IGE: Leveraging Data Science Master Programs to Enhance Professional Readiness in STEM PhD Students

Duke University, Durham NC

Investigators

Abstract

Traditional STEM graduate education is primarily dedicated to training students on how to succeed in academic jobs, despite the fact that most STEM PhD students leave academia after graduation. This traditional approach to graduate education leaves PhD students unprepared to enter the non-academic workforce upon graduation. A lack of adequate preparation not only adversely affects the students themselves, but also leads to missed opportunities for society, since STEM PhD students often have precisely the deep technical background needed to solve the growing number of data-driven problems society faces. This National Science Foundation Innovations in Graduate Education (IGE) award to Duke University will test whether Master-level data science programs, which usually have curricula that emphasize the professional skills and applied data skills missing from most PhD programs, can be leveraged to improve the preparation of PhD students. This project will test the outcomes of combining the applied approach of Master-level data science programs with the depth and experience of PhD STEM students. More specifically, it will determine which aspects of Master-level professional curricula translate to PhD students. The results will provide guidance on approaches to extend the impact of a growing investment in data science Master programs to doctoral-level students and will inform the education community on better preparing the next generation of STEM scientists to work with and improve methods surrounding big data. In so doing, this project will help strengthen the pipeline between universities and non-academic employers. This project will incorporate a select cohort of Duke's STEM PhD students into Duke's Master in Interdisciplinary Data Science (MIDS) Capstone projects with non-academic partners, and include the selected PhD students in the professional development activities of the MIDS program. Duke's MIDS program emphasizes comprehensive training in professional and communication skills in its coursework. The program culminates in a capstone project that requires students to solve a data-driven problem for a partner outside of the university. Students must apply the technical skills, theoretical knowledge, and professional skills they learned in the classroom to a real-life situation that requires interacting with a diversity of both technical and non-technical collaborators. The goal of this research is to determine which of these enhanced experiences can mitigate - and ultimately, overcome - the shortage of doctoral graduates with industry-relevant training, developed professional competencies, and deep domain knowledge. The principles guiding this IGE project stem from research on the use of vertically-integrated, topically-focused research teams as mechanisms to motivate effective, meaningful learning. The MIDS Capstone curriculum is based on evidence-backed practices from the team-based learning and service learning literature. The effectiveness of the project for STEM PhD students will be evaluated using survey, interview, and structured assessment data collected from students, faculty, and Capstone partners, as well as data from potential future employers and students' supervisors after they move to new positions. Outcomes measured will include students' professional skills, students' data science competencies, students' research accomplishments, and reported benefits to non-academic partners. The results will be used to develop scalable mechanisms for universities to extend the impact of their investment in data science Master programs to doctoral-level students. Doing so will strengthen the potential for PhD students to deploy their expertise to solve society's most pressing problems both inside and outside of academia and will provide richer opportunities for organizations to find data scientists with the specialized knowledge needed to solve problems within their area. The Innovations in Graduate Education (IGE) program is focused on research in graduate education. The goals of IGE are to pilot, test and validate innovative approaches to graduate education and to generate the knowledge required to move these approaches into the broader community. 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.