Large-scale analysis of the Learning Object Metd

1. On the use of Learning Object Metadata the GLOBE experience Xavier Ochoa, ESPOL JorisKlerkx, KULeuven Bram Vandeputte, KULeuven Erik Duval, KULeuven

2. http://www.slideshare.net/xaoch

3. LOM is known and widely used But its real use is not known

4. How much space 1000 LOM instances will take? What are the most used elements of LOM? Is it really a “standard”? Has it been extended as designed? What is the information stored in real instances? Is it better than Dublin Core for Educational Resources?

5. We need: Large-Scale, Real-World, Heterogeneous We select: GLOBE

6. GLOBE

7. http://www.globe-info.org/

8. Large-Scale: 630.000+ instances Real-World: being used and created Heterogeneous: 7 networks of LORs 4 continents

9. Results The interesting stuff

10. Size

11. Size ≈ 5 Kb

12. LOM Elements Use What parts of LOM are used anyway?

14. G.Title G.Identifier G.Language G.Description G.Keyword L.ContributionRole L.ContirubtionEntity M.Identifier M.ContributorRole M.ContributorEntity M.ContributorDate T.Location T.Format E.LearningResourceType R.Copyright R.Cost R.Description C.TaxonPath C.Purpose C.Taxon

15. G.Title G.Identifier G.Language G.Description G.Keyword L.ContributionRole L.ContirubtionEntity M.Identifier M.ContributorRole M.ContributorEntity M.ContributorDate T.Location T.Format E.LearningResourceType R.Copyright R.Cost R.Description C.TaxonPath C.Purpose C.Taxon Creator Identifier Title Date Type Subject Description LOM DC

16. G.Title G.Identifier G.Language G.Description G.Keyword L.ContributionRole L.ContirubtionEntity M.Identifier M.ContributorRole M.ContributorEntity M.ContributorDate T.Location T.Format E.LearningResourceType R.Copyright R.Cost R.Description C.TaxonPath C.Purpose C.Taxon Creator Identifier Title Date Type Subject Description LOM DC

17. LOM uses 20 out of 50 elements But captures more information than DC

18. Educational Section

19. 4 out of 11 Educational elements Community dependent

20. LOM Vocabulary Usage What is stored on LOM?

21. Educational.Context

22. Right.Cost

23. Rights.Copyrights

24. If you too want to play... http://is.gd/globemetadata

25. LOM Extensions What LOM forgot…

26. Only 3 additions: General – Learning Object Kind (MACE) 30.000 Instances Technical – Geolocation (MACE) 7.000 Instances General – Subtitle (KERIS) 5.000 Instances

27. There is little need of extension Nobody wants more electronic fields!

28. LOM XMLValidation Analysis Is it an interoperability standard?

29. LOM validation

30. Most common errors (loose)

31. LOM XML loose is widely implemented LOM XML strict is not

32. Good structural interoperability Although the value space is not clear

33. vCard causes 68% errors LOM developers hate vCard

34. LOM Metadata Quality Analysis Those pesky indexers…

35. Diversity of Vocabulary usage

36. Diversity of Vocabulary usage

37. Diversity of Vocabulary usage

38. Quality of Textual Descriptions

39. Quality of Textual Descriptions

40. Quality of Textual Descriptions

41. Quality of Textual Descriptions

42. There must be a QA process That is true for bothautomatic and manual metadata

43. Conclusion of the Conclusions This kind of studies should be made an integral part of the development of LOM (or any other metadata standard) (or any other Learning technology)

44. Want the data?Want the code? https://sites.google.com/site/globemetadata/

45. Gracias / Thank you / Grazie Xavier Ochoa xavier@cti.espol.edu.ec http://ariadne.cti.espol.edu.ec/xavier Twitter: @xaoch