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!
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