Enhancement of teaching outcome through neural prediction of the students' knowledge state
The neural mechanism for the dyadic process of teaching is poorly understood. Although theories about teaching have proposed that before any teaching takes place, the teacher will predict the knowledge state of the student(s) to enhance the teaching outcome, this theoretical Prediction‐Transmission...
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Published in | Human brain mapping Vol. 39; no. 7; pp. 3046 - 3057 |
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Main Authors | , , , , , , , , , , , , |
Format | Journal Article |
Language | English |
Published |
United States
John Wiley & Sons, Inc
01.07.2018
John Wiley and Sons Inc |
Subjects | |
Online Access | Get full text |
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Summary: | The neural mechanism for the dyadic process of teaching is poorly understood. Although theories about teaching have proposed that before any teaching takes place, the teacher will predict the knowledge state of the student(s) to enhance the teaching outcome, this theoretical Prediction‐Transmission hypothesis has not been tested with any neuroimaging studies. Using functional near‐infrared spectroscopy‐based hyperscanning, this study measured brain activities of the teacher–student pairs simultaneously. Results showed that better teaching outcome was associated with higher time‐lagged interpersonal neural synchronization (INS) between right temporal‐parietal junction (TPJ) of the teacher and anterior superior temporal cortex (aSTC) of the student, when the teacher's brain activity preceded that of the student. Moreover, time course analyses suggested that such INS could mark the quality of the teaching outcome at an early stage of the teaching process. These results provided key neural evidence for the Prediction‐Transmission hypothesis about teaching, and suggested that the INS plays an important role in the successful teaching. |
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Bibliography: | Funding information National Natural Science Foundation of China, Grant/Award Numbers: 31622030, 31411130158; Fundamental Research Funds for the Central Universities, Grant/Award Numbers: 2017EYT32, 2017XTCX04; Open Research Fund of the State Key Laboratory of Cognitive Neuroscience and Learning, Grant/Award Numbers: CNLYB1605, CNLZD1604 ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 14 content type line 23 Funding information National Natural Science Foundation of China, Grant/Award Numbers: 31622030, 31411130158; Fundamental Research Funds for the Central Universities, Grant/Award Numbers: 2017EYT32, 2017XTCX04; Open Research Fund of the State Key Laboratory of Cognitive Neuroscience and Learning, Grant/Award Numbers: CNLYB1605, CNLZD1604 |
ISSN: | 1065-9471 1097-0193 1097-0193 |
DOI: | 10.1002/hbm.24059 |