Towards Mind Wandering Adaptive Online Learning and Virtual Work Experiences
| dc.contributor.author | Conrad, Colin | |
| dc.contributor.author | Newman, Aaron J. | |
| dc.date.accessioned | 2022-06-17T15:02:12Z | |
| dc.date.available | 2022-06-17T15:02:12Z | |
| dc.date.issued | 2022-06-14 | |
| dc.description | This document is a preprint of a paper presented at the 2022 NeuroIS Retreat in Vienna, Austria. The full paper will be published by Springer in late 2022. | en_US |
| dc.description.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. | en_US |
| dc.identifier.citation | Conrad, C. and Newman, A. J. (2022). Towards mind wandering adaptive online learning and virtual work experiences. Proceedings of the 2022 NeuroIS Retreat. | en_US |
| dc.identifier.uri | http://hdl.handle.net/10222/81704 | |
| dc.relation.ispartof | Proceedings of the 2022 NeuroIS Retreat | en_US |
| dc.title | Towards Mind Wandering Adaptive Online Learning and Virtual Work Experiences | en_US |
| dc.type | Text | en_US |