Teaching Research Methods- one Fake Corporation at a Time.

 I have a complicated and deeply affectionate relationship with MGMT 610 (you can read my earlier post about how I fell in love with teaching Research Methods.  If you haven't read that post yet, go ahead -  I'll wait!).

The official course description of MGMT 610 calls it "the study and application of diagnostic and quantitative methods for problem diagnosis, implementation, and evaluation of the organizational development process and human resource management practices." Accurate, but sounds exactly like the kind of sentence that makes a student's eyes glaze over before the semester has even started.

In reality, beneath the verbiage, it is a course on how to figure out what is really going on in an organization using data! Data, carefully collected and honestly analyzed. It involves statistics, but goes well beyond statistics into the messier, more interesting territory of research design, data collection, and the art of presenting findings to decision-makers. And best of all, this is not a course about talking about using research and thinking about good research design; instead, students can actually get involved with doing real research.

Here is a problem I spent several semesters trying to solve. It is difficult to compress applied organizational research into a college semester. Doing real organizational research properly takes time that a semester simply does not have. One has to find a partner organization willing to be studied, identify a problem that is both meaningful and researchable, design a survey, gain Institutional Review Board approval (which takes more than a few weeks), collect data, and then actually analyze it. It would essentially be a full-time job. Something had to give, and I was not willing to let it be the learning.

So, I built GPV Inc.(If you're curious about GPV Inc., drop me a note -  I'm happy to share more.)

(image Generated by Gemini, 2026)

GPV Inc. (named after a little someone, the most significant person in my life) is a fictional multinational consulting firm, with organizationally messy problems. Not quite the firm you would want to work in, but definitely one that you want to study.  Rising turnover. A culture that worked beautifully when the company was small, but has become increasingly uneven as it has scaled. A workforce spanning four generational cohorts with very different relationships to work, flexibility, technology, and career development. And hovering over all of it, the specter of the Tech-Whose-Name-We-All-Dread.

The case is structured as a choose-your-own-adventure. Students read through the organizational context and then meet the HR analytics team. I designed these characters deliberately- reflecting the diversity students are likely to encounter in actual workplaces across gender, background, and professional orientation. And each one pushes against stereotype rather than confirming it. Each member of the team is investigating a different people management problem, and each problem becomes a potential research project. Students choose the one that genuinely interests them and spend the semester pursuing it.

I chose the contemporary tensions embedded in generational conflict, AI anxiety, questions of psychological safety, and manager effectiveness because these issues are showing up in real organizations right now. Students, with or without workplace experience, tend to recognize them immediately because they are not invented for pedagogical convenience.

The assignments of the course are also designed to scaffold the research process from beginning to end, so that by the time students sit down to write their final white paper, they have already done every component of it - defined their research question, conducted a literature review, built a survey instrument, collected and cleaned data, and run their analyses. The white paper is where it all comes together into something a decision-maker can read and act on. The fictional audience for that paper is Celia Hargrove, GPV's Chief People Officer, who wants findings grounded in data, not intuition, and recommendations specific enough to actually follow.

I wanted GPV Inc to deliver a consistent thread running through the entire semester in the form of a single organizational story that grows in complexity as students grow in capability. That way, every new technique they learn has some context. I hope my students learn about the process of research- in its messy, frustrating, annoying glory!

And I am hoping they also find GPV Inc. genuinely interesting, because exploring how organizations understand their own people and what it takes to get that understanding right is something I have never stopped finding fascinating myself. And I also hope they enjoy the course, even the assignments and research paper, because I certainly had a lot of fun building it.

NOT a Statistics Course: How I fell in love with teaching Research Methods

    As the professor, I am technically not supposed to have favorites, but Diagnostic Techniques and Research Methods (MGMT 610) is one of mine. Every semester, it teaches me something new. 

  Funny thing is, I wasn’t even sure I’d like it when I first got assigned the course. I was a brand-new Assistant Professor, there wasn’t a single textbook that wasn’t drowning in statistics, and everyone who’d taught it before had their own take. So I did what made the most sense: I taught it the way I wish research methods had been taught to me. 

    I mapped it out like a research study- process and application. The course scaffolds across the semester: starting with the business case for research and the literature review, then moves into research design, variable selection, hypotheses development, codebook set up, sample size analysis, survey creation, data collection and finally data analysis. Only the basics for the last part- SPSS only with t-test, ANOVA, and simple regression. No Moderators. No mediators (Alas!)

    I almost got "THIS IS NOT A STATS COURSE" tattooed on my forehead! I placed the message everywhere- on the syllabus, on the LMS, and in emails. 

    Designing the course was the easy part (as if!). Teaching it was where the learning curve hit! I ran headfirst into the tension of teaching for evaluation and teaching for learning. It's hard for students to focus on learning when every mistake costs them points. So I introduced a "resubmit with changes to improve your grade" policy. 

    Then came the online version. Then the qualitative research component, and then managing group dynamics. Then, helping students find parsimonious, research-worthy problems.  And now? AI!

    Always a learning curve, always a new challenge!