摘要
认知投入是决定学习有效发生的实质性投入,在协作学习中尤为关键。但在协作学习中学习者认知投入不均衡容易导致“搭便车”等负面学习行为的发生。并且,由于认知投入具有内隐性,对其的精准测量仍面临挑战。而基于客观生理数据,有望打开协作场景下认知投入测量“黑箱”。为此,研究从唤醒度和适应度两个维度描述协作场景下的认知投入,以184名参与“海绵校园设计”协作任务的大学生为研究对象,利用便携式生理设备采集学习者的皮肤电数据与心率数据,构建协作场景下认知投入的测量模型。研究结果表明:学习者的交感神经活动可以有效反映唤醒度水平,副交感神经活动则可以更加精准地测量适应度水平。通过信号处理技术与特征工程方法,研究从生理数据的时域、频域、形态三个层面构建15维特征,运用主成分回归方法验证得出,特征集合可以显著解释认知投入水平变异的39.7%,显示出测量模型良好的信效度,其中适应度体现了认知投入在协作任务中的定向,因而相比唤醒度具有更高的教育价值;在协作过程中,学习者的唤醒度呈现先降后升的趋势,适应度则持续提升。研究丰富了认知投入的理论,并为教师理解学生学情提供依据,有助于协作学习成效的改进与提升。
Cognitive engagement is essential for effective learning,particularly within collaborative learning contexts.However,imbalances in cognitive engagement among collaborative learners can result in negative behaviors,such as“free-riding”.Additionally,precisely measuring cognitive engagement remains a challenge due to its implicit nature.Advances in physiological data collection technologies offer a promising approach to reveal the“black box”of cognitive engagement measurement in collaborative settings.This study conceptualizes cognitive engagement in collaborative scenarios through two dimensions:arousal and adaptability.A total of 184 university students participated in a collaborative task called“Sponge Campus Design”,during which portable physiological devices were used to collect skin conductance and heart rate data.The goal was to develop a measurement model of cognitive engagement in collaborative learning contexts.Results indicate that sympathetic nervous system activity effectively reflects arousal levels,while parasympathetic nervous system activity serves as a more accurate measures of adaptation.Using signal processing and feature engineering techniques,the study identified 15 features across time-domain,frequency-domain,and morphological levels of the physiological data.Principal component regression analysis revealed that this feature set accounted for 39.7% of the variance in cognitive engagement,demonstrating strong reliability and validity of the measurement model.Adaptation,representing the directionality of cognitive engagement in collaborative tasks,was found to have greater educational value than arousal.During the collaborative process,learners’arousal levels followed a decreasing-then-increasing trend,while adaptation consistently improved.This study contributes to the theory of cognitive engagement,provides teachers with a deeper understand of student learning,and offers insights for enhancing collaborative learning outcomes.
作者
田浩
武法提
Tian Hao;Wu Fati(School of Teacher Education,Nanjing University of Information Science&Technology,Nanjing Jiangsu 210044;School of Educational Technology,Beijing Normal University,Beijing 100875)
出处
《远程教育杂志》
CSSCI
北大核心
2024年第5期65-76,共12页
Journal of Distance Education
基金
国家社会科学基金教育学一般课题“基于人机智能协同的精准学习干预研究”(项目编号:BCA200080)
2023年度江苏省教育科学规划青年专项课题“基于多层网络融合的大学生协作学习质量评估与干预策略研究”(项目编号:C/2023/01/87)的研究成果。
关键词
协作学习
认知投入
生理数据
测量模型
多模态学习分析
Collaborative Learning
Cognitive Engagement
Physiological Data
Measurement Model
Multimodal Learning Analytics