The cognitive scientist asking why learning is sometimes easy and sometimes hard

Darko Odic is a cognitive development researcher at the University of British Columbia. Darko studies the psychological factors that cause some children to struggle with mathematics. His goal is use this information to make education more equitable in the future and ensure that all children have learning opportunities that are tailored to their needs. Annie Brookman-Byrne talks with Darko about the challenges facing this research, and strategies for helping young children with math.

Annie Brookman-Byrne: What are you trying to understand about children’s learning?

Darko Odic: What makes some ideas easy to learn? And what makes some children better at learning them? These are the two big questions I ask in my research. Children usually learn their native language with surprising ease, but they learn formal mathematics, for example, which can be less complex, much more slowly. Similarly, some children are apparent prodigies, finding learning relatively easy, while others struggle to learn even basic ideas. I am trying to understand why these two types of variability exist when children learn new things.

With my team, I’m currently investigating early mathematical competencies. We are looking at the conceptions children have of numbers and math before they enter school, and asking how those conceptions affect how they learn formal math skills in school. For example, we recently found that well before children are ever introduced to a multiplication table, they have an intuitive sense of how to multiply approximately – we just have to find clever ways of asking them to do it. But while all children have this core competency, there are large differences in how well different children can carry out this kind of approximate multiplication. We are interested in understanding where mathematical intuitions like these come from, and why there are differences between children.

ABB: Is this a challenging area to study?

DO: Learning outcomes are shaped by many different factors, and as scientists we can control very few of them. For example, if a child is struggling with math, that might be partly because of a poor intuitive understanding of math. But it could also be partly due to a home environment where math doesn’t feature, or to the stress of being bullied in school, or to a curriculum that doesn’t allocate enough time for math. Since scientists cannot control most of these factors experimentally to see what has an impact, progress is very slow. Furthermore, any suggestions or interventions to improve math will likely have different outcomes for different groups of children, because some schools have the resources to implement them while others do not. When researching educational outcomes, we need to strike a tough balance between maintaining scientific rigour and taking into account real-life differences that we cannot control.

ABB: How will your research help children thrive?

DO: Owing to various historical factors, most educational systems in Western countries are set up as filters: Children are taught the basics, then tested to see if they have learned quickly enough to be promoted to advanced lessons. If they are lagging behind, they are told they should probably no longer engage with that subject. While this may be effective for creating a workforce, it doesn’t invest resources into understanding and helping the children who are struggling the most. My aim is to identify the psychological factors that lead some children to struggle. I hope that we can use this knowledge to go beyond focusing on individual children’s “talent”, and instead give all children a tailored curriculum that works for them, making education more equitable.

“Number words can be used in many contexts – in play, during walks, at the store, during storytime.”

ABB: What are your best evidence-based tips for helping young children with math?

DO: All young children are slow to learn how to count, and even when they know the number words in the right sequence, they rarely know what those words actually refer to! This process can be sped up by introducing number words into everyday talk. Many parents already spontaneously count with their kids, but new research suggests that it helps to go beyond mere counting. Number words can be used in many contexts – in play, during walks, at the store, during storytime. It doesn’t matter too much if children are misusing number words, or do not fully grasp them; they will understand eventually, and using number words more often will help them get there.

My second tip comes from the study of math anxiety. This is the feeling of unease, fear, and tension that many of us continue to feel when asked to do math in adulthood, for example when we’re helping a child with homework. Children are surprisingly sensitive to the anxiety adults show in our bodies and our actions – they pick up on it. Parents who are anxious about math are more likely to have children who are anxious about math as well. This anxiety can lead parents to talk about numbers less often. Dealing with math anxiety is not easy, of course. But relaxation exercises can be helpful, as can playing math-related games with children or, in extreme cases, seeking specialized classes that help parents or educators cope with their own anxiety surrounding math.

“Parents who are anxious about math are more likely to have children who are anxious about math as well.”

ABB: How optimistic do you feel about the cognitive development research happening right now?

DO: I am excited about the work that is teaching us broad lessons about how children’s minds work from a very young age, because once we know how children’s minds work more generally, we can have a positive impact in school and at home. For example, in my lab we have been researching the general question of how children catch mistakes when solving math problems. Luckily, decades of research have shown how children, adults, and even non-human animals detect errors and mistakes. This has led to the development of excellent scientific tools. For example, we have tools that look at eyes and measure the dilation of pupils in response to catching an error. Adults who are especially good at math are much more surprised than others when they see an erroneously solved math problem, and we can measure this by the degree of dilation in their pupils. We are now working on making these tools more applicable to children. That has given us a firm foundation that we can use in mathematics.

In general, I’m suspicious of getting too excited about the introduction of new tools, like machine learning, because often we end up reframing the problem to fit the tool rather than developing the tools that will help solve existing problems. I am much keener on finding ways of integrating lessons from decades of robust scientific work. I am eager to build on research that has shown what is valuable in the study of child development.