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Digital Learning, Emerging Technologies, Abundant Data, and Pedagogies of Care

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Keynote delivered at the Emerging Technologies in Authentic Learning Contexts Conference (Cape Town, South Africa), drawing links between my research on digital learning, emerging technologies, learner experiences, and the changing higher education landscape.

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Digital Learning, Emerging Technologies, Abundant Data, and Pedagogies of Care

  1. 1. Emerging  Technologies  in  Authen2c  Learning  Contexts  Conference   September  2015,  Cape  Town,  South  Africa   Digital Learning, Emerging Technologies, Abundant Data, and Pedagogies of Care! George Veletsianos, PhD! ! Canada Research Chair in Innovative Learning & Technology! Associate Professor! ! School of Education and Technology! Royal Roads University! Victoria, British Columbia, Canada!
  2. 2. Research  Focus   Learner,  instructor,  &  scholar  experiences   Emerging  technologies  &  emerging  prac2ces   Digital  educa2on;  online  networks     To  design  excep2onal,  empowering,  &  equitable    learning  experiences  
  3. 3. Key  takeaways   •  The  EdTech  industry.  A  remedy?   •  Big  Data,  Analy2cs,  and  experimental/Quant   approaches.  Capable  of  explaining  what,  how,  and   why  learning  happens?   •  Educa2on.  A  product  to  be  managed,  automated,   and  delivered?   •  Edech  is  founded  on  technodeterminis2c  thinking   •  How  is  all  this  supposed  to  foster  contexts  of  care?  
  4. 4. A  worldwide  economic   downturn   Globaliza2on  and   compe22on  à   interna2onaliza2on   policies   Increased  demand   for  educa2on     Curtailment  of  public   funding   Pressures  for   accountability   Impact  of  emerging   technologies   Higher  Educa2on  Trends  and  Pressures   Automa2on  à  Work?   Priva2za2on  
  5. 5. The  rise  of  “EdTech  as  a  remedy”  
  6. 6. The  rise  of  “EdTech  as  a  remedy”   “Whether the practice is called outsourcing, contracting out, or privatizing, the impact is the same. Food services, health care, the bookstore…endless array of activities that universities used to manage…” Kirp,  .L  (2003).  Shakespeare,  Einstein,  and  the  Bo3om  Line:  The  Marke9ng  of  Higher  Educa9on.   Cambridge,  MA:  Harvard  University  Press    
  7. 7. The  rise  of  “EdTech  as  a  remedy”   Online program management services
  8. 8. What  are  some  of  the  most  problema2c   assump2ons  of  EdTech?    
  9. 9.  “What  6.9  million  clicks  tell  us  about  how  to  fix   online  educa2on”                            (Conner-­‐Simons,  2014)       “We  can  see  everything  the  students  do”                                  (Chu,  2013)     Assump2on  #1:  Massive  data  sets  will  tell  us  all  that   we  need  to  know  about  learning  and  teaching  
  10. 10. Assump2on  #1:  Massive  data  sets  will  tell  us  all  that   we  need  to  know  about  learning  and  teaching   Results  from  a  2013-­‐2015  analysis  of  the  MOOC  literature:     “Automated  collec2on  of  secondary  data  (e.g.,  trace  data)  was   used  most  frequently  (73.2%  of  papers  used  this  method).  The   second  most  popular  data  collec2on  method  was  ques2onnaires/ surveys,  which  were  used  in  55.7%  of  papers….Interviews  (13.7%),   secondary  data  collected  by  humans  (13.7%),  tests  (8.7%),   observa2ons  (4.9%),  focus  groups  (4.4%),  and  other  (2.7%).”    
  11. 11. Assump2on  #1:  Massive  data  sets  will  tell  us  all  that   we  need  to  know  about  learning  and  teaching  
  12. 12. What  aspects  of  digital  learning  cannot  be  fully   understood  and  improved  using  data  trails?  
  13. 13. What  aspects  of  digital  learning  are  invisible  to   algorithms,  mining,  and  analy2cs?  
  14. 14. A.  Why  do  learners  par2cipate  in  digital  learning   environments  in  the  ways  that  they  do?  
  15. 15. B.  How  do  learners  overcome  challenges  in   digital  learning  environments?  
  16. 16. Embedded  in  seemingly  innocuous  descrip2ons   like  “managing  scale”  and  “crea2ng  efficiencies”   Assump2on  #2:  Educa2on  is  a  product  to  be   packaged,  automated,  &  delivered  
  17. 17. Assump2on  #2:  Educa2on  is  a  product  to  be   packaged,  automated,  &  delivered  
  18. 18. Assump2on  #2:  Educa2on  is  a  product  to  be   packaged,  automated,  &  delivered  
  19. 19. Assump2on  #3:    Techno-­‐determinism   It’s not that automated methods are undesirable “…it is rather that the terms on which they are proposed are driven by a productivity-oriented solutionism which has been critiqued for decades now” (Bayne, 2015)
  20. 20. Assump2on  #3:    Techno-­‐determinism   The Silicon Valley flavor of EdTech à a naïve belief in determinism Void of the most basic foundations of Educational Technology as a field of practice.
  21. 21. Assump2on  #3:    Techno-­‐determinism   Emerging  Technologies  and   Emerging  Prac2ces    are   defined  by  the  contexts  in   which  they  occur.    
  22. 22. Assump2on  #3:    Techno-­‐determinism   Emerging  Technologies  and  Emerging  Prac2ces     are  defined  by  the  contexts  in  which  they  occur.     They  share  four  characteris2cs     1.  Not  defined  by  newness   2.  Coming  into  being   3.  Not-­‐yetness   4.  Unfulfilled  but  promising  poten2al  
  23. 23. To  what  end?     The Silicon Valley flavor of EdTech What  needs  does  this  EdTech  serve?     Does  this  EdTech     create  a  context  of  care?     Does  this  EdTech  foster  pedagogies  of  care?      
  24. 24. Pedagogies  of  Care         Care.     A  core  element  of  pedagogy  (Noddings,  2003)  
  25. 25. To  what  end?       What  would  an     African  flavor  of  EdTech  look  like?     What  should  home  grown  solu2ons  look  like  &   what  issues  do  they  need  to  address?  
  26. 26. To  what  end?  
  27. 27. Thank  you!       Research  available  at:   hnp://www.veletsianos/ publica2ons         This  presenta2on:   www.slideshare.com/veletsianos     Contact:     veletsianos@gmail.com   @veletsianos  on  Twiner