edmedia2014-learning-analytics-keynote

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Keynote address, EdMedia 2014, 25th June, Tampere, Finland. Movie replay: http://people.kmi.open.ac.uk/sbs/2014/06/edmedia2014-keynote

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edmedia2014-learning-analytics-keynote

  1. 1. Learning Analytics: Welcome to the future of assessment? Simon Buckingham Shum Knowledge Media Institute, The Open University Visiting Fellow, University of Bristol (From August, University of Technology Sydney) simon.buckinghamshum.net twitter @sbskmi #LearningAnalytics #edmedia See the question at #edmediakeynote Keynote  address,  EdMedia  2014,  25th  June,  Tampere,  Finland   1
  2. 2. learning objective: leave with an expanded vision of analytics better questions to ask in your next analytics conversation 2
  3. 3. Big Data status report: 3 “Big data is like teenage sex: everyone talks about it, nobody really knows how to do it, everyone thinks everyone else is doing it, so everyone claims they are doing it...” https://www.facebook.com/dan.ariely/posts/904383595868
  4. 4. When the Chancellor announces the adoption of a new economic modelling technique… 4 …we query the limitations of the model
  5. 5. 5 …we query the limitations of the model
  6. 6. Siri is smart… 6 I was speaking at this event: http://codeactsineducation.wordpress.com
  7. 7. Siri is smart… “Find code acts in education” 7
  8. 8. Siri is smart… “Find code acts in education” 8
  9. 9. Similarly, when we are confronted with new learning analytics… LAK13 Panel: Educational Data Scientists: A Scarce Breed http://people.kmi.open.ac.uk/sbs/2013/03/lak13-edu-data-scientists-scarce-breed John Behrens (Pearson) 9
  10. 10. LAK13 Panel: Educational Data Scientists: A Scarce Breed http://people.kmi.open.ac.uk/sbs/2013/03/lak13-edu-data-scientists-scarce-breed John Behrens (Pearson) 10 …we should query the limitations of the model
  11. 11. h=ps://twi=er.com/Wiswijzer2/status/414055472451575808   “Note:  check  the   huge  difference   between  knowing   and  measuring…”   11
  12. 12. a  few  quick  examples  of   learning  analy5cs   12
  13. 13. It’s out of the labs and into products: every learning tool now has an “analytics dashboard” (a Google image search) 13
  14. 14. Intelligent tutoring for skills mastery (CMU) Lovett M, Meyer O and Thille C. (2008) The Open Learning Initiative: Measuring the effectiveness of the OLI statistics course in accelerating student learning. Journal of Interactive Media in Education 14. http://jime.open.ac.uk/article/2008-14/352 “In this study, results showed that OLI-Statistics students [blended learning] learned a full semester’s worth of material in half as much time and performed as well or better than students learning from traditional instruction over a full semester.”
  15. 15. Purdue University Signals: real time traffic-lights for students based on predictive model 15 Campbell et al (2007). Academic Analytics: A New Tool for a New Era, EDUCAUSE Review, vol. 42, no. 4 (July/August 2007): 40–57. http://bit.ly/lmxG2x Validate a statistical model from: •  ACT or SAT score •  Overall grade-point average •  CMS usage composite •  CMS assessment composite •  CMS assignment composite •  CMS calendar composite Predicted 66%-80% of struggling students who needed help
  16. 16. Purdue University Signals: real time traffic-lights for students based on predictive model 16 Pistilli, M. D., Arnold, K. and Bethune, M., Signals: Using Academic Analytics to Promote Student Success. EDUCAUSE Review Online, July/Aug., (2012). http://www.educause.edu/ero/article/signals-using-academic-analytics- promote-student-success “Results thus far show that students who have engaged with Course Signals have higher average grades and seek out help resources at a higher rate than other students.”
  17. 17. Spatial clustering algorithm to provoke reflection 17
  18. 18. Posture analysis of fieldwork students 18
  19. 19. …and many more examples including discourse analytics language technologies to assess the quality of online postings and debate social network analytics graph analytics to assess strength and topics of interpersonal ties epistemic game analytics assessing the degree of professional engagement in authentic project scenarios visualizations to reveal important patterns of tool use over time (see other presentations and tutorials) 19
  20. 20. but  before  we  get  carried   away,  let’s  just  pause…   20
  21. 21. Selwyn, N. (2014).  Data entry: towards the critical study of digital data and education. Learning, Media and Technology. http://dx.doi.org/ 10.1080/17439884.2014.921628 “observing, measuring, describing, categorising, classifying, sorting, ordering and ranking). […] these processes of meaning-making are never wholly neutral, objective and ‘automated’ but are fraught with problems and compromises, biases and omissions. 21
  22. 22. For Morozov, analytics is where technological solutionism hits education: 22 “This flight from thinking and the urge to replace human judgments with timeless truths produced by algorithms is the underlying driving force of solutionism.”
  23. 23. Could analytics help us shift from the calculating mind to the contemplative mind? 23 See also: Complexity, Computing, Contemplation, Learning? http://learningemergence.net/2011/05/04/cccl http://www.contemplativecomputing.org/2011/03/first-draft-of-a-contemplative-computing-article.html Alex Pang: “A contemplative stance can help people be more creative; deal with complex problems that require months or years to solve […] Contemplation promotes both self-sufficiency and close, questioning observation of the world, and both are particularly valuable in this moment in the history of technology.” Calculating Mind, Contemplative Mind http://people.kmi.open.ac.uk/sbs/2008/09/calculating-contemplative-mind
  24. 24. unpacking  the     core  ques5on  for   learning  analy5cs   24
  25. 25. can  we  tell  from  your  digital   profile  if  you’re  learning?   25
  26. 26. can  we  tell  from  your  digital   profile  if  you’re  learning?   26 Who?
  27. 27. can  we  tell  from  your  digital   profile  if  you’re  learning?   27 Who? How? With what confidence? After what kinds of training?
  28. 28. can  we  tell  from  your  digital   profile  if  you’re  learning?   28 Who? How? With what confidence? After what kinds of training? Sourcing which data, with what integrity?
  29. 29. can  we  tell  from  your  digital   profile  if  you’re  learning?   29 Who? How? With what confidence? After what kinds of training? Sourcing which data, with what integrity? What kind of learning? What kind of learner?
  30. 30. Accounting tools are not neutral Du Gay, P. and Pryke, M. (2002) Cultural Economy: Cultural Analysis and Commercial Life. Sage, London. pp. 12-13 “accounting tools...do not simply aid the measurement of economic activity, they shape the reality they measure”
  31. 31. In  what  senses  do  analy5cs     “shape  the  reality  they   measure”?   31
  32. 32. How  do  analyQcs  shape  educaQon?   Analytics reports at the organisational and national levels come with consequences at different scales — sometimes punitive, often impacting millions of people. PoliQcally   32
  33. 33. How  do  analyQcs  shape  educaQon?   What data, concepts and relationships do the analytics designers seek to model? Ontologically   33
  34. 34. Bowker, G. C. and Star, L. S. (1999). Sorting Things Out: Classification and Its Consequences. MIT Press, Cambridge, MA, pp. 277, 278, 281 “Classification systems provide both a warrant and a tool for forgetting [...] what to forget and how to forget it [...] The argument comes down to asking not only what gets coded in but what gets coded out of a given scheme.” 34
  35. 35. Visualising “attainment” and “progress” 35
  36. 36. Which analytics could reflect the progress that ‘Joe’ has made on so many other fronts other than his SATS? 36
  37. 37. Key modelling issue: unit of analysis !  Discourse analysis: how do machines and humans differ in the way they segment a transcript to make sense of it? !  Rosé, C. P., & Tovares A. (in press). What Sociolinguistics and Machine Learning Have to Say to One Another about Interaction Analysis. In L. Resnick, Asterhan C., & Clarke S. (Eds.), Socializing Intelligence Through Academic Talk and Dialogue. Washington, D.C.: American Educational Research Association !  Collective intelligence: If we are shifting from a sole focus on individual accomplishment, to that of group knowledge construction and performance, how do analytics assess changes in a group’s knowledge and processes? !  Chen, B., & Resendes, M. (2014). Uncovering what matters: Analyzing transitional relations among contribution types in knowledge-building discourse. In Proceedins of the Fourth International Conference on Learning Analytics And Knowledge - LAK ’14 (pp. 226–230). New York, New York, USA: ACM Press. doi:10.1145/2567574.2567606 37
  38. 38. How  do  analyQcs  shape  educaQon?   What thresholds, samples, relationships, patterns, etc. do the algorithms encode and seek? On what basis is a recommendation engine proposing interventions? Algorithmically   38
  39. 39. governingalgorithms.org   Learning  AnalyQcs   In  an  increasingly  algorithmic   world  […]  What,  then,  do  we   talk  about  when  we  talk  about   “governing  algorithms”?    39
  40. 40. governingalgorithms.org   A  technology  or  an  epistemology?   Barocas,  S.,  Hood,  S.  and  Ziewitz,  M.  (2013).   Governing  Algorithms:  A  Provoca5on  Piece.   Social  Science  Research  Network  Paper  2245322.   DOI:    h=p://dx.doi.org/10.2139/ssrn.2245322     Secrecy,  obscurity,  inscrutability   Agency,  automaQon,  accountabiliQes   A  typology  of  algorithms  by  genre?   The  inscrutability  of  algorithms   NormaQvity,  bias,  values   40
  41. 41. Open Learning Analytics: open source algorithmic transparency (at least for those who are literate) no analytics ‘lock-in’ for educators http://www.solaresearch.org/mission/ola
  42. 42. How  do  analyQcs  shape  educaQon?   What meaning-making does the representation and interaction design encourage? SemioQcally   42
  43. 43. outcome   How  do  analyQcs  shape  educaQon?   By  changing   the  system   dynamics   researchers  /  educators  /  instrucQonal  designers   administrators  /  leaders  /  policymakers   intent   43
  44. 44. outcome   How  do  analyQcs  shape  educaQon?   By  changing   the  system   dynamics   Faster  feedback  loops   could  enable  more  rapid   adaptaQon:  of  agents’   behaviour,  and  of  learning   resources  and  designs   researchers  /  educators  /  instrucQonal  designers   administrators  /  leaders  /  policymakers   intent   44
  45. 45. DelegaQon  of     authority  to  define   goals,  analyQcs,     and  meaning   How  do  analyQcs  shape  educaQon?   Distribution of power between educators, learners, leaders, community…? ?   ?  
  46. 46. How  do  analyQcs  shape  educaQon?   epistemology pedagogyassessment Knight, S., Buckingham Shum, S. and Littleton, K. (In Press, 2014). Epistemology, Assessment, Pedagogy: Where Learning Meets Analytics in the Middle Space. Journal of Learning Analytics. Open Access Eprint: http://oro.open.ac.uk/39226 the middle space of learning analytics What epistemological assumptions are shaping the assessment regime, and hence the pedagogy? What questions are analytics used to help answer? 46
  47. 47. Example: epistemological assumptions 47 Knight, S., Buckingham Shum, S. and Littleton, K. (In Press, 2014). Epistemology, Assessment, Pedagogy: Where Learning Meets Analytics in the Middle Space. Journal of Learning Analytics. Open Access Eprint: http://oro.open.ac.uk/39226 Allows testing of problem-solving and analysis - sifting information "if you allow communication, discussions, searches and so on, you eliminate cheating because it's not cheating any more. That is the way we should think."
  48. 48. Figure  from  Doug  Clow:  h=p://www.slideshare.net/dougclow/the-­‐learning-­‐analyQcs-­‐cycle-­‐closing-­‐the-­‐loop-­‐effecQvely  (slide  5)   How  do  analyQcs  shape  educaQon?   All  of  the  above  are   encapsulated  in  any   learning  analyQcs   deployment   48
  49. 49. 49   What  kinds  of  learners?   What  kinds  of  learning?   What  data  could  be   generated  digitally  from   the  use  context?     How  is  it  ‘cleaned’?   Does  your  theory  predict   pa=erns  signifying   learning?   What  human  +/or   solware  intervenQons  / recommendaQons?   How  to  render  the  analyQcs,   for  whom,  and  will  they   understand  them?   What  analyQcal  tools   could  be  used  to  find  such   pa=erns?   How  do  analyQcs  shape  educaQon?  
  50. 50. Conclusion:  AnalyQcs  profoundly  shape  educaQon…   Ontologically   Algorithmically   SemioQcally   Systemically   PoliQcally   Authority?   50
  51. 51. what  kinds  of  learning     are  we  opQmising     the  system  for?   51
  52. 52. Learning analytics for this? “The test of successful education is not the amount of knowledge that pupils take away from school, but their appetite to know and their capacity to learn.” Sir Richard Livingstone, 1941 52
  53. 53. “We’re looking at the profiles of what it means to be effective in the 21st century. […] Resilience will be the defining concept. When challenged and bent, you learn and bounce back stronger.” “Dispositions are now at least as important as Knowledge and Skills. … They cannot be taught. They can only be cultivated.” John Seely Brown 53 US Dept. of Educ. http://reimaginingeducation.org conference (May 28, 2013) Dispositions clip: http://www.c-spanvideo.org/clip/4457327 Whole talk: http://www.c-spanvideo.org/program/SecD Learning analytics for this?
  54. 54. “It’s more than knowledge and skills. For the innovation economy, dispositions come into play: readiness to collaborate; attention to multiple perspectives; initiative; persistence; curiosity.” Larry Rosenstock LearningREimagined project: http://learning-reimagined.com Larry Rosenstock: http://audioboo.fm/boos/1669375-50-seconds-of-larry-rosenstock-ceo-of-hightechhigh-on-how-he-would-re-imagine-learning Learning analytics for this?
  55. 55. “In the growth mindset, people believe that their talents and abilities can be developed through passion, education, and persistence … It’s about a commitment to … taking informed risks … surrounding yourself with people who will challenge you to grow” Carol Dweck Interview with Carol Dweck: http://interviewscoertvisser.blogspot.co.uk/2007/11/interview-with-carol-dweck_4897.html Another interview: http://www.youtube.com/watch?v=ICILzbB1Obg Learning analytics for this?
  56. 56. Important work by Tony Bryk et al.: Drivers of “Productive Persistence” http://www.carnegiealphalabs.org/persistence/
  57. 57. Important work by Tony Bryk et al.: Drivers of “Productive Persistence” http://www.carnegiealphalabs.org/persistence/ Note: a research- based rationale for architecting a suite of analytics techniques
  58. 58. Bryk: “sense of belonging” a key predictor of remedial maths completion 58 http://learningemergence.net/2014/05/27/tony-bryk-lecture
  59. 59. Envisioning a wholistic university education (and analytics to match) 59 http://reinventors.net/series/reinvent-university
  60. 60. discourse   learning  analy5cs?   60
  61. 61. 1st International Workshop on Discourse-Centric Learning Analytics analytics that look beneath the surface, and quantify linguistic proxies for ‘deeper learning’ Beyond number / size / frequency of posts; ‘hottest thread’ http://www.glennsasscer.com/wordpress/wp-content/uploads/2011/10/iceberg.jpg solaresearch.org/events/lak/lak13/dcla13
  62. 62. Discourse analytics on webinar textchat Ferguson, R. and Buckingham Shum, S., Learning analytics to identify exploratory dialogue within synchronous text chat. In: 1st International Conference on Learning Analytics and Knowledge (Banff, Canada, 2011). ACM Can we spot the quality learning conversations in a 2.5 hr webinar?
  63. 63. -60 -40 -20 0 20 40 60 80 9:28 9:32 9:36 9:40 9:41 9:46 9:50 9:53 9:56 10:00 10:05 10:07 10:07 10:09 10:13 10:17 10:23 10:27 10:31 10:35 10:40 10:45 10:52 10:55 11:04 11:08 11:11 11:17 11:20 11:24 11:26 11:28 11:31 11:32 11:35 11:36 11:38 11:39 11:41 11:44 11:46 11:48 11:52 11:54 12:00 12:03 12:04 12:05 Average Exploratory Discourse analytics on webinar textchat Sheffield, UK not as sunny as yesterday - still warm Greetings from Hong Kong Morning from Wiltshire, sunny here! See you! bye for now! bye, and thank you Bye all for now Given a 2.5 hour webinar, where in the live textchat were the most effective learning conversations? Not at the start and end of a webinar… Ferguson, R., Wei, Z., He, Y. and Buckingham Shum, S., An Evaluation of Learning Analytics to Identify Exploratory Dialogue in Online Discussions. In: Proc. 3rd International Conference on Learning Analytics & Knowledge (Leuven, BE, 8-12 April, 2013). ACM. http://oro.open.ac.uk/36664
  64. 64. -60 -40 -20 0 20 40 60 80 9:28 9:32 9:36 9:40 9:41 9:46 9:50 9:53 9:56 10:00 10:05 10:07 10:07 10:09 10:13 10:17 10:23 10:27 10:31 10:35 10:40 10:45 10:52 10:55 11:04 11:08 11:11 11:17 11:20 11:24 11:26 11:28 11:31 11:32 11:35 11:36 11:38 11:39 11:41 11:44 11:46 11:48 11:52 11:54 12:00 12:03 12:04 12:05 Average Exploratory Discourse analytics on webinar textchat Given a 2.5 hour webinar, where in the live textchat were the most effective learning conversations? Not at the start and end of a webinar but if we zoom in on a peak… Ferguson, R., Wei, Z., He, Y. and Buckingham Shum, S., An Evaluation of Learning Analytics to Identify Exploratory Dialogue in Online Discussions. In: Proc. 3rd International Conference on Learning Analytics & Knowledge (Leuven, BE, 8-12 April, 2013). ACM. http://oro.open.ac.uk/36664
  65. 65. Discourse analytics on webinar textchat -100 0 100 9:28 9:40 9:50 10:00 10:07 10:17 10:31 10:45 11:04 11:17 11:26 11:32 11:38 11:44 11:52 12:03 Averag Classified as “exploratory talk” (more substantive for learning) “non- exploratory” Given a 2.5 hour webinar, where in the live textchat were the most effective learning conversations? Not at the start and end of a webinar but if we zoom in on a peak… Ferguson, R., Wei, Z., He, Y. and Buckingham Shum, S., An Evaluation of Learning Analytics to Identify Exploratory Dialogue in Online Discussions. In: Proc. 3rd International Conference on Learning Analytics & Knowledge (Leuven, BE, 8-12 April, 2013). ACM. http://oro.open.ac.uk/36664
  66. 66. Rhetorical discourse analytics 66 OPEN QUESTION: “… little is known …” “… role … has been elusive” “Current data is insufficient …” CONTRASTING IDEAS: “… unorthodox view resolves …” “In contrast with previous hypotheses ...” “... inconsistent with past findings ...” SURPRISE: “We have recently observed ... surprisingly” “We have identified ... unusual” “The recent discovery ... suggests intriguing roles” http://technologies.kmi.open.ac.uk/cohere/2012/01/09/cohere-plus-automated-rhetorical-annotation De Liddo, A., Sándor, Á. and Buckingham Shum, S., Contested Collective Intelligence: Rationale, Technologies, and a Human-Machine Annotation Study. Computer Supported Cooperative Work, 21, 4-5, (2012), 417-448. http://oro.open.ac.uk/31052
  67. 67. Rhetorical discourse analytics 67 Human analyst
  68. 68. Rhetorical discourse analytics 68 Human analyst Computational analyst http://technologies.kmi.open.ac.uk/cohere/2012/01/09/cohere-plus-automated-rhetorical-annotation De Liddo, A., Sándor, Á. and Buckingham Shum, S., Contested Collective Intelligence: Rationale, Technologies, and a Human-Machine Annotation Study. Computer Supported Cooperative Work, 21, 4-5, (2012), 417-448. http://oro.open.ac.uk/31052
  69. 69. Rhetorical discourse analytics 69 Duygu Simsek’s PhD: http://people.kmi.open.ac.uk/simsek/research/ Glimpses of analytics capable of detecting higher order thinking. But humans will always read differently to machines Can we correlate this with “academic writing”, and can such analytics be used as formative feedback on drafts?
  70. 70. Rhetorical discourse analytics 70 Simsek D, Buckingham Shum S, Sándor Á, De Liddo A and Ferguson R. (2013) XIP Dashboard: http://oro.open.ac.uk/37391 CONTRAST SUMMARY & CONTRIBUTION
  71. 71. disposi5onal     learning  analy5cs?   71
  72. 72. Dispositional Learning Analytics Workshop 72 http://learningemergence.net/events/lasi-dla-wkshp http://learningemergence.net/2014/03/01/ assessing-learning-dispositions-academic-mindsets
  73. 73. Observation informal and formal Self-Diagnostic informal and formal Behavioural Analytics Assessing Learning Dispositions/Mindsets Future sweetspot... multiple lenses to provoke self-reflection
  74. 74. Childrens’ informal self-assessment of “managing distractions” http://learningemergence.net/2014/03/01/assessing-learning-dispositions-academic-mindsets
  75. 75. Mindset Works mindsetworks.com Based on the educational research of Carol Dweck into growth mindsets (Stanford) 75
  76. 76. ELLI: Effective Lifelong Learning Inventory
  77. 77. Quantifying learning dispositions agency; identity; motivation; responsibility Buckingham Shum, S. and Deakin Crick, R. (2012). Learning Dispositions and Transferable Competencies: Pedagogy, Modelling and Learning Analytics. Proc. 2nd Int. Conf. Learning Analytics & Knowledge. (29 Apr-2 May, Vancouver). Eprint: http://oro.open.ac.uk/32823 http://learningemergence.net/2012/04/30/learning-powered-learning-analytics A  wholisQc  visual,  intended  to   build  intrinsic  moQvaQon,   inviQng  stretch,  providing  a  new   language,  provoking   conversaQon  that  Qes  to  the   learner’s  idenQty  
  78. 78. Self-report through reflective blogging 9-10 yr old EnquiryBloggers • Bushfield School, Wolverton, UK EnquiryBlogger Wordpress Multisite plugins http://learningemergence.net/tools/enquiryblogger 78
  79. 79. Masters level EnquiryBloggers Graduate School of Education, University of Bristol EnquiryBlogger: blogging for Learning Power & Authentic Enquiry http://learningemergence.net/2012/06/20/enquiryblogger-for-learning-power-authentic-enquiry 79
  80. 80. 80 EnquiryBlogger teacher’s dashboard – direct navigation to learners’ blogs from the visual analytic
  81. 81. http://learningemergence.net/2014/03/01/assessing-learning-dispositions-academic-mindsets 2020? personal data cloud generates my dispositional profile for reflection from behavioural data? >>> help me take responsibility for my own learning Shaofu Huang: Prototyping Learning Power Modelling in SocialLearn http://www.open.ac.uk/blogs/SocialLearnResearch/2012/06/20/social-learning-analytics-symposium Simon Knight: http://people.kmi.open.ac.uk/knight/2014/02/knowledge-in-search Social network patterns, teamwork effectiveness and initiation of relationships Questioning, arguing and search behaviours reveal intrinsic curiosity and epistemic commitments Tagging/sharing/ blogging/social patterns reveal how you see connections between ideas Behavioural and somatic traces associated with perseverance, grit, tenacity; overcoming panic/stress when stretched
  82. 82. Your most recent mood comment: “Great, at last I have found all the resources that I have been looking for, thanks to Steve and Ellen. In your last discussion with your mentor, you decided to work on your resilience by taking on more learning challenges Your ELLI Spider shows that you have made a start on working on your resilience, and that you are also beginning to work on your creativity, which you identified as another area to work on. 1 2 3 45 Envisioning a social learning analytics dashboard Ferguson R and Buckingham Shum S. (2012) Social Learning Analytics: Five Approaches. Proc. 2nd International Conference on Learning Analytics & Knowledge. Vancouver, 29 Apr-2 May: ACM: New York, 23-33. DOI: http://dx.doi.org/10.1145/2330601.2330616 Eprint: http://oro.open.ac.uk/32910 82
  83. 83. Systems leadership and learning: LearningEmergence.net 83
  84. 84. looking forward…
  85. 85. 85 The big shifts that analytics could bring… Organisational Culture evidence-based decisions and org learning Academic Culture data-intensive learning sciences/ educ research Practitioner Culture evidence impact of learning designs; timely interventions C21 Qualities place these on a firm empirical evidence base
  86. 86. 86 Critical zones for research+practice… data-culture org. learning how do HEIs manage the embedding of real time analytics services? sensemaking meets computation creative intelligence + computational thinking educator data literacy how do staff learn to read and write analytics? pedagogical innovation how do learning analytics change student experience?
  87. 87. how to join in 87
  88. 88. The professional society… 88 http://SoLAResearch.org
  89. 89. Next Week… LASI #lasi2014 Learning Analytics Summer Institute International Society
 Educational 
 Data Mining" 89
  90. 90. h=p://www.solaresearch.org/events/lasi-­‐2/lasi2014/lasi-­‐local   90
  91. 91. The Learning Analytics Conference March 16-20, 2015 (NY) 91
  92. 92. conclusion     analy5cs  will  shape  educa5on   —  on  mul5ple  dimensions  an  analy5cs  approach     perpetuates  an  educa5onal  worldview     —  so  let’s  ensure  this  is   inten5onal  –  not  accidental...  

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