I am currently a postdoctoral fellow in the Department of Psychology at the University of Richmond. I earned a B.A. in Psychology at The University of North Carolina at Asheville, a M.A. in Experimental Psychology at Appalachian State University, a M.A. in Developmental Psychology from Cornell University, and a Ph.D. in Developmental Psychology at Cornell University.
In my current position, I teach a Psychology and Law seminar and a Introduction to Psychology course. I strongly believe in going beyond student evaluations, and trying to take an empirical approach to measuring student learning (see here for an example pertaining to my Psychology and Law class). Given the wealth of technological resources for teachers, it is easier than ever to provide numerous creative demonstrations of the topics in class. Click here for some online resources for excellent supplementary materials that can be used to demonstrate various psychological phenomena. Also, click here for some entertaining videos of my dog demonstrating various principles in psychology. For students interested in careers related to psychology and law click here for relevant resources.
My research is focused on how basic models of memory and cognition can inform our understanding of bias in judgment and decision making. That is, how do we leverage what we know about how memory works to help us understand why we are susceptible to systematic biases? Furthermore, can this approach provide us with ways to counter such biases (when avoiding bias is desirable?)
This broad approach (along with a winding path through a panoply of laboratories) has led me to publish in areas such as risky-choice, false memory, jury award decision making, public policy, motivated reasoning, and inductive category learning. Although my research interests in the realms of memory and decision making are varied, my approach has remained rooted in Lewin's maxim that "there is nothing as practical as a good theory". I apply findings from both basic cognitive theory and decision theory in order to generate new insights, which will improve how we make decisions and how we understand the decisions of others.
Click below for a list of publications:
Commitment to Open Science
If it isn't reproducible, it isn't science. The best way to ensure a science that is reproducible is to be as open as possible regarding the process that got you from hypothesis to experiment to publication. The social sciences have made great strides in the past decade towards a more open and reproducible science, through methods such as preregistration, registered reports, open peer review, the Open Science Framework (in which one can share materials, data, preregistrations), and a much stronger focus on statistical methodology. The only way we will be able to ensure that the insights gleaned from behavioral research and applied in the world are reliable is to further advocate for open science practices. Below are links to a list of resources that can help scientists make their work more open, statistically rigorous, and help practitioners know what to look for when attempting to make use of the literature.