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📄 Abstract
Abstract: 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.