phone calls with my mom became more difficult and I could no longer explain to her what I had been up to. My “research buds” shared Piled Higher and Deeper (Ph.D.) comics on Facebook poking fun at the phenomena, but I had a hard time finding humor in our shared experience. FN_BR3_079: So much for being a great communicator! Might as well live under a rock. Because I had surrounded myself with peers in the same situation, the issue didn’t really become a problem until a new crop of students began the second phase of this study. Everything I prided myself on was slipping away.

FN_SB2_012: Why can’t I connect with them? I’m a teacher, damnit! Or am I? 🙁

Lost in Translation 

In almost an inability to remember what it was like to struggle with the research process, I found it more difficult to engage the final cohort of students like the first. FN_BR3_104: There’s a gap between cohorts that I don’t really understand quite yet. They are struggling. How do I make this better? I’m at a loss here. It seemed my newfound connection to research terminology and the process of doing research left it difficult for me to connect student learning to new experiences and new experiences to student learning. The first cohort seemed to embrace new terms because they were anxious to finally get them. They anticipated them. They wanted them. The second cohort, however, didn’t seem to make connections in the same way. In some cases, the words seemed to pass by the experiences as if students were simply going through the motions. More times than I would like to admit, students wrote things like, “is she even talking to me?” or “I’m over trying to understand this class.” It hurt, but they were right. I was speaking a foreign language and oblivious that my connection was lost somewhere in translation. In feeling loss of teaching and communication skills, I was forced to reflect on differences emerging in the data, specifically my own – I spiraled into web of shame (Brown, 2006).

Gut Punch: Cognitive Dissonance & Reciprocal Engagement

“How can you expect me (student) to be engaged when you (teacher) aren’t?” (16_BR1_064)

FN_BR2_084: Stop the bus. What did she just say? Are you kidding me?!

Owww

I have no recollection of what I said in response to [student] that day, but I was completely taken aback by her comment. We had intentionally built an environment where students could feel comfortable saying things like this, but I doubt my response was indicative of that effort. I was angry. FN_BR2_084: I’m giving everything I’ve got over here. Who do they think they are? I spent the next few hours sitting at my desk ruminating on the remark. I started to wonder if we had given students too much power and freedom in the classroom. FN_BR2_085: This is why structure is important. She would never say that to [faculty member]. My rant continued on the next two pages and finally subsided with a final thought.

FN_BR2_087: Oh, wait. I told her to do that.

Cognitive Dissonance

The original remark about my perceived level of engagement resonated in eleven other student journals (all but two students’ present) that day. Students began to question my general level of interest and motivation in the course. It was pivotal. I spent weeks (and months, really) thinking about how many times I teach students to do one thing, while modeling a completely different behavior. I also considered the times I observed this type of behavior from my own teachers and mentors. This insight became a magnifying glass, of sorts, and I began examining almost all of my interactions. Could something as simple as “walking the walk and talking the talk” be paramount to this study? FN_BR3_012: “Do as I say, not as I do.” Looks like Dad’s old mantra is coming back to haunt me.

Although my reflection may seem trivial, to me it was revelatory. This study was originally designed to understand students and the experiences that engage them in learning, but all the while, I may have been looking in the wrong direction. I literally told them (on the first day of class) I wanted to find a new way. I told them I believed engagement to be a two-way process and I wanted their open and honest feedback. Yet, there I was ignoring my own levels of engagement. Even more, I was wrought with fear that others (faculty, mentors, etc.) might discover my less than stellar performance and quietly ask me to pack my things. In retrospect, that was a silly thought, but the stakes seemed so high at the time and I was far from hitting the mark. She [student 16_BR1_064] provided the one piece of information that changed the way I considered this study, twelve little words that haunted my brain for months. It broke my spirit, but enlightened my path.

Autopilot: The Harsh Reality of (Dis)engagement

“You are different, beautifully so, and people will benefit from your perspective.

Your words mean something. This experience is teaching you far more than what can be observed – it’s teaching you to believe in you.” (06_SB1_003)

The excerpt (06_SB1_003), above, was written on a postcard and taped face down into the pages of a student’s sketchbook. I thumbed through several times, never giving them too much thought, but once the tape started to give way, this postcard flipped over. It was one of ten she planned to send as little reminders to herself when she arrived back home. Lucky for me, she forgot to send them, and that afternoon, I sat by myself, read through each one, and bawled my eyes out.

FN_BR2_114: I’m exhausted.

When teachers say, “I’m exhausted”, I don’t really believe that’s what they mean. I’m sure they are tired and may think they are exhausted, but what I really hear them saying is, “I’m not excited about what I’m doing right now.” When teachers are engaged, they ignore being tired; they’re in the zone and running on fumes of passion.

FN_BR2_115: I’m really exhausted.

I recognize the blatant contradiction here, but that doesn’t change the reality of its occurrence. Comments like the one above peppered my field notes during the last six months of this study. I was ashamed to write down thoughts like, “What am I doing?” or “I don’t want to be here,” so I didn’t, but they occurred nearly three times as much. There I said it. I was on autopilot.

The shame of thinking these things, let alone including them in this study, was paralyzing. The idea of being “called out” for a less than perfect study because Iwas a less than perfect teacher was more than my pride (and future career) could take. I felt like a big ole’ phony. Surely, I wasn’t the only one to ever feel this way, right? Right? Do you think anyone else knows?

When students say, “I’m exhausted”, I don’t really believe that’s what they mean. I’m sure they are tired and may think they are exhausted, but what I really hear them saying is, “I’m not excited about what I’m doing right now.” When students are engaged, they ignore being tired; they’re in the zone and running on fumes of passion.

“I’m exhausted” (38_BR1_071).

Huh? It was like some form of black magic. My students couldn’t possibly be experiencing the same thing. We’re different. They don’t know what I know. The rare occurrence of this finding in the literature made the connection between my data and my students’ data even more difficult to accept. I needed some reassurance. FN_BR3_099: HELP!! I give up. This is impossible.

Cold Hard Truth

This study took me down a long, circuitous path. Communicating the findings (on paper) has been a monumental task, but I have told this story (to anyone who would listen) every day since it began. I wrestled with my own experiences— both teaching and learning—at every turn. I questioned and resisted what I considered to be “conformity;” I’ve been angry, frustrated, and disenchanted; and I developed a pretty large chip on my shoulder, too. FN_BR3_047: How can I communicate this experience? How do I adequately portray my own disengagement? How do I describe how much I’ve changed? I don’t even feel like a teacher anymore. I’ll never get a job after this.

To this point, the “pieces” or themes were like vignettes that lined the walls of my heart and mind for months, but they remained static without understanding the experience more holistically. The fact is, “words are hard”—hard to articulate, difficult to write, painful to digest, and often lost without the ones around them. The larger study began with specific research questions concerning the influences of experience on student engagement, however, “the path of discovery is not clearly marked, nor should it be” (Thorp, 2001, p. 37). I could have easily described student engagement throughout the entire study, outlined findings of the hyper-focused quasi-experimental design I set out to follow, and provided more direction for others to build on for the future, however, that would have alienated the most glaring pieces of data—my own. Identifying and addressing my experience within a high stakes learning environment provided insight into the concept of shame resilience. In addressing my own professional and personal experience with shame, I moved forward while highlighting what seems to be an emerging reality in high stakes academic environments – honest data reporting. In sharing this data, my feelings of powerlessness and isolation decreased when I invited others in. After letting go of the many ways this piece might be perceived and how that perception might affect my future career, I created more experiences with empathy, connection, power, and freedom than I could have ever expected (Brown, 2006).

Discussion

As the case with most naturalistic inquiry, the purpose of this study was not to infer to a larger population. Rather, the intent was to understand an unanticipated and, arguably, unfortunate phenomena: Teacher disengagement. Not only is the literature describing this phenomenon vague, it may be nonexistent. While teacher engagement is critical for the learning process, student expectations seem to be the immediate point of discussion. It’s important to mention the relationship between expectations and engagement – if expectations for learning or instruction are not met engagement will suffer for both teacher and student (Majkowski & Washor, 2014).

Experience was noted in no less than five of the seven research priority areas of the National Research Agenda (Roberts et al., 2016). Further, the history of, need for, and value of integration of experience into agricultural education environments was thoroughly noted by Baker, Robinson, and Kolb (2012). Despite the expansive number of researchers who have recommended integrating experiences into the educational environment, few have noted many of the potential unintended consequences of implementing deep, prolonged instructional experiences in a post-secondary environment. The occurrence of these consequences is not likely a new phenomenon. Yet, the implications of presenting ugly data or the unintended consequences of a study are not widely present in the agricultural education literature. Therefore, several elements should be investigated and considered by future studies:

Issues with Unrealizable Objectivity

Although it may seem as if I abandoned the design of this study somewhere along the way, that is not entirely the case. The design was like a too-tight sweater, uncomfortable but difficult to throw away. The truth is I became so focused on design that I had a difficult time connecting with the most important and significant part of my study: my students. It was important for me to tell that story, to illustrate the ways in which this study changed because I changed and allow the reader to come to conclusions on their own. Ignoring the growing pains would have omitted the difficult truths of an unrealizable objectivity – something I’m afraid is all too common in our research, but rarely explored. Reflecting on the power of vulnerability within the context of shame helped untangle this phenomenon; speaking shame is a pivotal opportunity for increased personal understanding and the development of personal and professional strategies for resilience (Brown, 2006). My attachment to design, and the research process for that matter, made it difficult for me to engage in the very environment I created. My quest to understand the complex nature of people and social interaction was beset by my transition from teacher to researcher. I was no longer the responsive and adaptable educator, but instead a rigid and design-focused researcher. I experienced the shame of foregoing a past pattern of thought by adopting the accepted norms of my high stakes environment, both losing and acquiring skillsets along the way.

Meaningful Connection in High Stakes Learning Environments

The process of learning new information is only engaging for so long without a personal connection between teachers and students. Harper and Quaye (2009) argued student engagement required more than an understanding of the teacher’s time and effort. The findings of this study provide evidence to support the influence of time and effort, but also raise questions of where that time and effort should be placed for effective learning. In this case, I placed the most time and effort on the process of conducting research instead of the people involved. I lost the connection with students when I stopped being responsive to their needs. There was no meaningful emotional connection to help make students connect to their learning experience, thus altering the overall learning environment. My commitment to people, to teaching people was ignored in my attempt to produce high quality research (Brown, 2006).

Might the high-stakes environments discussed by the National Research Council (1999) be to blame for the unintended consequences of disengagement by both students and teachers? Could the pressures of producing high quality research discourage teacher-researchers from improving instruction to engage students? Or is it simply the nature of research to become detached when adhering to focused and structured designs? Future research should consider the environmental and internal factors associated with faculty and graduate student expectations as it relates to student and teacher (dis)engagement in higher education; specifically, experiences with shame in academia and willingness to report honest data. Social scientists should consider moral and ethical implications of such, especially when expressing the realities of praxis in teaching and learning.

Connection Between Student & Teacher Experience

Often times, research considers the issues of student engagement independently from teacher engagement, providing a host of strategies to foster a better learning environment. However, rarely are variables considered side-by-side in a more holistic way. In doing so, it may be easier to notice the behaviors exhibited by students are not all that different from their teachers. Future research may benefit from observing engagement as a more universal phenomenon affecting teacher and student behavior similarly. Mojkowski and Washor (2014) contend student disengagement to be a deeper issue than previously believed. Student expectations are driving disengagement concerns. Students are struggling to fit into restrictive academic environments; therefore, a shift is necessary to focus on sustained engagement practices: relationships, challenge, play, relevance, authenticity, practice, choice, application, time, and timing (pg. 9).

The Problem with Theories

Although SCT was not the guiding force of this study, it served as a point of reference when considering factors of teaching and learning. At a granular level, factors suggested to change engagement were easy to understand, but the bigger challenge required I consider the way each and every interaction changed the next. It was a sequence of interactions, changes, and behaviors too large for me to see alone and the belief that a simple formula might uncover one solution was short-sighted. The simplification was intended to guide understanding, but a more complex analysis was needed. Literature identified SRT (Brown, 2006) as a means to shorten gaps of understanding and widen perspectives. SCT provided firm bounds for the study to begin while SRT provided a fluid construct for the data to exist.

The static and predictable nature of theories may lead people (especially young researchers) to believe the findings of this study (or any study for that matter) are merely formulaic in that the same person, doing the same thing, in the same way would provide the same answer every time. However, formulas are rigid and conventional, and albeit mathematical, function as a way to solve problems–human or otherwise. The sheer number of variables needed to consider the dynamic interaction between students and teachers during the process of learning is overwhelming, but should be considered, nonetheless. Might some teachers be restricted when conceptualizing teaching and learning as a formulaic process?

I contend student and teacher engagement, and thus, (dis)engagement to be more of a complex algorithm that adapts and changes. Although key “formulas” may make up an engagement algorithm, those formulas, the way they are arranged, and the many ways in which they change is more complex than what I could understand during the course of this study. Understanding the way this study emerged and the gravitational-type pull environment played in our findings would be too complex of a task without the consideration of a larger, adaptable algorithm. Future research should consider student and teacher (dis)engagement as an algorithm that stretches and changes in new, more dynamic ways. One potential method of inquiry is an algorithm based in SRT. Establishing a conceptual algorithm based on SRT may provide context for evaluating teachers in a complete emotional, social, and mental context. Understanding engagement with students and teachers demands an adaptable framework for teaching and learning.

New Methods in Agricultural Education

Ok. Hear me out. Many of the struggles of this study and my ability to adequately describe my experience may lie in our professions level of discomfort with more uncommonly used methods. As a graduate student, I worked alongside my mentors to develop a quasi-experimental study to “increase the rigor” associated with Agricultural Education research in the social sciences. All the while, this design held me back from truly understanding the phenomena at play. I struggled. I sought out additional qualitative methods, but rarely saw those methods in the pages of our journals. It seemed (to me) that I must adhere to a more structured design if I wanted to succeed. Might young researchers be hindered by our collective distaste for new methods? How can we mentor young researchers in rigorous methods spanning paradigms? What does the future of Agricultural Education (broadly defined) look like when young and old researchers alike struggle with making sense of a too tight and seemingly sterile science in a socially constructed discipline? Could the introduction of theories similar to the open-ended study of shame resilience provide a greater insight into teacher-student experiences? How do we help? Help.

References

Adams, T. E., Jones, S., & Ellis, C. (2014). Autoethnography: Understanding qualitative research. Oxford University Press.

Adams, T. E., & Manning, J. (2015). Autoethnography and family research. Journal of Family    Theory & Review7(4), 350–366. https://doi.org/10.1111/jftr.12116

Alcoff, L., & Potter, E. (Eds.). (2013). Feminist epistemologies. Routledge. https://doi.org/10.4324/9780203760093

Bain, K. (2004). What the best college teachers do. Harvard University Press.

Baker, M. A., Robinson, J. S., & Kolb, D. A. (2012). Aligning Kolb’s experiential learning theory with a comprehensive agricultural education model. Journal of Agricultural Education, 53(4), 1-16. https://doi.org/10.5032/jae.2012.04001

Bandura, A. (1986). Social foundations of thought and action: A social cognitive theory. Prentice-Hall. 

Bensimon, E. M., & Dowd, A. (2009). Dimensions of the transfer choice gap: Experiences of Latina and Latino students who navigated transfer pathways. Harvard Educational Review79(4), 632–659. https://doi.org/10.17763/haer.79.4.05w66u23662k1444

Brown, B. (2006). Shame resilience theory: A grounded theory study on women and shame. Journal of Contemporary Social Services, 87(1), 43–52. https://journals.sagepub.com/doi/pdf/10.1606/1044-3894.3483

Chickering, A. W., & Gamson, Z. F. (1987). Seven principles for good practice in undergraduate education. AAHE Bulletin, 39(7), 3–7. https://files.eric.ed.gov/fulltext/ED282491.pdf

Coates, H. (2007). A model of online and general campus-based student engagement. Assessment and Evaluation in Higher Education, 32(2), 121–141. https://doi.org/10.1080/02602930600801878

Creswell, J. W. (2009). Research design: Qualitative, quantitative, and mixed methods approaches. Sage. http://fe.unj.ac.id/wp-content/uploads/2019/08/Research-Design_Qualitative-Quantitative-and-Mixed-Methods-Approaches.pdf

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

Edgar, D. W., Retallick, M. S., & Jones, D. (2016). Research priority 4: Meaningful, engaged learning in all environments. In T. G. Roberts, A. Harder, & M. T. Brashears (Eds.), American Association for Agricultural Education national research agenda: 2016-2020 (pp. 37–40). Department of Agricultural Education and Communication. http://aaaeonline.org/resources/Documents/AAAE_National_Research_Agenda_2016-2020.pdf

Ellis, C. S., & Bochner, A. P. (2006). Analyzing analytic autoethnography: An autopsy. Journal of Contemporary Ethnography35(4), 429–449. https://doi.org/10.1177/0891241606286979

Given, L. M. (Ed.). (2008). The Sage encyclopedia of qualitative research methods. Sage Publications.

Guba, E. G. & Lincoln, Y. S. (1981). Effective evaluation: Improving the usefulness of evaluation results through responsive and naturalistic approaches. Jossey-Bass.

Harper, S. R., & Quaye, S. J. (2009). Beyond sameness, with engagement and outcomes for all: An introduction. In S. R. Harper & S. J. Quaye (Eds.), Student engagement in higher education (1-15). Routledge.

Hu, S., & Kuh, G. D. (2001, April 10-14). Being (dis)engaged in educationally purposeful activities: The influences of student and institutional characteristics [Paper presentation]. American Educational Research Association Annual Conference, Seattle, WA, United States. https://files.eric.ed.gov/fulltext/ED452776.pdf

Johnson, D. W., Johnson, R. T., & Smith, K. A. (1991). Cooperative learning: Increasing college faculty instruction productivity. ASHE-ERIC Higher Education Report No. 4. The George Washington University, School of Education and Human Development. https://files.eric.ed.gov/fulltext/ED343465.pdf

Krause, K. & Coates, H. (2008). Students’ engagement in first-year university. Assessment and Evaluation in Higher Education, 33(5), 493-505. https://doi.org/10.1080/02602930701698892

Kuh, G. D. (2009). The national survey of student engagement: Conceptual and empirical foundations. New Directions for Institutional Research, No. 141, 5–20. https://doi.org/10.1002/ir.283

Lincoln, Y. S., & Guba, E. G. (1985). Naturalistic inquiry. Sage. 

Lincoln, Y. S., Lynham, S. A., & Guba, E. G. (2011). Paradigmatic controversies, contradictions, and emerging confluences, revisited. In N. K. Denzin & Y. S. Lincoln (Eds.), The Sage handbook of qualitative research (4th ed., pp. 97–128). SAGE.

Magolda, P. M. (2005). Proceed with caution: Uncommon wisdom about academic and student affairs partnerships. About Campus, 9(6), 16–21. https://doi.org/10.1002/abc.113

Merriam, S. B. (1998). Qualitative research and case study applications in education. Jossey-Bass. 

Miles, M. B., Huberman, A. M., & Saldaña, J. (2014). Qualitative data analysis: A methods Sourcebook (3rd ed.). Sage.

Mojkowshi, C. & Washor, E. (2014). Student disengagement: It’s deeper than you think. The Phi Delta Kappan, 95(8), 8–10. https://kappanonline.org/student-disengagement-dropout-washor-mojkowski/

National Research Council. (1999). High stakes: Testing for tracking, promotion, and graduation. The National Academies Press. https://doi.org/10.17226/6336

National Research Council. (2009). Transforming agricultural education for a changing world.

National Academies Press. https://doi.org/10.17226/12602

Patton, M. Q. (2015). Qualitative research and evaluation methods (4th ed.). SAGE. 

Piaget, J. (1976). Piaget’s theory. In B. Inhelder, H. H. Chipman, & C. Zwingmann (Eds.), Piaget and his school (pp. 11-23). Springer-Verlag. https://doi.org/10.1007/978-3-642-46323-5_2

Roberts, T. G., Harder, A., & Brashears, M. T. (Eds). (2016). American Association for Agricultural Education national research agenda: 2016-2020. Department of Agricultural Education and Communication. http://aaaeonline.org/resources/Documents/AAAE_National_Research_Agenda_2016-2020.pdf

Saldana, J. (2016). The coding manual for qualitative researchers (3rd ed.). SAGE.

Sheldon, K.M. & Biddle, B.J. (1998). Standards, accountability, and school reform: Perils and pitfalls. Teachers College Record, 100(1), 164–180. https://www.tcrecord.org/Content.asp?ContentId=10304

Sorathia, K., & Servidio, R. (2012). Learning and experience: Teaching tangible interaction & edutainment. Procedia-Social and Behavioral Sciences, 64, 265–274. https://doi.org/10.1016/j.sbspro.2012.11.031

Thorp, L. G. (2001). The pull of the earth: An ethnographic study of an elementary school garden (Doctoral dissertation). Texas A&M University, College Station, Texas. https://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.1075.2874&rep=rep1&type=pdf

Reconceptualizing Problem-Solving: Applications for the Delivery of Agricultural Education’s Comprehensive, Three-Circle Model in the 21st Century

Whitney Figland, Dutchtown High School, whitney.figland@apsb.org

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

J. Joey Blackburn, Louisiana State University, jjblackburn@lsu.edu

PDF Available

Abstract

Problem-solving has been an integral tenet of school-based, agricultural education (SBAE) since its inception. However, in many ways, the pedagogy has changed considerably. This shift appears to have caused problem-solving’s pedagogical dimensions and underlying philosophical foundation to become conflated with other methods of instruction. Consequently, fundamental questions persist:“Should problem-solving be practiced as a distinct pedagogy?” And if so, “What implications exist for its use in SBAE?” In response, this philosophical study sought to examine perspectives on problem-solving and explain how it has been advanced in the discipline. A product of this investigation was the emergence of three principles that appear to be foundational to problem-solving: (1) identify problems, (2) analyze information, and (3) evaluate solutions. Distinguishing such principles helped describe how problem-solving has been operationalized historically. However, it also revealed a need to expand its current understanding and use. In response, we proposed the Integrated Problem-Solving Model for Agricultural Education to illuminate how it could be reconceptualized as a guiding philosophy for SBAE to better navigate increasingly complex issues and problems in the 21stCentury.

Introduction

Over the past few decades, a variety of instructional methods have been advanced in education to encourage students to obtain the skills they need to thrive in the 21stCentury (Koichu, 2019; Ulmer & Torres, 2007). However, more recently, it has become critical for educators to adopt methods of instruction that encourage students to develop higher-order thinking skills (Fuhrmann & Grasha, 1983; Jonassen, 2000; Ulmer & Torres, 2007). One explanation for this shift is that employers often view the ability to solve problems, a higher-order skill, as essential in the workplace (Gokhale, 1995; Robles, 2012; Zimmerman & Risemberg, 1997). Nevertheless, many students are not challenged to engage in real-world problems in their schooling (Jonassen, 2000). Instead, they learn through rote memorization and other forms of direct instruction in which the instructor passively transfers knowledge – an approach that does little to prepare students for a successful career (Jonassen, 2000). As a consequence, a need has emerged to embed more opportunities for students to authentically engage in problem-based experiences that accurately reflect the world in which they operate. Previous research has demonstrated that engaging students in learning activities that challenge their problem-solving abilities can foster metacognitive growth, i.e., the ability to reflect on learning and modify one’s behavior accordingly (Sproull, 2001). For example, through the use of such an approach, students learn to grapple with problems, from simple to complex, by developing solutions that complement the knowledge and skills they developed through their coursework (Jonassen, 2000).

From a historical perspective, the problem-solving approach can be traced to classical philosophers such as Socrates and Plato, who believed that individuals came to truth by socially constructing meaning through participation in debates (Phillips, 2010). For example, The Socratic Method draws on cooperative dialogue in which individuals answer questions that stir new thoughts and ideas about the nature of knowledge and knowing (Phillips, 2010). This early approach to problem-solving appeared to serve as a basis for contemporary views on the method and helped further distinguish it as a pedagogy (Dewey, 1910; Phillips, 2010). Using this foundation, John Dewey (1910) further concretized the key dimensions of problem-solving. For instance, in Dewey’s (1910) How We Think, he outlined five tenets called the Complete Action of Thought or Reflective Thinking that included: (1) a felt difficulty; (2) location and definition of a problem; (3) creation of possible solutions; (4) test solutions; and (5) further explorations and evaluation. These processes provided a basis for conceptualizing problem-solving as a process that could be used to mature students’ intellectual development and critical thinking (Dewey, 1910). However, Dewey never used the term problem-solving in his academic work.

Despite this, Dewey, along with other educational philosophers, paved the way for problem-solving to be recognized and practiced as a pedagogy in the 20thCentury (Moore & Moore, 1984). However, discourse on problem-solving has been muddled by the introduction of terms, such as problem-based learning (PBL) and inquiry-based instruction (IBI), that although are distinct in form and function also appear to exhibit striking “pedagogical congruence” (Parr & Edwards, 2004, p. 104). As a result, a definition for problem-solving does not appear to have reached consensus. Some disciplines have responded to this issue by crafting descriptions of the pedagogy that integrate the various perspectives of philosophers, researchers, and practitioners (Crunkilton & Krebs, 1967; Jonassen, 2000; Merwin, 1977). The definition of problem-solving, therefore, varies considerably among academic disciplines. For example, in technology education, Merwin (1977) defined problem-solving as “a sequence of procedures in the thinking process that a learner employs in dealing with a problem or task” (p. 123). Jonassen (2000) added that problem-solving could also allow students to “find [answers to] the unknown.” (p. 65). In agricultural education, however, Crunkilton and Krebs (1967) defined problem-solving “as a method of teaching in which the teacher guides the class through a series of questions. . .” (p. 90). Because of such variant depictions, therefore, problem-solving’s philosophical and operational tenets remain unclear.

Nevertheless, the pedagogy appears to have been considered an integral tenet of school-based, agricultural education (SBAE). For example, the use of the pedagogy emerged in SBAE in concert with the Smith-Hughes Act of 1917 (Moore & Moore, 1984). During this period, the U.S. experienced an industrial revolution, which shifted education and catalyzed reform efforts (Roberts, 1957; Roberts & Ball, 2009; Talbert et al., 2007). This shift also piqued national interest in the enhancement of skilled laborers (Roberts & Ball, 2009). Because of these changes in U.S. society, it is believed that problem-solving became diffused as a method of instruction in SBAE (Moore & Moore, 1984) and experienced more widespread adoption (Boone, 1990; Cano & Martinez, 1991; Crunkilton & Krebs, 1967; Dyer & Osborne, 1996; Flowers & Osborne, 1988; Hammonds, 1950; Krebs, 1967; Newcomb et al., 1993; Phipps & Osborne, 1988; Torres & Cano, 1995a; Torres & Cano, 1995b). However, problem-solving has been described, represented, and depicted in a variety of ways throughout its rich history in SBAE. Such variances were made explicitly clear in submissions that described problem-solving in The Agricultural Education Magazine (The Magazine).

For example, as evinced in The Magazine, problem-solving’s use in SBAE emerged in the mid 20th Century (Hammonds, 1950; Krebs, 1967). However, in many ways, the pedagogy, and other methods of instruction, have evolved considerably in the early 21st Century as practitioners responded to key shifts in American society (Roberts & Edwards, 2015, 2018). In particular, in the early 2000s, the enactment of No Child Left Behind (NCLB) created a turning point in U.S. education policy that resulted in wide-sweeping reform efforts, which required states to adopt learning standards and assessments to monitor better and track students’ progress, especially regarding mathematics, reading, and science (U.S. Department of Education, 2001). Such changes also largely influenced approaches to teaching and learning that were depicted in The Magazine. For instance, contributors published articles on learning approaches that featured: (a) PBL, (b) IBI, and (c) experiential learning that focused on applications of science, technology, engineering, and mathematics (STEM) (Retallick & Miller, 2005; Torres & Cano, 2005a).

Although such work was pivotal to positioning SBAE as relevant, during this period, problem-solving’s pedagogical dimensions and underlying philosophical foundation also appeared to become blurred and conflated with other teaching and learning approaches. As a consequence, a dichotomy emerged in which some practitioners began to represent problem-solving as a distinct method of instruction, while others articulated it as an approach that was largely synonymous with other pedagogies (Parr & Edwards, 2004). Because of these discrepancies in the problem-solving literature, a lack of clarity exists in SBAE regarding how problem-solving should be delivered conceptually. To complicate this issue further, however, early literature in SBAE (Crunkilton & Krebs, 1967; Moore & Moore, 1984) on problem-solving argued it lacked a solid theoretical foundation and should be approached with caution when used as a method of instruction. As a consequence, two questions persist: “Should problem-solving be practiced as a distinct pedagogical approach? And if so, “What implications exist for using problem-solving in the 21stCentury and beyond?” These questions motivated the current study.

Purpose

To address this issue, the purpose of this philosophical investigation was threefold: (1) describe existing perspectives and theories on problem-solving; (2) explain how problem-solving has been used as a method of instruction in SBAE; and (3) illuminate how the problem-solving could be reconceptualized to enrich the delivery of SBAE’s comprehensive, three-circle model. This research aligns with the American Association for Agricultural Education’s National Research Agenda Research Priority 7: Addressing Complex Problems. Specifically, this research addresses question one, “What methods, models, and programs are effective in preparing people to solve complex problems, interdisciplinary problems?”(Andenoro, Baker, Stedman, & Pennington, Weeks, 2016, p. 59).

Methods and Procedures

Philosophical research seeks to analyze existing axioms and beliefs in a given domain (Roberts & Edwards, 2020; Salevouris & Furay, 2015). This study, therefore, synthesized educational theories and perspectives from prominent problem-solving advocates, while also advancing new understandings for SBAE. From a philosophical perspective, problem-solving aligns with the worldview of pragmatism, which advances the belief that individuals construct meaning from their experiences as they interact with others and navigate issues and problems in a real-world context (Crotty, 1998). To meet the study’s purpose, we synthesized theoretical and practitioner-oriented work as well as empirical evidence supporting problem-solving through the use of the following sources: (a) books, (b) peer-reviewed journal articles, and (c) The Agricultural Education Magazine.

All references were subjected to internal and external criticisms to triangulate our findings (Salevouris & Furay, 2015). For instance, we evaluated each source for authenticity concerning its origin and content (Salevouris & Furay, 2015). Further, we analyzed how the investigation’s (a) findings, (b) conclusions, (c) implications, and (d) recommendations might provide inferences for future work. To accomplish this, we used a conceptual mapping technique in which we scrutinized each source’s existing similarities and discrepancies (Salevouris & Furay, 2015). For example, through mapping, we revealed each source’s interconnectedness and congruence with the study’s purpose (Salevouris & Furay, 2015). As a result, we developed key empirical assertions through the use of an analytic memoing technique (Saldaña, 2015). Then, we synthesized our findings by weaving our assertions into a narrative that described how problem-solving could be reimagined to deliver agricultural education’s comprehensive, three-circle model in transformative new ways.

Perspectives and Theories on Problem-Solving

Through our analysis, six leading perspectives – John Dewey, Rufus Stimson, Werrett Charters, William Lancelot, John Bransford, and Scott Johnson – on problem-solving appeared to most prominently shape existing thought and use of the pedagogy in SBAE as well as in teaching and learning more broadly. Our description of each perspective is provided next.

John Dewey

John Dewey largely gained prominence as a thought leader as a result of his time at the University of Chicago after creating a progressive school, called the Dewey Laboratory School, that he used to foment his philosophy and theory on experience and education (Dewey, 1910, 1938). Dewey believed that students should be viewed as active pursuers of knowledge that lived, worked, and interacted in the world as a social being (Hyland, 1993). Dewey was also a strong advocate for students actively engaging in experiences that were based on real-world issues and problems (Dewey, 1938). In particular, Dewey maintained that teaching students to think and solve problems was integral to creating successful members of society (Dewey, 1910). Further, Dewey (1910) detailed in How We Think his five-step model for reflective thinking. Dewey’s five axioms for reflective thinking included: (a) felt difficulty, (b) location and definition of the problem, (c) creation of solutions, (d) development of reasons for solutions, and (e) further exploration and evaluation (Dewey, 1910).

Rufus Stimson

Rufus Stimson has also been identified as a pivotal early leader to agricultural education in the U.S. (Moore, 1988, 2018). Perhaps, his most significant contribution to the discipline was the formalization of the project-based method, which is now recognized as the Supervised Agricultural Experience (SAE) component of agricultural education’s comprehensive, three-circle model (Camp & Crunkilton, 1985; Foor & Connors, 2010; Moore, 1988). Although Stimson (1911, 1919) did not use the term problem-solving, many of the core features of the project-based method, align naturally with the pedagogy. For example, Stimson (1911) advanced three major projects relevant for farm work: (1) improvement, (2) experimental, and (3) productive. In his description of project types, Stimson (1919) explained that each would require students to identify relevant problems, collect evidence, and design a strategy to respond to each unique issue or problem. Such work also deeply influenced his protégé Werrett Charters.

Werrett W. Charters

Werrett Charters was a student of Dewey for three years at the University of Chicago. It is because of this experience that Charters is often recognized as a disciple of Dewey and a proponent of his philosophy and beliefs on teaching and learning. However, he also made pivotal advancements to problem-solving in his own right. For instance, in Charters’ works Methods of Teaching and Teaching (1912) and Teaching the Common Branches (1924) he emphasized the importance of having students solve real-world problems that piqued their interest and motivated them to be actively engaged in the learning process (Charters, 1912, 1924). Similar to Dewey’s (1910) reflective thinking model, Charters advanced both inductive and deductive reasoning (Charters, 1924). However, Charters also theorized that inductive thinking processes could help propel students’ deductive thinking as they work through contextualized problems, form hypotheses, and arrive at concrete solutions (Charters, 1912). As a result, Charters (1924) advanced three stages of problem-solving: (a) definition of the problem, (b) creation of a hypothesis, and (c) testing and verifying the solution. Such advancements appear to have profoundly influenced how problem-solving was operationalized in its formative years in SBAE.

William Lancelot

William Lancelot was another early proponent of problem-solving in SBAE. Lancelot received his bachelor’s degree in agricultural education in 1919 and shortly after pursued his master’s degree in education at Columbia University. During his graduate studies, Lancelot was introduced to the works of Dewey and Charters, which greatly influenced by his views on education and society (Lancelot, 1944). As a result, Lancelot advocated for transitioning education from a rote memorization model to one that closely mirrors problem-solving (Lancelot, 1944). In his book Permanent Learning (1944), he described different types of problems that students may encounter during their educational experiences, how to use such problems productively, ways to integrate problems across contexts, and the uses of the problem-solving in regard to teaching and learning. Further, Lancelot (1944) conceptualized 10 steps that educators could use to implement problem-solving as a pedagogy. Similar to Dewey and Charters, Lancelot also articulated the role of inductive and deductive reasoning. Because of his deep connection to SBAE, his work appeared to influence the discipline profoundly. However, in the proceeding decades, other prominent educational leaders influenced SBAE as well.

John D. Bransford

John Bransford was an educational psychologist at the University of Washington who authored several critical works regarding cognition, learning styles, and teaching. For example, in Bransford’s and Stein’s (1984) The IDEAL Problem Solver, he introduced an approach to problem-solving that encompassed the ideas and theories of several key theorists such as Kolb (1984), Newell and Simon (1972), and Sterberg (1981). The IDEAL problem-solving model also drew on concepts from the Socratic method, the scientific method, and John Dewey’s reflective thinking model (Phipps, Osborne, Dyer, & Ball, 2008). In particular, the IDEAL problem-solving model largely reconceptualized Dewey’s reflective thinking model using the following processes: (a) identify problems and opportunities, (b) develop goals, (c) explore possible strategies, (d) anticipate outcomes, and (e) look back. It is critical to note that in the IDEAL problem-solving model, each step is fluid and may not unfold successively (Bransford & Stein, 1984). Figure 1 depicts Bransford’s and Stein’s (1984) IDEAL problem-solving model.

Figure 1

Bransford’s and Stein’s (1984) IDEAL Problem-Solving Model

Note. Adapted from “The Influence of Cognitive Diversity on Group Problem-solving Strategy” by A. J. Lamm, C. W. Shoulders, G. T. Roberts, T. A. Irani, L. J. Snyder, and J. Brendemuhl, 2012, Journal of Agricultural Education, 53(1), p. 19. Copyright 2012 by Journal of Agricultural Education. Reprinted with permission.

Scott Johnson

Anothervein of literature that has greatly influenced problem-solving theory and practice is troubleshooting. And, perhaps, the individual that has most profoundly advanced thought on troubleshooting is Scott Johnson. For example, Johnson’s (1989) technical troubleshooting model provided conceptual guidance for practitioners to support students as they navigate complex curricular problems. In the first phase of the model, students collect and interpret information through two primary sources: (1) procedural knowledge, and (2) external sources (Johnson, 1991). Procedural knowledge refers to an individual’s understandings that result from processes such as reading diagrams, using mathematical formulas, and understanding manuals (Johnson, 1989). Meanwhile, external sources of information typically originate from the knowledge that individuals glean from jobs, technical support, and evaluations (Johnson, 1989). Of note, both sources of knowledge help troubleshooters form a more concrete understanding of the problem (Johnson, 1991). Based on Johnson’s (1989) model, after individuals acquire information from the aforementioned sources, they enter an interpretation phase (Johnson, 1991). This step is critical because troubleshooters must identify which concepts are relevant based on their prior learning and experiences (Johnson, 1989). If enough information has been gathered, then the troubleshooter can then move into the hypothesis generation phase. During this step, individuals generate one or more hypotheses about the problem (Elstein et al., 1978; Frederiksen, 1984; Johnson, 1989). After the hypothesis generation phase, troubleshooters evaluate their results, which allows the troubleshooter to test their hypotheses and determine whether it should be accepted or rejected (Johnson, 1991). If the troubleshooter did not solve the problem, they restart the process, as depicted in Figure 2 (Johnson, 1991).

Figure 2

Troubleshooting Model

Note. Adapted from “A description of expert and novice performance differences on technical troubleshooting tasks” by S.D. Johnson, 1989, Journal of Industrial Teacher Education, 26(3), p. 20. Copyright 1989 by Journal of Industrial Teacher Education. Reprinted with permission.

Problem-Solving’s Use in SBAE

In addition to being articulated by leading educational theorist, problem-solving has also been advanced in SBAE since its early inception as a way to facilitate authentic learning for students (Moore & Moore, 1984; Parr & Edwards, 2004; Retallick & Miller, 2005; Torres & Cano, 2005b). As an illustration, Phipps and Cook (1956) advanced Dewey’s (1910) stages of problem-solving by contextualizing the pedagogy using examples in agriculture. Later, Crunkilton and Krebs (1967) introduced five key phases to consider when using the problem-solving in SBAE. Those phases included: (a) interest approach; (b) create objectives; (c) anticipate problems; (d) solve the problem; (e) evaluate and apply (Crunkilton & Krebs, 1967).

Further, Phipps and Osborne (1988) described their views on problem-solving in The Handbook on Agricultural Education in Public Schools. Phipps and Osborne’s (1988) approach included similar elements outlined in previous works on problem-solving. For instance, their six-step method included: (a) experience a situation, (b) locate and define the problem, (c) attempt a trial solution, (d) explore reference and information, (e) arrive at a group solution, and (f) evaluate. Finally, Newcomb et al. (1993) addressed problem-solving in Methods of Teaching Agriculture, which appears to be one of the most recent attempts to outline the pedagogy for SBAE. In this work, the problem-solving method to teaching and learning is outlined in six steps, which were grounded in the previously reported literature. Those six steps to teaching the problem-solving approach in agricultural education included: (a) interest approach, (b) objectives to be achieved, (c) problems to be solved or answered, (d) problem solution, (e) test solutions through application, and (f) evaluate solutions (Newcomb et al., 1993). Therefore, through our analysis, it appeared that leading perspectives on problem-solving and prominent literature in SBAE demonstrated significant “pedagogical congruence” (Parr & Edwards, 2004, p. 104). As a consequence, a synthesis of these concepts was warranted to advance thought on problem-solving for SBAE.

Synthesis: Advancing the Shared Principles of Problem-Solving

To advance new understandings, we distilled shared principles from the leading perspectives on problem-solving and the SBAE literature. To accomplish this, we grounded our approach in a concept known as consilience, first introduced by William Whewell (1840). Consilience represents the merging of stands of knowledge from various disciplines, perspectives, and domains to offer new understandings of a phenomenon (Whewell, 1840). Using this approach, we engaged in a mapping technique to visualize each perspective’s similarities and discrepancies while also acknowledging that some authors might not have specifically used the term problem-solving but in essence were describing a similar concept. A product of this procedure was the emergence of three shared principles that appear to be foundational to existing descriptions and representations of problem-solving as a pedagogy. To promote understanding, we chose to represent the shared principles using practical language in hopes that practitioners, researchers, and theorists alike might find them useful. Given such caveats, we offer the three principles of problem-solving that emerged from our analysis: (1) identify problems, (2) analyze information, and (3) evaluate solutions.

Principle #1: Identify Problems

A fundamental characteristic of problem-solving is ensuring that students have the knowledge and skills they need to identify relevant problems (Bransford & Stein, 1984; Crunkilton & Krebs, 1967; Dewey, 1910, 1938; Charters, 1912, 1924; Lancelot, 1944; Newcomb et al., 1993; Phipps & Osborne, 1988). This notion applies to whether problems are presented in the context of a classroom or in a more authentic learning environment (Dewey, 1910, 1938). To equip students with such skills, however, requires introducing them to foundational agricultural knowledge so that they can begin to understand connections, notice disturbances, and appropriately detect when an issue or problem exists (Lancelot, 1944). Therefore, developmental appropriateness is of central importance to ensure that students are prepared as they gain exposure to problems (Charters, 1924), especially in the context of SBAE. As a consequence, SBAE teachers should frame problems in ways that challenge students, but that do not trigger forms of dissonance that may be interpreted as uneducative (Dewey, 1910). Through a synthesis of the literature, it became apparent that to ensure students are able to identify problems successfully, SBAE instructors must scaffold them in ways that allow students to mature before they confront issues and problems of a greater cognitive complexity (Bransford & Stein, 1984; Charters, 1912, 1924; Crunkilton & Krebs, 1967; Dewey, 1910; Goossen et al., 2017; Lancelot, 1944).

Principle #2: Analyze Information

As inevitable and ubiquitous as problems are in everyday life, human beings often resist analyzing trends and other relevant data to arrive at possible solutions (Dewey, 1910; Phipps & Osborne, 1988). An essential principle of problem-solving, therefore, is to analyze information. Through our synthesis, we noted that authors of seminal works on problem-solving described a plethora of ways to collect and analyze relevant evidence. For example, articulated strategies included conducting observations (Dewey, 1910, 1938), analyzing test and control specimen (Charters, 1924), as well as generating a hypothesis based on individuals’ procedural or external sources of knowledge and then assembling relevant corroborating or disconfirming evidence (Johnson, 1989). Despite the diversity in strategies available, however, SBAE teachers should ensure that students systematically collect information and evaluate it using rigorous procedures (Bransford & Stein, 1984; Charters, 1924; Dewey, 1910, 1938; Johnson, 1989, 1991).

Principle #3: Evaluate Solutions

Because problem-solving is a process, the solution emerges over time, through trial and error (Bransford & Stein, 1984; Charters, 1912; Crunkilton & Krebs, 1967; Dewey, 1910, 1938; Lancelot, 1944; Newcomb et al., 1993; Phipps & Osborne, 1988). Due to the dynamic nature of such, the evaluation of a solution is in a constant state of flux by which new discoveries can alter the beginning, middle, or late phases of the problem-solving process (Dewey, 1938; Johnson, 1989, 1991). This developmental view of the final principle, therefore, recognizes that as students learn and acquire information, an iterative progression transpires in which they co-influence past, present, and future solutions to numerous issues and problems (Dewey, 1938; Charters 1924). It is through this non-linear process; therefore, that SBAE students can critically reflect and begin to authentically evaluate whether their solution to a given problem is viable.

Reconceptualizing Problem-Solving for SBAE

Embedded in the three principles of problem-solving are features that stand as prominent attributes of the pedagogy. Therefore, our synthesis of ideas, theories, and models was a necessary step to illuminate how problem-solving has been advanced and used as a method of instruction. However, this process also revealed the need to expand our current view and understanding of problem-solving in SBAE. We maintain that such a reconceptualization could crystalize new possibilities for future research, theory, and practice.

For example, although problem-solving has largely been represented as a method of instruction, and rightfully so, we maintain that problem-solving’s current limits and parameters in SBAE could be expanded so that it may also be viewed as a guiding philosophy for the discipline. To that end, we offer (see Figure 3) the Integrated Problem-Solving Model for Agricultural Education to demonstrate how this idea could be operationalized in SBAE. In the model’s development, our goal was to enrich agricultural education’s comprehensive, three-circle model by embedding the core principles of problem-solving – identify problems, analyze information, and evaluate solutions – in a way that would aptly depict the synergistic and complementary power of this merger.

Figure 3

Integrated Problem-Solving Model for Agricultural Education

Note. The principles of problem-solving are shaded to demonstrate their permeability through and between each dimension of SBAE.

Foundationally, therefore, the model advances the notion that problem-solving is entrenched through and between each dimension of agricultural education. Consequently, the principles of problem-solving are interwoven with the three components of agricultural education: (a) classroom and laboratory, (b) Supervised Agricultural Experience (SAE), and (c) The National FFA Organization (FFA). It is important to note that the principles of problem-solving are not exclusive to a single dimension of agricultural education. Instead, they should be considered permeable as the problem-solving process unfolds for students through trial-and-error.

To contextualize the model, we developed the following example to demonstrate how the model might be used in SBAE. To begin, consider a student enrolled in an Introduction to Horticulture course (Classroom and Laboratory) who noticed that the Poinsettias she planted in class a few weeks prior appeared to be stunted in growth (Principle #1: Identify Problems). To capitalize on the learning embedded in this problem, her SBAE teacher encouraged her to reflect on the learning concepts introduced earlier in the semester. After a few minutes, she answered, “Maybe it is because the plants are under the shade cloth, so they are not getting enough sunlight.” Her SBAE teacher responded, “That is a great start, perhaps, you should design a project (SAE) that will allow you to collect data to determine whether or not your hypothesis is correct.” Over the next few weeks, she collected data using control and experimental trials, and as a result, began to observe trends through an analysis of relevant information (Principle #2: Analyze Information). After this procedure, she drew the conclusion that because Poinsettias are a tropical flower, they were not getting enough direct sunlight when placed under a shade cloth in the greenhouse. She also developed a solution to this problem for individuals who may be experiencing similar issues. Because her SBAE teacher perceived she had done quality work, he encouraged her to carry out additional trails so this knowledge could be used to impact the community through a service project (FFA). As a result, she decided to work with the local FFA Officer Team to organize a professional development opportunity for senior citizens based on the knowledge she had acquired through her classroom and Supervised Agricultural Experiences (SAEs). During this session, she also asked the senior citizens to provide feedback on their experience so that she could more carefully evaluate the solutions she provided regarding growing Poinsettias (Principle #3: Evaluate Solutions). As illustrated above, the SBAE teacher wove the three principles of problem-solving throughout each programmatic dimension of agricultural education – classroom and laboratory, SAE, and FFA – for his student. Such use of problem-solving may be easy to dismiss as common sense. However, we counter this position on several grounds. First, what may appear to be common sense for some, may not be viewed as such by those who are new to the discipline, have little experience, or have only considered limited perspectives on problem-solving. And finally, existing descriptions of problem-solving in SBAE do not appear to have represented it in ways that capture the intricacies of the reconceptualization advanced in our philosophical discussion.

Conclusions

Problem-solving has evolved considerably since its early origins. For example, initially, it was depicted as a distinct method of instruction (Charters, 1912). However, since that time, it appears to have become conflated with other pedagogical approaches (Parr & Edwards, 2004). As a consequence, the tenets of problem-solving became ambiguous over time (Crunkilton & Krebs, 1967; Moore & Moore, 1984). In this investigation, therefore, we sought to examine existing perspectives on problem-solving and explain how problem-solving has been used as a method of instruction. Through our analysis, we conclude that six leading perspectives – Dewey, Stimson, Charters, Lancelot, Bransford, and Johnson – appeared to most profoundly influence the ways in which the pedagogy has been operationalized. From these leading perspectives, we also conclude that three shared principles of problem-solving could be distilled: (1) identify problems, (2) analyze information, and (3) evaluate solutions. The first principle, identify problems, reflected that need for educators to scaffold problems in ways that are challenging but also developmentally appropriate so that students can gain confidence before attempting to solve problems of a greater complexity (Bransford & Stein, 1984; Crunkilton & Krebs, 1967; Dewey, 1910, 1938; Charters, 1912; 1924; Lancelot, 1944). Meanwhile, the second principle, analyze information, represented the need for students to collect and analyze quality data using rigorous procedures before drawing conclusions about a problem (Bransford & Stein, 1984; Charters, 1924; Dewey, 1910; Johnson, 1989, 1991).

The last principle, evaluate solutions, suggested that because problem-solving is a process, students should evaluate their solutions to problems over time through trial and error (Bransford & Stein, 1984; Crunkilton & Krebs, 1967; Dewey, 1910, 1938; Charters, 1912, 1924; Lancelot, 1944; Newcomb et al., 1993; Phipps & Osborne, 1988). Although our distillation of the shared principles helped describe how the pedagogy has been operationalized as a method of instruction, it also called attention to the need to expand our current use of problem-solving. Therefore, we introduced the Integrated Problem-Solving Model for Agricultural Education, which advanced the principles of problem-solving embedded through and between each component of agricultural education’s comprehensive, three-circle model: (a) classroom and laboratory, (b) SAE, and (c) FFA. We argue, therefore, that problem-solving can not only be operationalized as a pedagogy but also a guiding philosophy for SBAE moving forward.  

Implications, Recommendations, and Discussion

In recent decades, a growing number of voices from business, government, and higher education have called for more curricular focus to be placed on enhancing agriculture graduates’ ability to communicate, think critically, and innovate (Blickenstaff et al., 2015; Fields et al., 2003). By fostering these process-oriented skills, it is reasoned that future agriculturalist who enter the workforce will be better prepared to traverse a world fraught with complexities that require them to adapt and solve problems on issues such as climate change, disease, global hunger, and water scarcity (National Research Council, 2014; Roberts et al., 2020; Warren English et al., 2018). In response, this philosophical investigation illustrated the ways in which SBAE could draw on its problem-solving foundations to reposition itself, as the headwinds of change threaten to intensify in the 21stCentury and beyond (Brown, 2016). However, such a reorientation will be complex for the discipline to adopt, with even basic discussions about this change, presenting numerous conceptual and practical hurdles.

As a consequence, we offer the following possibilities for future research and practice. First, more dialogue is needed about problem-solving, when conceptualized as both a method of instruction as well as a guiding philosophy for SBAE. To achieve this, perhaps professional development sessions could be offered by the American Association for Agricultural Education (AAAE) and the National Association of Agricultural Education (NAAE). A concerted effort should also be dedicated to diffusing the Integrated Problem-Solving Model for Agricultural Education. As such, we recommend the model be shared, along with illustrative case study examples, in The Magazine as well as the FFA New Horizons. Teacher educators should also introduce the model to preservice teachers by having them consider innovative ways to integrate such into their future SBAE programs. We also suggest that podcasts, popular press articles, and other communication mediums promote SBAE students, advisors, and programs that use the model in exemplary ways. Finally, we recommend the use of social network analysis to analyze the model’s diffusion challenges better by identifying opinion leaders who influence others in SBAE at the node, dyad, and network levels (Borgatti et al., 2018).

Although problem-solving has a deeply entrenched philosophical foundation in SBAE (Moore & Moore, 1984), more work is needed to explore its dimensions. Therefore, we recommend that research be conducted to examine the programmatic outcomes associated with use of problem-solving as a guiding philosophy. For example, does such an approach improve students’ career readiness, creativity, critical thinking, engagement, learning, and motivation (Roberts & Robinson, 2018)? Further, what motivates a SBAE instructor to adopt such a philosophy in an individual program? Additional research is also needed to examine the outcomes of problem-solving’s use as a method of instruction in SBAE. As an illustration, how do the ways SBAE teachers conceptualize, use, and talk about problem-solving affect student outcomes? And do students who solve problems through team-based learning approaches learn better than those assigned individual problem-solving projects (Figland et al., 2020)? These corollary questions warrant further examination.

References

Andenoro, A. C., Baker, M., Stedman, N. L. P., & Pennington Weeks, P. (2016). Research priority 7: Addressing complex problems. In T. G. Roberts, A. Harder, & M. T. Brashears, (Eds.), American Association for Agricultural Education national research. University of Florida.

Blickenstaff, S. M., Wolf, K. J., Falk J. M., & Foltz. J. C. (2015). College of agriculture faculty perceptions of student skills, faculty competence in teaching areas and barriers to improving teaching. NACTA Journal, 59(3), 219-226. https://www.jstor.org/stable/nactajournal.59.3.219

Borgatti, S. P., Everett, M. G., & Johnson, J. C. (2018). Analyzing social networks (2nd ed.). Sage.

Boone, H. N. (1990). Effect of level of problem-solving approach to teaching on student achievement and retention. Journal of Agricultural Education, 31(1), 18-26. https://doi.org/10.5032/jae.1993.03010

Bransford, J. D., & Stein, B. S. (1984). The IDEAL problem solver: A guide for improving thinking, learning, and creativity. WH Freeman and Company.

Brown, K. (2016). Resilience, development and global change. Routledge.

Camp, W. G. & Crunkilton, J. R. (1985). History of agricultural education in America: The great individuals and events. Journal of the American Association of Teacher Educators in Agriculture, 26(1), 57-63. https://doi.org/10:5032/jaate.1985.01057

Cano, J., & Martinez, C. (1991). The relationship between critical thinking ability and level of cognitive performance of selected vocational agriculture students. Journal of Agricultural Education, 32(1), 24-29. https://doi.org/10.5032/jae.1991.01024

Charters, W.W. (1912). Methods of teaching. Row, Peterson & Company.

Charters, W.W. (1924). Teaching the common branches. The Riverside Press.

Crotty, M. (1998). The foundations of social research: Meaning and perspective in the research process. Sage.

Crunkilton, J. R., & Krebs, A. H. (1967). Teaching agriculture through problem-solving. The Interstate Printers & Publishers, Inc.

Dewey, J. (1910). How we think. Dover Publications.

Dewey, J. (1938). Experience and education. Simon and Schuster.

Dyer, J. E., & Osborne, E. W. (1996). Effects of teaching approach on problem-solving ability of agricultural education students with varying learning styles. Journal of Agricultural Education37, 36-43. https://doi.org/10.5032/jae.1996.04038

Elstein, A. S., Shulman, L. S., & Sprafka, S. A. (1978). Medical problem solving analysis of clinical reasoning. Evaluation & the Health Professions, 13(1), 5-36. https://doi.org/10.1177/016327879001300102

Fields, A. M., Hoiberg, E., & Othman, M. (2003). Changes in colleges of agriculture at land-grant institutions. NACTA Journal, 47(4), 7-15. https://www.jstor.org/stable/43765799

Figland, W. L., Blackburn, J. J., & Roberts, R. (2020). Undergraduate students’ perceptions of team-based learning during an introductory agricultural mechanics course: A mixed methods study. Journal of Agricultural Education, 61(1), 262-276. https://doi.org/10.5032/jae.2020.01262

Flowers, J., & Osborne, E. W. (1988). The problem-solving and subject matter approaches to teaching vocational agriculture: Effects on student achievement and retention. The Journal of Agricultural Education, 29(1), 20-26. https://doi.org/10.5032/jaatea.1988.01020

Foor, R. M. & Connors, J. J. (2010). Pioneers in an emerging field: Who were the early agricultural educators? Journal of Agricultural Education, 51(3), 23-31. https://doi.org/10:5032/jae.2010.030123

Fuhrmann, B. S., & Grasha, A. F. (1983). The past, present, and future in college teaching: Where does your teaching fit? Little, Brown, and Company.

Gokhale, A. A. (1995). Collaborative learning enhances critical thinking. Journal of Technology Education, 7(1), 22-30. https://scholar.lib.vt.edu

Goossen, C. E., Roberts, R., Kacal, A., Whiddon, A. S., & Robinson, J. S. (2017). The effect of the inquiry-based teaching method on students’ content knowledge and motivation to learn about biofuels, Journal of Southern Agricultural Education Research, 66(1), 1-18. http://www.jsaer.org/pdf/Vol66/66-01-005.pdf

Hammonds, C. (1950). Teaching agriculture. McGraw-Hill Inc.

Hyland, T. (1993). Vocational reconstruction and Dewey’s instrumentalism. Oxford Review of Education19(1), 89-100. https://doi.org/10.1080/0305498930190107

Johnson, S. D. (1989). A description of expert and novice performance differences on technical troubleshooting tasks. Journal of Industrial Teacher Education, 26(3), 19–37. https://doi.org/10.1111/j.1937-8327.1988.tb00021.x

Johnson, S. D. (1991). Productivity, the workforce, and technology education. Journal of Technology Education, 2(2), 32-49. https://files.eric.ed.gov/fulltext/EJ458790.pdf

Jonassen, D. H. (2000). Toward a design theory of problem-solving. Educational Technology: Research and Development, 48(4), 63-85. http://link.springer.come/article/10.007%2FBF02300500LI=true#page-1

Koichu, B. (2019). Problem posing in the context of teaching for advanced problem solving. International Journal of Educational Research, 103(1), 1-24. https://doi.org/10.1016/j.ijer.2019.05.001

Kolb, D. A. (1984). Experience as the source of learning and development. Prentice Hall.

Krebs, A. H. (1967). For more effective teaching (2nd ed.). The Interstate Printers and Publishers, Inc.

Lamm, A. J., Shoulders, C., Roberts, T. G., Irani, T. A., Snyder, L. J. U., & Brendemuhl, J. (2012). The influence of cognitive diversity on group problem solving strategy. Journal of Agricultural Education53(1), 18-30. https://doi.org/10.5032/jae.2012.01018

Lancelot, W. H. (1944). Permanent learning. John Wiley & Sons.

Merwin, W. C. (1977). Models for problem-solving. The High School Journal61(3), 122-130. https://www.jstor.org/stable/40365318

Moore, G. E., & Moore, B. A. (1984). The problem-solving approach to teaching: Has it outlived its usefulness? Journal of the American Association of Teacher Educators in Agriculture, 25(2), 3-10. https://doi.org/10.5032/jaatea.1984.02011

Moore, G. E. (1988). The forgotten leader in agricultural education: Rufus W. Stimson. Journal of the American Association of Teacher Educators in Agriculture, 29(3),50-58. https://doi.org/10.5032/jaatea.1984.03050

Moore, G. E. (2018). Identifying the first generation leaders in agricultural education: The lost Stimson manuscript. Journal of Agricultural Education, 59(4), 137-158. https://doi.org/10.5032/jae.2018.04137

National Research Council. (2014). Spurring innovation in food and agriculture: A review of the USDA agriculture and food research initiative program. National Academy Press.

Newcomb, L. H., McCracken, J., Warmbrod, J. R., & Whittington M. S. (1993). Methods of teaching agriculture. Pearson.

Newell, A. S., & Simon, H. A. (1972). Human problem-solving. Englewood Cliffs.

Parr, B., & Edwards, M. C. (2004). Inquiry-based instruction in secondary agricultural education: Problem-solving an old friend revisited. Journal of Agricultural Education45(4), 106-117. https://doi.org/10.5032/jae.2004.04106

Phillips, C. (2010). Socrates café: A fresh taste of philosophy. WW Norton & Company.

Phipps, L. J., & Cook, G. C. (1956). Handbook on teaching vocational agriculture. The Interstate Printers and Publishers, Inc.

Phipps L. J., & Osborne, E. W. (1988). Handbook on agricultural education in public schools. The Interstate Printers & Publishers, Inc.

Phipps, L. J., Osborne, E. W., Dyer, J. E., & Ball, A. (2008). Handbook on agricultural education in public schools (6th ed.). Thomson Delmar Learning.

Retallick, M. S., & Miller, W. W. (2005). Learning for life through inquiry. The Agricultural Education Magazine, 78(3), 17-19. https://www.naae.org/profdevelopment/magazine/archive_issues/Volume73/v73i3.pdf

Roberts, R., & Edwards, M. C. (2015). Service-learning’s ongoing journey as a method of instruction: Implications for school-based, agricultural education. Journal of Agricultural Education, 56(2), 217-233. https://doi.org/10.5032/jae.2015.02217

Roberts, R., & Edwards, M. C. (2018). Imaging service-learning in The Agricultural Education Magazine from 1929-2009: Implications for the method’s reframing and use. Journal of Agricultural Education. 59(4), 15-35. https://doi.org/10.5032/jae.2018.03015

Roberts, R., & Edwards, M. C. (2020). Overcoming resistance to service-learning’s use in the preparation of teachers for secondary agricultural education: A reframing of the method’s diffusion challenges. Journal of International Agricultural and Extension Education, 27(1), 15-33. https://doi.org/10.5191/jiaee.2020.27102

Roberts, R.& Robinson, J. S.(2018).The motivational changes preservice agricultural education teachers endure while facilitating quality supervised agricultural experiences: A six-week project-based learning experience. Journal of Agricultural Education, 59(1), 255-270.https://doi.org/10.5032/jae.2018.01255

Roberts, R.,& Stair, K. S., Granberry, T. (2020). Images from the trenches: A visual narrative of the concerns of preservice agricultural education teachers.

Journal of Agricultural Education, 61(2), 324-338. https://doi.org/10.5032/jae.2020.02324

Roberts, R. W. (1957). Vocational and practical arts education: History, development, and principles. Harper and Brothers.

Roberts, T. G., & Ball, A. L. (2009). Secondary agricultural science as content and context for teaching. Journal of Agricultural Education, 50(1), 81-91. https://doi.org/10.5032/jae.2009.01081

Robles, M. M. (2012). Executive perceptions of the top soft skills needed in today’s workplace. Business Communication Quarterly75(4), 453-465. https://doi.org/10.1177%2F1080569912460400

Saldaña, J. (2015). Thinking qualitatively: Methods of mind. Sage.

Salevouris, M. J., & Furay, C. (2015). The methods and skills of history: A practical guide (4th ed.). John Wiley and Sons, Inc.

Sproull, B. (2001). Process problem solving: A guide for maintenance and operations teams. Productivity Press.

Sternberg, R. J. (1981). Intelligence and no entrenchment. Journal of Educational Psychology73(1), 1-16. https://doi.org/10.1037/0022-0663.73.1.1

Stimson, R. W. (1911). The vocational agricultural school. With special emphasis on part-time work in agriculture. University of Chicago Press.

Stimson, R. W. (1919). Vocational agricultural education by home projects. Macmillan.

Talbert, B. A., Vaughn, R., Croom, D. B., & Lee, J. S. (2007). Fundamentals of agricultural education (2nded.).The Interstate Printers & Publishers, Inc.

Torres, R. M., & Cano, J. (1995a). Examining cognition levels of students enrolled in a college of agriculture. Journal of Agricultural Education, 36(1), 46-54. https://doi.org/10.5032/jae.1995.01046

Torres, R. M., & Cano, J. (1995b). Increasing thinking skill through HOT teaching. The Agricultural Education Magazine, 68(6), 8-9. https://www.naae.org/profdevelopment/magazine/archive_issues/Volume68/v68i6.pdf

Ulmer, J. D., & Torres, R. M. (2007). A comparison of the cognitive behaviors exhibited by secondary agriculture and science teachers. Journal of Agricultural Education48(4), 106-116. https://doi.org/10.5032/jae.2007.04106

U.S. Department of Education. (2001). The condition of education, 2001. Author. https://nces.ed.gov/pubs2001/2001072.pdf

Zimmerman, B. J., & Risemberg, R. (1997). Self-regulatory dimensions of academic learning and motivation. In G. D. Phye (Ed.), The educational psychology series. Handbook of academic learning: Construction of knowledge (pp. 105-125). Academic Press.

Warren English, C., Alston, A. J., Graham, A. & Roberts, R. (2018). An analysis of North Carolina superintendents’ views regarding the presence of future-ready graduate attributes within the instructional environment. Journal of Southern Agricultural Education Research, 68(1), 1-15. http://jsaer.org/pdf/Vol68/2018_009%20formatted%20to%20print

Whewell, W. (1840). The philosophy of inductive sciences. Parker.