Introduction to Interpretive Research Designs

Research proposals are increasingly a part of scholarly life. The topics for theses and dissertations require prior approval; funding support usually depends on a committee’s assessment of competing research proposals. Funding committees tasked with assessing proposals ask: Is the proposed topic significant? Will the proposed research address a recognized problem, solve a theoretical puzzle, or shed light on a heretofore unexamined area? Will this researcher bring the needed background, skills, and substantive knowledge to complete the proposed research? And most pertinent to this course: Does the design of the research—its methodology, methods, data and analytic techniques—address the research question in a convincing, coherent manner?

The expectations associated with the term “research design” vary. In some disciplines and/or research communities, the common approach to research design assumes variables-based research (and may even presume that randomized, control experiments are the “best” designs). Other disciplines and research communities are much more eclectic in their approaches to research and embrace methodological pluralism. Still, even in more pluralistic settings, research proposals may be scrutinized by those who have very particular conceptualizations of design and of research. Those conducting interpretive research need to be able to communicate their research purposes, design logics, and evaluative standards to such reviewers.

Research design, then, is a social endeavor. Articulating one’s research question, project and approach to a variety of audiences in a variety of settings is essential to learning what one wants to do. Moreover, if others cannot understand what your project is about that may indicate a lack of clarity in what you are attempting or, at least, that you are not clearly communicating your research goals. From brief oral descriptions of your project over coffee to a more formal written proposal, convincing one’s audience(s) is key. Wherever you are in the research process, this course will enable you to deepen your understanding of your topic, familiarize yourself with the key elements of interpretive research design, and practice articulating (and perhaps even defending) the approach you have chosen to your research question.

In addition to lecture and class discussion, students will work together in ‘lab sessions’ during the afternoons and/or evenings (Days 1-4). Detailed instructions will be given for these sessions, but the general approach is that students will draft and share sections of a research proposal with members of their research groups. Re-writing will occur over the four days to produce a short, written proposal as a record of learning from the course. On Day 5, participants will orally present their research proposals to the class. For those who already have written proposals, there are two options: (1) Revising the proposal with a particular funding agency in mind. (2) Drafting a related or new proposal as part of an imagined (or actual) research agenda. (Note that assignment details for all labs will be made available to registered participants.)

• Lab 1. One-page draft – research question and significance in the context of identified literature.
• Lab 2. Edit, refine research question and literature; draft discussion and justification for anticipated data generation.
• Lab 3. Draft discussion of choice of analytic methods.
• Lab 4. Revise to produce proposal coherence across questions, data, analysis, anticipated contributions.

A caveat. Effective research design is highly contextual. Effectiveness depends on: the state of knowledge on a particular topic including areas of consensus and debate; the interests, talents, and methodological predispositions brought to that topic by the researcher; disciplinary conventions as well as the scholarly conversations and research communities engaged by the research; access to sites and data and ethical contingencies and constraints that may limit designs; and the funding priorities of governmental and private sources. In short, there is no universal template for achieving appealing, convincing, and fundable research proposals. An advantage of class members coming from a number of disciplines is that discussions and lab exercises should raise everyone’s awareness of these contextual factors (which may be tacitly known within disciplines and, thus, not actively discussed or analyzed).

Course objectives

• To learn to recognize and to formulate interpretive research questions;
• To understand and acquire the vocabulary appropriate to interpretive research design;
• To recognize and add to one’s research capacity an abductive logic of inquiry;
• To practice assessing the connections between research questions, forms of data, and implied contributions;
• To be able to articulate the rationale for interpretive research including its approach to design, access, selection, and evaluative criteria.
• To produce a brief research proposal as a record of course learning.

What this course will not cover

• Although any research proposal must include its choice of and justification for its particular approaches to data analysis, the specifics of particular interpretive analytic techniques will not be covered in this course.
• Although the basic philosophical presuppositions of interpretive research will be introduced (i.e., its constructivist ontology and intersubjectivist epistemology), in-depth consideration and discussion of philosophy of social science is beyond the purview of this course.
• Although the course interrogates the meaning of the term “mixed methods,” it does not take up the approach to design envisioned by, e.g., the Journal of Mixed Methods Research.

Required texts

Schwartz-Shea, Peregrine, and Yanow, Dvora. 2012. Interpretive Research Design: Concepts and Processes. New York and London: Routledge. [SS&Y in the daily list]

Yanow, Dvora, and Schwartz-Shea, Peregrine, eds. 2014. Interpretation and Method: Empirical Research Methods and the Interpretive Turn. 2nd ed. Armonk, NY: M.E. Sharpe. [Y&SS2 in the daily list]

Additional articles:  Please see detailed day-to-day schedule below.

Pre-course assignments

#1 Background reading assignments to be completed before the course begins:

Schwartz-Shea, Peregrine. 2015. “Interpretive Social Science.” Encyclopedia of Political Thought. Edited by Michael T. Gibbons, Diana H. Coole, Elisabeth Ellis, and Kennan Ferguson. Wiley-Blackwell Publishers.

From the required text Interpretation and Method, 2014:

• Wherefore “Interpretive?” An introduction, pp. xiii-xxii.
• Chapter 1, Yanow, Dvora, Thinking Interpretively: Philosophical Propositions in the Social Sciences,” pp. 5-26.

#2 Introductions:

Once the course is confirmed, I will be asking you to briefly introduce yourself via email to all those registered. In particular, I would appreciate your answering the following questions:

• Are you currently working on a research proposal?
• What are the primary methods of data generation that you plan to use or have used?
• What specific questions or concerns, if any, are you bringing with you to the course?

If I receive your introductions by 20 July, I will try to plan to address the mentioned questions/concerns during the course.

No prerequisite knowledge is required to take this introductory course. Those who will benefit most from the course are those currently planning research (i.e., working on a research proposal) or who will do so in the future; those who have completed field research and are in the “writing up” stage will also benefit from several parts of the course, such as understanding and communicating (e.g., to reviewers) what the appropriate quality standards are for assessing interpretive work. (Note that the pre-course assignments, given below, include basic introductions to the nature of interpretive research. For those who wish to deepen their background in this area, see: the supplementary readings section below for additional recommended readings on philosophy of social science; the sources listed on p. 44 of the required text, Interpretive Research Design.)