Acquisition Of Skill Sets And Mental Models Over Time
Keywords
Familiarity; Learning; Localization; Mental model; Skill acquisition; Target identification; Time; Training; UAV; UGV
Abstract
This paper is intended discuss issues associated with different measures of ability and performance with respect to the operation of multiple unmanned systems. In describing these differences, we are interested in illustrating general trends of skill acquisition and factors that may influence the rate at which skills are acquired over time. Based on the results across two experiments, we argue that declarative knowledge (e.g. target familiarity) represents a dimension performance that can improve over a short period of time (~2 hours), but other dimensions of performance (e.g. correct localization using ground images) represent difficult dimensions of performance that require long periods of time for significant improvement (+9 hours). Furthermore, individual differences, such as spatial ability, and reconnaissance performance appear to be associated with the rate at which operators improved at performing different types of localization tasks. Implications of these findings are discussed..
Publication Date
4-19-2016
Publication Title
Advances in Cognitive Ergonomics
Number of Pages
597-606
Document Type
Article; Book Chapter
Personal Identifier
scopus
Copyright Status
Unknown
Socpus ID
84878066685 (Scopus)
Source API URL
https://api.elsevier.com/content/abstract/scopus_id/84878066685
STARS Citation
Fincannon, Thomas; Ososky, Scott; Keebler, Joseph; and Jentsch, Florian, "Acquisition Of Skill Sets And Mental Models Over Time" (2016). Scopus Export 2015-2019. 3885.
https://stars.library.ucf.edu/scopus2015/3885