All speakers gesture when they talk. Gestures are a type of action––an action done in the air that does not directly affect objects. Both gestures and actions-on-objects can promote learning, but having gesture as part of a math lesson makes it easier to remember and extend that lesson than having action as part of the lesson. This program of research uses neural data to figure out why. Two hypotheses, both of which might be correct, are possible: (1) Gesture promotes learning by helping children abstract beyond particular exemplars used in instruction. (2) Action impedes learning by tying children to the particulars of the exemplars used in instruction. It is difficult to disentangle these two mechanisms at the behavioral level because both hypotheses lead to the same outcome––better learning following gesture than action. The research uses neuroimaging to measure activity during a math lesson and determine whether different areas of the brain are activated during gesture- vs. action-based instruction. Understanding the neural processes that underlie learning through gesture vs. action can help distinguish between these two hypotheses, and lead to more finely tuned recommendations to teachers for using these tools in the classroom.
The research program aims to distinguish between the two hypotheses in a math lesson under two conditions: when children observe an instructor produce gestures or actions (Study 1); when children themselves produce gestures or actions (Study 2). Study 1 uses fMRI (functional magnetic resonance imaging) and Study 2 uses fNIRS (functional near infrared spectroscopy) to measure neural activity while 8- to 10-year-old children in 3rd and 4th grade receive gesture- or action-based instruction in the pre-algebra concept of math equivalence (the notion that two sides of an equation must be equal). Neural activity in abstraction areas is expected to occur during gesture instruction; neural activity in object areas is expected to occur during action instruction). Differences in neural processes during instruction will be used to predict children’s learning outcomes after instruction. fNIRS is a new technology that has been underused in educational neuroscience, but has the potential to be used in the classroom to measure neural activity during learning from multiple students simultaneously. This work is an early step in testing that possibility.
This project is funded by the EHR Core Research (ECR) program, which supports work that advances fundamental research on STEM learning and learning environments, broadening participation in STEM, and STEM workforce development.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
