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Learning Analytics      explorations of learning data                  Andrew Deacon        Centre for Educational Technol...
Outline•   Understandings of learning analytics•   Instructional design case•   Data landscape in learning organizations• ...
Search-term: ‘Analytics’                  Google Trends
Learning AnalyticsThe measurement, collection, analysisand reporting of data about learnersand their contexts, for purpose...
Age of Big DataSource: The Economist
An Instructional Design Case
Merrill on IDInstruction involves directing students toappropriate learning activities;guiding students to appropriate kno...
NewsScripts: Scriptwriting exercise 1) Watch footage, note     2) Write script following   3) Take note of  significant de...
NewsScripts: Nit-picking bot• Rather than lots of instructions  – that students would not follow anyway• Provide feedback ...
NewsScripts: Context• 2nd year UCT Media Studies course• Linked to lectures on media writing genres• 250 students• 2h to c...
Questions for ID• Why is it so difficult to entrench such learning  interventions in university curricula?• Curriculum int...
Educational data landscape              Institutional                   Individual (in wider Communities of Practice)     ...
Within the institutional contexts
Purdue Universitys Course Signals• Early warning signs  provides intervention to  students who may not  be performing well...
Students’ use of Vula in a course                           Submission of                            assignmentsPolling of...
Sociogram of a discussion forum                      Dawson (2010)
Words in chats used by failing students
Words used by Lecturers vs Students                                    Marks;                                    thanks;‘W...
Predicting success  Chemistry – 1st year courseNBT - National Benchmark Tests
Predicting success
Predicting success
Predicting success
Beyond the institution context     Social Media / PLEs / CoP
Big breakthroughs happenwhen what is suddenlypossible meets what isdesperately necessary.                      Thomas Frie...
High profile MOOCs
Coursera open online course
Coursera open online course• Gamification course  – 81,000 registrations  – 8,280 received certificates (10%)• Participati...
Gamification course participation100%80%                           Registers60%                           Watchers        ...
Coursera: learning from videos               Concept Mapping or Retrieval PracticeJ D Karpicke, J R Blunt Science 2011;331...
If our aim is to understand people’sbehaviour rather than simply to recordit, we want to know about primarygroups, neighbo...
UCT and social media• Prominent links to:  – Facebook  – Flickr  – LinkedIn  – YouTube
Twitter: UCT chatter• Six months of data (April – Sept 2011)• Tweets including a UCT hashtag or text      #UCT, #Ikeys, Un...
Twitter: apps & locationsBlackberry     Twitter   Ubersocial   Others         17%                                         ...
Twitter: tweeter relationshipsSmall number offrequent tweeters1. Drama student  (162)2. UCT Radio  (132)3. Science student...
Twitter: viral #UCT6 months of tweets     Varsity Cup                          final                                     H...
Flickr: helicopter crash at UCT         Ian Barbour - http://www.flickr.com/people/barbourians/
Twitter: helicopter crash at UCT• Peak of 140 tweets  in 5 minutes• Media organisations  tweets get re-tweeted• Crash or h...
Facebook: all friend relationshipsPaul Butler http://www.facebook.com/notes/facebook-engineering/visualizing-friendships/4...
1st-year coursecombinations                   HS                   HUMCOM             SCI                         EBE
Effective visualisationsThe success of a visualization is basedon deep knowledge and care aboutthe substance, and thequali...
Correlation and causation• Correlation does not imply causation  – Covariation is a necessary but not a sufficient    cond...
Future scenarios• Learning analytics for educational research   –   Instructional data within wider contexts   –   Social ...
Software references•   Gephi – network analysis, data collection•   NodeXL – network analysis, data collection•   TAGS – T...
Literature references• Baker, S.J.D., Yacef, K. (2009) The State of Educational Data Mining  in 2009: A Review and Future ...
FatFonts references• by Miguel Nacenta, Uta Hinrichs, and Sheelagh Carpendale• Area of each number is exactly proportional...
Learning Analytics - L&D Community of Practice 2012
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Learning Analytics - L&D Community of Practice 2012

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Learning analytics to inform learning design.

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Learning Analytics - L&D Community of Practice 2012

  1. 1. Learning Analytics explorations of learning data Andrew Deacon Centre for Educational Technology University of Cape TownLearning and Development community of practice – 9 Nov 2012
  2. 2. Outline• Understandings of learning analytics• Instructional design case• Data landscape in learning organizations• Trends within the organization context• Connections with external contexts• Future scenarios
  3. 3. Search-term: ‘Analytics’ Google Trends
  4. 4. Learning AnalyticsThe measurement, collection, analysisand reporting of data about learnersand their contexts, for purposes ofunderstanding and optimising learningand the environments in which itoccurs.Learning Analytics 2011 Conference, https://tekri.athabascau.ca/analytics
  5. 5. Age of Big DataSource: The Economist
  6. 6. An Instructional Design Case
  7. 7. Merrill on IDInstruction involves directing students toappropriate learning activities;guiding students to appropriate knowledge;helping students rehearse, encode, andprocess information;monitoring student performance;and providing feedback as to theappropriateness of the student’s learningactivities and practice performance.
  8. 8. NewsScripts: Scriptwriting exercise 1) Watch footage, note 2) Write script following 3) Take note of significant details and TV news writing feedback on research online. conventions. some issues.
  9. 9. NewsScripts: Nit-picking bot• Rather than lots of instructions – that students would not follow anyway• Provide feedback on script – Check script length e.g., read at 3 words per second – Flag words editors avoid e.g., never use: ‘As the footage shows’ – Emphasise active voice e.g., avoid: ‘were’
  10. 10. NewsScripts: Context• 2nd year UCT Media Studies course• Linked to lectures on media writing genres• 250 students• 2h to complete 180-word script• 10% of mark• Used since 2001 (with gaps)
  11. 11. Questions for ID• Why is it so difficult to entrench such learning interventions in university curricula?• Curriculum integration tensions (relevance) – Media writing & Essay writing – Media production & Theory & critique – Online teaching spaces & Traditional modes
  12. 12. Educational data landscape Institutional Individual (in wider Communities of Practice) Institutional data Personal Learning Social media & learning environments Environments (PLE) & social learning• ERP Systems• Historical performance data• Learning management system data• Libraries• School application data• Turnitin Reports• Demographics Data is Data is Data is • Accessible • Almost unattainable • Restricted • Can identify individuals • Difficult to link to individuals • Difficult to link to individuals
  13. 13. Within the institutional contexts
  14. 14. Purdue Universitys Course Signals• Early warning signs provides intervention to students who may not be performing well• Marks from course• Time on tasks• Past performance Source: http://www.itap.purdue.edu/learning/tools/signals
  15. 15. Students’ use of Vula in a course Submission of assignmentsPolling ofstudents Site visits Content accessed Chat room activitySectioningof students
  16. 16. Sociogram of a discussion forum Dawson (2010)
  17. 17. Words in chats used by failing students
  18. 18. Words used by Lecturers vs Students Marks; thanks;‘Weiten’ – test; textbook Tut; author guys Week; pages Used more by Used more byLecturers/tutors Students
  19. 19. Predicting success Chemistry – 1st year courseNBT - National Benchmark Tests
  20. 20. Predicting success
  21. 21. Predicting success
  22. 22. Predicting success
  23. 23. Beyond the institution context Social Media / PLEs / CoP
  24. 24. Big breakthroughs happenwhen what is suddenlypossible meets what isdesperately necessary. Thomas Friedman New York Times, 15 May 2012
  25. 25. High profile MOOCs
  26. 26. Coursera open online course
  27. 27. Coursera open online course• Gamification course – 81,000 registrations – 8,280 received certificates (10%)• Participation – 20,000 forum posts – 187,000 peer evaluations by 13,000 students – Facebook group: 3,400 members – Twitter: > 2,700 tweets #gamification12
  28. 28. Gamification course participation100%80% Registers60% Watchers Submitters40% Writers Certificate20% 0%
  29. 29. Coursera: learning from videos Concept Mapping or Retrieval PracticeJ D Karpicke, J R Blunt Science 2011;331:772-775 Published by AAAS
  30. 30. If our aim is to understand people’sbehaviour rather than simply to recordit, we want to know about primarygroups, neighbourhoods, organizations,social circles, and communities; aboutinteraction, communication, roleexpectations, and social control.Allen Barton, 1968, cited in Freeman (2004) Source: CC BY-SA 3.0
  31. 31. UCT and social media• Prominent links to: – Facebook – Flickr – LinkedIn – YouTube
  32. 32. Twitter: UCT chatter• Six months of data (April – Sept 2011)• Tweets including a UCT hashtag or text #UCT, #Ikeys, University of Cape Town, …• Attributes; how tweets are amplified• Just over 5,000 tweets Cannot capture every tweet on the topic And some data cleaning required
  33. 33. Twitter: apps & locationsBlackberry Twitter Ubersocial Others 17% Blackberry 27% Smartphone geo-location 20% 36% Cell phones
  34. 34. Twitter: tweeter relationshipsSmall number offrequent tweeters1. Drama student (162)2. UCT Radio (132)3. Science student (84)
  35. 35. Twitter: viral #UCT6 months of tweets Varsity Cup final Helicopter crash
  36. 36. Flickr: helicopter crash at UCT Ian Barbour - http://www.flickr.com/people/barbourians/
  37. 37. Twitter: helicopter crash at UCT• Peak of 140 tweets in 5 minutes• Media organisations tweets get re-tweeted• Crash or hard-landing? 2 hours after the event
  38. 38. Facebook: all friend relationshipsPaul Butler http://www.facebook.com/notes/facebook-engineering/visualizing-friendships/469716398919
  39. 39. 1st-year coursecombinations HS HUMCOM SCI EBE
  40. 40. Effective visualisationsThe success of a visualization is basedon deep knowledge and care aboutthe substance, and thequality, relevance and integrity of thecontent. (Tufte 1981)
  41. 41. Correlation and causation• Correlation does not imply causation – Covariation is a necessary but not a sufficient condition for causality – Correlation is not causation (but could be a hint)
  42. 42. Future scenarios• Learning analytics for educational research – Instructional data within wider contexts – Social media & PLE outside formal contexts – Modelling and predicting success – Supporting intervention opportunities – Reproducible research – Ethical considerations• Learning analytics for visualisations – Presenting data in engaging forms – Relating several variables
  43. 43. Software references• Gephi – network analysis, data collection• NodeXL – network analysis, data collection• TAGS – Twitter data collection (Google Drive)• Word cloud – R package (wordcloud)• Geo-location map – R package (RgoogleMaps)• Excel – spreadsheet, charts• SPSS – statistical analysis, graphs
  44. 44. Literature references• Baker, S.J.D., Yacef, K. (2009) The State of Educational Data Mining in 2009: A Review and Future Visions: http://www.educationaldatamining.org/JEDM/images/articles/vol1 /issue1/JEDMVol1Issue1_BakerYacef.pdf• Dawson, S. 2010. ‘Seeing’ the learning community: An exploration of the development of a resource for monitoring online student networking. British Journal of Educational Technology, 41(5), 736- 752.• Freeman, C. (2004) The Development of Social Network Analysis: A Study in the Sociology of Science. Empirical Press: Vancouver, BC Canada.• Fritz, J. (2011) Learning Analytics. Presentation prepared for Learning and Knowledge Analytics course 2011 (LAK11). http://www.slideshare.net/BCcampus/learning-analytics- fritz
  45. 45. FatFonts references• by Miguel Nacenta, Uta Hinrichs, and Sheelagh Carpendale• Area of each number is exactly proportional to its value - http://fatfonts.org Source: http://fatfonts.org

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