Impact of construction industrial noise on workers' learning efficiency: A study based on electroencephalogram analysis
CAO Xinying1, ZHENG Decheng2, QIN Peicheng1, LI Xiaodong3
1. School of Civil and Architectual Engineering, Hainan University, Haikou 570228, China; 2. International Business School, Hainan University, Haikou 570228, China; 3. Department of Construction Management, Tsinghua University, Beijing 100084, China
摘要为研究建筑工业噪声对建筑产业工人学习效率的影响，招募29名建筑工人作为被试进行实验。将工业噪声类型分为平稳噪声与复杂噪声，每组被试均随机进行特定噪声类型下的对照组（日常白噪声）、低噪声组（均值60 dB （A））、中噪声组（均值70 dB （A））和高噪声组（均值80 dB （A））4个不同级别噪声干扰下的实验。通过脑电（EEG）特征提取与认知科学结合的方法收集并研究被试在不同噪声类型与级别下的行为与认知状态数据。结果显示：与平稳噪声环境相比，复杂噪声环境更容易导致工人的学习效率降低。相同噪声类型下，噪声级别大小对工人学习效率的影响无显著差异。不同噪声类型对工人认知状态的影响无显著差异。复杂噪声环境下不同级别的噪声对工人认知状态的影响无显著差异。平稳噪声环境下不同级别的噪声对工人的认知负荷的影响不存在显著差别，但是对注意力的影响存在显著差异。相关性分析结果表明：注意力与认知负荷呈负相关，反应时间与正确率不相关，注意力和认知负荷与正确率不相关，注意力与反应时间呈负相关，认知负荷与反应时间呈正相关，由此验证了认知状态在噪声与工人的学习效率之间存在中介效应。该研究结果为制定针对性措施降低噪声对建筑工人认知状态的影响提供了科学依据。
Abstract：[Objective] In this study, the impact of industrial noise on the learning efficiency of construction industry workers was investigated. Twenty-nine workers from a prefabricated component factory were recruited as study participants. [Methods] Industrial noise is generally classified as steady noise and complex noise. Each group of participants was randomly assigned to four different noise interference conditions of one of the two noise types, which were as follows:control group (daily white noise), low noise group (60 dB(A)), medium noise group (70 dB(A)), and high noise group (80 dB(A)). Each experimental session included a 5-minute instructional video and 20 multiple-choice questions related to the video content. The instructional video and test questions were sourced from the National Prefabricated Construction Vocational Skills Competition Exam Question Bank. Furthermore, the content of the instructional videos was designed by training instructors at the component factory to address the practical knowledge needs of the workers, and this content was synthesized into instructional videos. The test questions included knowledge points extracted from the instructional videos. Each instructional video and its corresponding test questions had similar levels of difficulty, with text quantity differences controlled within 10%. During the experiment, electroencephalogram (EEG) data were collected using Emotive-EPOC X EEG equipment. After preprocessing, including filtering, bad segment removal, and independent component analysis, the power spectral density (PSD) values for various frequency bands were extracted from the EEG data. Subsequently, these PSD values were utilized to evaluate the attention and cognitive load levels of the participants during the experiment. Behavioral data (accuracy and reaction time) were collected with psychological software and compared with the cognitive state data. Kruskal-Wallis variance analysis and Mann-Whitney U tests were employed to compare the differences in behavioral data and cognitive state data among the different groups. Pearson's correlation coefficient was utilized to evaluate the relationships between various data sets. [Results] The results of the comparative analysis reveal that, compared to a steady noise environment, a complex noise environment results in lower accuracy and longer reaction times, indicating that complex noise environments are more likely to reduce the learning efficiency of workers. However, within the same noise type, the noise level does not substantially affect the learning efficiency of workers. Moreover, different noise types have no remarkable effect on the cognitive state of workers, and different noise levels in a complex noise environment have no considerable differences in their impact on the worker's cognitive state. In a steady noise environment, different noise levels do not significantly affect cognitive load; however, they do considerably impact attention which significantly decreases when the noise reaches 80 dB(A). Correlation analysis reveals that attention is negatively correlated with cognitive load, and there is no significant correlation between reaction time and accuracy. Attention and cognitive load are not correlated with accuracy. Attention is negatively correlated with reaction time, while cognitive load is positively correlated. This implies that engaging in cognitive tasks increases the workers' cognitive load, leading to decreased attention levels and longer reaction times. Therefore, this study confirms the mediating effect of cognitive states on the relationship between noise and workers' learning efficiency. [Conclusions] This work offers a scientific basis for developing targeted measures to reduce the impact of noise on the cognitive states of construction workers and to enhance their learning efficiency.
曹新颖, 郑德城, 秦培成, 李小冬. 建筑工业噪声对工人学习效率的影响——基于脑电的研究[J]. 清华大学学报（自然科学版）, 2024, 64(2): 189-197.
CAO Xinying, ZHENG Decheng, QIN Peicheng, LI Xiaodong. Impact of construction industrial noise on workers' learning efficiency: A study based on electroencephalogram analysis. Journal of Tsinghua University(Science and Technology), 2024, 64(2): 189-197.
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2024, Vol. 64 
