Marti Hearst
UC Berkeley
Teaching as Coaching and Learning at Scale

Massive open online courses are inspiring many to think anew about how they teach and learn, at all levels of scale, remotely and in person. I will describe two research results stemming from rethinking teaching, inspired by learning at scale: a new method for student-based evaluation of information visualizations, and the results showing that small group discussions online can improve student outcomes. I will then opine on my view of teaching as coaching and an idea I call MOOCs in Progress.

Marti Hearst is a Professor at UC Berkeley in the School of Information and EECS. Her research is in computational linguistics, search user interfaces, information visualization, and improving learning at scale. She wrote "Search User Interfaces" (Cambridge) in 2009, co-founded the ACM Conference on Learning at Scale in 2014, and was named an ACM Fellow in 2013. She has received four student-initiated Excellence in Teaching Awards, including in 2014 and 2015.