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Board # 78 : Training Students with T-shaped Interdisciplinary Studies in Predictive Plant Phenomics

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Conference

2017 ASEE Annual Conference & Exposition

Location

Columbus, Ohio

Publication Date

June 24, 2017

Start Date

June 24, 2017

End Date

June 28, 2017

Conference Session

Graduate Studies Division Poster Session

Tagged Division

Graduate Studies

Page Count

12

Permanent URL

https://peer.asee.org/27925

Download Count

34

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Paper Authors

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Julie A. Dickerson Iowa State University

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Julie Dickerson is a Professor at Iowa State University in the Department of Electrical and Computer Engineering (ECpE). She served as a program officer at the National Science Foundation in the Advances in Biological Informatics Program and the Postdoctoral Research Fellowships in Biology Program in the Biology Directorate as the lone engineer. She has also served as the Chair of the Bioinformatics and Computational Biology program at Iowa State University.

She holds a B.S. degree in electrical engineering from the University of California, San Diego. She received her master's degree and Ph.D. in electrical engineering from the University of Southern California. She designed radar systems for Hughes Aircraft Company and Martin Marrietta while getting her Ph.D. Her current research activities are in systems biology, bioinformatics, bioinformatics education, and data visualization. She was a Carver Fellow in the Virtual Reality Applications Center and a member of the Baker Center for Bioinformatics in the Plant Sciences Institute and the Human-Computer Interaction Program. Dr. Dickerson has over 120 peer-reviewed publications in journals, book chapters, and conference proceedings and supervises research projects funded by the National Science Foundation, ARDA, and the United States Department of Agriculture.

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Theodore (Ted) J. Heindel Iowa State University Orcid 16x16 orcid.org/0000-0002-8142-9938

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Theodore (Ted) Heindel is currently the Bergles Professor of Thermal Science in the Department of Mechanical Engineering at Iowa State University; he also holds a courtesy professor appointment in the Department of Chemical and Biological Engineering. He directs the Experimental Multiphase Flow Laboratory at ISU, which houses a unique instrument for performing X-ray visualization studies of large-scale complex fluid flows. This instrument can also be used to visualize root systems for phenotyping. Ted’s teaching emphasis is in the area of thermal science (thermodynamics, fluid dynamics, and heat/mass transfer) and measurement and instrumentation. He has also developed two new graduate-level courses: "ME 531: Advanced Energy Systems and Analysis" and "ME 585: Fundamentals of Predictive Plant Phenomics." He has been recognized for his teaching efforts through the College of Engineering’s Superior Engineering Teacher of the Year Award, and was twice selected by graduating seniors as mechanical engineering’s Professor of the Year. He has co-authored one book and published over 75 peer-reviewed journal papers and over 220 conference papers, abstracts, and technical reports. Ted received his B.S. from the University of Wisconsin – Madison and his M.S. and Ph.D. from Purdue University, all in mechanical engineering with an emphasis in the thermal sciences

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Carolyn J. Lawrence-Dill Iowa State University

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Carolyn Lawrence-Dill has devoted the last 20 years to developing computational systems/solutions that support the plant research community. Her work enables the use of existing and emerging knowledge to establish common standards and methods for data collection, integration, and sharing. Such efforts help to eliminate redundancy, improve the efficiency of current and future projects, and increase the availability of data and data analysis tools for plant biologists working in diverse crops across the world. Carolyn led the USDA’s maize model organism database MaizeGDB (http://maizegdb.org/) for a decade, currently coordinates the development of the information platform for the US maize Genomes to Fields Initiative (http://www.genomes2fields.org/), and is an active member of the community working to put in place methods for phenotype data access, analyses, and re-use. To learn more about her contributions to plant biology and information access, visit https://scholar.google.com/citations?user=bHQPmtEAAAAJ&hl=en. In addition to research and development efforts, Lawrence-Dill is a coPI on the NSF-funded grant "NRT: Plant Predictive Phenomics," which supports the development of mechanisms to train the next generation of scientists and engineers to work together on shared problems that involve plant biology, data sciences, and engineering.

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Patrick S. Schnable Iowa State University

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Jill Wittrock University of Northern Iowa

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Jill Wittrock is the Assistant Director at the Center for Social and Behavioral Research and an Assistant Professor in the Department of Political Science at the University of Northern Iowa.

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Mary E. Losch University of Northern Iowa

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Mary Losch is Professor of Psychology and Director of the Center for Social and Behavioral Research at the University of Northern Iowa. Her classroom teaching has included courses in Psychology of Gender Differences and graduate courses in Research Design and Program Evaluation. In addition to her administrative and teaching duties, she has designed and directed over 90 survey, evaluation, and applied social science research projects. Her research publications span survey methods, social science and health disciplines. She is adjunct clinical associate professor at the University of Iowa College of Public Health and also serves on the Advisory Board for the University of Iowa College of Public Health. She is active in the American Association for Public Opinion Research (AAPOR) and has been elected twice to the Executive Council. Dr. Losch also has an extensive background in human research participant protections including previous service as chair of the University of Northern Iowa IRB.

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Abstract

Modern sensors and data analysis techniques make it feasible to develop methods to predict plant growth and productivity based on information about their genome and environment. The NSF Research Traineeship (NRT) Predictive Plant Phenomics (P3) Specialization implements the T-training model proposed by the American Society of Plant Biology (ASPB) and described in “Unleashing a Decade of Innovation in Plant Science: A Vision for 2015-2025.”[1] The goal of the P3 program is to prepare graduate students with the understanding and tools to design and construct crops with desired traits that can thrive in a changing environment. Students with “T-shaped” experiences will differ from traditional STEM graduate programs that produce students with deep disciplinary knowledge in at least one area. This depth represents the vertical bar of the "T". The horizontal bar represents their ability to effectively collaborate across a variety of different disciplines [2], which is the focus of P3.

The first cohort of students began their training in August 2016 with a two-week “boot camp” short course to introduce the students to the basic topics they will need to succeed. The four-credit P3 core graduate course (Fundamentals of Predictive Plant Phenomics) taken the first year of the program expands upon the boot camp and is comprised of classroom and hands-on laboratory components. The P3 core course has two key objectives: 1) bring all students’ knowledge up to the same level for issues that pertain to plant phenomics, sensor engineering, and data analysis, and 2) begin the process of teaching students the needed terminology to speak across disciplines. A companion paper submitted to the ASEE Graduate Studies Division discusses the first offering of this course. Additionally, the collaborative spirit required for students to thrive will be strengthened through the establishment of a community of practice to support collective learning (i.e., a P3 graduate learning community).

The P3 program is being evaluated both internally and externally. The internal evaluation focuses on metrics such as student recruitment and retention, program outcomes, and student performance. The external evaluation includes pre-test and post-test designs for quantitative assessments of how well the program is developing scientists and engineers with broad skillsets to address the research needs to increase understanding of agricultural production. Qualitative measures include in-depth interviews and focus groups of student students. Evaluation activities follow a recursive design so that the project can be continually informed and improved by the evaluation findings in real time. This evaluation has already been applied to the initial boot camp activities. The overall view of the activities was positive from both the trainees and program administrators. However, the students felt that the introductory sessions should be more hands-on and structured more for beginners in the field. This input will be applied to future designs.

1. American Society of Plant Biologists, Unleashing a Decade of Innovation in Plant Science - A Vision for 2015-2025, in Plant Science Decadal Vision. 2013, American Society of Plant Biologists,. p. 36.

2. T-Summit 2016, “What is the T?”, http://tsummit.org/t, viewed October 2016.

Dickerson, J. A., & Heindel, T. T. J., & Lawrence-Dill, C. J., & Schnable, P. S., & Wittrock, J., & Losch, M. E. (2017, June), Board # 78 : Training Students with T-shaped Interdisciplinary Studies in Predictive Plant Phenomics Paper presented at 2017 ASEE Annual Conference & Exposition, Columbus, Ohio. https://peer.asee.org/27925

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