If we better understood what happens inside students’ brains as they listen to lectures and complete assignments, would instructors be able to teach more effectively?
Lynch School researchers are investigating this question with the help of electroencephalography (EEG), a neuroimaging tool that measures electrical activity in the brain.
Assistant Professor Ido Davidesco, who joined the Lynch School in 2024 and leads the Lab-to-Classroom Research Group, uses portable EEG devices to study collaborative learning among high school and college students in classroom settings. Augustus Long Professor of Education Marina Bers, who leads the Lynch School’s DevTech Research Group, is launching an EEG study this fall to understand the neurology of how elementary students learn computer coding. These researchers look forward to collaborations that will combine their interests, leveraging Davidesco’s training in cognitive neuroscience and Bers’ expertise in computer science education.
Literacy and the coding brain
Marina Bers
For Bers, it’s important to conceive of coding as another form of literacy. “When you’re reading and writing, you’re using a traditional literacy,” she says. “It has grammar and syntax, symbols—and you’re using that to communicate to others. When you code, it’s the same thing. You’re learning a symbolic system to represent an abstract concept so you can share it.”
Framing coding as literacy has neurological implications as well: decades of research have identified the types of brain activity associated with the production and processing of language. Bers is keen to know if that same brain activity is associated with coding. Her lab is planning a study that will use portable EEG devices to record children’s brain activity as they code with ScratchJr, a programming language for five- to seven-year-olds that Bers helped develop.
Bers has been researching the cognitive and neurological processes involved in coding since 2018, and she now believes that with EEG she has found the right tool for answering her research questions. Her previous studies used other imaging technologies that turned out not to be well-suited to the purpose, she says. A study using functional magnetic resonance imaging (fMRI) required subjects to lie still, which limited the tasks they could do during the experiment. A study using functional near infrared spectroscopy (fNIRS) produced noisy data that was too difficult to analyze. Bers is optimistic that portable EEG devices will strike the right balance between providing useful data and allowing children to code in an environment that resembles normal classroom conditions.
Bers’ lab is planning a study that will use portable EEG devices to record children’s brain activity as they code with ScratchJr, a programming language that she helped develop.
The research could help her lab create better curricula and tools for teaching coding. “For example,” she says, “we might learn what aspects of ScratchJr require more focused attention or more teaching time, and what level of alphabetical literacy is more conducive to learning to code.”
If the research shows that children’s brains process traditional literacy and coding similarly, that could also lead to wider use of coding in different subjects. “Traditionally, people have introduced coding as part of STEM—science, math, engineering, and technology,” she says. “But maybe we should integrate coding throughout the curriculum, like we do with reading and writing.”
Learners on the same wavelength
Ido Davidesco
For a National Science Foundation-funded study published last year, Davidesco and his colleagues placed groups of four college students and a lecturer in a simulated classroom and used EEG to record all participants’ brain activity. The researchers analyzed the EEG data to see when and how well the brain waves of participants aligned, a phenomenon known as brain-to-brain synchrony. The researchers tested students on the content of the lecture before, immediately after, and one week after the lecture. Comparing students’ answers to the test questions with the EEG data showed that students learned the most at times during the lecture when their brain waves were synchronized—when the students were, literally, on the same wavelength.
In a follow-up study, Davidesco explored the impact of brain activity among students working in collaborative teams. He asked groups of high school biology students to wear EEG devices as they worked together to build a model of a cell. As he and his research team analyze data from the experiment, they’re looking at how student engagement varies throughout the task. They’re also comparing observations of student behavior with the EEG data—looking to see if students who appear engaged or disengaged actually are.
In another aspect of the study, the researchers are comparing brain synchrony and students’ self-reported measures of social closeness. One of Davidesco’s preliminary findings is that friends displayed higher brain-to-brain synchrony during the task than did students who were only acquaintances. He hopes this study and future ones will improve teachers’ approaches to collaborative learning.
Davidesco explored the impact of brain activity among students working in collaborative teams. One preliminary finding is that friends displayed higher brain-to-brain synchrony during the task than did students who were only acquaintances.
“We know that collaborative learning overall is quite effective,” he says, but not all students benefit equally. Studying students’ brain activity in classrooms might provide a deeper understanding of why some benefit from collaborative work more than others do. “For instance, we know that efficacy has a lot to do with how you place students in groups, and yet there is controversy about how this should be done. Do we want groups that are relatively homogeneous or heterogeneous? Do we want to let students pick their own partners—which they often want—or is it better for the teacher to assign students to groups?”
EEG studies may help teachers better understand how to create student groups where everyone is learning more together than they would learn on their own.
Future research
Thus far, all of Davidesco’s research has been with older students, and he hopes to expand this research through collaborations with Bers. Together, they plan to investigate how brain-to-brain synchrony affects the way young students learn to code when working in collaborative groups—perhaps assigning students to a variety of two-person teams to see how different pairings affect synchrony and learning.
“Ido has a solid background in cognitive neuroscience,” says Bers. “I have a solid background in computer science education, so he and I will be natural partners.”
Davidesco envisions many opportunities to make connections between neuroscience and education. The tools used in neuroscience research—like EEG and eye-tracking—have great potential to expand education research. “The methods we tend to use in education research are limited in their temporal resolution, in the sense that we cannot just keep asking students every minute how engaged they are, because that by itself is distracting,” he says. “With EEG, we get millisecond by millisecond readings of students’ brain data and, indirectly, their engagement level. I think that’s where things get really interesting because it allows us to ask more sophisticated questions.”
Davidesco would like to see more neuroscience research move from the laboratory to the classroom, where students can interact naturally and teachers can influence study design and implementation. “Researchers can get input from teachers to make sure the questions they ask and the materials they’re using are relevant and can produce usable knowledge.”
Coming soon: M.A. in Learning, Design, and Technology
The Lynch School will soon begin accepting applications to a new master’s program launching in September 2025 that will train students to create, lead, and evaluate learning environments that incorporate cutting-edge technologies. Through project-based coursework, students will build portfolios in preparation for doctoral programs or for careers as learning experience designers, instructional designers, curriculum developers, and educational technology consultants.