Title
Translating Learning Theories Into Physiological Hypotheses
Keywords
Adaptive training; Augmented cognition; Learning efficiency
Abstract
The battlefield has become an increasingly more complicated setting in which to operate. Additional stressors, complexity, and novel situations have challenged not only those in the field, but consequently also those in training. More information must be imparted to the trainees, yet more time is not available. Thus, in this paper, we consider one way to optimize the delivery and acquisition of knowledge that can be meaningfully applied to the field setting. We hypothesize that for learning efficiency to be maximized, we need to keep learners in a constant state of engagement and absorption. As such, we consider neuro-physiological hypotheses that can help prescribe mitigation strategies to reduce the impact of sub-optimal learning. © 2009 Springer.
Publication Date
12-1-2009
Publication Title
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume
5638 LNAI
Number of Pages
678-686
Document Type
Article; Proceedings Paper
Personal Identifier
scopus
DOI Link
https://doi.org/10.1007/978-3-642-02812-0_77
Copyright Status
Unknown
Socpus ID
77952004269 (Scopus)
Source API URL
https://api.elsevier.com/content/abstract/scopus_id/77952004269
STARS Citation
Vogel-Walcutt, Jennifer J.; Nicholson, Denise; and Bowers, Clint, "Translating Learning Theories Into Physiological Hypotheses" (2009). Scopus Export 2000s. 11397.
https://stars.library.ucf.edu/scopus2000/11397