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      <journal-title-group>
        <journal-title>3rd March</journal-title>
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    <article-meta>
      <title-group>
        <article-title>The 8th Workshop on Predicting Performance Based on the Analysis of Reading and Learning Behavior (DCLAK25)</article-title>
      </title-group>
      <contrib-group>
        <aff id="aff0">
          <label>0</label>
          <institution>Brendan Flanagan (Kyoto University, Japan) - Owen H.T. Lu (National Chengchi University, Taiwan) - Atsushi Shimada (Kyushu University, Japan) - Namrata Srivastava (Vanderbilt University</institution>
          ,
          <country country="US">USA)</country>
          <institution>- Albert C.M. Yang, National Chung-Hsing University</institution>
          ,
          <country country="TW">Taiwan</country>
        </aff>
      </contrib-group>
      <pub-date>
        <year>2025</year>
      </pub-date>
      <volume>9</volume>
      <issue>00</issue>
      <abstract>
        <p>This workshop was organised as part of the pre-conference program for the 14th International Conference on Learning Analytics and Knowledge (LAK'25). The event was designed as a symposium scheduled for full-day duration on 3th March 2025. As the adoption of digital learning materials in modern education systems is increasing, the analysis of reading behavior and their effect on student performance gains attention. The main motivation of this workshop is to foster research into the analysis of students' interaction with digital textbooks, and find new ways in which it can be used to inform and provide meaningful feedback to stakeholders: teachers, students and researchers. The previous years workshops at LAK19 and LAK20 focused on reading behavior in higher education, and LAK21, LAK22, LAK23 and LAK24 on secondary school reading behavior and pre/post COVID-19 pandemic changes. Participants of this year's workshop will be given the opportunity to analyze several different datasets, including secondary school prediction of academic performance for more than one subject. As with previous years, additional information on lecture schedules and syllabus will also enable the analysis of learning context for further insights into the preview, in-class, and review reading strategies that learners employ. In addition, this workshop will accept a wide range of research topics on learning analytics, educational technology, and learning support systems in the post COVID-19 era, including applications of AI in education, proposals for new educational systems, new evaluation methods, and so on. Each paper submitted to the workshop underwent a rigorous double-blind review by at least two reviewers. Each paper was evaluated with respect to four criteria: 1) quality of content, 2) significance for theory and practice, 3) originality and level of innovativeness, 4) fitting to the workshop theme. The review results of each paper were subsequently discussed by the workshop chairs resulting in a decision of acceptance or rejection. As a result, we accepted 2 papers to be published in this workshop. We would like to thank all the authors who submitted their work for this event, as well as our program committee for providing the detailed feedback for all the papers. Organising committee</p>
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      <title>-</title>
      <p>- Hsiao-Ting Tseng (National Central University, Taiwan)
- Fumiya Okubo (Kyushu University, Japan)
- Eduardo Davalos Anaya (Vanderbilt University, USA)
- Hiroaki Ogata (Kyoto University, Japan)
Programme Committee
- Anna Huang (NCU, Taiwan)
- Christopher Yang (Kyoto University, Japan)
- Hiroki Nakayama (Yamagata University, Japan)
- Hsiao-Ting Tseng (National Central University, Taiwan)
- Mohammad Nehal (Hosei University, Japan)</p>
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