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dc.contributor.advisorNunamaker, Jay F., Jr.en
dc.contributor.authorGrimes, George Mark
dc.creatorGrimes, George Marken
dc.date.accessioned2015-06-11T19:23:47Zen
dc.date.available2015-06-11T19:23:47Zen
dc.date.issued2015en
dc.identifier.urihttp://hdl.handle.net/10150/556821en
dc.description.abstractThis dissertation presents three studies consisting of seven experiments that investigate the relationship between human-computer interaction (HCI) behavior and changes in cognitive states by using keystroke dynamics (KD) and mouse dynamics (MD) as physiological indicators of cognitive change. The first two chapters discuss the importance of being able to detect changes in affect, cognitive load, and deception and provide a theoretical base for this research, pulling heavily from cognitive science, psychology and communication literature. We also discuss the current state of the art in keystroke and mouse dynamics and what makes the techniques presented here different. Chapters three and four present five experiments that explore the influence of affect and cognitive load on KD and MD. The results of these experiments suggest that many features of typing and mouse movement behavior including transition time, rollovers, duration, number of direction changes, and distance traveled are influenced by changes in affect and cognitive load. In chapter five we operationalize these findings in a credibility assessment context and describe two experiments in which participants behave deceptively in computer mediated interactions. In both experiments, we find significant differences in typing behavior, in line with the findings of the first two studies. Chapter six summarizes the results and provides a way forward for future research in human computer interaction. The work presented in this dissertation describes a novel approach to inferring cognitive changes using low cost, non-invasive, and transparent monitoring of HCI behavior with important implications for both research and practice.
dc.language.isoen_USen
dc.publisherThe University of Arizona.en
dc.rightsCopyright © is held by the author. Digital access to this material is made possible by the University Libraries, University of Arizona. Further transmission, reproduction or presentation (such as public display or performance) of protected items is prohibited except with permission of the author.en
dc.subjectCognitive Loaden
dc.subjectHuman Computer Interactionen
dc.subjectKeystroke Dynamicsen
dc.subjectMouse Dynamicsen
dc.subjectTypingen
dc.subjectManagement Information Systemsen
dc.subjectAffecten
dc.titleAnalysis of Human Computer Interaction Behavior for Assessment of Affect, Cognitive Load, and Credibilityen_US
dc.typetexten
dc.typeElectronic Dissertationen
thesis.degree.grantorUniversity of Arizonaen
thesis.degree.leveldoctoralen
dc.contributor.committeememberValacich, Joseph S.en
dc.contributor.committeememberBurgoon, Judee K.en
dc.contributor.committeememberNunamaker, Jay F., Jr.en
dc.description.releaseRelease after 15-May-2016en
thesis.degree.disciplineGraduate Collegeen
thesis.degree.disciplineManagement Information Systemsen
thesis.degree.namePh.D.en
refterms.dateFOA2016-05-15T00:00:00Z
html.description.abstractThis dissertation presents three studies consisting of seven experiments that investigate the relationship between human-computer interaction (HCI) behavior and changes in cognitive states by using keystroke dynamics (KD) and mouse dynamics (MD) as physiological indicators of cognitive change. The first two chapters discuss the importance of being able to detect changes in affect, cognitive load, and deception and provide a theoretical base for this research, pulling heavily from cognitive science, psychology and communication literature. We also discuss the current state of the art in keystroke and mouse dynamics and what makes the techniques presented here different. Chapters three and four present five experiments that explore the influence of affect and cognitive load on KD and MD. The results of these experiments suggest that many features of typing and mouse movement behavior including transition time, rollovers, duration, number of direction changes, and distance traveled are influenced by changes in affect and cognitive load. In chapter five we operationalize these findings in a credibility assessment context and describe two experiments in which participants behave deceptively in computer mediated interactions. In both experiments, we find significant differences in typing behavior, in line with the findings of the first two studies. Chapter six summarizes the results and provides a way forward for future research in human computer interaction. The work presented in this dissertation describes a novel approach to inferring cognitive changes using low cost, non-invasive, and transparent monitoring of HCI behavior with important implications for both research and practice.


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