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A Passive Brain-Computer Interface for Monitoring Engagement during Robot-Assisted Language Learning

Jos Prinsen, Ethel Pruss, Anita Vrins, Caterina Ceccato, Maryam Alimardani

发表年份
2022
引用次数
12

摘要

Brain Computer Interface (BCI) technology offers the possibility to monitor users’ attention and engagement during learning tasks, enabling adaptation of pedagogical strategies for a personalized learning experience. In this paper, we present an EEG-based passive BCI system for real-time evaluation of user engagement during a language learning task. The EEG Engagement Index, which has been previously associated with attention and vigilance, is measured from three frontal electrodes and used in this system as a neural indicator of engagement. To validate our system, we used it in a human-robot interaction (HRI) setting, in which a robot tutor monitored the learner’s brain activity and adapted its tutoring strategy when a lapse in engagement was detected. We discuss the challenges and preliminary results from our pilot study with eight participants.

关键词

Computer scienceBrain–computer interfaceHuman–computer interactionInterface (matter)RobotArtificial intelligencePsychologyElectroencephalographyOperating systemNeuroscience

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