Ideal candidates connect theory to practice through human-centered design, learning analytics, and classroom-embedded research; attend to ethics, effectiveness, and impacts of AI; and envision next-gen STEM teaching, curriculum, and assessment responsive to diverse learners and educational settings.

We are especially interested in scholars who design, study, and critically evaluate AI in learning environments to improve teaching, learning, and equitable outcomes in K–12 and higher-education contexts.

And she's not wasting any time. On the first day meeting with graduate students in her class Mathematical Thinking and Problem Solving, they had a lively discussion about the role of spatial thinking in early mathematical cognition.

They're talking about building collaborations; exploring higher ed systems; together finding a path to yes; more community involvement; recognizing and seeing students; and maybe even a pickleball team.

Specifics are at homecoming.berkeley.edu/event/berkel...