Theses and Dissertations
This collection includes both ASU Theses and Dissertations, submitted by graduate students, and the Barrett, Honors College theses submitted by undergraduate students.
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- Creators: Blais, Chris
- Creators: McNamara, Danielle
Description
Recognition memory is examined by exposing a person to a stimulus and later prompting them with the same stimulus to examine their ability to accurately acknowledge that the stimulus was previously encountered (Kahana, 2012). In recognition memory, confidence ratings are taken during the testing phase to assess how confident the participant is that the old-new judgment that they just made is accurate (Busey et al., 2000). Confidence is a metacognitive assessment about the accuracy of perception of decision making based on the amount, speed, and clarity of thoughts that come to mind (Dunlosky and Metcalfe, 2008). The goal of the current study is to better understand how assessing recognition memory using a variety of test procedures influences memory accuracy using the signal detection theory and adding multiple confidence scales that vary in granularity. Based on the previous literature, it is hypothesized that; 1) tasks ordered sequentially will produce greater recognition accuracy (d') than the simultaneous (dual task) condition; 2) confidence scale of 3 points will produce a larger d' than the 7 point scale, and the 7 point scale will produce a larger d' than the 100 point scale; and 3) task mode (ordered vs. sequenced) will interact with confidence scale granularity to predict memory accuracy, such that sequential judgments lessen demands on working memory that come from maintaining an increasing number of decision criteria in comparison to the dual task. Results indicated all hypotheses were not upheld. The findings suggest that taxing working memory may not affect decisional accuracy on a recognition task incorporating confidence judgments.
ContributorsSullivan, Krysten Jennifer (Author) / Brewer, Gene (Thesis director) / Blais, Chris (Committee member) / Davis, Mary (Committee member) / Department of Psychology (Contributor) / Barrett, The Honors College (Contributor)
Created2017-12
Description
Early adolescence is a pivotal stage of social and emotional development. Socialization traditionally occurs in person, but social interactions via technology (e.g., social media, video games) have grown in popularity. However, little research has been conducted on how early adolescents interact with technology and how these interactions relate to their socialization as well as other factors such as reading habits or academic achievement. Seventh and eighth grade students (n = 719) completed a survey that captured information about their technology use, their academic habits and performance, and extracurricular involvement. It was hypothesized that those involved in more extracurricular activities would use the internet more socially and that internet use would be negatively correlated to both academic performance and recreational reading. Responses indicated that a majority of students have access to technology (e.g. internet, computers, television, gaming consoles, and tablets) in their homes. Social media use differed drastically between platforms. Analyses indicated a relation between amount of extracurricular activities on social television watching and social internet use, but not on social gaming. A significant negative correlation was found between recreational reading and time spent socializing online, but there was no significant effect of these factors on academic performance. Thus, hypotheses were partially supported by the relation between amount of extracurriculars and social internet use and the negative correlation between time spent socializing online and recreational reading.
ContributorsHorner, Kate Elizabeth (Author) / McNamara, Danielle (Thesis director) / McCarthy, Kathryn (Committee member) / Davis, Mary (Committee member) / Division of Teacher Preparation (Contributor) / Department of Psychology (Contributor) / Barrett, The Honors College (Contributor)
Created2017-12