| NSF Org: |
DGE Division Of Graduate Education |
| Recipient: |
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| Initial Amendment Date: | July 21, 2017 |
| Latest Amendment Date: | July 21, 2017 |
| Award Number: | 1735359 |
| Award Instrument: | Standard Grant |
| Program Manager: |
Daniel Denecke
ddenecke@nsf.gov (703)292-8072 DGE Division Of Graduate Education EDU Directorate for STEM Education |
| Start Date: | September 1, 2017 |
| End Date: | August 31, 2023 (Estimated) |
| Total Intended Award Amount: | $2,995,055.00 |
| Total Awarded Amount to Date: | $2,995,055.00 |
| Funds Obligated to Date: |
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| History of Investigator: |
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| Recipient Sponsored Research Office: |
5801 S ELLIS AVE CHICAGO IL US 60637-5418 (773)702-8669 |
| Sponsor Congressional District: |
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| Primary Place of Performance: |
5801 South Ellis Avenue Chicago IL US 60637-5418 |
| Primary Place of
Performance Congressional District: |
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| Unique Entity Identifier (UEI): |
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| Parent UEI: |
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| NSF Program(s): |
NSF Research Traineeship (NRT), Project & Program Evaluation |
| Primary Program Source: |
04001718DB NSF Education & Human Resource |
| Program Reference Code(s): |
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| Program Element Code(s): |
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| Award Agency Code: | 4900 |
| Fund Agency Code: | 4900 |
| Assistance Listing Number(s): | 47.076 |
ABSTRACT
In the near future, humanity will be confronted with unprecedented challenges as we seek to maintain the economic growth that drives prosperity while managing increasing environmental stresses. In particular, continuing development is necessarily accompanied by rising demand for food, energy, and water. Advancing the understanding of these complex and interacting systems requires training a next generation of interdisciplinary scientists with the computational skills required to exploit growing torrents of relevant data. This National Science Foundation Traineeship (NRT) award to the University of Chicago will produce students who are fully grounded in their respective disciplines and who have the computational skills and breadth of knowledge needed to address and communicate the food-energy-water system in all of its complexity. This project anticipates providing training for thirty (30) MS and PhD students, including fifteen (15) funded trainees, from across the physical, biological, and social sciences, uniting them with a common focus on computation and data analysis. The project's vision is to create a new model for interdisciplinary training that gives students the ability to collaborate and work across fields and to apply cutting-edge computational methods.
The trainees' educational program is structured to generate a cohesive community of young researchers who have regular, in-depth interactions and opportunities to share expertise across disciplines. Program components include: (1) two-week bootcamps prior to the start of each Fall quarter that provide skills training and introduce cross-disciplinary material, including modules on computing, data analysis, and statistics; (2) a year-long core course sequence consisting of an introduction to the food-energy-water system followed by a data analysis practicum in which students work in interdisciplinary teams to analyze datasets; (3) communication and professional development training; (4) international experience opportunities; and (5) community building activities. All educational elements will be opened to students across the University of Chicago whenever possible. An important goal of the program is to improve the recruitment and retention of graduate students from underrepresented groups. Finally, to enable dissemination of the educational model to other institutions, the project will quantitatively evaluate the benefits of the education program and publicly disseminate all educational material to facilitate its use.
The NSF Research Traineeship (NRT) Program is designed to encourage the development and implementation of bold, new potentially transformative models for STEM graduate education training. The Traineeship Track is dedicated to effective training of STEM graduate students in high priority interdisciplinary research areas, through comprehensive traineeship models that are innovative, evidence-based, and aligned with changing workforce and research needs.
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PROJECT OUTCOMES REPORT
Disclaimer
This Project Outcomes Report for the General Public is displayed verbatim as submitted by the Principal Investigator (PI) for this award. Any opinions, findings, and conclusions or recommendations expressed in this Report are those of the PI and do not necessarily reflect the views of the National Science Foundation; NSF has not approved or endorsed its content.
The UChicago NRT-INFEWS program (Data Science for Energy and Environmental Research, or DSEER) was intended to advance understanding of interactions between human society and our environment, and to develop training programs that prepare students to do so. Specific educational objectives included:
- introduce students to interdisciplinary problems in food, energy, and water
- give students access to and understanding of the analytical techniques used in other fields
- build skills in computing, statistics, and data analytics required for students to tackle problems involving large datasets
- pioneer new strategies for skills training in 2-week mini-courses
- improve student communication skills, to both facilitate interaction across disciplines and translating the results of complex problems for non-academic audiences
- provide a structured, supportive introduction to research that can help lower barriers to participation and enhance the success of students from underrepresented groups.
The broader goal of the program was to demonstrate and assess innovative educational practices and models that could then be applied widely both at UChicago and elsewhere.
Our education and training modules brought together student trainees from diverse fields in two-year residencies involving skills-building courses, workshops, weekly research meetings, and collaborative interdisciplinary research projects paired with a practicum on scientific writing. The program served 18 fully funded DSEER trainees (15 PhD and 3 MS students) in wide-ranging fields – Computer Science, Ecology and Evolution, Economics, Evolutionary Biology, Geophysical Sciences, Physics, Public Policy, and Statistics – as well as multiple affiliates. Because no single person can master all skills, an important component of the program was building a diverse community of students who can share expertise and participate in interdisciplinary collaborations. The program’s largest element, Environmental Data Science Bootcamps, also served graduate and undergraduate students across the university. DSEER trainees first took the bootcamps, then helped design and teach courses to others. The goal was to provide students with a means of accessing skills in computation, data analysis, and statistics that are needed for modern research in environmental sciences, but which are not formally taught in many graduate programs. The bootcamps were heavily oversubscribed, showing the depth of demand for new educational practices; in total they served over 800 students over 5 years. (From 2018-2022 they served 72, 102, 100, 305, and 270 students, respectively, with a mixture of in-person and remote participation, on topics such as Fundamental of Scientific Computing, Computing for Research, Time Series Analysis, Data Visualization Strategies, The Statistics of Spatial Data, Demystifying Machine Learning, and Life During Grad School.) As expected, both traineeships and bootcamps proved a strong draw for traditionally underrepresented students. Trainees and bootcamp participants were both 40% female and 17% and 20% URM, respectively, meeting or exceeding the proportions of every field represented other than Public Policy. Final assessments were strongly positive both from trainees and bootcamp participants. Of the program alumni that have completed their PhDs, many have gone on to prestigious postdocs, while 2 of the 3 MS students chose to enter PhD programs.
The DSEER program has begun to produce institutional transformation, given the strong demand it revealed and the positive reviews produced. The bootcamp curricula, materials, and recorded lectures are available online and are being used by multiple groups, and the program overall now provides the basis for a proposed master’s program. Culturally, the program has shown faculty how interdisciplinary projects can produce successful research outcomes and link faculty together, and that time spent on them provides new skills that enhance students’ discipline-specific work. The program has demonstrated the value of skills training and structured, supportive research experiences for "jump starting" graduate students into research, helping them cross disciplinary boundaries, and giving them the tools they need for success in science.
Last Modified: 03/12/2024
Modified by: Elisabeth Moyer
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