Towards Mind Wandering Adaptive Online Learning and Virtual Work Experiences

Colin Conrad () and Aaron J. Newman
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Colin Conrad: Dalhousie University
Aaron J. Newman: Dalhousie University

A chapter in Information Systems and Neuroscience, 2022, pp 261-267 from Springer

Abstract: Abstract NeuroIS researchers have become increasingly interested in the design of new types of information systems that leverage neurophysiological data. In this paper we describe the results of machine learning analysis which validates a method for the passive detection of mind wandering. Following the presentation of the results, we describe ways that this technique could be applied to create a neuroadaptive online learning and virtual meeting tool which may improve users’ retention of information by providing auditory feedback.

Keywords: Electroencephalography (EEG); Machine learning applications; Neuro-adaptive systems; Mind wandering (search for similar items in EconPapers)
Date: 2022
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Persistent link: https://EconPapers.repec.org/RePEc:spr:lnichp:978-3-031-13064-9_27

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DOI: 10.1007/978-3-031-13064-9_27

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