构建多模态数据集，分析手机使用对远程教育学习者的影响
A multimodal dataset for understanding the impact of mobile phones on remote online virtual education
- 通过16个同步传感器采集行为、生理与生物特征数据
- 120名学习者分三组，发现手机使用引发显著生理变化
- 适合教育技术、人机交互与学习分析领域研究者
本文提出IMPROVE数据集，一个用于评估手机使用对在线教育学习者影响的多模态资源。该数据集包含120名学习者在不同手机互动水平下的行为、生物特征、生理及学业表现数据，涵盖30分钟教育视频观看、文档阅读和选择题测试任务。实验采用16个同步传感器（包括EEG、眼动追踪、视频摄像头、智能手表、击键动态）记录学习过程，手机使用事件由监督员标注，并通过半监督重标注优化。技术验证确保信号质量，统计分析揭示了与手机使用相关的生物特征变化。数据集公开于GitHub和Science Data Bank，支持edBB、edX和LOGGE三个平台的同步记录，以标准格式（.csv、.mp4、.wav、.tsv）提供，并附详细使用指南。
原文摘要 · Abstract (English)
This work presents the IMPROVE dataset, a multimodal resource designed to evaluate the effects of mobile phone usage on learners during online education. It includes behavioral, biometric, physiological, and academic performance data collected from 120 learners divided into three groups with different levels of phone interaction, enabling the analysis of the impact of mobile phone usage and related phenomena such as nomophobia. A setup involving 16 synchronized sensors-including EEG, eye tracking, video cameras, smartwatches, and keystroke dynamics-was used to monitor learner activity during 30-minute sessions involving educational videos, document reading, and multiple-choice tests. Mobile phone usage events, including both controlled interventions and uncontrolled interactions, were labeled by supervisors and refined through a semi-supervised re-labeling process. Technical validation confirmed signal quality, and statistical analyses revealed biometric changes associated with phone usage. The dataset is publicly available for research through GitHub and Science Data Bank, with synchronized recordings from three platforms (edBB, edX, and LOGGE), provided in standard formats (.csv, .mp4, .wav, and .tsv), and accompanied by a detailed guide.
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