<?xml version="1.0" encoding="utf-8"?>
<export-example>
  <doc>
    <id>3388</id>
    <completedYear/>
    <publishedYear>2020</publishedYear>
    <thesisYearAccepted/>
    <language>eng</language>
    <pageFirst>32</pageFirst>
    <pageLast>40</pageLast>
    <pageNumber/>
    <edition/>
    <issue>March</issue>
    <volume>3</volume>
    <type>article</type>
    <publisherName>Michigan State University</publisherName>
    <publisherPlace/>
    <creatingCorporation/>
    <contributingCorporation/>
    <belongsToBibliography>0</belongsToBibliography>
    <completedDate>--</completedDate>
    <publishedDate>--</publishedDate>
    <thesisDateAccepted>--</thesisDateAccepted>
    <title language="eng">The gaze relational index as a measure of visual expertise</title>
    <abstract language="eng">Eye tracking is a powerful technique that helps reveal how people process visual information. This paper discusses a novel metric for indicating expertise in visual information processing. Named the Gaze&#13;
Relational Index (GRI), this metric is defined as the ratio of mean fixation duration to fixation count.&#13;
Data from two eye-tracking studies of professional vision and visual expertise in using 3D dynamic medical visualizations are presented as cases to illustrate the suitability and additional benefits of the&#13;
GRI. Calculated values of the GRI were higher for novices than for experts, and higher in non-representative, semi-familiar / unfamiliar task conditions than in domain-representative familiar tasks.&#13;
These differences in GRI suggest that, compared to novices, experts engaged in more knowledge-driven, top-down processing that was characterized by quick, exploratory visual search. We discuss future&#13;
research aiming to replicate the GRI in professional domains with complex visual stimuli and to identify the moderating role of cognitive ability on GRI estimates.</abstract>
    <parentTitle language="eng">Journal of Expertise</parentTitle>
    <identifier type="issn">2573-2773</identifier>
    <identifier type="url">https://www.journalofexpertise.org/articles/volume3_issue1/JoE_3_1_Gegenfurtner.pdf</identifier>
    <enrichment key="BegutachtungStatus">peer-reviewed</enrichment>
    <licence>Creative Commons - CC BY - Namensnennung 4.0 International</licence>
    <author>Andreas Gegenfurtner</author>
    <author>Jean-Michel Boucheix</author>
    <author>Hans Gruber</author>
    <author>Florian Hauser</author>
    <author>Erno Lehtinen</author>
    <author>Richard K. Lowe</author>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>eye tracking</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>fixations</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>information processing</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>professional vision</value>
    </subject>
    <subject>
      <language>deu</language>
      <type>uncontrolled</type>
      <value>visual expertise</value>
    </subject>
    <collection role="institutes" number="FakEI">Fakultät Elektro- und Informationstechnik</collection>
    <collection role="othforschungsschwerpunkt" number="16315">Information und Kommunikation</collection>
    <collection role="oaweg" number="">Diamond Open Access - OA-Veröffentlichung ohne Publikationskosten (Sponsoring)</collection>
    <collection role="institutes" number="">Laboratory for Safe and Secure Systems (LAS3)</collection>
  </doc>
</export-example>
