Assessing Performance Using Kinesic Behavior Cues In A Game-Based Training Environment

Keywords

Behavior cue detection; Game-based training; Gaming strategies; Kinesics; Performance

Abstract

Warfighters are trained in Behavior Cue Analysis to detect anomalies in their environment amongst several domains. This research highlights the Kinesics domain for Behavior Cue Analysis training. As efforts to transition from live, classroom-based training to distributed virtual environment training continue, investigating instructional gaming strategies that elicit improved performance and user perception becomes progressively important. Applying gaming strategies (e.g., goals, competition, feedback, etc.) to Simulation-Based Training, offers a novel approach to delivering the core curriculum for Behavior Cue Analysis. This paper examines two game-based strategies (i.e., excessive positive feedback and competition) to determine the difference in performance scores (i.e., detection and classification accuracy). The results showed no significant difference in performance; however, insight was gained on the significance of excessive positive feedback. Consequently, the paper considers the application of game-based strategies for training behavior cues, as well as discusses the limitations and alternatives for future research.

Publication Date

1-1-2015

Publication Title

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

Volume

9179

Number of Pages

421-428

Document Type

Article; Proceedings Paper

Personal Identifier

scopus

DOI Link

https://doi.org/10.1007/978-3-319-21067-4_43

Socpus ID

84947250858 (Scopus)

Source API URL

https://api.elsevier.com/content/abstract/scopus_id/84947250858

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