Stanford Graduate School of Education
Jason Yeatman’s research lies at the intersection of education and neuroscience. The overarching theme in his lab is understanding the interplay between brain development, education experience, and learning outcomes, specifically reading abilities. By combining quantitative neuroimaging methods with educational interventions, he strives to understand how a child’s unique pattern of brain maturation predisposes them to succeed or struggle in a specific education program. Over time, he plans to develop personalized intervention programs that are tailored and timed to characteristics of an individual’s neurobiology.
My plans for the fellowship period
Neuroscience is a powerful tool for addressing educationally relevant questions. Brain measures provide mechanistic insights into the foundations of learning that cannot be gleaned from behavioral measures alone. Through this fellowship, I will combine three different approaches toward the goal of “Precision Education”. (1) Experiments: By experimentally manipulating environmental factors in an educational intervention we can determine how specific aspects of a child’s environment impact brain development and learning. My lab is running intervention studies for children with dyslexia to understand the neurobiological foundations of successful intervention. (2) Computational modeling: To diagnose the factors that contribute to an individual’s reading difficulties, ideally, we would have models of the computations performed by the brain’s reading circuitry. I strive to build formal models of the neural computations involved in skilled reading, relate these models to learning, and test the model predictions across different types of experiments. (3) Open-source software: New research questions become possible with new methods. Precision Education aims to tailor education to characteristics of the individual student, based on profiles of neurobiological, genetic, behavioral and environmental factors. Developing software to integrate different types of quantitative measurements, meet the challenges of Big Data, and facilitate Precision Education will continue to be a focus of the lab.
How will my work change children’s and youth’s lives?
Literacy is at the foundation of academic success. Learning this complex cognitive function–decoding visual symbols into sound and meaning–is the crux of the first few years of education. However, as a child progresses through school, they are expected to use reading as a tool for learning: Math is taught through word problems, history through textbooks, and reasoning skills through analyzing text. Children that struggle learning to read quickly find themselves struggling to keep up in many academic domains. It is therefore no surprise that reading skills are one of the strongest predictors of long-term academic success. Reading disability (i.e., developmental dyslexia) puts children at a disadvantage throughout school and confers substantial risk for anxiety and depression. By pursuing deeper insights into mechanisms of reading difficulties we can develop innovative tools to help children overcome their challenges. Based on our research into individual differences and multiple risk factors for dyslexia we are developing automated tools for diagnosing learning differences and adapting to the individual. Through partnerships both within and outside of academia we hope to develop cost-effective tools that leverage new technology to address the diversity of challenges that many children face as they learn to read.