Recipient Organization
UNIVERSITY OF FLORIDA
G022 MCCARTY HALL
GAINESVILLE,FL 32611
Performing Department
Agricultural Education and Communication
Non Technical Summary
The United States has long identified public understanding of science as a priority (Shen, 1975). Yet as recently as 2008, less than 30% of adults were skilled enough to comprehend The New York Times' Science section (J. D. Miller, 2010). A thorough understanding of science "plays a critical role in the quality of our national debate and, in turn, the health of our democracy" (Meinwald & Hildebrand, 2010, p. vii) as well as the preparedness of a globally-competitive workforce (Carnevale, Smith, & Melton, 2011; Goecker, Smith, Smith, & Goetz, 2010; National Research Council, 2012). Traditionally, opportunities for engaging in science, technology, engineering, and math (STEM) focus on formal classroom learning environments and experiences. Americans spend a significant amount of time in formal school as youth. However, adults and even school-aged children actually spend more time outside of school than in, and therefore, people have more opportunities to engage with STEM outside the classroom throughout their lives (Falk & Dierking, 2010). Researchers have struggled to identify what learning in non-classroom experiences may look like; recent re-characterization of the nature of the experiences to include affective features such as identity have helped conceptualize a holistic picture of development (Falk & Dierking, 2000). Formal classroom teachers also struggle to incorporate authentic STEM experiences in their lessons (Hume & Coll, 2010). In addition, many efforts to investigate STEM overlook the large segment of students and researchers in agricultural and natural resources fields. This project will examine three related issues to broad engagement with Ag-STEM in all learning settings: the use of visualizations of scientific data to support learning about current research; public engagement with science for learning through novel programming and contemporary agricultural issues; and support for implementing authentic STEM experiences in K-12 classrooms. Through mixed methods research in these areas, I will build theory on public engagement with Ag-STEM and develop quantitative measures to investigate these issues and Ag-STEM learning with broad audiences. The research will include agricultural and natural resources disciplines in the fields and topics of study, and results from the research will be shared with both Agricultural and STEM Education communities.
Animal Health Component
100%
Research Effort Categories
Basic
(N/A)
Applied
100%
Developmental
(N/A)
Goals / Objectives
This proposal takes a broad scope and will cover research related to improving public engagement with STEM, specifically agricultural STEM, via a combination of: improvements of specific tools for engagement, namely data visualizations; discipline-universal methods for promoting engagement via formal and informal settings; and specific workshops and research on teacher professional development to implement authentic contemporary agriscience lessons in secondary school classrooms. In addition, this project will use the contemporary issue of genetic engineering in food as a test bed for many of the ideas that have emerged from previous research. For example, I will design and test research-based interventions to support increased public coherence with scientific guidance on the issue. "Engagement" in this project will cover the gamut of gathering, processing, and using information, and involve both burgeoning Ag-STEM professionals and the public in other professions.The presentation of this research to both STEM Education and Agricultural Education researchers and practitioners will foster increasing collaborations among the traditionally separate lines of work. Ultimately, increased public engagement with Ag-STEM will support future Ag-STEM workforce development and participatory democracy.
Project Methods
This project will involve three parallel lines of inquiry and thus three primary objectives with associated methods. The subobjectives are potential options offered for concrete examples. Their exact execution is subject to funding.Objectives:In both formal and informal settings,Characterize and improve learner engagement with scientific data visualizationsUnderstand meaning-making strategies and barriers to meaning-makingInvestigate the use of scaffolds internal and external to the visualizations for improving meaning-making.Investigate interaction with data visualization on various multitouch form factors including touch tables, touch walls, and touch-enabled spheres.Investigate public engagement with Ag-STEMDetermine public perception of relations among agriculture, STEM, medicine, and researchInvestigate topic-specific educational interventionsInvestigate methods for engaging the public around current research through exhibits and programs.Investigate implementation of authentic Ag-STEM experiences in K-12 classroomsInvestigate barriers to implementation remaining teacher professional development workshopsInvestigate student learning with authentic Ag-STEM experiences.Objective 1.Building on previous research, I will design experimental versions of visualizations and their supporting materials. These experimental versions will include scaffolds in the form of elements such as color ramp, geographic labels, and measurement units that have been altered to better fit lay public's everyday scientific understanding. The supporting materials in captions, exhibit kiosks, and comparison visualizations will also incorporate a non-academic register of language and access public funds of knowledge.Sub-objective 1a. I will recruit study participants in both laboratory and in situ settings such as museums and on the Internet. I will present the various versions of the visualizations and supporting materials and use surveys, interviews, and participant observations (Webb, Campbell, Schwartz, & Sechrest, 2000) to probe user prior knowledge and experience, meaning-making strategies, effective use of the data in the visualizations, and barriers to meaning-making. To determine effective use of the data, I will examine (1) pattern recognition, (2) comparing normal or baseline states with anomaly conditions, and (3) comparing normal states of different data parameters, such as temperature and salinity. Data analysis will involve qualitative coding using constant comparative methods for open-ended survey questions, interviews, and observations, and parametric and non-parametric quantitative analysis of survey responses and comparison groups as appropriate. I will design a rubric to address competence at pattern recognition and comparison/contrasting. Participants' descriptions of this distribution will be scored as incorrect, partially correct, correct, or correct and sophisticated.Sub-objective 1b. I will iteratively refine and re-test the visualizations and supporting materials based on strategies and barriers that emerge from surveys, interviews, and observations. This approach will be based on design research methodology (Barab, 2006). Sub-objective 1c. I will compare interactions with similar visualizations projected in both two- and three-dimensions. For example, visualizations on a touch-enabled flat screen can be mounted horizontally on a tabletop or vertically on a wall. For flat screens, projections can display the entire globe in a rectangular or other compromise projection or show only a portion of the globe at a time, such as with Google Earth. The latter projection of only a portion at a time is also more comparable to the view of a single user of a touch-enabled spherical display. Data collection and analysis methods will be primarily qualitative.Objective 2.Subobjective 2a. As communication underlies all education and outreach efforts, it is important that we understand exactly what background our audiences draw on when making sense of our campaigns. This subobjective will assess what the public thinks about when they hear terminology that professionals may use, and specifically how terms may or may not be related in the public's mind. I will continue mixed-methods assessment for use with large populations based on work in my previous Hatch project using personal meaning mapping (Stofer & Newberry III, 2017) to determine alignment of views of science and agriculture. In this new Hatch project, I will expand this work to examine terms including research, medicine, technology, and engineering collected from public audiences. Then I will deploy this tool as an online survey with public audiences to generate background information on how the public uses these terms.Subobjective 2b. One funded endeavor will investigate public understanding of and attitudes toward genetic engineering. Using focus groups across the United States, my collaborators and I will investigate both communication and education interventions to improve perceptions. Communication interventions will include various messaging strategies, while education interventions will include various formats for message sharing, such as through printed materials, videos, or in-person public engagement. Focus group analysis will be primarily qualitative to subsequently design surveys for larger quantitative experimental comparison studies of the most promising communication and education interventions.Subobjective 2c. To understand how the public gathers information about current research, I will conduct evaluations and research on various exhibits and programs at informal learning settings. This may include design of particular Extension programs or even production of ongoing programs such as "talk science with me" (Stofer et al., under review). These studies will use quantitative methods including survey tools on expectations of how to engage (Stofer et al., 2019), value of exhibits (Bitgood, 2013), and content, and qualitative methods including visitor observation and interviews. Analysis will be as in Subobjective 1a.Objective 3.Teacher professional development is an ongoing area of research. Recent models emphasize partnerships with scientists for professional development particularly around contemporary science topics such as emerging pathogens (Brown, Bokor, Crippen, & Koroly, 2014) or collaborative design with teachers revising their existing lessons (Tammen, Faux, Meiri, & Jacque, 2018). Current funding for such workshops will allow data collection on these two models in particular.Subobjective 3a. Based on two currently funded teacher professional development workshops, I will use a) pre- and post- surveys of both content knowledge, attitudes, and other affective measures; b) personal meaning mapping; c) teacher daily workshop reflections; d) focus groups; and e) individual follow up interviews to investigate the successes and challenges of implementing curricula from the workshops into their classrooms. Data analysis will be qualitative and quantitative as appropriate.Subobjective 3b. Using the teachers from the professional development workshops in subobjective 3a, I will investigate student learning with these lessons with either personal meaning maps or teacher-collaboratively-designed pre- and post-tests. Data analysis for personal meaning maps will be qualitative, while data from pre- and post-tests will use appropriate paired quantitative measures.