Teaching

I teach the way I worked. In the UX sequence students run real studies on real people from the first week, because contextual inquiry and task analysis only make sense once you've been surprised by a participant. In the capstone, teams build functional prototypes for external clients and present to them, so scoping, trade-offs, and saying no become part of the course rather than something they meet later. In analytics, I teach experimentation from the funnels and instrumentation I used at Amazon, with the failure modes included.

I've found that students who have been through this sequence interview differently: they have a story about a participant, a client, and a metric that moved, and they can explain what they'd do differently.

Introduction to HCI; UX research methods; interaction design studio; experimentation and product analytics; product management for engineers; human factors and human-systems integration; a client-facing capstone. Happy to develop a graduate seminar on technology in constrained and improvised environments.

Capstone teams delivered working prototypes to external partners in every term I ran the course. I supervise the way I was supervised: weekly, with the student's question at the centre, and with the expectation that the work ends in something that runs.