Improving human learning and memory via cognitive models

by Michael C. Mozer

Dept. of Computer Science and Institute of Cognitive Science, University of Colorado, Boulder

Date

Friday, October 23, 2009

Time

3:00 p.m. — 4:00 p.m.

Place

Lindley Hall, Rm. 102

Abstract: In school and beyond, individuals need to learn facts: proficiency in a foreign language involves knowing the translation of English words; becoming a physician requires associating symptoms with diseases; surviving in the wilderness may depend on identifying whether a snake or berry is poisonous. We are developing techniques to assist individuals in learning and retaining knowledge. These techniques are based on computational cognitive models of memory, which predict recall accuracy under differing training conditions (e.g., duration, frequency, and spacing of study). Using numerical optimization techniques and queries to the model, we can determine the training conditions that yield the most durable memories. We describe two cognitive models, one that predicts retention as a function of the temporal lag between study sessions, and another that predicts which individual item in a set will most benefit from further study. We have validated these models using behavioral experiments, and we are currently developing electronic learning aids that utilize model predictions to optimize human memory.

This work is a collaboration with Harold Pashler, Owen Lewis, Robert Lindsey, Nicholas Cepeda, and Ed Vul.
 

Biography:  Michael Mozer received his PhD in 1987 from UCSD and, after a postdoc with Geoff Hinton at University of Toronto, took a faculty position at the University of Colorado, Boulder, where he remains today. Dr. Mozer is currently Professor in the Department of Computer Science and the Institute of Cognitive Science, and has served as the President of the Cognitive Science Society. Dr. Mozer’s research focuses on neural and statistical models of human learning, perception, and generalization, and the application of cognitive models to practical engineering problems.
 

A printable version of the colloquium flyer is available for printing.   

Colloquium Provided By:

the School of Informatics