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
