Cargando…

Collaborative Learning Quality Classification Through Physiological Synchrony Recorded by Wearable Biosensors

Interpersonal physiological synchrony has been consistently found during collaborative tasks. However, few studies have applied synchrony to predict collaborative learning quality in real classroom. To explore the relationship between interpersonal physiological synchrony and collaborative learning...

Descripción completa

Detalles Bibliográficos
Autores principales: Liu, Yang, Wang, Tingting, Wang, Kun, Zhang, Yu
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8116552/
https://www.ncbi.nlm.nih.gov/pubmed/33995232
http://dx.doi.org/10.3389/fpsyg.2021.674369
_version_ 1783691418460487680
author Liu, Yang
Wang, Tingting
Wang, Kun
Zhang, Yu
author_facet Liu, Yang
Wang, Tingting
Wang, Kun
Zhang, Yu
author_sort Liu, Yang
collection PubMed
description Interpersonal physiological synchrony has been consistently found during collaborative tasks. However, few studies have applied synchrony to predict collaborative learning quality in real classroom. To explore the relationship between interpersonal physiological synchrony and collaborative learning activities, this study collected electrodermal activity (EDA) and heart rate (HR) during naturalistic class sessions and compared the physiological synchrony between independent task and group discussion task. The students were recruited from a renowned university in China. Since each student learn differently and not everyone prefers collaborative learning, participants were sorted into collaboration and independent dyads based on their collaborative behaviors before data analysis. The result showed that, during group discussions, high collaboration pairs produced significantly higher synchrony than low collaboration dyads (p = 0.010). Given the equivalent engagement level during independent and collaborative tasks, the difference of physiological synchrony between high and low collaboration dyads was triggered by collaboration quality. Building upon this result, the classification analysis was conducted, indicating that EDA synchrony can identify different levels of collaboration quality (AUC = 0.767 and p = 0.015).
format Online
Article
Text
id pubmed-8116552
institution National Center for Biotechnology Information
language English
publishDate 2021
publisher Frontiers Media S.A.
record_format MEDLINE/PubMed
spelling pubmed-81165522021-05-14 Collaborative Learning Quality Classification Through Physiological Synchrony Recorded by Wearable Biosensors Liu, Yang Wang, Tingting Wang, Kun Zhang, Yu Front Psychol Psychology Interpersonal physiological synchrony has been consistently found during collaborative tasks. However, few studies have applied synchrony to predict collaborative learning quality in real classroom. To explore the relationship between interpersonal physiological synchrony and collaborative learning activities, this study collected electrodermal activity (EDA) and heart rate (HR) during naturalistic class sessions and compared the physiological synchrony between independent task and group discussion task. The students were recruited from a renowned university in China. Since each student learn differently and not everyone prefers collaborative learning, participants were sorted into collaboration and independent dyads based on their collaborative behaviors before data analysis. The result showed that, during group discussions, high collaboration pairs produced significantly higher synchrony than low collaboration dyads (p = 0.010). Given the equivalent engagement level during independent and collaborative tasks, the difference of physiological synchrony between high and low collaboration dyads was triggered by collaboration quality. Building upon this result, the classification analysis was conducted, indicating that EDA synchrony can identify different levels of collaboration quality (AUC = 0.767 and p = 0.015). Frontiers Media S.A. 2021-04-29 /pmc/articles/PMC8116552/ /pubmed/33995232 http://dx.doi.org/10.3389/fpsyg.2021.674369 Text en Copyright © 2021 Liu, Wang, Wang and Zhang. https://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 Psychology
Liu, Yang
Wang, Tingting
Wang, Kun
Zhang, Yu
Collaborative Learning Quality Classification Through Physiological Synchrony Recorded by Wearable Biosensors
title Collaborative Learning Quality Classification Through Physiological Synchrony Recorded by Wearable Biosensors
title_full Collaborative Learning Quality Classification Through Physiological Synchrony Recorded by Wearable Biosensors
title_fullStr Collaborative Learning Quality Classification Through Physiological Synchrony Recorded by Wearable Biosensors
title_full_unstemmed Collaborative Learning Quality Classification Through Physiological Synchrony Recorded by Wearable Biosensors
title_short Collaborative Learning Quality Classification Through Physiological Synchrony Recorded by Wearable Biosensors
title_sort collaborative learning quality classification through physiological synchrony recorded by wearable biosensors
topic Psychology
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8116552/
https://www.ncbi.nlm.nih.gov/pubmed/33995232
http://dx.doi.org/10.3389/fpsyg.2021.674369
work_keys_str_mv AT liuyang collaborativelearningqualityclassificationthroughphysiologicalsynchronyrecordedbywearablebiosensors
AT wangtingting collaborativelearningqualityclassificationthroughphysiologicalsynchronyrecordedbywearablebiosensors
AT wangkun collaborativelearningqualityclassificationthroughphysiologicalsynchronyrecordedbywearablebiosensors
AT zhangyu collaborativelearningqualityclassificationthroughphysiologicalsynchronyrecordedbywearablebiosensors