CogSci 2016 - Hypothesis generation and self-directed learning

At CogSci this year I presented some new work on hypothesis generation and its role in self-directed learning (specifically, the learning of categorical rules). This project explores the idea that hypothesis generation is a bottleneck in active learning, as is suggested by a lot of work in classic cognitive tasks as well as studies from educational psychology. The results give an example of how biases in the hypothesis generation process can have a big impact on whether people can efficiently learn different kinds of rules.

For more on this project, see the paper in the proceedings and the poster below (PDF).