Interdisciplinary Graduate Methods (Spring 2024)

Course Information

COM 682: Interdisciplinary Graduate Methods

Location: BRNG 1245

Class Hours: Tuesdays and Thursdays, 12:00–1:15 PM

Instruction Team

Instructor: Jeremy Foote

Email: jdfoote@purdue.edu

Office Hours: Tuesdays, 2–4 pm in BRNG 2156 or by appointment

Teaching Assistant: Dyuti Jha

Email: bjha@purdue.edu

Office Hours: By appointment

Course Overview and Learning Objectives

This course is an introduction to research methods in the social, behavioral, and health sciences. Doing academic research is about much more than just knowing the correct commands to run in your favorite statistical software. In this course, we will focus on principles rather than techniques; we will consider concepts like how to identify a good question, how to measure the constructs we care about, and how to design research that can address our questions convincingly.

As will be discussed in more detail below, the course will be focused around guest lectures from experts in different aspects of research design from around Purdue. These lectures will typically be on Tuesdays, with a more discussion-based class centered on the same topics held on Thursdays.

I will consider this class a complete success if, at the end, every student can:

• Develop an understanding of the fundamentals of interdisciplinary science and research design across the social behavioral and health sciences.
• Develop practical skills for establishing interdisciplinary collaboration, conducting research in collaborative teams.
• Learn best practices for ethical, rigorous, and reproducible research.
• Gain exposure to a variety of research approaches, including quantitative, qualitative, exploratory, and confirmatory approaches.
• Be able to apply a research method to a topic relevant to your own research.
• Improve critical thinking ability in research design and methods.
• Improve written and verbal communication of research methods.

Required resources and texts

Readings

There are no required textbooks for the class. Readings will come from two places:

• Expert readings: Each of our experts will provide a set of readings to accompany their lecture. It is expected that you will read these before the lecture and come prepared to discuss them.

• Social science readings: For our Thursday classes, I will identify supplemental readings that apply the concept from the Tuesday lecture to the social sciences.

I will put all of the readings on our Brightspace page, and will link to as many as possible from this page.

Course logistics

Note About This Syllabus

Although the core expectations for this class are fixed, the details of readings and assignments will shift based on how the class goes. As a result, there are three important things to keep in mind:

1. Although details on this syllabus will change, I will not change readings or assignments less than five days before they are due. If you plan to read more than five days ahead, contact me first.
2. Check your email. Because this a wiki, you will be able to track every change by clicking the history button on this page. I will also summarize these changes in a announcements that will be sent via Brightspace email.

Class Sessions

On Tuesdays, we will typically hear a lecture from a Purdue professor who is an expert in the topic of that week. Our guest speakers will provide readings and will lead a lecture + discussion about the topic.

On Thursdays, we will review an additional set of readings on the same topic, focused on how the topic relates to doing social scientific research. Readings will be a mix of conceptual and empirical papers and articles, and each week one or two students from the class will prepare and circulate discussion questions, and then lead the in-class discussion.

Office hours and email

• I will hold office hours from 2–4 on Tuesdays and by appointment.
• I am also available by email. You can reach me at jdfoote@purdue.edu. I try hard to maintain a boundary between work and home and I typically respond only on weekdays during business hours (~9-5) but during the week I will generally respond within 24 hours.

Assignments

There will be two main assignments. Each is discussed in detail below but here is a brief summary:

1. Research Project Design: The main outcome of this course will be to design a research project exploring a social science question
2. Discussion Leader: For a Thursday class, you will lead a discussion about the topic of the week

Research Project Design

As a demonstration of your learning in this course, you will design a research project. I strongly urge you to work on a project that will further your academic career outside of the class. There are many ways that this can happen. Some obvious options are to prepare a project that you can submit for publication, that you can use as pilot analysis that you can report in a grant or thesis proposal, and/or that fulfills a degree requirement. The default expectation is that you will prepare the project on your own but it may be possible to work as a small team (maximum 3 people). Team projects are expected to be more ambitious than individual projects. Multiple intermediate assignments will help you to develop your idea and to get feedback from me and others.

The final deliverable will be:

• A proposal of no more than 8 double-spaced pages (page count does not include references, figures, tables, or appendices).
  • Use 12-pt font
  • Papers over the page limit will be penalized
• The proposal should be organized as: a) introduction, b) background/theory, c) methods (specifying data, sampling strategy, measures, etc.), and d) dummy results (sample tables and or/figures).
• A typical methods section for a quantitative study includes subsections on: Data and sampling, study design, dependent variables, independent variables, control variables, and an analytic strategy.
• Measurement instruments and other supplementary material can be included as an appendix to the proposal, and will not count towards the 8 page limit.

There are several intermediate milestones (outlined below), and deadlines to help you accomplish a successful research project. Unless otherwise noted, all deliverables should be submitted via Brightspace.

Hypotheses

Due dates

In class feedback: January 25; Final idea: January 29

Maximum length

1.5 pages

Early on in the class, you will bring three ideas for research projects to class. For each idea, you should provide 1) a brief description of your research topic 2) your research questions, hypotheses, or objectives, and 3) a brief description of data that you could gather or use. In total, your ideas should be no more than 1.5 pages. We will circulate ideas in class and workshop them in small groups. You will then identify what you see as the most promising project, which you will submit on Brightspace.

Literature Review

Due date

February 19

Maximum length

~4-5 pages

Based on the principles discussed in class, you will complete a full draft of a Background / Theory section. While norms differ for the length of literature reviews across disciplines and even across journals, this will be an exercise in making an argument with brevity, and your document should be no more than 5 pages (excluding references).

The paper should make an argument for what the problem is that you are studying, definitions of key terms, concepts, and constructs, and an argument for your hypotheses / research questions. Typically, these will appear near the end of the literature review.

Methods and Dummy Results

Report due date

March 18

Maximum length

~3 pages

You will identify an analytical strategy that is appropriate for answering your research questions or testing your hypothesis. You will explain how you will obtain the data for your study, how you will measure the variables of interest, and (assuming you are taking a quantitative approach), what statistical tests you will run.

You will also create dummy results. You will consider how you would like to explain and visualize your results and create dummy versions of these plots. This can include regression tables, scatterplots, boxplots, correlation tables, etc. You can create these either with synthetic data or create them by hand (e.g., by drawing them).

Final Presentation

Presentation due date

April 22 and April 24

Maximum length

8 minutes

The presentation will provide an opportunity to share a brief summary of your project with the other members of the class. All presentations will need to be a maximum of 8 minutes long. Concisely communicating an idea in the time allotted is an important skill in its own right. Presentations should be uploaded to Brightspace.

Leading Discussions

On the first day, I will ask you to sign up to lead the discussion for two weeks during the class. When leading the discussion, you will prepare a set of discussion questions (typically ~10 questions) based on the readings for that week, which you will circulate to the class at least 24 hours in advance. Typically, we will take a few minutes at the beginning of class for housekeeping / answering outstanding questions, but these discussions will be the bulk of our time each Thursday.

When you are not presenting, I expect you to read the week's readings, read the discussion questions, and come prepared to discuss them.

Reflection papers

As discussed in more detail below, two times during the course I will ask you to respond to a set of reflection questions. These questions are intended to help you to think about what you have learned and accomplished and to craft goals for the remainder of the course. They are also an important way for me to gather feedback about how the course is going so that I can adjust.

Grades

This course will follow a "self-assessment" philosophy. I am more interested in helping you to learn things that will be useful to you than in assigning grades. The university still requires grades, so you will be leading the evaluation of your work. At the beginning of the course, I will encourage you to think about and write down what you hope to get out of the course. Three times during the course you will reflect on what you have accomplished thus far, how it has met, not met, or exceeded expectations, based both on rubrics and personal goals and objectives. At each of these stages you will receive feedback on your assessments. By the end of the semester, you should have a clear vision of your accomplishments and growth, which you will turn into a grade. As the instructor-of-record, I maintain the right to disagree with your assessment and alter grades as I see fit, but any time that I do this it will be accompanied by an explanation and discussion. These personal assessments, reflecting both honest and meaningful reflection of your work will be the most important factor in final grades.

I suggest that we use the following rubric in our assessment:

• 20%: class participation, including attendance, participation in discussions, lectures, and group work
• 5%: Hypotheses
• 10%: Literature Review
• 10%: Methods and Dummy Results
• 25%: Final Project paper
• 15%: Final Presentation including your slides and presentation.
• 15%: Discussion Leadership

My interpretation of grade levels (A, B, C, D/F) is the following:

A: Reflects work the exceeds expectations on multiple fronts and to a great degree. Students reaching this level of achievement will:

• Do what it takes to learn the principles, including looking to outside sources if necessary.
• Design an ambitious, well-developed research project that is ready to implement.
• Take intellectual risks, offering interpretations based on synthesizing material and asking for feedback from peers.
• Sharing work early allowing extra time for engagement with others.
• Do the readings. Be prepared for both Tuesday lectures and Thursday discussion sections, and be actively engaged.
• Write reflections that grapple meaningfully with lessons learned as well as challenges.
• Complete all or nearly all assignments at a high level.

B: Reflects strong work. Work at this level will be of consistently high quality. Students reaching this level of achievement will:

• Be more safe or consistent than the work described above.
• Ask meaningful questions of peers and engage them in fruitful discussion.
• Exceed requirements, but in fairly straightforward ways
• Compose complete and sufficiently detailed reflections.
• Complete nearly all of the assignments at a high level

C: This reflects meeting the minimum expectations of the course. Students reaching this level of achievement will:

• Turn in and complete required assignments on time.
• Be collegial and continue discussion, through asking simple or limited questions.
• Compose reflections with straightforward and easily manageable goals and/or avoid discussions of challenges.
• Not complete assignments or turn some in in a hasty or incomplete manner.

D/F: These are reserved for cases in which students do not complete work or participate. Students may also be impeding the ability of others to learn.

Schedule

NOTE: This section will be modified throughout the course to meet the class's needs. Check back in often. There are links to each day's slides. Note that these are slides from an earlier version of the class and will typically be updated the day of each class.

Week 1: Philosophy of Science (January 8)

Tuesday

Readings:

Agenda:

• Class overview and expectations — We'll walk through this syllabus.
• Sign up as discussant (2 weeks)

Thursday

Guest Speaker: Dr. Sebastian Murgueitio Ramirez (Philosophy)

Readings:

• Scientific Method

Week 2: Research Questions and Hypotheses (January 15)

Tuesday

Guest Speaker: Dr. Torsten Reimer (Communication)

Readings:

1. Section 2.5 of Chapter 2 in Gravetter and Forzano

2. Page 1-7 from Gigerenzer et al.

3. The first two pages of Davis (1971).

Assignments Due:

• Turn in brief reflection about what you hope to get from this class (on Brightspace)

Thursday

Readings:

• Huntington-Klein. "Research Questions". The Effect.
• Schwartz. "The importance of stupidity in scientific research". Journal of Cell Science. BrightSpace
• (Recommended) The rest of Davis. "That's Interesting!". Philosophy of the Social Sciences.

Discussion Leader(s):

Julius

Jake

Week 3: Theories and Theoretical Frameworks (January 22)

Tuesday

Guest Speaker: Dr. Robin Stryker (Sociology)

Readings:

• Robin Stryker. 2006. Chair’s Corner: Challenges to Theory Growth and Growth of the Theory Section. Newsletter for the ASA Theory Section 28(4) 2006.
• Robin Stryker. 1996: “Beyond History vs. Theory: Strategic Narrative and Sociological Explanation, Sociological Methods and Research 24: 204-252. (Reading the first part of the article through p. 332 will be especially helpful.)

Assignments Due:

• Hypotheses Assignment

Thursday

Readings:

• Rojas. Preface. Theory for the Working Sociologist (Purdue University Library Link)
• Healy. Fuck Nuance. Sociological Theory. Brightspace
• Identify three papers from your field and take note of how they talk about theory and theoretical frameworks. Come prepared to discuss both individual-level approaches and higher-level patterns that you see.

Discussion Leader(s):

Julius

Week 4: Concepts and Measurements (January 29)

Tuesday

Guest Speaker: Dr. Louis Tay (Psychology)

Readings:

1. Hoyle, R. H., Borsboom, D., & Tay, L. (2024). Measuring constructs. In D. Gilbert, S. Fiske, E. Finkel, & W. Mendes (Eds.), The Handbook of Social Psychology.

2. Jebb, A. T., Ng, V., & Tay, L. (2021). A review of key Likert scale development advances: 1995–2019. Frontiers in psychology, 12, 637547.

Assignments Due:

Thursday

Readings:

• D'Ignazio, C., & Klein, L. (2020). Introduction: Why Data Science Needs Feminism. In Data Feminism. https://data-feminism.mitpress.mit.edu/pub/frfa9szd
• Goertz. Chapter 2. Social Science Concepts and Measurement
• After reading Goertz, take three papers in your field and see if you can fit them into Goertz's framework: identify the top-level concept, the secondary-level dimensions, and data-indicator levels. Come prepared to discuss and share.

Discussion Leader(s):

Jin Baldick

Week 5: Ethics in Research (February 5)

Tuesday

Guest Speaker: Dr. Jeff Haddad (Health and Kinesiology)

Readings:

• Miller and Emmanual (2008). Quality-Improvement Research and Informed Consent. New England Journal of Medecine.

Assignments Due:

Thursday

Readings:

• The Belmont Report: Ethical Principles and Guidelines for the Protection of Human Subjects of Research (Brightspace)
• Salganik. Ethics. In Bit By Bit

Discussion Leader(s):

Amy Janis

Week 6: Causal Inference (February 12)

Tuesday

Guest Speaker: Dr. Shawn Bauldry (Sociology)

Readings:

1. Barringer, S. N., Eliason, S. R., & Leahey, E. (2013). A History of Causal Analysis in the Social Sciences. In Handbooks of Sociology and Social Research (pp. 9-26). (Handbooks of Sociology and Social Research). Springer Science and Business Media B.V.. https://doi.org/10.1007/978-94-007-6094-3_2

2. Rohrer, J. M. (2018). Thinking clearly about correlations and causation: Graphical causal models for observational data. Advances in methods and practices in psychological science, 1(1), 27-42.

Assignments Due:

Thursday

Readings:

• Cunningham. Introduction. Causal Inference: The Mixtape
• Angrist and Pischke. Chapters 1--2. Mostly Harmless Econometrics (On Brightspace)

Discussion Leader(s):

Amy Janis

Week 7: Experimental Studies (February 19)

Tuesday

Guest Speaker: Dr. Trenton Mize (Sociology)

Readings:

1. Mize TD, Manago B. The past, present, and future of experimental methods in the social sciences. Soc Sci Res. 2022 Nov;108:102799. doi: 10.1016/j.ssresearch.2022.102799. Epub 2022 Oct 3. PMID: 36334924. You can skip Section 6.

2. Hainmueller, J., Hangartner, D., & Yamamoto, T. (2015). Validating vignette and conjoint survey experiments against real-world behavior. Proceedings of the National Academy of Sciences, 112(8), 2395-2400.

Assignments Due:

• Literature Review

Thursday

Readings:

• King et al. A “politically robust” experimental design for public policy evaluation, with application to the Mexican Universal Health Insurance program. Journal of Policy Analysis and Management (Brightspace)

Discussion Leader(s):

Jorge

Week 8: Observational Studies (February 26)

Tuesday

Guest Speaker: Dr. Kristine Marceau (Human Development and Family Science)

Readings:

C J Mann. Observational research methods. Research design II: cohort, cross-sectional, and case-control studies

Munaro et al. 2021. Triangulating Evidence through the Inclusion of Genetically Informed Designs

Assignments Due:

• First self-assessment reflection is due (on Brightspace).

Thursday

Readings:

• Salganik. Chapter 2. Bit By Bit: Social Research in the Digital Age

Discussion Leader(s):

Assignment Due:

Cassidy Munoz, Josh

Week 9: Surveys (March 4)

Tuesday

Guest Speaker: Dr. James McCann (Political Science)

Readings:

• McCann, J. A., & Jones-Correa, M. (2016). Key Design Features of the 2012 Latino Immigrant National Election Study. RSF: The Russell Sage Foundation Journal of the Social Sciences, 2(3), 230-235. (Brightspace)
• Moy, P., & Murphy, J. (2016). Problems and Prospects in Survey Research. Journalism & Mass Communication Quarterly, 93(1), 16-37.

(Brightspace)

• Pew. Writing Survey Questions

Assignments Due:

• Sign up for a Self Reflection Discussion on my calendar at https://jeremydfoote.com/calendar/ (15 minutes)
  • Sometime in the next ~week
  • Please prioritize office hours (Tuesdays from 2-4)

Thursday

Readings:

• Pew. How Public Polling Has Changed in the 21st Century

Discussion Leader(s):

Jin Baldick

Josh

Week 11: Sampling (March 18)

Tuesday

Guest Speaker: Dr. Sharon Christ (Human Development and Family Science)

Readings:

• Sampling: Design and Analysis 3rd Edition, by Sharon Lohr
  • I. Introduction (pp. 1-10, 17).(Brightspace)
    • Sections 1.1 - 1.3.6 and 1.6
  • II. Simple Probability Samples (pp.31-39, 44-46) (Brightspace)
    • Sections 1, 2, and 4

Assignments Due:

• Methods and Dummy Results

Thursday

Readings:

• Geddes (1990). How the Cases You Choose Affect the Answers You Get: Selection Bias in Comparative Politics. Political Analysis. (Brightspace)
• Henrich, J., Heine, S., & Norenzayan, A. (2010). The weirdest people in the world? Behavioral and Brain Sciences. (Brightspace)

Discussion Leader(s):

Jake

Week 12: Interviews and Focus Groups (March 25)

Tuesday

Guest Speaker: Dr. Haocen Wang (Nursing)

Readings: - Intro to reading and appraising qualitative research

- Focus Groups

- Intro to Qual Research

- Morse 2015

Assignments Due:

Thursday

Readings:

• Jiménez, T.R., Orozco, M. (2021). Prompts, Not Questions: Four Techniques for Crafting Better Interview Protocols. Qualitative Sociology (Brightspace)

Discussion Leader(s):

Cassidy Munoz, Claire Rosenberger

Assignment Due:

Week 13: Ethnography and Participant Observation (April 1)

Tuesday

Guest Speaker: Dr. Laura Zanotti (Anthropology)

Readings:

• Madison, D. S. (2020). Critical ethnography : method, ethics, and performance (3rd edition.). SAGE Publications, Inc.

Chapters 1, 2, and 4.

• SUISEEYA, K. R. M., & ZANOTTI, L. (2023). From Method to Methodology at Plural Sites of Agreement-Making. Conducting Research on Global Environmental Agreement-Making, 186.

Assignments Due:

Thursday

Readings:

• [Optional] Geertz, C. (2005). Deep Play: Notes on the Balinese Cockfight. Daedalus. (Brightspace)
• [Optional] Geertz, C. (1973). "Thick Description: Toward an Interpretive Theory of Culture". The Interpretation of Cultures. (On Brightspace)

Discussion Leader(s):

Wei-Lin

Week 14: Mixed Methods Design (April 8)

Tuesday

Guest Speaker: Dr. Zhao Ma (Natural Resource Social Science)

Readings:

Assignments Due:

Thursday

Readings:

• Johnson, R. B., & Onwuegbuzie, A. J. (2004). Mixed Methods Research: A Research Paradigm Whose Time Has Come. Educational Researcher. (Brightspace)
• Creamer, E. G. (2018). Chapter 1. An Introduction to Fully Integrated Mixed Methods Research. (On Brightspace)

Discussion Leader(s): Wei-Lin, Claire Rosenberger

Week 15: Computational Methods and Prediction (April 15)

Tuesday

Guest Speaker: Dr. Jeremy Foote (Communication)

Readings:

• Lazer et al. Computational Social Science. Science (Brightspace)
• Nelson, L. K. (2020). Computational Grounded Theory: A Methodological Framework. Sociological Methods & Research, 49(1), 3-42. https://doi.org/10.1177/0049124117729703
• Foote, J. Shaw, A., Hill, B.M. Communication networks do not predict success in attempts at peer production, Journal of Computer-Mediated Communication, Volume 28, Issue 3, May 2023, zmad002, https://doi.org/10.1093/jcmc/zmad002

Assignments Due:

Thursday

Readings:

• Jens Ludwig, Sendhil Mullainathan, Machine Learning as a Tool for Hypothesis Generation, The Quarterly Journal of Economics, 2024;, qjad055, https://doi.org/10.1093/qje/qjad055

Discussion Leader(s):

Jorge

Week 17: Final Paper Due (April 30)

Assignment Due:

• Final paper due
• Final self reflection due

Administrative Notes

Attendance Policy

It is expected that students will be present, on time, for every class session. When conflicts or absences can be anticipated, such as for many University-sponsored activities and religious observations, you should inform me of the situation as far in advance as possible. For unanticipated or emergency absences when advance notification is not possible, contact me as soon as possible by email. It is your responsibility to seek out support from classmates for notes, handouts, and other information.

Incomplete

A grade of incomplete (I) will be given only in unusual circumstances. The request must describe the circumstances, along with a proposed timeline for completing the course work. Submitting a request does not ensure that an incomplete grade will be granted. If granted, you will be required to fill out and sign an “Incomplete Contract” form that will be turned in with the course grades. Any requests made after the course is completed will not be considered for an incomplete grade.

Academic Integrity

While I encourage collaboration, I expect that any work that you submit is your own. Basic guidelines for Purdue students are outlined here but I expect you to be exemplary members of the academic community. Please get in touch if you have any questions or concerns.

AI Use Policy

While we are in the early days of generative AI, I believe it's clear that 1) it is an incredible tool that is here to stay and 2) we don't yet have norms about what kinds of uses are ethical and acceptable.

In this class, you are welcome to use AI in ways that move you closer toward our class goals. In other words, I want you to identify uses that help you to understand and critique research approaches, develop interesting and impactful ideas, and present your ideas with clarity.

For example, for many of the topics of the course, generative AI would likely be a very good tutor. You can ask an LLM like ChatGPT to quiz you about a topic from the course. You can also use Claude AI to upload a reading, and then ask questions about it to make sure that you understand it.

This article and the accompanying paper give a number of great use cases for AI which promote learning and understanding.

On the other hand, there are obvious misuses of generative AI, such as completely creating a project or assignment that you turn in verbatim. However, there is no bright line that demarcates when AI moves from a helpful editor to the one really doing the work. I trust you to be wise in how you make decisions and to truthfully explain and explore your choices in your self reflections.

Nondiscrimination

I strongly support Purdue's policy of nondiscrimination (below). If you feel like any member of our classroom—including me—is not living up to these principles, then please come and talk to me about it.

Purdue University is committed to maintaining a community which recognizes and values the inherent worth and dignity of every person; fosters tolerance, sensitivity, understanding, and mutual respect among its members; and encourages each individual to strive to reach his or her own potential. In pursuit of its goal of academic excellence, the University seeks to develop and nurture diversity. The University believes that diversity among its many members strengthens the institution, stimulates creativity, promotes the exchange of ideas, and enriches campus life.

Students with Disabilities

Purdue University strives to make learning experiences as accessible as possible. If you anticipate or experience physical or academic barriers based on disability, you are welcome to let me know so that we can discuss options. You are also encouraged to contact the Disability Resource Center at: drc@purdue.edu or by phone: 765-494-1247.

Emergency Preparation

In the event of a major campus emergency, I will update the requirements and deadlines as needed.

Mental Health

If you or someone you know is feeling overwhelmed, depressed, and/or in need of mental health support, services are available. For help, such individuals should contact Counseling and Psychological Services (CAPS) at 765-494-6995 during and after hours, on weekends and holidays, or by going to the CAPS office of the second floor of the Purdue University Student Health Center (PUSH) during business hours.

Acknowledgements

Many of the readings from this course are from syllabi by Christine Sennott and Logan Strother. Thanks as well to the AMAP team for helping to structure and promote the course.