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Ian Piper: How a little structure goes a long way in educational content


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Ian Piper: How a little structure goes a long way in educational content

  1. 1. A little structure goes a long way
 Some case studies from educational content Dr Ian Piper
 Tellura Information Services Ltd.
  2. 2. Three case studies across 15 years National Grid for Learning (NGfL) Curriculum Online The National Strategies Some more recent work
  3. 3. Educational content - a familiar landscape… There’s too much stuff, so it’s hard to find There’s not enough structure, so it’s hard to parse We don’t know where it is, so we may not even find it We don’t know how relevant it is We don’t know how good it is We don’t know whether we’re allowed to use it
  4. 4. The National Grid for Learning (2001 - 2004) A relational database of several thousand quality assured educational content providers including links to online presence A search index (Inktomi Ultraseek) based on this database A search index of the online presence (several million pages) A categorisation scheme using the Inktomi Content Classification Engine
  5. 5. NGfL website UI Categories from CCE Results matching query Link to website for resource
  6. 6. What worked well Popular - usage of the site started high and stayed high Relevant results - classification through structured records and of text content gave high degree of confidence in product Fine-tuned results - smaller population of sites to search gave more specific answers Quality - only quality-assured products were featured on the system Performance - thousands of sites and fewer than 10 million pages
  7. 7. What we learned Manually intensive and bureaucratic to set up subscribers Loss of the serendipity factor in searching Classification engine was limited; it relied on exact matching text strings in keyword metadata or web page body to a category Some of the products weren’t websites, so couldn’t easily be indexed
  8. 8. Curriculum Online 2004 - 2008 A database of commercial and non-commercial content providers of educational products ranging from whiteboards to websites Content providers had to meet stringent quality requirements (that’s right, they hadn’t learned from the NGfL experience) Content discovery driven by relational database search of the provider’s record (no content from content provider websites) Use of a range of controlled vocabularies (hurrah!) to enable multiple dimensions and levels of classification
  9. 9. Curriculum Online website UI List items loaded from controlled vocabularies Feature items
  10. 10. What worked well Gave a level playing field to non-commercial and commercial content providers Allowed users to give feedback, which tailored search results
  11. 11. What we learned Awful user experience (no user-centred design) Performance problems and other bugs diminished user satisfaction Some commercial providers gamed the system (tagged every content item with every vocabulary term) to try to get to the top of search results Registration process was slow and very bureaucratic (maybe we hadn’t learned that well from NGfL!)
  12. 12. The National Strategies (2007 - 2011) A vast collection of government educational content Teachers required to use this content for teaching Original site very unpopular: Hard to find content Publication cycle slow Content and navigation structure too rigid and inflexible
  13. 13. Our solution Centre the system on structured and tagged information objects All content items stored as first-class objects (in Drupal) All navigation and discovery via metadata tagging Every content object tagged by experts against a range of controlled vocabularies Controlled vocabularies developed iteratively based on experience Controlled vocabularies built on open standards (Zthes and SKOS)
  14. 14. Controlled vocabulary manager
  15. 15. Linking content to vocabularies
  16. 16. What worked well Very popular with teachers - massive increase in usage and satisfaction ratings Very short content production cycle Content surfaced dynamically everywhere it needed to, so far more flexible than before Rules-based navigation could be fine-tuned without disrupting content
  17. 17. What we learned Subject matter experts are vitally important to get effective tagging Standards and house rules are important for consistency Don’t over-tag content Be agile, be prepared to iterate Tag at the lowest (most precise) level possible Even the most innovative design cannot withstand a new political vision (The National Strategies website was closed in 2011)!
  18. 18. A global publishing company (2013 onward) A move from paper-based publishing to digital-first publishing A need to improve content re-use capability A desire to create a global knowledge network An understanding of the potential value of tagged and aligned content, but no clear vision of how to make it happen What follows is a work in progress…
  19. 19. (Some parts of) the solution Create a better digital content architecture A content model based on content objects and containers A product workflow centred on re-use and multiple output channels Create mechanisms for managing vocabularies and curricula Focus content production on potential for re-use, by Creating objects at the appropriate level of granularity Aligning objects to vocabularies and curricula
  20. 20. Guiding principles Standards matter more than tools; solutions must be product- agnostic Architecture needs to work from macro to micro level Need to align objects using a variety of classification schemes On the web (we’re fans of the 5-star model!) Available to the audience via simple interfaces Content must be easily accessible via an effective API
  21. 21. Where we’re coming from
  22. 22. Where we’re going to
  23. 23. An improved content object model
  24. 24. An improved containment model
  25. 25. A model for linking content
  26. 26. A model for linking content
  27. 27. A knowledge network model
  28. 28. Early lessons It’s hard work, but… The potential is already evident Technical solutions are not enough; people, culture and processes matter more A little structure goes a long way!
  29. 29. Thank you