Date of Award


Degree Type


Degree Name

Master of Arts - Psychology



First Advisor

Dr. Steven Estrada

Second Advisor

Dr. Scott Drury

Third Advisor

Dr. Sylvia Middlebrook

Fourth Advisor

Dr. George Day


Preferred modes of thinking, otherwise known as biases, have been well documented in adult reasoning and decision-making (Evans, 2003; Gilovich, Griffin, & Kahneman, 2002; Reyna & Brainerd, 2011; Tversky & Kahneman, 1986). Researchers have explained these biases by proposing that the basis for them is a system of thought that relies mostly on intuition and “gut feelings” rather than logical analysis of the situation (Reyna & Brainerd, 2011; Tversky & Kahneman, 1986). According to standard dual-process theories, intuition is described as a thought process so quick, it is automatic and, at times unconscious; conversely, analytical thinking is slow and steady, involving analysis and conscious deliberation (Reyna & Brainerd, 2011). Though several dual-process models for cognition have been proposed, including system 1/system 2, prototype/willingness, and the hot/cold empathy gap, only fuzzy-trace theory offers concrete predictions concerning development that are consistent with known data (Kruglanski & Gigerenzer, 2011; Reyna & Casillas, 2009). For example, research has shown that adults display greater reasoning biases than children, in that adults are more likely than children to process and use extraneous information, such as inconsequential differences in wording, in their decisions (Jacobs & Potenza, 1991; Reyna & Ellis, 1994). Of interest for the current study, fuzzy-trace theory posits that different ways of processing lead to different outcomes in risk-taking behavior. Further, fuzzy-trace theory proposes a framework that explains how risk perception changes across the lifespan and how these changes often lead to less risk-taking from childhood and adolescence into adulthood (Reyna, 2012; Reyna et al., 2018; Reyna & Adam, 2003; Reyna & Farley, 2006).

Creative Commons License

Creative Commons License
This work is licensed under a Creative Commons Attribution-Noncommercial-No Derivative Works 4.0 License.



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