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    <title>SPLICE: Datasets and Data Analytics</title>
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      <h1>Datasets and Data Analytics</h1>

      <p>
        A primary mission for SPLICE is to support
        infrastructure to collect educational datasets, make them
        available to researchers, and provide appropriate analysis
        tools.
      </p>

      <p>
        The <a href="https://splice.cs.vt.edu/datasetcatalog/">
          SPLICE Dataset Catalog</a> provides a collection of datasets
        available from various sources. We welcome contributions of
        datasets!
      </p>
      <p>
        Here are our current dataset sources that are included in the
        dataset catalog:
      </p>
      <ul>
        <li><a href="https://pslcdatashop.web.cmu.edu/">Datashop</a>@CMU</li>
        <li>A <a href="https://docs.google.com/spreadsheets/d/1ccD5kB8yC8xSoYsWrmfBS0HcSAmesWGOVyID1psywJg/edit?gid=0#gid=0">
            compilation of open-source datasets</a> in computing
          education, curated by the "Where is the data? Finding and
          reusing datasets in computing education" CompEd 23' working
          group. The working group aims to make research data more
          accessible and encourage open data practices in the computing
          education research (CER) community. For more information,
          please refer to the working group's paper: Kiesler, Natalie,
          John Impagliazzo, Katarzyna Biernacka, Amanpreet Kapoor, Zain
          Kazmi, Sujeeth Goud Ramagoni, Aamod Sane, Keith Tran, Shubbhi
          Taneja, and Zihan Wu. "Where's the Data? Exploring Datasets in
          Computing Education." In Proceedings of the ACM Conference on
          Global Computing Education Vol 2, pp. 209-210. 2023.
        </li>
      </ul>

      Some featured datasets: These are datasets used to support the
      listed publications.
      <ul>
        <li>Demirtas, Fowler, & Cunningham (2024).
          <a href="https://educationaldatamining.org/edm2024/proceedings/2024.EDM-long-papers.5/">Reexamining Learning Curve Analysis in Programming
            Education: The Value of Many Small Problems.</a>
          In <i>Proceedings of the 17th International Conference on
            Educational Data Mining.</i></li>
        <li>Huang et al (2023),
          <a href="https://www.lrdc.pitt.edu/schunn/papers/Huang-skillintegration.pdf">
            Supporting skill integration in an intelligent
            tutoring system for code tracing.</a></li>
        <li> Rivers et al (2016),
          <a href="http://www.krivers.net/files/icer2016-paper.pdf">
            Learning Curve Analysis for Programming: Which Concepts do Students Struggle With?</a>
          <i>Proceedings of ICER 2016</i>.


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