University of Pittsburgh
The primary research focus of the lab is causal learning - how people learn cause-effect relationships from their experiences (e.g., this new medicine I have been trying seems to work well). We are especially interested in causal learning from time series data, in which the causes and effects exhibit gradual changes over time.
A more recent interest is the role of memory, especially long-term memory, for learning causal relations. We are currently conducing smartphone experiments to study causal learning and memory over 3-4 weeks.
Another current direction is studying how politically motivated reasoning affects causal judgments.
We are also interested in causal learning in everyday life, for example how people test whether a medicine is working or not, try new diets, or assess the efficacy of other lifestyle changes they make. We are also interested in how people form beliefs in 'pseudoscience' therapies that are not actually effective.
One of the primary goals of science is to uncover causal relations. We are interested in understanding how to teach causal inference in research methods classrooms to improve science education. See Resources for more info.
More broadly, we are interested in when and whether human decision makers make judgments that are approximately 'normative' (correct).
Ciara (pronounced like Keira Knightley) is a fourth year graduate student and has a Master's from Pitt and Seton Hall. She studies how well people learn causal relations over 24 days using smartphone studies, and is also interested in graph interpretation.
Zac is a fourth year graduate student and has a Master's from San Jose State. Zac is especially interested in motivated reasoning and scientific belief, and is also studying long-term learning and retention in relation to the maintenance of certification exams for doctors.
Yiwen (pronounced as 'even') is a second year graduate student and is coming with a bachelors from Zhejiang University. Yiwen is working on smartphone-based causal learning studies.
|Causality and Multiple Regression||R Shiny app for learning about the relation between Causality and Multiple Regression.|
|PsychCloud||Tutorial and Code for making psychology experiments (or interactive websites more generally) hosted on Google App Engine and Google's Could. This is he we program web experiments.|
|Research Methods Dojo||Tutorials for research methods students on within vs. between subjects designs, carryover, practice, and fatigue effects.|
|Causal Strength Calculators||Code for models of causal strength including Rescorla-Wagner (Rescorla & Wagner, 1972), ∆P (Jenkins & Ward, 1965), Power-PC (Cheng, 1997), and Temporal-difference (Sutton & Barto, 1987).|