A month ago, the Field Atlas of AI in Education was a paragraph in an email I sent to our learning design team, half expecting to be told it was too much.
This week, I ran a full test session with a working prototype.
The Atlas is a shared, evolving knowledge artifact that students in our EdM in AI & Education will build together: real cases, real tools, real policies, analyzed by practitioners and inherited by every cohort that follows. Instead of discussion posts that disappear at the end of the term, students write for a real audience that will actually use their work.
The part I tested this week is the AI interlocutor. It reads a student's draft entry and asks structured questions that push toward deeper analysis. It never rewrites. It never supplies the interpretation. In my test session it noticed that my draft failed to specify the funding context of the source I was analyzing, and instead of telling me what to add, it posed a design question back and let my answer determine the revision.
That is the difference between AI that does the thinking and AI that demands it.
None of this exists without Wendy Colby's incredible team at BU Virtual. Nour Mounajed and Michaela Dengg, Ph.D. did not just build what I described. They interrogated the idea, made design decisions I had not thought to make, and returned a system that is better than the one I imagined, in a month. That is not production support. That is intellectual partnership, and it is the difference between a course that talks about thoughtful AI and a program that embodies it.
One of the great privileges of this work is getting to think alongside people whose craft sharpens your own. This team does that every time.
So much of the best work in higher education happens like this: behind the scenes, between drafts, in design meetings nobody live-tweets. Learning designers rarely get public credit for the thinking that shapes what students experience. They should. Consider this a small correction.
And it is exactly this kind of collaboration that makes our EdM in AI & Education what it is. We are not teaching about AI from a safe distance. Students learn inside systems built on the very principles we teach, designed by people who sweat every pedagogical decision. If you are an educator trying to figure out what AI means for your classroom, your school, or your career, this is the program where you will not just study that question. You will live it.
https://lnkd.in/eaHrCisX Boston University Boston University Wheelock College of Education & Human Development