Causal Reasoning
How do children learn to identify cause-and-effect relationships? My work investigates the development of causal inference through the lens of temporal predictions, associative learning, and similarity-based representations.
PhD Student
Department of Psychology, Carnegie Mellon University
My research investigates how we make sense of the world around us. I study how human beings build functional representations over the course of development to make meaningful predictions across physical, social, and abstract causal domains. To explore these questions, I use cognitive developmental approaches and computational tools to uncover the mechanisms underlying these abilities.
I am advised by Dr. David Rakison in the Infant Cognition Lab.
How do children learn to identify cause-and-effect relationships? My work investigates the development of causal inference through the lens of temporal predictions, associative learning, and similarity-based representations.
How do we understand friendship and the actions of others? My research explores the development of social reasoning, focusing on how we build mental representations to interpret and predict the behavior of the people around us.
Young children are remarkable learners. My research examines how exploration supports knowledge acquisition and cognitive flexibility.
Choi, R. W. J., & Rakison, D. (2025). First contact: Children’s emerging sensitivity to causality in second-order learning. Proceedings of the Annual Meeting of the Cognitive Science Society, 47.
How do young children “connect the dots” between separate experiences to make predictions in causal contexts? This research suggests that as children develop robust expectations about physical contact, these beliefs not only support their ability to link events but also begin to constrain their generalizations: while younger children are more likely to make these leaps when objects do not touch, older children increasingly rely on physical contact to make generalized predictions.
How are causal events encoded in our mental representations, and how do those representations change across development? This project uses vectorized event descriptions and distributed semantic analysis to probe the structure of causal event representations and how they differentiate along features like physical contact.
Department of Psychology
Carnegie Mellon University
5000 Forbes Avenue
Pittsburgh, PA 15213