Understanding shooting bias using a dual mechanisms of control framework

Deciding to use lethal force with a firearm is a critical decision that has major implications within society. In order to investigate racial bias in shooting decisions, the current dissertation uses the First-Person Shooter Task (FPST). Previous literature has shown that shooting decisions in this task are made faster and more often towards Black targets when compared to White targets. The relationship between this shooting bias and individual differences in cognitive ability is explored. The FPST was presented in three different conditions, each with trial proportions that varied in level of stereotype congruency (i.e., trials that are congruent with racial stereotypes). A Baseline condition presented an even distribution of Black Armed, Black Unarmed, White Armed, and White unarmed targets. A Mostly Congruent condition presented most (80%) of the Black targets as armed and most (80%) of the White targets as unarmed. A Mostly Incongruent condition presented most of the Black targets as unarmed and the White targets as mostly armed. Working memory, theoretically represented as a system of three separate components, was related to shooting behavior in these FPST conditions. The attentional control component of working memory was shown to be more related to shooting bias when compared to the capacity-related components, especially in the Mostly Incongruent condition (where most trials required making shooting decisions that go against racial stereotype). Study 2 used Confirmatory Factor Analysis to test whether attentional control ability was separate from proactive and reactive control strategy usage. Results showed that the attentional control ability was independent from which attentional control strategy was used. Finally, relating attentional control ability and attentional control strategies to shooting behavior, results showed that people with high attentional control and high proactive control usage were more likely to correctly adjust their expectations of threat in the Mostly Incongruent condition when compared to people with lower ability. People with low attentional control and high proactive control usage were more likely to adjust their expectations of threat based on racial stereotypes. Overall, these findings provide new insight into how cognitive ability interacts with shooting decisions in order to produce racial shooting bias

Individual Differences in the Acquisition of Strategies in a Complex Task

A multi-session experiment explored the relationship between individual differences and the development of strate-gies in a complex task environment. In the first session, participants completed measures of working memory and adaptivity.Participants then performed 4.5 hours of a multitasking activity that involved prioritizing, selecting, and sorting objects intobins under time pressure. The analyses reported here focus on how participants prioritized objects in a queue of objects andselected objects from that queue for sorting. Priority selection strategies were automatically extracted using machine learningmethods. Differences in strategy use were related to measures of working memory and adaptivity. Strategy use and strategychange mediated the relationship between task performance and individual differences. A hierarchical clustering analysis re-vealed patterns of strategy shifts that distinguished between participants who improved and those who did not. These resultsprovide a basis for examining strategy training geared toward individuals’ cognitive abilities

Evaluation of Methods for Tracking Strategies in Complex Tasks

In complex tasks, high performers often have better strategies than low performers even with similar practice. Relativelylittle research has examined how people form and modify strategies in tasks that permit a large set of possible strategies.One challenge with such research is determining strategies based on behavior. Three algorithms were developed to trackthe task features people employ in their strategies while performing a complex task. An ACT-R model that performs thetask was created to collect simulated data with a range of known strategies. The performance of the three algorithms iscompared, and a decision tree classification algorithm yielded the best performance across the test cases. Summary datafrom applying the algorithms to human data on the tasks is also presented and highlights potential challenges for futurework. However, this approach to tracking strategy exploration may enable further development of theories about howpeople search for good strategies