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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An empirical assessment of the magician's "off-beat

Description
Magicians are informal cognitive scientists who regularly test their hypotheses in the real world. As such, they can provide scientists with novel hypotheses for formal psychological research as well as a real-world context in which to study them. One domain where magic can directly inform science is the deployment of…

Magicians are informal cognitive scientists who regularly test their hypotheses in the real world. As such, they can provide scientists with novel hypotheses for formal psychological research as well as a real-world context in which to study them. One domain where magic can directly inform science is the deployment of attention in time and across modalities. Both magicians and scientists have an incomplete understanding of how attention operates in time, rather than in space. However, magicians have highlighted a set of variables that can create moments of visual attentional suppression, which they call "off-beats," and these variables can speak to modern models of temporal attention. The current research examines two of these variables under conditions ranging from artificial laboratory tasks to the (almost) natural viewing of magic tricks. Across three experiments, I show that the detection of subtle dot probes in a noisy visual display and pieces of sleight of hand in magic tricks can be influenced by the seemingly irrelevant rhythmic qualities of auditory stimuli (cross-modal attentional entrainment) and processes of working memory updating (akin to the attentional blink).
ContributorsBarnhart, Anthony S (Author) / Goldinger, Stephen D. (Thesis advisor) / Glenberg, Arthur M. (Committee member) / Homa, Donald (Committee member) / Simons, Daniel J. (Committee member) / Arizona State University (Publisher)
Created2013
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The Impact of Blocked vs. Distributed Category Learning on Subsequent Generalization

Description
It is a well-established finding in memory research that spacing or distributing information, as opposed to blocking all the information together, results in an enhanced memory of the learned material. Recently, researchers have decided to investigate if this spacing effect is also beneficial in category learning. In a set of…

It is a well-established finding in memory research that spacing or distributing information, as opposed to blocking all the information together, results in an enhanced memory of the learned material. Recently, researchers have decided to investigate if this spacing effect is also beneficial in category learning. In a set of experiments, Carvalho & Goldstone (2013), demonstrated that a blocked presentation showed an advantage during learning, but that ultimately, the distributed presentation yielded better performance during a post-learning transfer test. However, we have identified a major methodological issue in this study that we believe contaminates the results in a way that leads to an inflation and misrepresentation of learning levels. The present study aimed to correct this issue and re-examine whether a blocked or distributed presentation enhances the learning and subsequent generalization of categories. We also introduced two shaping variables, category size and distortion level at transfer, in addition to the mode of presentation (blocked versus distributed). Results showed no significant differences of mode of presentation at either the learning or transfer phases, thus supporting our concern about the previous study. Additional findings showed benefits in learning categories with a greater category size, as well as higher classification accuracy of novel stimuli at lower-distortion levels.
ContributorsJacoby, Victoria Leigh (Author) / Homa, Donald (Thesis director) / Brewer, Gene (Committee member) / Davis, Mary (Committee member) / Department of Psychology (Contributor) / Barrett, The Honors College (Contributor)
Created2017-12