The Applied Statistics Workshop (Gov 3009) meets all academic year, Wednesdays, 12pm-1:30pm, in CGIS K354. This workshop is a forum for advanced graduate students, faculty, and visiting scholars to present and discuss methodological or empirical work in progress in an interdisciplinary setting. The workshop features a tour of Harvard's statistical innovations and applications with weekly stops in different fields and disciplines and includes occasional presentations by invited speakers. Free lunch is provided.
Joseph Jay Williams presents
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.