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Wearable Neurophysiological Recordings in Middle-School Classroom Correlate With Students’ Academic Performance

The rapid development of wearable bio-sensing techniques has made it possible to continuously record neurophysiological signals in naturalistic scenarios such as the classroom. The present study aims to explore the neurophysiological correlates of middle-school students’ academic performance. The el...

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Autores principales: Zhang, Yu, Qin, Fei, Liu, Bo, Qi, Xuan, Zhao, Yingying, Zhang, Dan
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6240591/
https://www.ncbi.nlm.nih.gov/pubmed/30483086
http://dx.doi.org/10.3389/fnhum.2018.00457
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author Zhang, Yu
Qin, Fei
Liu, Bo
Qi, Xuan
Zhao, Yingying
Zhang, Dan
author_facet Zhang, Yu
Qin, Fei
Liu, Bo
Qi, Xuan
Zhao, Yingying
Zhang, Dan
author_sort Zhang, Yu
collection PubMed
description The rapid development of wearable bio-sensing techniques has made it possible to continuously record neurophysiological signals in naturalistic scenarios such as the classroom. The present study aims to explore the neurophysiological correlates of middle-school students’ academic performance. The electrodermal signals (EDAs) and heart rates (HRs) were collected via wristband from 100 Grade seven students during their daily Chinese and math classes for 10 days in 2 weeks. Significant correlations were found between the academic performance as reflected by the students’ final exam scores and the EDA responses. Further regression analyses revealed significant prediction of the academic performance mainly by the transient EDA responses (R(2) = 0.083, p < 0.05, with Chinese classes only; R(2) = 0.030, p < 0.05, with both Chinese and math classes included). By combining the self-report data about session-based general statuses and the neurophysiological data, the explained powers of the regression models were further improved (R(2) = 0.095, p < 0.05, with Chinese classes only; R(2) = 0.057, p < 0.05, with both Chinese and math classes included), and the neurophysiological data were shown to have independent contributions to the regression models. In addition, the regression models became non-significant by exchanging the academic performances of the Chinese and math classes as the dependent variables, suggesting at least partly distinct neurophysiological responses for the two types of classes. Our findings provide evidences supporting the feasibility of predicting educational outputs by wearable neurophysiological recordings.
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spelling pubmed-62405912018-11-27 Wearable Neurophysiological Recordings in Middle-School Classroom Correlate With Students’ Academic Performance Zhang, Yu Qin, Fei Liu, Bo Qi, Xuan Zhao, Yingying Zhang, Dan Front Hum Neurosci Neuroscience The rapid development of wearable bio-sensing techniques has made it possible to continuously record neurophysiological signals in naturalistic scenarios such as the classroom. The present study aims to explore the neurophysiological correlates of middle-school students’ academic performance. The electrodermal signals (EDAs) and heart rates (HRs) were collected via wristband from 100 Grade seven students during their daily Chinese and math classes for 10 days in 2 weeks. Significant correlations were found between the academic performance as reflected by the students’ final exam scores and the EDA responses. Further regression analyses revealed significant prediction of the academic performance mainly by the transient EDA responses (R(2) = 0.083, p < 0.05, with Chinese classes only; R(2) = 0.030, p < 0.05, with both Chinese and math classes included). By combining the self-report data about session-based general statuses and the neurophysiological data, the explained powers of the regression models were further improved (R(2) = 0.095, p < 0.05, with Chinese classes only; R(2) = 0.057, p < 0.05, with both Chinese and math classes included), and the neurophysiological data were shown to have independent contributions to the regression models. In addition, the regression models became non-significant by exchanging the academic performances of the Chinese and math classes as the dependent variables, suggesting at least partly distinct neurophysiological responses for the two types of classes. Our findings provide evidences supporting the feasibility of predicting educational outputs by wearable neurophysiological recordings. Frontiers Media S.A. 2018-11-12 /pmc/articles/PMC6240591/ /pubmed/30483086 http://dx.doi.org/10.3389/fnhum.2018.00457 Text en Copyright © 2018 Zhang, Qin, Liu, Qi, Zhao and Zhang. http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
spellingShingle Neuroscience
Zhang, Yu
Qin, Fei
Liu, Bo
Qi, Xuan
Zhao, Yingying
Zhang, Dan
Wearable Neurophysiological Recordings in Middle-School Classroom Correlate With Students’ Academic Performance
title Wearable Neurophysiological Recordings in Middle-School Classroom Correlate With Students’ Academic Performance
title_full Wearable Neurophysiological Recordings in Middle-School Classroom Correlate With Students’ Academic Performance
title_fullStr Wearable Neurophysiological Recordings in Middle-School Classroom Correlate With Students’ Academic Performance
title_full_unstemmed Wearable Neurophysiological Recordings in Middle-School Classroom Correlate With Students’ Academic Performance
title_short Wearable Neurophysiological Recordings in Middle-School Classroom Correlate With Students’ Academic Performance
title_sort wearable neurophysiological recordings in middle-school classroom correlate with students’ academic performance
topic Neuroscience
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6240591/
https://www.ncbi.nlm.nih.gov/pubmed/30483086
http://dx.doi.org/10.3389/fnhum.2018.00457
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