This blog was written by Rachel Young and Malini Nambiar, STEP Ph.D. students.

The Science Technology and Environmental Policy (STEP) PhD program at SPIA aims to leverage multidisciplinary research approaches to address environmental and technological issues facing our world. Students pursuing this degree recognize the importance of having a foot in both the technical and natural sciences as well as the social sciences. But how does one design a curriculum that trains researchers and scholars with a variety of backgrounds to do interdisciplinary work?

STEP has a bit of a “choose-your-own-adventure” approach to courses, within some reasonable boundaries and guidelines. This gives students flexibility to get additional training in disciplines or methods that they feel they need more support in, while also ensuring that students have a standardized training once they complete their courses. However, this often leaves students, including me, feeling a bit nervous and confused about how to best take advantage of the flexibility.

To provide a general guideline, current STEP PhD students have created the chart below, which lays out a typical schedule for the first two years of coursework. The schedule below showcases some of the required courses that can be substituted across different departments and highlights possible STEP subject-area electives. In sum, the requirements include five required courses, three STEP subject-area elective courses, and a multi-day training session on research ethics.
 

First Year

Fall Semester

• (Optional) SPIA 507c: Quantitative Analysis (Advanced) (audit) OR (Optional) POL 571: Quantitative Analysis I 
• SPIA 511c: Microeconomic Analysis for Policymakers (Advanced)
• * SPIA 521: Domestic Politics, OR * SPIA 541: International Politics, OR * SPIA 561: The Comparative Political Economy of Development
• STEP subject area course

Spring Semester

• SPIA 508c: Econometrics and Public Policy (Advanced) OR POL 572: Quantitative Analysis II
• STEP subject area course
• STEP subject area course
• Elective course (optional)

Second Year

Fall Semester

• POL 506: Qualitative Methods
• * Advanced Economic Analysis course: e.g. SPIA 581c: Energy Economics,
  OR SPIA 562C: Economic Analysis of Development (Adv)
• Elective course (optional)
• Elective course (optional)

Spring Semester

• Study for Generals
• STEP subject area course
• Elective course (optional)
• Elective course (optional)

Notes: * Can be taken in the Fall of the first or second year of the program

STEP subject area courses: A minimum of three courses relevant to the student’s interests, either from within SPIA or from science or engineering departments, selected with approval of the primary advisor and the faculty coordinator of the STEP PhD cluster. There is a lot of flexibility in which courses students can take. Some examples include:

• GEO561: Earth's Atmosphere (Fall)
• SPIA 586D: Topics in Science, Technology and Environmental Policy - Global Environmental Governance (Spring)
• SPIA 598 / POP 508: Epidemiology (Spring)
• SPIA 594O: Behavioral science for environmental decision making (half term, Fall)
• SPIA 594R: Urbanization, migration and climate change (half term, Spring)
• SPIA 594T: International Migration (half term, Spring)
• SPIA 593n: GIS for Policymakers (half term, Fall)
• AOS 527: Atmospheric radiative transfer (Fall)
• POP 501: Survey of population problems (Fall)
• EEB 504: Fundamental concepts in EEB (Fall)
• EEB 533: Theoretical Ecology (Fall)
• ENV 407: Africa's Food and Conservation Challenge (Fall 2017, which approval for graduate level extra project)
• ENE 522: Introduction to the Electricity Sector-Engineering, Economics, and Regulation (Spring)
• MAE 539: Optimization Methods for Energy Systems Engineering (Fall)
• AOS 537: Atmospheric Chemistry (Spring)
• SPIA 727: Directed reading course

When deciding between substitutable required courses and selecting STEP subject-area electives, you may want to consider the following criteria (listed in no particular order):

1. Provides training in relevant research methods.
2. Taught by a potential professor for your committee.
3. Covers theory or readings relevant for your self-designed general exams.
4. Covers theory or knowledge needed for your research projects and post-PhD career.
5. Includes a paper or project component that could lead to a dissertation chapter.
6. STEP required course.

Generally, when selecting courses, it is best to see if the course fulfills at least 3 of the criteria above. For example, in my second year I took a machine learning statistics course, POL 574 Quantitative Methods IV: Statistical Learning, taught by Prof. Dean Knox. This course gave me training in a relevant research method that I need, had a project component that is part of my dissertation, and was required for my general exam. In addition, I was interested in having Prof. Knox as an (informal) advisor. Meaning that the course met 4 of the criteria, even though it was not listed on the SPIA PhD program administrative requirement guidelines (also known as the PhD program “blue sheets”).

In addition to the above criteria, it is important to remember that time spent taking courses beyond the requirements or the scope of your broad research interests could be otherwise spent on research projects, teaching requirements, getting involved in student clubs, and personal time.

In general, when picking classes, it is always good to take a step back and remember that this process is meant to train us to write a dissertation that answers a big question. Your courses should help you get to that end point in the straightest possible path—with a few intellectual tangents along the way.