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Generating secondary/derived products from OpenLearn/OU XML documents.

Generating secondary/derived products from OpenLearn/OU XML documents.

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  • [ABSTRACT: the Open University’s open educational resources are derived from course units that are authored as structured XML documents on the OpenLearn site. Tony Hirst shows how new products can be derived from document archives, if we think of them as ‘data’.]The current OU workflow results in the production of structured XML documents that can be used to generate several different "output" document formats, from HTML documents for use in the VLE to eBooks and PDFs. But XML documents can also be viewed as a database within which different asset types can be reliably identified. In this presentation, I will review how OU-XML documentsas used in course production and OpenLearn workflows can be mined in order to create course specific search engines (as well as reflecting on why these might NOT be such a good idea after all) and annotatable mindmap styled overviews of module units.
  • For some years, I have been running a Google Custom Search Engine over resources linked to from the Relevant Knowledge short course, T151 Digital Worlds. The course is built on a resource based learning model, and draws heavily on content available on the public web. The search engine is embedded within an iframe within a page contained within the VLE, and styled in sympathy with the styling of the VLE itself.[Show example of analytics/reporting available from CSE]
  • For several years, I have been exploring how we might make use of third party, linked to resources within the course context. Trivially, we might view them as of three types: resources linked to by the course team; resources that are discovered and shared within the course context; and resources that are discovered via web searches related to the course.
  • The notion of a custom course search engine is based on extending a search over a set of course materials to include the resources linked to from the course. Doing this locally would require identifying the course linked resources, crawl them, index them, and make them available to the course search tool. By using a Google custom search engine, we can use Google’s index to provide a search over at least the publicly linked to resources. (Note that the custom search engine will not be able to search over the course material themselves if they are not public. [Google news as searching over content that is behind a paywall in return for a first click view of the content. Could we do the same with education content?]
  • ?if a GlossaryTerm is labeled as such within the body of an OpenLearn XML document, we should be able to retrieve the contextualisingpargraph and include this as part of the search results. But I don’t do this..
  • Transcript

    • 1. Making the most ofstructured content:data products from OpenLearn XML Tony Hirst Dept of Communication and Systems, The Open University
    • 2. So how do we get the links?
    • 3. OU XML
    • 4. BUT…
    • 5. …the index is typically too small to be of much interest
    • 6. So what elsemight we be able to do?
    • 7. OU-XML lets you treat SA* documents as databases…* Structured authoring
    • 8. If the documents are just datasets, whatsecondary or derived products can weproduce from them?
    • 9. Automatic outline extraction:mindmap view
    • 10. Parent Unit Unit code Section Section Heading
    • 11. Coursewidedirectories: learning outcomes
    • 12. Course Learning OutcomeXYX123 Have an understanding of PXYZ123 Be able to do QABC123 Have an understanding of R
    • 13. Grab a list of course units from OpenLearnFor each unit: - Generate the URL for the XML version of each unit - Grab the XML for the unit - Extract learning outcomes, image locations, glossary items and link information
    • 14. Coursewide directories: OpenLearnimage finder
    • 15. Unit Image Location Caption Description/alt text Acknowledgements
    • 16. Coursewide directories: OpenLearnmeta-glossary
    • 17. Unit Glossary Item Description
    • 18. Dynamic outline generation:mindmap view
    • 19. - unit- unitset- Learning outcome- Glossary item- figure
    • 20. DiscOUOU KMi project (d’Aquin et al)
    • 21. Search Engine Text Adventures
    • 22. What’smissing…?
    • 23. … search-based pedagogy…?
    • 24.