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        <identifier>oai:dcpapers.dublincore.org:952136290</identifier>
        <datestamp>2013-09-02</datestamp>
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      <dc:title>Reusing Textual Resources in Educational Assessment: Adding Text Readability Metrics to Learning Metadata</dc:title>
      <dc:creator>Foulonneau, Muriel</dc:creator>
      <dc:creator>Ras, Eric</dc:creator>
      <dc:creator>Abou Zeid, Elie</dc:creator>
      <dc:creator>Atéchian, Talar</dc:creator>
      <dc:subject>education</dc:subject>
      <dc:subject>assessment</dc:subject>
      <dc:subject>text readability metrics</dc:subject>
      <dc:subject>Web mining</dc:subject>
      <dc:description>Many digital libraries have identified learners as a core audience. Indeed, many of 
                    their resources can be reused in educational contexts. Nevertheless, the search criteria used for retrieving 
                    texts as a specific multimedia type are limited. They often do not include properties specific to 
                    educational contexts. Assigning LOM metadata to a theatre play or a painting is difficult, since it was 
                    not created for a particular learning context. However, it is possible to assign metadata to textual 
                    resources based on their characteristics and map these characteristics to an IEEE LOM or DCMI Audience 
                    metadata element. Text readability metrics for instance can be mapped to educational audiences. In the 
                    scope of the iCase project, we are developing an assessment item generation system. We have therefore 
                    analyzed metadata models for assessment resources and defined a set of metadata which should be assigned 
                    to the multimedia components of assessment items. A major challenge consists in relating multimedia 
                    resources to the specific audience metadata. In order to include external resources such as texts, we 
                    developed a component available as a Web service to assign metrics related to text readability. In this 
                    paper, we present metadata for assessment items and introduce readability metrics.</dc:description>
      <dc:publisher>Dublin Core Metadata Initiative</dc:publisher>
      <dc:date>2013-09-02</dc:date>
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      <dc:identifier>https://doi.org/10.23106/dcmi.952136290</dc:identifier>
      <dc:identifier>https://dcpapers.dublincore.org/article/952136290</dc:identifier>
      <dc:source>Dublin Core Metadata Initiative Conference Proceedings</dc:source>
      <dc:language>en</dc:language>
      <dc:relation>https://www.wikidata.org/wiki/Q120636628</dc:relation>
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