I’ll be teaching a course on globalization again in the spring term. As usual, I’ve built the course around a StoryMap ethnography project, but I’m incorporating field research in response to how I’m seeing students (mis)use AI. The field research component comes from Amanda’s Best Breakfast in Town, which I used once before in 2019. This time each team of students will need to identify a Best Coffee in Town by evaluating the effects of coffee production in some other country and how and why the coffee is consumed locally. At minimum students might learn a little about the off-campus community. Best case scenario is that they talk with the people who produce the coffee and learn something about them.
Project outcomes thus now depend much more on engaging with the physical world than they used to, and I’ve changed my assessment metrics accordingly by down-weighting text-driven activities that students can offload to AI, such as the location and synthesis of published source material. Students will now need to do a better job with the harder elements of the project, which now comprise a far greater share of assignment grades — which should have the added benefit of helping me continue to combat grade inflation. To illustrate this, here is the rubric I’ll be using to score the final, complete versions of students’ StoryMaps:
