Interactive teaching plays an important role in how people acquire skills and learn about how the world works. But how does teaching work? What are the cognitive and computational mechanisms that support teaching others how to do things? In this talk, I discuss two types of non-verbal teaching interactions: teaching with reward/punishment and teaching by demonstration. Understanding these forms of interactive teaching requires characterizing dependencies between teachers, learners, and their shared environment, as well as how teachers and learners reason about those dependencies over time. I will discuss several computational models and behavioral experiments that provide insight into these processes. In particular, I will discuss how people’s teaching strategies reveal that they model learners as performing sophisticated theory of mind inferences, even in non-verbal interactions involving demonstration and rewards. These findings provide insight into the cognitive mechanisms that support human cultural transmission.
Mark Ho is a computational cognitive scientist interested in human social cognition and problem solving. He is currently a postdoc at the Computational Cognitive Science Lab with Prof. Tom Griffiths at Princeton University. His work uses ideas from machine learning and artificial intelligence to understand how people solve problems individually and collectively through mechanisms such as teaching. Mark received his Ph.D. in Cognitive Science and M.S. in Computer Science from Brown University, and received a B.A. in Philosophy from Princeton University. Visit his website at https://markkho.github.io/ and follow him on Twitter @Mark_Ho_.