文本呈现方式对视觉舒适度的影响——基于人工智能与脑电协同的分析

The Impact of Text Presentation Mode on Visual Comfort:From the Perspective of AI and EEG Synergy

人工智能与脑神经科学在揭示教育规律中发挥着重要作用。大量研究从理论上阐述了两者结合的价值,但少有实证研究厘清相应的技术路径和解释方式。其原因是教育场景缺少复杂脑神经数据的智能特征提取方案,以及适配的智能分类和预测模型。本研究以40名在线德语学习者的脑电数据集为样本,将60个德语句子用四种媒体表征方式呈现,基于变分模态分解和样本熵的方法分析和解释学习者不同脑功能区和波段对数字资源呈现方式对视觉舒适度影响的内在原因,并通过机器学习分类方法比较在线学习视觉舒适度的自动识别精确度,为人工智能协同脑神经创设适宜的学习环境提供了理论基础,有助于优化学习者脑电的智能特征提取和分类方法,为构建健康的在线学习环境提供评价策略。

Prior research has certified the value of implementing Artificial intelligence and brain neuroscience on revealing the law of education.There still lacks empirical research to clarify the technological path and interpretation method although some studies have theoretically elaborated the value of combining the two disciplines.The possible reason may due to the deficiency of intelligent feature extraction scheme of complex neural data and adaptive classification and prediction model.Based on EEG technique,the current study recruited 40 online German learners to read 60 German sentences presented in four media representations in online context.Based on the method of variational mode decomposition and sample entropy,the internal reasons for the influence of different digital resources on visual comfort were analyzed from different brain functional areas and bands of learners.Finally,the classification method of machine learning is used to compare the automatic recognition accuracy of visual comfort level in online learning.This study provides a theoretical basis for the effectiveness of the analysis of learning environments in collaboration with the neural brain of artificial intelligence.In practice,it optimizes the intelligent feature extraction and classification methods of learners'EEG,and provides an important assessment for the construction of a healthy online learning environment in the future.