422 Brogden Psychology Building
1202 W. Johnson St.
Madison, WI 53706
AS 1998, Math/ Science Studies, Genesee Community College, Batavia, New York
BA 2001, Brain and Cognitive Sciences, University of Rochester, Rochester, New York
MA 2005, Brain and Cognitive Sciences, University of Rochester
PhD 2008, Brain and Cognitive Sciences, University of Rochester
Postdoctoral Fellowship 2008-11, Human/Machine Learning and Computational Vision, University of Minnesota, Minneapolis
Dr. Green's research interests are in human learning - in particular in the perceptual, motor, and cognitive domains. Specific topics of interest can be broken down into three broad themes:
Transfer of Learning: Given appropriate training conditions (e.g. sufficient time on task, proper spacing of training sessions, feedback, etc) humans will tend to improve on virtually any perceptual and/or cognitive task. One critical question though is under what training conditions do you only get better at the trained task (for example, if you do a lot of Sudoku, you may really only get better at Sudoku - not other types of reasoning tasks) and under what conditions do you see generalization from the trained task to a new task (for example, if you learn to drive in a car, you'll likely be better at driving a pickup truck than you would have been without any driving experience at all)?Rate of Learning: There are large inter-individual differences in the rate with which new perceptual, motor, and cognitive tasks are learned as well as large differences in the rates of learning produced by various training paradigms. The key questions are thus: 1) what traits/characteristics - either of the individual or the task - will allow us to best predict the rate with which an individual will learn a new task and 2) how can we manipulate either the individual or the task to alter the rate of learning (typically to increase the rate of learning)?
Depth of Learning: In laboratory studies of learning, participants are usually given a specific task to practice for a particular period of time. They have no choice in what task to practice or for how long they will practice. In the real-world though, these are both decisions that have to be made by a learner. Is it worth investing my time and resources in an attempt to improve performance on this task in the first place? If I have started practicing, is it worth continuing? Making such decisions rationally requires that the participant estimate not only their current level of skill and the value of performing the task given that level of skill, but also to estimate the rate with which their skills are likely to improve with practice time and the value of performing the task given their potentially improved performance.
PubMed Listing of Publications