Instructor-learner brain coupling discriminates between instructional approaches and predicts learning

Yafeng Pan, Suzanne Dikker, Pavel Goldstein, Yi Zhu, Cuirong Yang, Yi Hu

Research output: Contribution to journalArticlepeer-review

Abstract

The neural mechanisms that support naturalistic learning via effective pedagogical approaches remain elusive. Here we used functional near-infrared spectroscopy to measure brain activity from instructor-learner dyads simultaneously during dynamic conceptual learning. Results revealed that brain-to-brain coupling was correlated with learning outcomes, and, crucially, appeared to be driven by specific scaffolding behaviors on the part of the instructors (e.g., asking guiding questions or providing hints). Brain-to-brain coupling enhancement was absent when instructors used an explanation approach (e.g., providing definitions or clarifications). Finally, we found that machine-learning techniques were more successful when decoding instructional approaches (scaffolding vs. explanation) from brain-to-brain coupling data than when using a single-brain method. These findings suggest that brain-to-brain coupling as a pedagogically relevant measure tracks the naturalistic instructional process during instructor-learner interaction throughout constructive engagement, but not information clarification.

Original languageEnglish
Article number116657
JournalNeuroImage
Volume211
DOIs
StatePublished - 1 May 2020

Bibliographical note

Funding Information:
This work was supported by the National Natural Science Foundation of China ( 31872783 ), the Key Specialist Projects of Shanghai Municipal Commission of Health and Family Planning ( ZK2015B01 ), the Programs Foundation of Shanghai Municipal Commission of Health and Family Planning ( 201540114 ), NSF ECR Award ( 1661016 ), and the General Project of Humanities and Social Sciences of the Ministry of Education ( 19YJA190010 ).

Publisher Copyright:
© 2020 The Authors

Keywords

  • Brain-to-brain coupling
  • Decoding
  • Instruction
  • Social interactive learning
  • fNIRS hyperscanning

ASJC Scopus subject areas

  • Neurology
  • Cognitive Neuroscience

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