Innovation and Program Structure
This program trains “T” type interdisciplinary data professionals who harness the power of data for decision making and in advancing the frontiers of data driven science. The “T” metaphor frames the balance of disciplinary depth and interdisciplinary breadth required to address complex data-focused problems. The vertical of the “T” represents disciplinary knowledge (focused and deep) while the horizontal of the “T” represents knowledge across disciplines (broad and multifaceted). Program elements are content-rich (“T” depth) and transferrable across disciplines (“T” breadth). Because foundational disciplinary knowledge and technical skills will vary between graduates from different disciplines, D3M@Tufts trains two types of Data Professionals.
Policy-Savvy Data Experts
These Data Professionals—primarily from STEM disciplines—advance the frontiers of data science and are able to (a) identify, analyze, and solve a problem with 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 have training in policy-relevant skills. They learn to tell the stories their numbers demand, and to interface and collaborate with less-technically-trained decision-makers in their workplace.
Data-Proficient Decision Makers
These Data Professionals—primarily from non-STEM disciplines—use data in policy and decision making. They are 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 science-informed advice in an actionable way and communicate results for effective action.
Modular Course Elements
One of the biggest structural challenges to educating data professionals is the tradeoffs that many students face in putting their disciplinary research and degree requirements on hold to take several additional courses to become a Data Professional. We address this challenge by carefully developing Modular Course Elements (MCEs), drawing contents from existing courses. This training element is transformative, flexible, scalable, and transferrable to any institution and is adaptable to the student’s prior education and future plans.
Most academic preparation is siloed by courses and disciplines, but problems in the real world require collaboration among and input from professionals and practitioners with a broad range of preparation. Students’ immersion in a complex, real problem will provide them experience in full "virtuous circles" of data discovery → data analysis → data insights → data-informed policy → decision making and implementation → effectiveness analysis of proposed interventions. This work involves teams of students and faculty from Tufts as well as invited data professionals from the public and private sectors. This opportunity is be open to all students, but required for D3M@Tufts fellowship students.