Duration: 10/01/2017 to 09/30/2022

Administrative Advisor(s):

NIFA Reps:

Non-Technical Summary

Statement of Issues and Justification

The agricultural and natural resource industry must address a variety of significant, and often controversial, issues as a result of it consisting of a multitude of complexly intertwined societal functions — food, fuel, and fiber — all of which “have to be fulfilled, simultaneously, in a framework in which inputs (i.e., soil, water, air) are increasingly tight” (Aerts, De Tavernier, & Lips, 2009, p. 331). Determining how these functions are carried out individually and collectively is an equally complex mixture of politics, economics, science, ethics, culture, and consumerism. Unfortunately, people are either incapable or unwilling to engage in civil discourse to develop efficient action as “opportunities for honest discussion are reduced in today’s polarized environment” (Epstein & Graham, 2007, p. 1). As society becomes more connected, both nationally and globally, the need for people to communicate and work collaboratively to address agriculture and natural resource issues is becoming increasingly important. These critical issues include (a) food security, (b) climate variability and change, (c) water, (d) bioenergy, (e) childhood obesity, and (f) food safety (NIFA, n.d.).

Pyschological and sociological dimensions play a large role in how people make decisions, including how they work collaboratively and communicate with one another. Cognitive styles, or an individual’s preferred way of organizing and retaining information (Keefe, 1979), need to be studied in order to better understand decision making, encourage civil discourse, and inform the development of educational programming that integrates critical agricultural and natural resource issues into formal and non-formal learning environments. In addition, as the U.S. population becomes more urbanized and diverse, cultural influences must be understood to ensure educational program is applicable to a variety of audiences that all play a role in the broader food system but make decisions differently. The overall purpose of this project is to develop a decision support system to aid in (a) the identification and stakeholder implementation of new technologies and practices (e.g. water conservation technologies such as drip irrigation or soil moisture censors, water treatment technologies such as carbon filters or chlorination allowing for water reuse, genetic modification to increase crop yields, drones as delivery information systems to enhance pesticide and fertlizer accuracy) (b) the ability to integrate holistic perspectives on agriculture and natural resources issues into formal and non-formal educational programs, and (c) to ensure cultural consideration in the decision making process.

Related, Current and Previous Work

Research has been focusing on the influences of cognitive styles on decision making for quite some time (Witkin, Moore, Goodenough, & Cox, 1977). Keefe (1979) defined cognitive styles as a learner’s preferred way of organizing and retaining information. Within the realm of cognitive styles, critical thinking style has been recurrently identified as necessary for students in the 21^st century and crucial for individuals to be able to deal with decisions faced every day (Myers & Dyer, 2006; Torres & Cano, 1995). Along with critical thinking, problem solving style and learning style are the primary cognitive styles being examined within the field of education and of special interest to agricultural educators. In fact, agricultural educators are rapidly increasing the amount of research and education focused on understanding and utilizing cognitive function in an attempt to improve educational programs (Boone, 1990; Cano, 1993; Dyer & Osborne, 1996a; Parr & Edwards, 2004) and to improve the integration of cultural perspectives into the learning process (Bunch, Blackburn, Danjean, Stair, & Blanchard, 2015; Danjean, Bunch, & Blackburn, 2015; Danjean, McClure, Bunch, Kotrlik, & Machtmes, 2014; McClure, Danjean, Bunch, Machtmes, & Kotrlik, 2014).

A variety of research examining how critical thinking style, problem solving style, and learning style as individual concepts impact decision making, specifically in learning environments, has been conducted within agricultural education (Blackburn & Robinson, 2016; Blackburn, Robinson, & Lamm, 2014; Boone, 1990; Cano, 1993, 1999; Cano & Martinez, 1991; Dyer & Osborne, 1996a, 1996b; Garton, Spain, Lamberson, & Spiers, 1999; Parr & Edwards, 2004; Rudd, Baker, & Hoover, 1998; Sandlin & Price, 2016; Torres & Cano, 1994).  In addition, researchers have examined how critical thinking disposition and problem solving style may be linked through creative thinking. Studies have identified creative thinking as an essential part of critical thinking (Maltzman, 1960; Newell, Shaw, & Simon, 1962; Russell, 1956; Torrance & Torrance, 1973; Vinacke, 1952). At the same time, there is some debate as to whether creative thinking and problem solving are significantly different concepts. Kirton (2003) argued that problem solving style does not differentiate whether an individual is creative or not, but rather the differences in the way they express their creativity. Friedel, Irani, Rhoades, Fuhrman, and Gallo (2008) found low levels of correlation between critical thinking and problem solving, but concluded the two are probably more independent than previously thought and may be impacting decision making separately. An understanding of how these two concepts inter-relate around decision making is still unanswered.

Further, the adoption of innovations into learning environments tends to follow the same path as adoptions by other social groups (Rogers, 2003).  For example, consider the adoption of the smartphone for learning purposes in agriculture classrooms. Over 90% of agriculture teachers in Louisiana personally own a smartphone and more than half are allowed by district policy to use them in their classrooms, yet, many teachers rarely or never utilize smartphones for learning purposes in their classrooms (Smith, Stair, & Blackburn, 2017).  However, research has indicated agriculture teachers are often not properly trained as to how to effectively utilize new innovations in their classrooms, with many teachers reporting they have self-taught how to use technologies for learning (Kotrlik & Redmann, 2009; Kotrlik, Redmann, Harrison, & Handley, 2009; Redmann, Kotrlik, & Douglas, 2003).  The smartphone is in the early phases of adoption in secondary classrooms, high quality professional development opportunities may be needed to encourage more teachers to adopt this technology (Guskey, 2002).

Cognitive relationships between critical thinking style and learning style have also been explored (Friedel, et al., 2008; Myers & Dyer, 2006; Lamm, Rhoades, Irani, Roberts, Unruh Snyder, & Brendemuhl, 2011; Rudd, Baker, & Hoover, 2000; Torres & Cano, 1995). While studying these relationships in undergraduate students, Rudd et al. (2000) reported no significant correlation between learning style and critical thinking disposition. Torres and Cano (1995) also expressed the need for further study when they discovered learning style only accounted for 9% of the variance in critical thinking ability. Lamm et al. (2011), however, found a relationship did exist between learning style and critical thinking disposition. While overall problem solving style scores and learning style scores were not strongly correlated, connections between constructs within the styles were uncovered and found to be significant. The finding leaves open a question of how these two concepts work independently and collaboratively in influencing decision making.

More recently, researchers have started to focus on how cognitive styles influence team dynamics during the decision making process in order to enhance educational initiatives, communication strategies, and leadership programming around critical agricultural and natural resource issues. In a recent study, Lamm, Carter, Settle, & Odera (2016) found that problem solving style influenced how opinion leaders worked collaboratively in teams while building agendas around critical agricultural and natural resource issues. In this study, the findings suggested that teams representing diverse problem solving styles enhanced the consensus building process. These results imply that when building teams around critical issues educators should focus on establishing well-structured groups that will allow participants to “share their conceptual and procedural knowledge . . . so that all [participants] are actively engaged in the problem-solving process and differences of opinion are resolved in a reasonable manner” (Heller & Hollabaugh, 1992, p. 637).

Educators have many pedagogical and andragogical techniques at their disposal.  Culture is often a determining factor in their success. There are many definitions of culture; in the simplest form, culture includes the beliefs, social forms, and material traits of a social group, including races, religion and otherwise (Merriam-Webster, 2017). Not only have theorists (Knowles, Holton, & Swanson, 2011; Rogers, 2003) written about the importance of culturally relevant content and approaches to meet educational needs and goals, but agricultural education and extension practitioners have corroborated this idea in the classroom (Bunch et al., 2015; Danjean et al., 2015) and in non-formal education settings (Cater, Bunch, & Danjean, 2016; Sandlin, 2015; Sandlin, Murphrey, Lindner, & Dooley, 2013). As an extension of this concept, and in alignment with the model of the interaction of culture and consumer behavior, the cultural value system is directly linked to consumer behavior (Luna & Gupta, 2001).

While research examining how cognitive styles impact decision making in general is abundant, research focusing on how cognitive styles impact how decisions are made around critical agricultural and natural resources has just begun. Therefore, the subject matter area is ripe for further investigation. The researchers believe developing a multi-state, national decision support system will aid in widespread stakeholder adoption of new technologies and practices, educators’ integration of holistic perspectives on complex agriculture and natural resources issues into formal and non-formal environments, and will foster cultural consideration in the decision making process through targeted educational interventions.

Objectives

1. Determine how the psychological and sociological dimensions of decision making influence the adoption of new technologies and practices addressing critical agricultural and natural resource issues.
   
2. Identify how the psychological and sociological dimensions of decision making impact future agricultural and natural resource professionals ability to integrate holistic perspectives to address critical agricultural and natural resource issues.
   
3. Ascertain the impact of culture on the psychological and sociological dimensions of decision making when addressing agricultural and natural resource issues.
   

Methods

Objective #1: Determine how the psychological and sociological dimensions of decision making influence the adoption of new technologies and practices addressing critical agricultural and natural resource issues.

Experiment 1 Objective – Determine the impact of cognition on the decision making process when encouraging the adoption of new technologies and practices (e.g. water conservation technologies such as drip irrigation or soil moisture censors, water treatment technologies such as carbon filters or chlorination allowing for water reuse, genetic modification to increase crop yields, drones as delivery information systems to enhance pesticide and fertlizer accuracy)

A series of experiments will be conducted examining the impact of problem solving style, learning style, critical thinking style, behavioral style, and/or personality type on the decision making processes when encouraging the adoption of new technologies and practices. These studies will utilize validated instruments to assess individual cognitive differences that influence the decision making process in combination with a researcher-developed scale to determine willingness and intention to adopt new technologies and practices. Findings will be disseminated in the form of conference presentations, extension publications, and journal articles.  Further, these findings will be utilized to inform the practice of teaching and program development in formal and non-formal environments.

Experiment 2 Objective – Determine the aggregated effect of cognition on adoption across content areas and with diverse audiences.

An experiment will be conducted that utilizes combined data collected from agriculture and natural resources professionals, educators, and faculty when encouraging the adoption of new technologies and practices.  These data will be examined to determine collective effect of cognition on adoption, as well as compare and contrast similarities and differences across stakeholder groups. Findings will be disseminated in the form of conference presentations and journal articles. Further, these findings will be utilized to inform the practice of teaching and program development in formal and non-formal environments.

Objective #2: Identify how the psychological and sociological dimensions of decision making impact future agricultural and natural resource professionals ability to integrate holistic perspectives to address critical agricultural and natural resource issues.

Experiment 1 Objective – Determine how cognitive style impacts undergraduate students’ ability to work collaboratively when solving agricultural and natural resource problems.

To fulfill this objective an experiment will be conducted with undergraduate agriculture courses currently being taught at the collaborating universities. Undergraduate students in these courses will be targeted because they represent the future workforce that will be working with the agricultural and natural resource industry and have already shown interest in agriculture and natural resources when they self-selected into the course.

Students will take an online survey identifying their cognitive styles. The participants will then be broken into groups which will be manipulated based on their cognitive styles (based on either homogenous or heterogeneous styles). Each group will then be given an assignment where they have to work collaboratively to solve a specified agricultural issue with the intent of examining how cognitive styles impact group dynamics and academic performance. Success will be measured based on identified assignment outcomes. In addition, focus groups and/or key informant interviews will be conducted to collect rich, qualitative data on the differences in team dynamics and academic performance. Data will be analyzed to determine if and how cognitive style influences how students work collaboratively to solve agriculturally-related issues and will be disseminated in the form of conference presentations and journal articles.

Experiment 2 Objective – Determine the impact of cognitive style on agricultural educators’ systems thinking related to agriculture and natural resources issues.

To fulfill this objective an experiment will be conducted with school-based agricultural education teachers, extension professionals, and college of agriculture faculty. Participants will take an online survey identifying their cognitive styles and their perceived interdisciplenary perspectives on agriculture and natural resource issues.  Data will be analyzed using social network analysis to identify the density and interconnectedness of their perspectives taking cognitive style into account. The findings will be disseminated in the form of conference presentations, journal articles, and extension programming.

Objective #3: Ascertain the impact of culture on the psychological and sociological dimensions of decision making when addressing agricultural and natural resource issues.

Experiment 1 Objective – Assess the impact of culture on decision making when addressing agriculture and natural resource issues based on cognitive styles.

Experiments will be conducted with agriculture and natural resources professionals and stakeholders to assess the impact of culture and how decisions are made based on individual and/or team cognitive characteristics. Participants will complete an inventory to determine cognitive style prior to engaging in a decision making process around an agriculture and natural resource issue. Data will be collected through key informant interviews and focus group interviews to assess the impact of cultural characteristics on the decision making process. The findings will be disseminated in the form of conference presentations, journal articles, and extension programming.

Experiment 2 Objective – Determine the impact of cognitive style on agricultural educators’ integration of multicultural concepts when teaching in formal and nonformal environments over time.

To fulfill this objective, short and long-term experiments will be conducted with school-based agricultural education teachers, extension professionals, and college of agriculture faculty. Participants will take an online survey identifying their cognitive styles prior to participating in a cultural experience. The participants’ integration of multicultural concepts into their teaching practice will be assessed at several points over time. Similarities and differences in decision making will be assessed based their identified cognitive styles. The findings will be disseminated in the form of conference presentations and journal articles.

Measurement of Progress and Results

Outputs

• Analyzed survey data
• Analyzed focus group transcriptions
• Analyzed interview transcriptions
• Field notes from direct observation
• Multi-state national decision support system

Outcomes or Projected Impacts

• Widespread stakeholder adoption of new technologies and practices
• Educators’ integration of holistic perspectives on complex agriculture and natural resources issues into formal and non-formal environments
• Cultural consideration in the decision making process

Milestones

(2018):Establish organizational structure and project management.

(2019):Use previous literature and initial research findings to develop a theoretical model to serve as the foundation for research that will be used to develop a multi-state national decision making support tool.

(2020):A multi-state national website will be developed for knowledge management and the sharing of information/data.

(2022):A decision making support tool will be developed based on research findings conducted utilizing the theoretical model.

Projected Participation

View Appendix E: Participation

Outreach Plan

Objective #1: Determine how the psychological and sociological dimensions of decision making influence the adoption of new technologies and practices addressing critical agricultural and natural resource issues.

Experiment 1 Objective – Determine the impact of cognition on the decision making process when encouraging the adoption of new technologies and practices (e.g. water conservation technologies such as drip irrigation or soil moisture censors, water treatment technologies such as carbon filters or chlorination allowing for water reuse, genetic modification to increase crop yields, drones as delivery information systems to enhance pesticide and fertlizer accuracy)

A series of experiments will be conducted examining the impact of problem solving style, learning style, critical thinking style, behavioral style, and/or personality type on the decision making processes when encouraging the adoption of new technologies and practices. Data from the participating states will be combined to develop and test the validity and reliability of a scale to determine willingness and intention to adopt new technologies and practices. Further, these findings will be utilized to inform the practice of teaching and program development in formal and non-formal environments in the participating states through the development of consistent curriculum to measure collective impact.

Experiment 2 Objective – Determine the aggregated effect of cognition on adoption across content areas and with diverse audiences.

An experiment will be conducted that utilizes combined data collected from agriculture and natural resources professionals, educators, and faculty in the participating states when encouraging the adoption of new technologies and practices.  These data will be accessible through a shared website and will be examined to determine collective effect of cognition on adoption, as well as compare and contrast similarities and differences across stakeholder groups. 

Objective #2: Identify how the psychological and sociological dimensions of decision making impact future agricultural and natural resource professionals ability to integrate holistic perspectives to address critical agricultural and natural resource issues.

Experiment 1 Objective – Determine how cognitive style impacts undergraduate students’ ability to work collaboratively when solving agricultural and natural resource problems.

To fulfill this objective a series of experiments will be conducted with undergraduate and graduate agriculture courses currently being taught at the collaborating universities. Data will be shared on the project website and analyzed collectively to determine if and how cognitive style influences how students work collaboratively to solve agriculturally-related issues. The findings will be disseminated in the form of conference presentations and journal articles.

Experiment 2 Objective – Determine the impact of cognitive style on agricultural educators’ systems thinking related to agriculture and natural resources issues.

To fulfill this objective a series of experiments will be conducted with school-based agricultural education teachers, extension professionals, and college of agriculture faculty at participating universities. Data will be analyzed using social network analysis to identify the density and interconnectedness of their perspectives taking cognitive style into account. The resulting maps and related recommendations will be shared on the project website.

Objective #3: Ascertain the impact of culture on the psychological and sociological dimensions of decision making when addressing agricultural and natural resource issues.

Experiment 1 Objective – Assess the impact of culture on decision making when addressing agriculture and natural resource issues based on cognitive styles.

Experiments will be conducted with agriculture and natural resources professionals and stakeholders at participating universities to assess the impact of culture and how decisions are made based on individual and/or team cognitive characteristics. Data will be collected through focus group interviews to assess the impact of cultural characteristics on the decision making process within a variety of locations. The results and recommendations will be shared through academic conference presentations, journal articles and white papers available on the project website.

Experiment 2 Objective – Determine the impact of cognitive style on agricultural educators’ integration of multicultural concepts when teaching in formal and nonformal environments over time.

To fulfill this objective, short and long-term experiments will be conducted with school-based agricultural education teachers, extension professionals, and college of agriculture faculty at participating universities. The participants’ integration of multicultural concepts into their teaching practice will be assessed at several points over time in diverse locations through a consistent curriculum the team has developed. Similarities and differences in decision making will be assessed based their identified cognitive styles. The curriculum and associated white papers will be made available on the project website. Results and recommendations will be shared through academic conference presentations and journal articles.

Organization/Governance

We will elect a Chair, a Chair-elect, and a Secretary. The Past-Chair will also be considered a part of the officer team. All officers will be elected for two-year terms to provide continuity. Administrative guidance will be provided by an assigned Administrative Advisor and a NIFA Representative. Subcommittees will be planned for specific functions as they arise. 

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Attachments

Land Grant Participating States/Institutions

FL, HI, LA, MI

Non Land Grant Participating States/Institutions