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This mixed methods research paper explores whether and how different types of funding influence STEM doctoral students’ time to degree completion and degree progress. We developed regression models using Survey of Earned Doctorates, complemented by qualitative interviews with 38 STEM doctoral students. Our results show that primary funding and number of funding types were significant predictors of time to complete their doctoral program. Further, different types and sequence of funding may influence doctoral students’ individual productivities on research, teaching, and networking. STEM departments and advisors can support doctoral student agency by providing suitable funding types related to their career goal and proper sequences of funding which align with their program process.
Nathan Hyungsok Choe, The University of Texas - Austin
Maura J. Borrego, The University of Texas - Austin
Timothy J Kinoshita, Virginia Polytechnic Institute and State University
Kevin A. Nguyen, The University of Texas - Austin
David Knight, Virginia Polytechnic Institute and State University