Current Projects

Desire-Based Reasoning and Source Monitoring
Where you learn a piece of information affects how you use it. For example, if you are shopping for a car, it's important to remember which advice came from your Aunt Rita (runs a car repair shop, knows exactly how often every model breaks down) and which came from your Uncle Ted (always buys cars that break down just after the warranty expires). However, how you want to think about information also affects your memory for where you learned it. If you go on to win a car in a contest, you may prefer to think that Uncle Ted said it was a terrible model, even if Aunt Rita actually said it.In our lab, we've demonstrated this type of desire-based reconstruction for predictions both about others and about oneself (Gordon, Franklin, & Beck, 2005; Barber, Gordon, & Franklin, 2009).

Source Credibility Judgment
Work on desire-based reasoning led me to become interested in how we decide that sources are trustworthy in the first place. How do you know that the Chicago Tribune is more likely to be accurate than the National Enquirer? How long does it take you to come to this judgment? How easy would it be to change your mind, and how much evidence would it take before you were willing to do so? My studies in this area examine:

how behavioral measures of source credibility compare with self-report measures
what factors (past record of accuracy, similarity to self, etc.) cause a source to be judged as credible or non-credible
how conflicting information is weighted in credibility judgments
how models of a source credibility can change over time

Source Monitoring and Bilingualism
In collaboration with Kiel Christianson at University of Illinois Urbana-Champaign, I am looking at how bilinguals recall the original language of written passages, and what factors make this recall easier and more difficult. We expect our findings to have implications both for the cognitive organization of bilingualism and source monitoring theory.

Reasoning About Emerging Technologies
Nanotechnology, genetics, computer science, and cognitive science are all rapidly developing areas that promise sweeping transformation in the coming years and decades. Predictions about the form these transformations will take are contradictory, ranging from the apocalyptic to the utopian and filling the entire spectrum in between. I'm interested in what factors shape these judgments, and how we come to conclusions about technologies that don't yet exist.My most recent paper in this area focuses on the ways that people learn about emerging technologies from fiction (Gordon, 2009).