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dc.contributor.authorHohenstern, Joseph Francis
dc.date.accessioned2014-03-04T18:24:35Z
dc.date.available2014-03-04T18:24:35Z
dc.date.issued2009-12
dc.identifier.otherhohenstern_joseph_f_200912_ms
dc.identifier.urihttp://purl.galileo.usg.edu/uga_etd/hohenstern_joseph_f_200912_ms
dc.identifier.urihttp://hdl.handle.net/10724/26073
dc.description.abstractAlgorithm animation (AA) involves the process of cycling through and graphically generating a series of snapshots taken of an algorithm’s critical states over the course of its execution. Professionals in the computing community have a strong intuition that these forms of visualization act as powerful pedagogical tools to foster student comprehension and learning of an algorithm’s abstract notations. However, this popular belief has left researchers wondering about AA effectiveness due to its mixed performance in studies and underutilized in education. Since viewers rely heavily on visual stimuli when viewing an AA, the extra burden could hinder their performance in the comprehension of algorithms. It is the goal of this study to lessen the burden on the visual stimuli by using non-speech audio to reinforce and/or replace some graphical representations. Another technique we examine is the use of ideograms to make AAs more clear and concise.
dc.languageeng
dc.publisheruga
dc.rightspublic
dc.subjectalgorithm animations, non-speech audio, ideograms
dc.titleAnalysis of ideogram and non-speech audio techniques in algorithm animations
dc.typeThesis
dc.description.degreeMS
dc.description.departmentComputer Science
dc.description.majorComputer Science
dc.description.advisorEileen Kraemer
dc.description.committeeEileen Kraemer
dc.description.committeeMaria Hybinette
dc.description.committeeDaniel Everett


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