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bioRxiv · 10.1101/2022.09.20.508656

Electroencephalogram Data Collection for Student Engagement Analysis with Audio-Visual Content

Upadhyay, R.·Singh, M.·Mishra, S.·Mehta, J.·Bansal, A.·Baranwal, M.·Kumar, V.
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Abstract

Recognizing and monitoring students attention during learning is crucial to successful knowledge acquisition since it influences cognitive function. As a result, gaining a precise picture of a learners mental state may enable interactive learning systems to alter tutoring content, devise effective help tactics, and improve learning outcomes. In computer-based learning environments, keeping track of students mental states is vital. Investigating the feasibility of utilizing active learning in enhancing student engagement index when exposed to various visual stimuli is the genesis of this work. The research includes collecting EEG data from 20 participants (ten males, ten females) while resting and being subjected to various virtual infotainment/educational content. The EEG data were collected using the Allengers Neuro PLOT, a 40-channel wet electrode system. The work includes raw and pre-processed EEG data under quiescent and audio-visual continuous cues. The recorded data is accommodated by a sophisticated EEG data pre-processing pipeline and will be available to the research community for usage. Specifications Table O_TBL View this table: org.highwire.dtl.DTLVardef@340852org.highwire.dtl.DTLVardef@e5c51org.highwire.dtl.DTLVardef@cefb1borg.highwire.dtl.DTLVardef@c7d208org.highwire.dtl.DTLVardef@ae4824_HPS_FORMAT_FIGEXP M_TBL C_TBL

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Upadhyay, R., Singh, M., Mishra, S., Mehta, J., Bansal, A., Baranwal, M., Kumar, V.. 2022-09-22. Electroencephalogram Data Collection for Student Engagement Analysis with Audio-Visual Content. https://doi.org/10.1101/2022.09.20.508656

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