Matching Items (36)
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- All Subjects: psychology
- Creators: Schweitzer, Nicholas
- Creators: Cooke, Nancy J.
Description
Intuitive decision making refers to decision making based on situational pattern recognition, which happens without deliberation. It is a fast and effortless process that occurs without complete awareness. Moreover, it is believed that implicit learning is one means by which a foundation for intuitive decision making is developed. Accordingly, the present study investigated several factors that affect implicit learning and the development of intuitive decision making in a simulated real-world environment: (1) simple versus complex situational patterns; (2) the diversity of the patterns to which an individual is exposed; (3) the underlying mechanisms. The results showed that simple patterns led to higher levels of implicit learning and intuitive decision-making accuracy than complex patterns; increased diversity enhanced implicit learning and intuitive decision-making accuracy; and an embodied mechanism, labeling, contributes to the development of intuitive decision making in a simulated real-world environment. The results suggest that simulated real-world environments can provide the basis for training intuitive decision making, that diversity is influential in the process of training intuitive decision making, and that labeling contributes to the development of intuitive decision making. These results are interpreted in the context of applied situations such as military applications involving remotely piloted aircraft.
ContributorsCovas-Smith, Christine Marie (Author) / Cooke, Nancy J. (Thesis advisor) / Patterson, Robert (Committee member) / Glenberg, Arthur (Committee member) / Homa, Donald (Committee member) / Arizona State University (Publisher)
Created2011
Description
Although there are many forms of organization on the Web, one of the most prominent ways to organize web content and websites are tags. Tags are keywords or terms that are assigned to a specific piece of content in order to help users understand the common relationships between pieces of content. Tags can either be assigned by an algorithm, the author, or the community. These tags can also be organized into tag clouds, which are visual representations of the structure and organization contained implicitly within these tags. Importantly, little is known on how we use these different tagging structures to understand the content and structure of a given site. This project examines 2 different characteristics of tagging structures: font size and spatial orientation. In order to examine how these different characteristics might interact with individual differences in attentional control, a measure of working memory capacity (WMC) was included. The results showed that spatial relationships affect how well users understand the structure of a website. WMC was not shown to have any significant effect; neither was varying the font size. These results should better inform how tags and tag clouds are used on the Web, and also provide an estimation of what properties to include when designing and implementing a tag cloud on a website.
ContributorsBanas, Steven (Author) / Sanchez, Christopher A (Thesis advisor) / Branaghan, Russell (Committee member) / Cooke, Nancy J. (Committee member) / Arizona State University (Publisher)
Created2011
Description
Recent research has identified affirmation of transcendence and exposure to violent Bible verses as being related to greater prejudice toward value-violating out-groups (Blogowska & Saroglou, 2012; Shen et al., 2013). Effects of exposure to specific Bible verses on attitudes toward out-groups have not been measured in combination with the Post-Critical Belief Scale developed by Hutsebaut (1996). The relationships between exposure to scriptural endorsements of prejudice, affirmation vs. disaffirmation of transcendence, literal vs. symbolic processing of religious content, and prejudice toward value-violating out-groups were examined using an online survey administered to a sample of U.S. adults (N=283). Greater affirmation of transcendence scores were linked to greater prejudice toward atheists and homosexuals and more favorable ratings of Christians and highly religious people. Lower affirmation of transcendence scores were linked to less favorable ratings of Christians and highly religious people and more favorable ratings of atheists. Exposure to scriptural endorsements of prejudice did not have a significant effect on levels of prejudice in this study.
ContributorsGrove, Richard (Author) / Robles, Elías (Thesis advisor) / Hall, Deborah (Committee member) / Schweitzer, Nicholas (Committee member) / Arizona State University (Publisher)
Created2013
Description
Deoxyribonucleic Acid (DNA) evidence has been shown to have a strong effect on juror decision-making when presented in court. While DNA evidence has been shown to be extremely reliable, fingerprint evidence, and the way it is presented in court, has come under much scrutiny. Forensic fingerprint experts have been working on a uniformed way to present fingerprint evidence in court. The most promising has been the Probabilistic Based Fingerprint Evidence (PBFE) created by Forensic Science Services (FSS) (G. Langenburg, personal communication, April 16, 2011). The current study examined how the presence and strength of DNA evidence influenced jurors' interpretation of probabilistic fingerprint evidence. Mock jurors read a summary of a murder case that included fingerprint evidence and testimony from a fingerprint expert and, in some conditions, DNA evidence and testimony from a DNA expert. Results showed that when DNA evidence was found at the crime scene and matched the defendant other evidence and the overall case was rated as stronger than when no DNA was present. Fingerprint evidence did not cause a stronger rating of other evidence and the overall case. Fingerprint evidence was underrated in some cases, and jurors generally weighed all the different strengths of fingerprint testimony to the same degree.
ContributorsArthurs, Shavonne (Author) / McQuiston, Dawn (Thesis advisor) / Hall, Deborah (Committee member) / Schweitzer, Nicholas (Committee member) / Arizona State University (Publisher)
Created2012
Description
Researchers have found inconsistent effects (negative or positive) of social relationships on self-control capacity. The variation of findings may depend on the aspects of social relationships. In this study, rather than examining overall social relationships and self-control, characteristics in social relationships were clearly defined, including social support, social connection and social conflict, to determine their specific effects on self-control. An online survey study was conducted, and 292 college students filled out the survey. For data analysis, path analysis was utilized to examined the direct effect and indirect effect from social relationships to self-control. Results showed social connection and social conflict may indirectly associate with self-control through stress, but social support does not. It may suggest, in traditional stress buffering model, it is the social connection in social support that really reduce the stress. Concerning the direct effects, social support and social connection were significantly associated with self-control directly, but social conflict does not. This result may support the Social Baseline Theory that positive social relationships have direct regulating effects. Results are good for guidance of experimental manipulation of social relationships in study of social influences of self-control.
ContributorsGuan, Xin (Author) / Burleson, Mary (Thesis advisor) / Roberts, Nicole (Committee member) / Schweitzer, Nicholas (Committee member) / Arizona State University (Publisher)
Created2012
Description
Research on priming has shown that a stimulus can cause people to behave according to the stereotype held about the stimulus. Two experiments were conducted in which the effects of elderly priming were tested by use of a driving simulator. In both experiments, participants drove through a simulated world guided by either an elderly or a younger female voice. The voices told the participants where to make each of six turns. Both experiments yielded slower driving speeds in the elderly voice condition. The effect was universal regardless of implicit and explicit attitudes towards elderly people.
ContributorsFoster, L Bryant (Author) / Branaghan, Russell (Thesis advisor) / Becker, David (Committee member) / Cooke, Nancy J. (Committee member) / Arizona State University (Publisher)
Created2012
Description
By extracting communication sequences from audio data collected during two separate five-person mission-planning tasks, interaction patterns in team communication were analyzed using a recurrence-based, nonlinear dynamics approach. These methods, previously successful in detecting pattern change in a three-person team task, were evaluated for their applicability to larger team settings, and their ability to detect pattern change when team members switched roles or locations partway through the study (Study 1) or change in patterns over time (Study 2). Both traditional interaction variables (Talking Time, Co-Talking Time, and Sequence Length of Interactions) and dynamic interaction variables (Recurrence Rate, Determinism, and Pattern Information) were explored as indicators and predictors of changes in team structure and performance. Results from these analyses provided support that both traditional and dynamic interaction variables reflect some changes in team structure and performance. However, changes in communication patterns were not detected. Because simultaneous conversations are possible in larger teams, but not detectable through our communication sequence methods, team pattern changes may not be visible in communication sequences for larger teams. This suggests that these methods may not be applicable for larger teams, or in situations where simultaneous conversations may occur. Further research is needed to continue to explore the applicability of recurrence-based nonlinear dynamics in the analysis of team communication.
ContributorsFouse, Shannon (Author) / Cooke, Nancy J. (Thesis advisor) / Becker, David (Thesis advisor) / Gorman, Jamie (Committee member) / Arizona State University (Publisher)
Created2012
Description
Scientists, lawyers, and bioethicists have pondered the impact of scientifically deterministic evidence on a judge or jury when deciding the sentence of a criminal. Though the impact may be one that relieves the amount of personal guilt on the part of the criminal, this evidence may also be the very reason that a judge or jury punishes more strongly, suggesting that this type of evidence may be a double-edged sword. 118 participants were shown three films of fictional sentencing hearings. All three films introduced scientifically deterministic evidence, and participants were asked to recommend a prison sentence. Each hearing portrayed a different criminal with different neurological conditions, a different crime, and a different extent of argumentation during closing arguments about the scientifically deterministic evidence. Though the argumentation from the prosecution and the defense did not affect sentencing, the interaction of type of crime and neurological condition did.
ContributorsMeschkow, Alisha Sadie (Author) / Schweitzer, Nicholas (Thesis director) / Robert, Jason (Committee member) / Patten, K. Jakob (Committee member) / Barrett, The Honors College (Contributor) / Department of Psychology (Contributor)
Created2014-05
Description
Risk assessments are key legal tools that can inform a number of legal decisions regarding parole sentencing and predict recidivism rates. Due to assessments being
historically performed by humans, they can be prone to bias and have come under various
amounts of scrutiny. The increased capability and application of machine learning
technology has lead the justice system to incorporate algorithms and codes to increase
accuracy and reliability. This study researched laypersons’ attitudes towards these algorithms
and how they would change when exposed to an algorithm that made errors in the risk
assessment process. Participants were tasked with reading two vignettes and answering a series
of questions to assess the differences in their perceptions towards machine learning and
clinician-based risk assessments. The research findings showed that individuals lent more trust
to clinicians and had more confidence in their assessments when compared to machines, but
were not significantly more punitive when it came to attributing blame and judgement for the
consequences of an incorrect risk assessment. Participants had a significantly more positive
attitude towards clinician-based risk assessments, noting their assessments as being more
reliable, informed, and trustworthy. Participants were also asked to come to a parole decision
using the assessment of either a clinician or machine learning algorithm at the end of the study
and rate their own confidence in their decision. Results found that participants were only
significantly less confident in their decision when exposed to previous instances of risk
assessments with error, but that there was no significant difference in their confidence based
solely on who conducted the assessment.
ContributorsMa, Angeline (Author) / Schweitzer, Nicholas (Thesis advisor) / Powell, Derek (Committee member) / Smalarz, Laura (Committee member) / Arizona State University (Publisher)
Created2023
Description
In the legal system, the prediction of a person’s risk of committing a crime has mostly been based on expert judgment. However, newer techniques that employ machine learning (ML)—a type of artificial intelligence—are being implemented throughout the justice system. Yet, there is a lack of research on how the public perceives and uses machine learning risk assessments in legal settings. In two mock-trial vignette studies, the perception of ML-based risk assessments versus more traditional methods was assessed. Study 1 was a 2 (severity of crime: low, high) x 2 (risk assessment type: expert, machine learning) x 2 (risk outcome: low, high) between-subjects design. Participants expressed ethical concerns and discouraged the use of machine learning risk assessments in sentencing decisions, but punishment recommendations were not affected. Study 2 was a within-subjects design where participants were randomly assigned read through one of three crime scenarios (violent, white-collar, sex offense) and one of three risk assessment techniques (expert, checklist, machine learning). Consistent with Study 1, participants had ethical concerns and disagreed with the use of machine learning risk assessments in bail decisions, yet their own decisions and recommendations did not reflect these concerns. Overall, laypeople express skepticism toward these new methods, but do not appear to differentially rely on ML-based versus traditional risk assessments in their own judgments.
ContributorsFine, Anna (Author) / Schweitzer, Nicholas (Thesis advisor) / Salerno, Jessica (Committee member) / Smalarz, Laura (Committee member) / Arizona State University (Publisher)
Created2021