Instructor-learner body coupling reflects instruction and learning

Abstract

It is widely accepted that nonverbal communication is crucial for learning, but the exact functions of interpersonal coordination between instructors and learners remain unclear. Specifically, it is unknown what role instructional approaches play in the coupling of physical motion between instructors and learners, and crucially, how such instruction-mediated Body-to-Body Coupling (BtBC) might affect learning. We used a video-based, computer-vision Motion Energy Analysis (MEA) to quantify BtBC between learners and instructors who used two different instructional approaches to teach psychological concepts. BtBC was significantly greater when the instructor employed a scaffolding approach than when an explanation approach was used. The importance of the instructional approach was further underscored by the fact that an increase in motion in the instructor was associated with boosted BtBC, but only during scaffolding; no such relationship between the instructor movements and BtBC was found during explanation interactions. Finally, leveraging machine learning approaches (i.e., support vector and logistic regression models), we demonstrated that both learning outcome and instructional approaches could be decoded based on BtBC. Collectively, these results show that the real-time interaction of teaching and learning bodies is important for learning and that the instructional approach matters, with possible implications for both in-person and online learning.

Spontaneous movement synchrony as an exogenous source for interbrain synchronization in cooperative learning

“…An alternative claim, complement to the previous one, proposes that exogenous factors, referring to cues or influences outside the brain, such as movement synchrony (i.e., alignment in movements structure, direction, and pace) from an embodied perspective, also link to IBS, as inspired by recent takes (Shamay-Tsoory et al, 2019). Supporting the latter claim, our recent research has observed spontaneous movement synchrony and its association with learning outcome during learning interactions (Pan, Dikker, et al, 2022). Also, movement synchrony has been strongly linked to IBS in studies on social behavior (Koul et al, 2023b).…”

Intrinsic Organization of Occipital Hubs Predicts Depression: A Resting-State fNIRS Study

“…We employed a grid search-based approach for hyperparameter optimization to determine the optimal regression parameters (i.e., C , γ , and ε ). A nested cross-validation method was implemented [ 65 ], with the outer leave-one-out cross validation (LOOCV) estimating the generalization performance of the model and inner 10-fold CV estimating and selecting the optimal hyperparameters. The prediction accuracy was estimated using the Pearson correlation coefficient between the predicted and actual values [ 66 ].…”

Associations of Empathy with Teacher–Student Interactions: A Potential Ternary Model

“…Second, educators currently rely on single modal data for teaching and learning assessment, which overlooks important aspects of teaching such as nonverbal communication. To address this limitation, various multimodal technologies can be used to analyze teacher-student interactions, including EEG and fNIRS to observe changes in the cerebral cortex, eye tracking to monitor eye movements, skin conductance to examine physiological mechanisms, and video-based computer vision to detect teacher-student movement [79]. Such technologies enable a more comprehensive assessment of cognitive processes and neural responses during teacher-student interactions.…”