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CRIT LAB: Assigning Educational Standards to Educational Resources Using a Computer-assisted Tool

Join us for an in-depth session on the Content Assignment Tool (CAT), designed to streamline the process of assigning educational standards to digital learning resources. Discover how natural language processing technology can assess content and suggest relevant standards, creating a more efficient workflow for educators. Explore the tool through a guided tour, share feedback, and engage in discussions about its integration with cataloging systems. Learn how CAT incorporates indexed math and science standards from various national and state frameworks. Improve your resource selection process and enhance educational accountability.

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CRIT LAB: Assigning Educational Standards to Educational Resources Using a Computer-assisted Tool

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  1. CRIT LAB:Assigning Educational Standards to Educational Resources Using a Computer-assisted Tool Holly Devaul DLESE Program Center, UCAR Anne Diekema CNLP, Syracuse University

  2. Session goals • Introduce the Content Assignment Tool (CAT), a tool designed to assist in assigning educational standards to digital learning resources • Guided tour • Time to explore • Feedback (structured and not), questions, and discussion

  3. Why? • National focus on accountability and assessment is tied to standards • Library users and educators have requested resources with standards provided • Many, many standard systems… manual process of cataloging is time-consuming

  4. Natural Language Processing technology assesses resource content, suggests educational content standards • Human makes final choices • Machine Learning improves results over time • Integration with cataloging tool is eventual goal, demo with DCS under development

  5. CAT capabilities • Includes indexed math and science standards from: • National Science Education Content Standards • National Council of Teachers of Mathematics • State standards (math and science): • Minnesota • Ohio • New York • Colorado • Massachusetts

  6. CAT capabilities Users can: • Choose which standards to use • Restrict grade level of standards searched • Select standards to retain from results list • Browse lists of standards to add those not returned by the tool • Save the data to improve future performance

  7. Guided tour URL of tool: http://casaa1.cnlp.org/casaa/ Login/password: user1/pass1….user20/pass20 Click on a Sample learning resource url to open a new window to a resource Copy-paste url into the LearningResource URL box Choose Select Standards Source, and Standards Topic Choose Start Grade and End Grade Click on Suggest Standards

  8. Set query variables

  9. Results returned; check √ those that you agree with and click

  10. Build your list • My Selections lists standards you have chosen • Refine search using • See complete list of possible standards and add to list using • Change your mind

  11. Browse hierarchical list of standards, add to list

  12. Improve results in subsequent searches • Click to invoke Machine Learning technology and improve results over time

  13. Next steps • Release API for communication with external cataloging tools • Demo with Collection System underway • Conduct study of robustness of suggestions • Add more standards to the index • State-to-national standards mapping

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