[gov3009-l] Applied Statistics 2/22/17 - Joseph Jay Williams

Hi all, This week at the Applied Statistics workshop we will be welcoming Joseph Jay Williams, a Research Fellow in the Vice Provost for Advances in Learning Research Group at Harvard University. He will be presenting work entitled "Perpetually enhancing human learning through dynamic, personalized, collaborative experimentation." Please find the abstract below and on the website. We will meet in CGIS Knafel Room 354 at noon and lunch will be provided. Best, Pam Title: Perpetually enhancing human learning through dynamic, personalized, collaborative experimentation Abstract: There is a proliferation of websites and mobile apps for helping people learn new concepts (e.g. online courses), and learn how to change health habits and behavior (e.g. websites for reducing depression, apps for quitting smoking). How can we use data from real-world users to rapidly enhance and personalize these technologies? I show how we can build self-improving systems by reimagining randomized A/B experimentation as an engine for collaboration, dynamic enhancement, and personalization. I present a novel system that enhanced learning from math problems, through crowdsourcing explanations and automatically experimenting to discover the best. My second application boosted responses to an email campaign, by experimentally discovering how to personalize motivational messages to a user's activity level. These self-improving systems use experiments as a bridge between designers, social-behavioral scientists and researchers in statistical machine learning.