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Toward Rapid and Predictive Neurodynamic Feedback and Scaffolding for Teams

Building Intelligent Tutoring Systems for Teams

ISBN: 978-1-78754-474-1, eISBN: 978-1-78754-473-4

Publication date: 20 September 2018

Abstract

This chapter describes a neurodynamic modeling approach which may be useful for dynamically assessing teamwork in healthcare and military situations. It begins with a description of electroencephalographic (EEG) signal acquisition and the transformation of the physical units of EEG signals into quantities of information. This transformation provides quantitative, dynamic, and generalizable neurodynamic models that are directly comparable across teams, tasks, training protocols, and team experience levels using the same measurement scale, bits of information. These bits of information can be further used to dynamically guide team performance or to provide after-action feedback that is linked to task events and team actions.

These ideas are instantiated and expanded in the second section of the chapter by showing how these data abstractions, compressions, and transformations take advantage of the natural information redundancy in biologic signals to substantially reduce the number of data dimensions, making the incorporation of neurodynamic feedback into Intelligent Tutoring Systems (ITSs) achievable.

Keywords

Acknowledgements

Acknowledgments

The studies were supported in part by the JUMP Foundation for Simulation Research, by The Defense Advanced Research Projects Agency under contract number(s) W31P4Q12C0166, and with funding from the Illinois Neurological Institute.

Citation

Stevens, R., Galloway, T.L., Willemsen-Dunlap, A. and Avellino, A.M. (2018), "Toward Rapid and Predictive Neurodynamic Feedback and Scaffolding for Teams", Building Intelligent Tutoring Systems for Teams (Research on Managing Groups and Teams, Vol. 19), Emerald Publishing Limited, Leeds, pp. 153-172. https://doi.org/10.1108/S1534-085620180000019011

Publisher

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Emerald Publishing Limited

Copyright © The Learning Chameleon, Inc., 2018