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.

Teaching with the Tech-Whose-Name-We-All-Dread

 A Year Ago, I Panicked. (Again.)

A year ago, I was deeply uneasy about the sheer ubiquity of the Tech-Whose-Name-We-All-Dread (TWNWAD). It was everywhere, dominating the news, colonizing our collective headspace, and creeping, rather insidiously, into my classroom.

Suddenly, students were submitting these beautiful looking, very mediocre assignments. Impeccable grammar. Endless em dashes. Polished prose. And the most painfully trite arguments imaginable, all delivered in response to carefully designed written prompts.

This, of course, triggered yet another existential crisis. (I get those when confronted with particularly bad papers.)

The horrifying thought: everything I had learned, everything I had taught so far, was slowly becoming useless. Obsolete.

And then came the second realization, arguably worse. TWNWAD was here. It wasn’t going away. And pretending it didn’t exist was no longer an option.

Enter the Sane Saviors

Thank the universe for sane, thoughtful guides, most notably Ethan Mollick, who operate in the same management education space but talk not about moral panic, but about embracing, learning, and evolving alongside TWNWAD. His book Co-Intelligence was, quite genuinely, a lifesaver.

So I asked myself:

How do I understand this thing and adapt it for the classroom so that it becomes a pedagogical tool rather than an academic menace?

That question eventually became AI in Action.

How AI in Action Was Born

AI in Action is a semester long project I designed for my graduate course, MGMT 628: Human Resource Development, first introduced in Winter 2026. The core idea is simple. If AI is reshaping Learning and Development, then students shouldn’t just talk about it. They should build with it.

In this project, students learn about artificial intelligence by creating their own AI powered tools. Specifically, they build a Retrieval Augmented Generation (RAG) training bot designed to deliver HRD content.

The project unfolds in stages:

• Students author professional training documents on a chosen HRD topic 

• They design the bot’s persona and system prompt 

• They upload and curate content.

• They test the bot extensively.

• Finally, they produce an analytical report examining bias, data security, hallucination risks, trust, and regulatory compliance.

Students critically engage with bias amplification, data security, hallucinations, and ethical risk. They grapple with transparency and accountability in AI driven training systems and explore how regulation plays out in corporate Learning and Development contexts. These ideas surface in the term paper and classroom debates, so the technical and societal dimensions of AI stay tightly linked.

In designing the project, I followed AACSB’s guidance for teaching AI across three key domains: understanding the technology, using the tools, and evaluating their impact.

And honestly, Learning and Development is the perfect test bed. SHRM keeps reminding us that AI is rapidly reshaping L&D, so where else should we experiment?

Building the Bot (and Loving My Students even more)

Armed with an EMU e Fellows grant (which covered a Claude Pro license) and more than a little optimism, I set out this semester.

The results exceeded expectations.

My students were skeptical, which I loved. Overly compliant people don’t question assumptions, and they certainly don’t help with exploration. We started by developing training materials on metrics used in Learning and Development. Our textbooks mention these, but never consistently. Worst case scenario, we’d at least walk away with a solid glossary of T&D metrics.

Then we defined the learner persona and the training bot persona, because, training without a persona is just depressing.

Finally, we built a no code RAG bot using Claude Pro.

Click here to access our Training Bot

There are moments when I absolutely adore my students. Our bot turned out to be mean. Unkind. Sarcastic. Possibly a little too much. But mercifully, it wasn’t the cloying, aggressively encouraging creature we initially imagined.

And somehow, it worked. Really well.

What This Project Actually Did

This project wasn’t just about wrestling with a new technology. Sure, we could have coded more elegantly. We could have reduced bias further. We could have refined the language.

But it forced me to think deeply about what I teach and why. I found myself becoming philosophical about the nature of work and what parts of it are genuinely human versus purely mechanical.

Designing this experience pushed me to reflect on training design, content creation, evaluation, and most crucially, the learner experience itself. I learned far more about Learning and Development by trying to teach it through AI than I ever expected.

Taking It Public

At the Gen AI Spring Summit 2026 at Eastern Michigan University, I had the privilege of sharing this journey during a panel discussion alongside one of my students. Reflecting together on how the project challenged both our technical abilities and our professional assumptions was deeply rewarding.

The audience response was phenomenal.

Yes, we had the usual code checkers telling us all the ways we were “wrong” (useful, actually). But we also had incredibly thoughtful conversations about what the bot was, what it did, and how its architecture shaped the interaction itself. Watching people engage so seriously, and curiously, with the project reminded me why I do this work.

Because sometimes, confronting the TWNWAD doesn’t mean surrendering to it.

It means learning how to argue back, thoughtfully, critically, and maybe with a little sarcasm. And always the coffee!

(image generated by Google's Nano Banana 2 model)