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          <dc:identifier>https://hdl.handle.net/2286/R.I.54933</dc:identifier>
                  <dc:rights>http://rightsstatements.org/vocab/InC/1.0/</dc:rights>
                  <dc:date>2019</dc:date>
                  <dc:format>87 pages</dc:format>
                  <dc:type>Doctoral Dissertation</dc:type>
          <dc:type>Academic theses</dc:type>
          <dc:type>Text</dc:type>
                  <dc:language>eng</dc:language>
                  <dc:contributor>Henry, Matthew McClellan</dc:contributor>
          <dc:contributor>Atkinson, Robert K</dc:contributor>
          <dc:contributor>Johnson-Glenberg, Mina C</dc:contributor>
          <dc:contributor>Nelson, Brian C</dc:contributor>
          <dc:contributor>Arizona State University</dc:contributor>
                  <dc:description>Doctoral Dissertation Educational Technology 2019</dc:description>
          <dc:description>Evidence suggests that Augmented Reality (AR) may be a powerful tool for &lt;br/&gt;&lt;br/&gt;alleviating certain, lightly held scientific misconceptions.  However, many &lt;br/&gt;&lt;br/&gt;misconceptions surrounding the theory of evolution are deeply held and resistant to &lt;br/&gt;&lt;br/&gt;change. This study examines whether AR can serve as an effective tool for alleviating &lt;br/&gt;&lt;br/&gt;these misconceptions by comparing the change in the number of misconceptions &lt;br/&gt;&lt;br/&gt;expressed by users of a tablet-based version of a well-established classroom simulation to &lt;br/&gt;&lt;br/&gt;the change in the number of misconceptions expressed by users of AR versions of the &lt;br/&gt;&lt;br/&gt;simulation. &lt;br/&gt;&lt;br/&gt;The use of realistic representations of objects is common for many AR &lt;br/&gt;&lt;br/&gt;developers. However, this contradicts well-tested practices of multimedia design that &lt;br/&gt;&lt;br/&gt;argue against the addition of unnecessary elements. This study also compared the use of &lt;br/&gt;&lt;br/&gt;representational visualizations in AR, in this case, models of ladybug beetles, to symbolic &lt;br/&gt;&lt;br/&gt;representations, in this case, colored circles.  &lt;br/&gt;&lt;br/&gt;To address both research questions, a one-factor, between-subjects experiment &lt;br/&gt;&lt;br/&gt;was conducted with 189 participants randomly assigned to one of three conditions: non&lt;br/&gt;&lt;br/&gt;AR, symbolic AR, and representational AR. Measures of change in the number and types &lt;br/&gt;&lt;br/&gt;of misconceptions expressed, motivation, and time on task were examined using a pair of &lt;br/&gt;&lt;br/&gt;planned orthogonal contrasts designed to test the study’s two research questions.  &lt;br/&gt;&lt;br/&gt;Participants in the AR-based condition showed a significantly smaller change in &lt;br/&gt;&lt;br/&gt;the number of total misconceptions expressed after the treatment as well as in the number &lt;br/&gt;&lt;br/&gt;of misconceptions related to intentionality; none of the other misconceptions examined &lt;br/&gt;&lt;br/&gt;showed a significant difference. No significant differences were found in the total &lt;br/&gt;&lt;br/&gt;number of misconceptions expressed between participants in the representative and &lt;br/&gt;&lt;br/&gt;symbolic AR-based conditions, or on motivation. Contrary to the expectation that the &lt;br/&gt;&lt;br/&gt;simulation would alleviate misconceptions, the average change in the number of &lt;br/&gt;&lt;br/&gt;misconceptions expressed by participants increased. This is theorized to be due to the &lt;br/&gt;&lt;br/&gt;juxtaposition of virtual and real-world entities resulting in a reduction in assumed &lt;br/&gt;&lt;br/&gt;intentionality.</dc:description>
                  <dc:subject>Educational technology</dc:subject>
          <dc:subject>Augmented Reality</dc:subject>
          <dc:subject>Misconceptions</dc:subject>
          <dc:subject>Mixed reality</dc:subject>
          <dc:subject>Natural selection</dc:subject>
                  <dc:title>Exploring the Efficacy of Using Augmented Reality to Alleviate Common Misconceptions about Natural Selection</dc:title></oai_dc:dc></metadata></record></GetRecord></OAI-PMH>
