- Winter 2023
Syllabus Description:
Course Description:
The course is designed as a workshop to introduce advanced graduate students to combining field methods from across the social sciences and to allow students to make significant progress on their own research strategies.
Required Readings:
William Trochim and James Donnelly, The Research Methods Knowledge Base 3rd Edition, Atomic Dog, 2006.** Available Online at Amazon, make sure you buy the right edition, I will also make the text available in E-Copy on Canvas if you choose not to purchase **
All other readings will be provided by Professor Long and available on Canvas.
Course Objectives:
The overall goal of the course is to help students make progress on their research strategies by learning about and using a combination of various social science methods and forms of data collection from the “field.” Narrowly, the class has relevance for students in American politics, international relations, comparative politics, public policy, economics, area studies, and empirically-oriented political theory. More broadly, the methods we cover will come from a range of social science disciplines, including anthropology, economics, political science, public health, data science, and sociology. While many students’ research strategies will fall within the realm of political science or public policy because either your independent or dependent variables will include something “political” or “policy” oriented, our approach to field methods will remain agnostic as to particular questions or variables.
I have designed this course not only as an introduction to various field methods, but also as a “workshop” to include four main goals for each session. The first goal is to introduce students to the main research strategies for scholars in the social sciences who gather data from the field. This includes readings marked as “Method” and will typically also include a short lecture from me on the method specifically in class.
The second goal is to read and discuss what I consider to be examples for each method, indicated by “Applied” readings. We will discuss the application of the method in these readings in class. Students will note that many of the “applied” readings are authored by me and/or my colleagues. This is not because I believe these applied readings are particularly high quality, but rather that they are demonstrative of the week’s method and I’m able to share with students some firsthand research design and implementation aspects of the papers that I will convey.
The third goal is a “Practicum” regarding important project components to writing research proposals and papers, applying for funding, ethics and IRB, data transparency and replicability, and other “process” concerns from starting to think about research designs to seeing it in published form. The “practicum” part of class will be a short mini-lecture and demonstration by me.
The fourth goal is to allow students to make progress on and receive feedback regarding their own research strategies as the course develops with weekly “Assignments for Class.” Students will be asked to post these short assignments to Canvas with a Google Document that they share with me before the start of each week’s class session. Typically, the previous week’s “Practicum” will directly relate to the form and content of the current week’s “Assignment for Class.” Professor Long will provide feedback on students’ assignments each week and as the course goes on in the shared document.
In class, we will think holistically about the range of methods used in the social sciences and how we can combine them to answer our research questions. This will be done in the context of what we know about the “experimental” ideal and causal inference from the medical and physical sciences, and how that has informed research design strategies and concerns with validity in the modern social sciences and program design and evaluation.
As such, you will notice the course is organized around modules that specify threats to internal validity and external validity based on the assignment rule of treatment variables and how research findings are then relayed to academic and policy audiences broadly. Therefore, while this course presents a particular, if increasingly conventional and standardized, approach to social science research design and policy evaluation, it is atypical compared to other “methods” classes that students may have encountered.
First, this is not a class in experimental design: while we will advance the assignment rule as a core concern shaping problems of inference and much of my own work involves field and survey experiments, the class will not focus exclusively on experiments. While UW does not currently offer an “experiments only” class (I may some day….), the readings covered in Module 1 provide important guidance and resources that students who are interested in experiments should follow up on with respect to the particular, and increasingly complex and controversial, threats to experimental validity (as particularly discussed in development economics and development-oriented comparative politics).
Second, this is not a class in qualitative design: while this course counts for the “Multi-Method and Qualitative” certificate at UW, students will quickly learn that Professor Long makes no ontological, methodological, or mathematical distinction between “quantitative” and “qualitative” data. In this class, I present “qualitative” methods as an important consideration that underlies *all* research design strategies, in particular measurement (as we review in Module 1). However, the readings covered in Modules 2 and 3 provide importance guidance and resources that students interested in applied qualitative methods should pursue (particularly in UW’s Sociology, Anthropology, and Law departments; I am happy to offer advice on that).
Third, this is not a class in quantitative methods: see points above on experiments and qualitative research. The same logic also applies to students taking this course in the quantitative methods sequence at the Center for Statistics & Social Sciences. Students will note that unlike most of the classes at CSSS, this is a “design” based course, not an analysis based course. As I will highlight throughout the course, my approach to research design and policy design and evaluation is that most of the important and hard decisions should and have to be made at the design stage. This course focuses on what that means with respect to then gathering “found” or “created” data in the field and how one addresses threats to inference with such data. This differentiates it from more introductory research design, causal inference, or philosophy of science classes, but it also differentiates it from advanced methods classes that focus specifically on quantitative data analysis. However, the course does requires that students already have some familiarity with econometrics in order to understand the design, results, and discussion of the applied papers we read.
Course Requirements:
Readings:
Students are expected to complete all readings and be prepared to discuss them in workshop. There will be no formal presentations of the readings. Students should expect me to adopt a “cold-call” method typical in law, business, and professional school.
Weekly Assignments:
Each week, students will see instructions on what parts of their research strategy they should come prepared to discuss. I will ask that students post short paragraphs or writing to this effect to Canvas in our shared Google docs, and simultaneously, they should keep a running document that includes each week’s component, as this will help form the draft of the final research strategy. Each student should keep up with these assignments to ensure that they are making progress on their research strategies throughout the quarter.
NB: Students will naturally begin the class thinking that a certain weeks’ method is more “interesting” or “germane” to their work than another week’s. While this will be the case for many students and their final research strategies will reflect this, one goal of the course is to push students to always think about the range of methods they could use to answer research questions – even if they never actually utilize that method for a particular project. No matter what, in your career, you will need to consume all manner of research methods that you may not particularly specialize in. Moreover, no matter what you think now, I guarantee you things will change and you will grow in your interests and the world will change and cause you to re-evaluate your past notions and trainings on methods. That’s good! It’s just important at this stage to keep an open-mind and allow oneself to learn.
Final Research Strategy:
By the end of the quarter, students should use the weekly assignments and feedback to produce a significant writing assignment that brings together a multi-method research plan that builds on each weekly assignment. This could take the form of a research proposal for the NSF dissertation grant, program design and evaluation plan for an organization or government agency, an MA thesis, a draft prospectus, draft chapters from a dissertation, an SSRC application, or any other writing product that clearly states a question, theory, hypotheses, and strategy for collecting data through various methods in the field. Students should plan the format of the research strategy strategically to meet the goals of where they are in the program. NB: I do not expect students to have actually conducted the research and analyzed the data that they plan for the research strategy. Therefore, the assignment is just that: a plan for doing research, not a completed research project. I will discuss this more in class.
Course Evaluation:
Weekly Participation: 30%
Final Research Strategy: 70%