People form their beliefs based on just a subset of all of the potential information available in the world. Everyday, people make decisions about what to read, what to watch, who to talk to, where to look, and what to click. We study how they make these decisions, and how these decisions interact with cognitive processes to determine human beliefs.

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We are learning scientists. We draw inspiration from classic learning theories in education and psychology, like those by Jean Piaget, Maria Montessori, and Lev Vygotsky. We build computational models inspired by these classic theories that allow us to make specific predictions and generate testable competing hypotheses about learning dynamics (for example, the relationship between the learning context and learning outcomes).

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We employ a combination of computational methods with behavioral experiments to study the acquisition and elaboration of human beliefs, starting in infancy but continuing through adulthood. We use eye-trackers to measure visual fixations to screens during passive viewing, and touchscreens to study touch-based exploration. We also employ computer-based learning experiments with both children and adults.  

 

Our results are quantitative theories about how data interacts with learners’ growing knowledge. These formal theories can function as the “back-end” for learning technologies, in addition to informing parenting, educational, and clinical practices. They can also help predict how new technologies may interact with human belief formation processes. More broadly, they help explain why people hold the beliefs that they do, sometimes even in the face of contradictory evidence.