Assessing Threat Detection Scenarios through Hypothesis Generation and Testing

Autor: Laura A. Zimmerman, Drew A Leins, Singer T Singer, Jessica Marcon, Christopher L Vowels, Ron Mueller
Rok vydání: 2015
Předmět:
DOI: 10.21236/ad1002692
Popis: The purpose of this research was to explore the decision-making processes of Soldiers with different levels of experience as they evaluated scenarios with varying levels of uncertainty. This research focused on understanding the interaction of experience and uncertainty on hypothesis generation and testing, and on the relationship between confidence and decision-making. Soldiers engaged in computer-based exercises that measured decision-making performance in a threat detection task. These exercises involved reading threat-relevant scenarios and then reporting threat decisions. We gained a better understanding as to how Soldiers select and integrate cues in uncertain decision environments involving potential threats by having them complete such exercises. Findings indicated that experienced and inexperienced Soldiers tended to focus on different priority threats (or what they perceived as the most important threats). Experienced Soldiers were likely to report more discrete threats when identifying their priority threat in each scenario. They were also more likely to search information that confirmed their initial hypotheses. Overall, changes in hypotheses appeared to be associated with lower initial confidence ratings. Across experience levels, Soldiers tended to search relevant details more often than irrelevant details. Those findings provide insight into the cognitive processes Soldiers with varying levels of experience use to make threat decisions in certain and uncertain environments.
Databáze: OpenAIRE