Human teaching and learning are highly social. Much of learning emerges as a result of observation and interaction with others (e.g., a teacher) throughout our lifespan. While the research mainly focused on a student OR teacher in the learning process, recent evidence highlights the significance of the interpersonal dynamic during the learning. In particular, recent technological advances has opened unprecedented opportunities to study how teacher-student coordination shapes behaviors through learning. Movement coordination in any social situation may result in synchrony between the interacting people. This phenomenon is well-known in animals and humans. For example, when two people walk together, they tend towards synchronization. Yet there have been few direct links applying teacher-student synchrony to the rich field of learning science, including that focusing on learning interactions. Addressing this gap, the present work examines how the rapidly developing filed of interpersonal science is contributing to our understanding of teaching and social learning.
Strikingly, previous studies have identified interpersonal movement coordination between learners and instructors, but the relationship between synchronized body movement, learning, and instruction (e.g., academic performance, instructional approaches) is largely unknown. As such, the focus of our study lied on the exact functions of interpersonal coordination between instructors and learners. Specifically, we aimed at clarifying what role instructional approaches play in the synchronizing physical motion between teachers and learners, and crucially, how such synchrony might affect learning.
To these ends, we used a video-based Motion Energy Analysis (MEA) to quantify the synchrony between learners and teachers during the acquisition of psychological concepts. MEA is a computer-vision method based on the assessment of differences in sequences of frames in video recordings, providing a straightforward way to capture and quantify instructor’s and learner’s movements and nonverbal behavioral coordination. We compared the movement synchrony across two well-known pedagogical methods differing one another in terms of engagement modes: (1) explanation, i.e., teachers provide meaningful explanatory information to enhance learners’ comprehension, and (2) scaffolding, i.e., teachers give supportive scaffoldings including asking key questions and providing hints that are aimed at redirecting learners’ actions and understanding.
We found that movement synchrony was significantly greater when the teacher employed a scaffolding approach than when an explanation approach was used. The importance of instructional approach was further underscored by the fact that an increase in motion in the teacher was associated with boosted synchrony, but only during scaffolding (vs. explanation). Finally, leveraging machine learning approaches, we demonstrated that both learning outcomes and instructional approaches could be predicted by the movement synchrony. These results echo our previous neuroimaging study showing that the coupling between learners’ and teachers’ brains discriminates between instructional approaches and predicts learning.
The implications of the present study suggest that the dynamic interaction of teaching and learning bodies is essential for learning and that the instructional approach matters. Educators should re-examine their expectations on the functions of nonverbal communication and adjust their instructional style accordingly. A future direction is to our methodological and analytical approaches for studying learning difficulties and disabilities. Movement synchrony is deemed to serve as an objective and sensitive measure, providing new insights into relationships between learning outcome, behaviors, and communicative deficits in students demonstrating difficulties.
We believe our study holds strong relevance for various fields, such as psychology, pedagogics, and social sciences, in particular those targeting social behavior and teaching-learning settings. Our article will also be of interest to researchers working across species and in the clinic.
Learn more by reading our research article: Instructor-learner body coupling reflects instruction and learning, published by npj Science of Learning.
Poster Image Photo by Max Fischer
Pan, Y., Dikker, S., Zhu, Y. et al. Instructor-learner body coupling reflects instruction and learning. npj Sci. Learn. 7, 15 (2022). https://doi.org/10.1038/s41539-022-00131-0
Pan, Y., Dikker, S., Goldstein, P. et al. Instructor-learner brain coupling discriminates between instructional approaches and predicts learning. NeuroImage. 211, 116657 (2020). https://doi.org/ 10.1016/j.neuroimage.2020.116657
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