In one of her most recent studies, Tanya Evans faced a Herculean task: She needed to convince 6-year-olds to stay completely still for minutes at a time.
As a neuroscientist at the University of Virginia, Evans works with data gathered through magnetic resonance imaging machines, or MRIs, which require a subject to stay completely still. While convincing young children not to wiggle around in the machine can be a challenge, the reward is a rich set of brain data that sheds light on how our brains process information.
In that particular study, as each child solved arithmetic problems, Evans was able to record their brain activity – a physiological marker of learning, happening in real time.
Evans is a new addition to UVA’s Curry School of Education faculty and the research team at CASTL, the Center for the Advanced Study of Teaching and Learning. A researcher in the emerging field of educational neuroscience, she focuses on studying the brains of children who struggle to learn reading and math.
Here, she shares how brain data adds a new dimension to education research, the value of working across disciplines and why it’s never too late to learn something new.
Q. Your background is in chemical engineering, neuroscience and medicine. How did you end up at an education school?
A. I’ve always been interested in K-12 education and learning more generally. Before beginning graduate school, I spent some time teaching K-12 students. Pursuing neuroscience research with my graduate school mentor, an expert in learning disabilities, was a natural synthesis of multiple interests.
I’ve also always loved research and science, but for me, there was something unsatisfying about studying chemicals and machines; I find the complexity of human behavior much more interesting. So educational neuroscience ended up being the perfect way for me to apply my scientific background to a field focused on human development.
Chemical engineering is fundamentally about understanding systems, and as an educational neuroscientist, I’m applying that ability to understand systems to the study of something that’s a bit more tangible – learning and education.
Q. Educational neuroscience is a relatively new area of study. What does it mean exactly, and where did it come from?
A. I think of educational neuroscience as an endeavor in the science of learning. Applying neuroscience knowledge and methodologies in educational research gives additional insight into how learning happens, physiologically, in the brain.
Neuroscience can be studied on a number of levels – some neuroscientists will spend an entire career studying just one tiny part of the brain. Combining decades of research in the study of learning with a greater understanding of higher-order cognitive systems allows for insights to be brought to bear on research questions relevant to a child sitting in the classroom.
Interdisciplinary science requires willingness from multiple fields; it takes both neuroscientists and educational researchers who are willing to learn how to speak a common language. Neuroscience needed to mature enough as a field to bring the understanding and tools relevant to questions being asked in educational research.
Q. What can neuroscience data add to applied education research?
A. Neuroscience adds value to classroom measurements and behavioral tests because with brain data, we’re able to add information about the physiological mechanisms that drive skills or behaviors.
For instance, let’s say a study is able to increase children’s literacy skills through a reading intervention. The addition of brain data allows you to explore at the brain level what is was driving that effect. We can see if it’s connected to memory systems, phonological processing, object perception or even a combination of factors.
A physiological marker of learning, intervention effectiveness or skill level in a particular domain can provide solid insight into why we see certain behaviors. It can be particularly useful in instances where measurements are limited, or where results are inconsistent at a behavioral level – in these cases, brain data can be an adjudicating factor.
Q. Can you share an example from your recent work?
A. In a recent study published with my colleagues at Stanford University, we looked at the relationship between children’s attitudes toward math, their math performance and their brain function. Essentially, we found that children who have positive attitudes toward math perform better on math assessments – and this is mediated by brain systems involved in memory. We expected involvement in emotional and affective l-regions of the brain, but finding a relationship between a child’s attitudes and beliefs and their core learning systems is fascinating.
Q. As a neuroscientist, what benefits does a position within a school of education offer you and your work?
A. I’m incredibly excited to work more closely with educational researchers. It would be naïve of me, as a neuroscientist, to think that I can come up with the most relevant research questions without input from those with extensive experience working with students and educators in classrooms. I think that these collaborations will give rise to some exciting research.
For example, in the past, I’ve worked on teams designing educational interventions where everyone in the room was a neuroscientist. In one project that my colleagues and I are working on now, we have clinical psychologists, developmental scientists and experts in curriculum design, as well as parents and teachers at the table. This open dialogue is extremely important.
I’m excited by the potential to do what I see as high-impact work. The prospect of collaborating with educational researchers who are engaged in educational policy, and to be able to do science that could make have a direct impact on children’s lives, is incredibly inspiring.
Q. Interdisciplinary work inevitably involves a lot of collaboration with people who might not think the same way that you do. Why is that important, and what kind of collaborations are you looking forward to?
A. As an educational neuroscientist, I am truly immersed in interdisciplinary science. The work that I do requires people to come together from disparate fields and speak a common language. It’s pretty valuable to take people who were trained in different disciplines and put them together to work toward a common goal. If you always surround yourself with like-minded people, then your ability to think outside of the box and ask relevant questions is limited.
When I first came to Curry, I didn’t realize the extent of the diversity of faculty research and training. There are many researchers within Curry who are studying human development more generally, as well as those with a focus on student motivation, classroom instruction, educational equality and access, school transitions, policy, nutrition and exercise.
I’m also really excited about connecting with researchers across Grounds through UVA’s interdisciplinary initiatives, such as the Brain Institute and the Data Science Institute. I think that UVA is a unique place in that it has such strengths in disciplines that all cross my interests – education, medicine and psychology. I feel very fortunate to be here.
Q. What’s one thing that you’d like everyone to know about the science of learning?
A. With children in particular, I think we need to get away from the idea of fixed capability – that we are born with certain strengths and weaknesses that cannot be changed. Children come into a classroom with a high degree of capability, but not always the right tools and the right skills.
Neuroscience research has shown us that the brain is not modular – in other words, one particular brain l-region isn’t responsible for one particular function. Your brain is comprised of a network of l-regions that work in concert to accomplish a given task, and its plasticity and malleability are astounding.