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Learning Analytics -Towards a New Discipline-

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The talk, motivated by the present state of learning and education, identifies a need for a systematic change of the present preactice. Learning analytics is identified as a possible way to good to address this open challenge. Some connections with evidence-based medicine are drawn. Finally, learning analytics is defined as well as some open research challenges.

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  • The position of Learning Analytics between older buzz areas as Pedagogical Patterns and Instructional design theory is not clear.
    How does learning analytics differ from the data collection and analysis that is done for Instructional design development?
    Can the broad-scale Learning analytics offer a meta-analytical solution how the Pedagogical patterns can be created and Learning theories validated?
    Who is the target of Learning analytics - the designer or the learner, and if the latter should be able to use learning analytics, shouldn't the visualization and feedback of learning analytics results be part of the learning analytics conceptualization as well?
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Learning Analytics -Towards a New Discipline-

  1. 1. Learning Analytics - Towards a New Discipline- Dragan Ga šević Email: dgasevic@acm.org https://semtech.athabascau.ca
  2. 3. <ul><li>Social Web and PLEs are here! </li></ul>
  3. 4. <ul><li>Are we happy with the present in learning and education? </li></ul>
  4. 5. <ul><li>How do we know how we are doing? </li></ul>
  5. 6. Topics to discuss <ul><li>Learning environments today </li></ul><ul><li>Learning analytics – definition </li></ul><ul><li>Learning analytics – approaches & challenges </li></ul>
  6. 7. <ul><li>Part I </li></ul><ul><li>Learning Environments Today </li></ul>
  7. 8. Today’s idea of “learning”
  8. 9. Learning Paths http://www.w3.org/2006/Talks/1023-sb-W3CTechSemWeb/DataServicesWebAppMetro2.jpg
  9. 10. Educational Ecosystems Authoring Reusability Packaging Educators Reusability Adaptivity Evolution Collaboration with educators and students
  10. 11. Educational Ecosystems Authoring Reusability Packaging Educators Feedback Learning and Collaborating Personalization Adaptivity Context-awareness Social interaction … Learners
  11. 12. Educational Ecosystems Educators Learners Authoring Reusability Packaging Learning and Collaborating Community Peer-Review Presenting Administration Mobile
  12. 13. Learning (Life) not in a box! A small part of a software engineer’s life
  13. 14. Learning ecosystem … … … … … A small part of a software engineer’s life
  14. 15. <ul><li>Part II </li></ul><ul><li>Learning Analytics </li></ul>
  15. 16. <ul><li>A systematic change needed! </li></ul>
  16. 17. Learning Analytics – What? <ul><li>Measurement, collection, analysis, and reporting of data about learners and their contexts </li></ul>
  17. 18. Learning Analytics – Why? <ul><li>Understanding and optimising learning and the environments in which learning occurs </li></ul>
  18. 19.
  19. 20. Evidence-based Education As the integration of best research evidence with practitioner expertise and stakeholder values The goal made up based on
  20. 21. Evidence-based BPM
  21. 22. Current best evidence from research to integrate with practical experience and human values in the decision making process
  22. 24. Example How to develop presentation skills in asynchronous course delivery?
  23. 25. Approach “ YouTube-like” to present Students record their presentations and share with their peers
  24. 27. How to discuss such presentations? By using discussion forums (in Moodle)
  25. 29. Participation in discussions is part of the course mark
  26. 30. <ul><li>Part III </li></ul><ul><li>Learning Analytics Approaches and Challenges </li></ul>
  27. 33. Learning Analytics <ul><li>What and how to collect and report? </li></ul><ul><li>Measurement, collection, analysis, and reporting of data about learners and their contexts </li></ul>
  28. 34. <ul><li>Ubiquitous learning analytics </li></ul><ul><ul><li>Tool and format independent </li></ul></ul><ul><ul><li>Aggregates and integrates </li></ul></ul>
  29. 35. Semantic Web <ul><li>Ontologies: Interconnecting applications </li></ul><ul><ul><li>Shared domain conceptualizations </li></ul></ul>
  30. 36. Linked Data http://richard.cyganiak.de/2007/10/lod/
  31. 37. Linked Data http://richard.cyganiak.de/2007/10/lod/
  32. 38. <ul><li>“ A crazy problem requires a crazy solution!” </li></ul><ul><li>(Griff Richards, 2005) </li></ul>
  33. 39. Learning Context Ontology: LOCO Jovanović, J., Knight, C., Gašević, D., Richards, G., &quot;Learning Object Context on the Semantic Web,&quot; 6th IEEE International Conference on Advanced Learning Technologies , Kerkrade, The Netherlands, 2006 pp. 669-673 ( Best paper award ).
  34. 40. Education Social Semantic Web <ul><li>Combining Social and Semantic Web aspects </li></ul><ul><ul><li>OAST and LOCO-Analyst </li></ul></ul>
  35. 41. LOCO-Analyst
  36. 42. Formative Evaluation Ali, L., Hatala, M. Gašević, D., Jovanović, J., &quot;A Qualitative Evaluation of Evolution of a Learning Analytics Tool,&quot; Computers & Education , 2011 (in press), http://goo.gl/lCvMT Category Sub-category Q8 Suggestions for improving Visualization/GUI 77.8% Annotations 5.66% Other Features 11.11% No suggestions but liked Data Visualization - Interface Design 5.56% Annotations -
  37. 43. <ul><li>Visual learning analytics </li></ul><ul><ul><li>Ubiquitous LA impossible w/o visual </li></ul></ul><ul><ul><ul><li>Information overload </li></ul></ul></ul>
  38. 44. LOCO-Analyst
  39. 45. LOCO-Analyst
  40. 46. LOCO-Analyst
  41. 47. LOCO-Analyst
  42. 48. Student comprehension
  43. 49. Evaluation of LOCO-Analyst <ul><li>Predictors of the perceived utility </li></ul><ul><ul><li>information about interactions of students </li></ul></ul><ul><ul><ul><li>social networking </li></ul></ul></ul><ul><ul><li>students’ comprehension of content </li></ul></ul><ul><ul><ul><li>collaborative tagging </li></ul></ul></ul><ul><ul><li>intuitiveness & ease-to-understand of the presentation of the above two </li></ul></ul>
  44. 50. Learning Analytics <ul><li>What to measure? </li></ul><ul><li>Measurement, collection, analysis, and reporting of data about learners and their contexts </li></ul>
  45. 52. http://learningworksforkids.com/EF/metacognition.html
  46. 53. Learning Analytics <ul><li>How to analyze? </li></ul><ul><li>Measurement, collection, analysis, and reporting of data about learners and their contexts </li></ul>
  47. 54. http://goo.gl/jtO3i SNAPP http://nodexl.codeplex.com/
  48. 55. http://www.processmining.org
  49. 56. http://www.cs.waikato.ac.nz/ml/weka
  50. 57. Submission: October 16, 2011
  51. 58. <ul><li>Learning analytics </li></ul><ul><li>more </li></ul><ul><li>meaningful & ubiquitous </li></ul><ul><li>with semantic technologies </li></ul>
  52. 59. Thank you!

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