“No one ever made a decision because of a number. They need a story,†explained Nobel Laureate Daniel Kahneman. Telling stories, while remaining true to the data, is a defining challenge of this century. Narratives are persuasive but not objective; numbers are often objective but not persuasive. For science to provide the broadest beneficial impact to society, its findings need to be communicated with both scientific integrity and authentic empathy. Although a growing number of interdisciplinary careers demand this dual fluency, current graduate curricula do not adequately prepare students to master these skills. At many institutions, training remains siloed, and curricular partitions separate those with skills in data science theory, deep domain-specific knowledge, and policy analysis. These partitions do not map well to the real world, where the most pressing social and environmental challenges demand interdisciplinary innovation and collaboration. Effective interdisciplinary collaboration requires a level of exposure, experience, and practice in real-world problem-solving that combines numbers and narratives. This National Science Foundation Research Traineeship (NRT) award to Tufts University will address this need by educating Data Professionals who will synthesize numbers and narratives to design and implement data-driven solutions that are technically efficient and contextually appropriate. The project anticipates training over 140 masters and doctoral trainees: 20 NRT Fellows with stipends, 50 NRT Problem-Focused Immersion Fellows, 60 NRT Travel Awardees, and 12 NRT Module Developers.
This NRT will train two types of data professionals. Policy-Savvy Data Experts—primarily from STEM disciplines—will advance the frontiers of data science and will be able to (a) identify, analyze, and solve a problem with the appropriate data-driven theory, tools, and techniques; and (b) adapt and acquire skill sets to harness emerging data-focused technologies, techniques, and tools. At the same time, they will have training in policy-relevant skills and be able to collaborate with the less technically trained decision-makers in their workplace. Data-Proficient Decision Makers—primarily from non-STEM disciplines—will use data in policy development and decision making. They will be able to (a) collaborate effectively on teams that include users and producers of data, including scientists, engineers, practitioners, and decision-makers with different backgrounds and perspectives; and (b) provide data-informed advice in an actionable way as well as broadly communicate those results for effective action. Trainees will have hands-on experience with a growing portfolio of data science tools and methods that facilitate the rapid translation of data into actionable information. Training will be grounded in finding, defining and resolving problems from both data-rich (i.e., big data) and data-scarce contexts common to many real-world resource problems – including those at the intersection of Food, Energy, Water, and Ecosystems. This NRT model will provide an interdisciplinary theory-practice synthesis by building on two potentially transformative components: (1) Modular Course Elements (MCEs); and (2) Problem-Focused Immersion (PFI). A unique aspect of this NRT is the use of a common database across the MCEs, akin to the adoption of a common book in Writing Across the Curriculum programs. The proposed problem-focused and theory-practice synthesis strategy will foster deeper actionable collaboration among data science experts, domain experts, practitioners, and decision-makers. With this project’s commitment and plan to educate Data Professionals from STEM and non-STEM disciplines, it will actively pursue broadening participation in data science from under-represented groups. Content-rich, modular and adaptable nature of program elements will make them transferrable across disciplines and institutions and sustainable beyond the NRT grant period.
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 program is dedicated to effective training of STEM graduate students in high priority interdisciplinary or convergent research areas through comprehensive traineeship models that are innovative, evidence-based, and aligned with changing workforce and research needs.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
