Learning Outcomes

ESoS PhD graduates will be able to demonstrate competence in qualitative and quantitative methodologies in the behavioral and social sciences by applying them to original research in environmental topics. They will develop data science skills to be able to work with complex workflows, large data, and/or spatial data science. Students in both subplans will be trained to design and execute rigorous research that advances scientific understanding and impacts policy. We expect that the quantitative learning objectives will be achieved largely through methods coursework and that the topical and institutional knowledge objectives will be achieved through topical depth requirements.

EBS subplan graduates will demonstrate competence in natural and social scientific theories. They will demonstrate epistemological fluency across a range of environmental social sciences theories and methodological approaches, and they will be able to critically evaluate and deploy these frameworks in context-appropriate ways that maintain coherence between the underlying ontological assumptions and epistemological commitments. 

GEP subplan graduates will use and evaluate methodologies and approaches from multiple quantitative social sciences, natural science, and computer science. They will apply knowledge of the policies and institutions that shape environmental outcomes to evaluate and/or address complex sustainability problems.