Successfully reported this slideshow.
We use your LinkedIn profile and activity data to personalize ads and to show you more relevant ads. You can change your ad preferences anytime.

The Future of Learning Analytics

1,870 views

Published on

Presentation given at Onderwijsdagen 2015, 11.11.2015, #owd2015 #laceproject

Published in: Education
  • Be the first to comment

The Future of Learning Analytics

  1. 1. The  future  of  Learning  Analy2cs   Wat  is  haalbaar  en  wat  is  wenselijk?   Hendrik  Drachsler|  Open  Universiteit   Onderwijsdagen  2015|  11  November  2015   #laceproject,  #owd2015,  @hdrachsler  
  2. 2. 3   • Hendrik Drachsler Associate Professor Open Universiteit, Welten Institute • Research topics: Personalization, Recommender Systems, Learning Analytics, Mobile devices • Application domains: Schools, HEI, Medical education WhoAmI   2006 - 2009
  3. 3. 3   Research  ac8vi8es  
  4. 4. The  LACE  project   4   K12   Workplace   HEI  §  Community-­‐building  through  events  &   communica8on  channels/social  media   (cross-­‐disciplinary  HEI,  K12,  Workplace)     §  Technology  transfer  &  best  prac8ce     §  Organized  22  events,  and  contributed  to  33   (tutorials,  workshops,  conferences,  etc.   LACE  –  Onderwijsdagen,  #owd2015,  RoUerdam,  Netherlands  –  11  November  2015    European  support  ac2on  aimed  at  integrate  communi2es  working  on  LA  from  schools,   workplace  and  universi2es    
  5. 5. LACE  Goals  and  objec2ves   5   •  Objec2ve  1  –  Promote   knowledge  crea2on  and   exchange       •  Objec2ve  2  –  Increase  the   evidence  base       •  Objec2ve  3  –  Contribute  to   the  defini2on  of  future   direc2ons       •  Objec2ve  4  –  Build  consensus   on  interoperability  and  data   sharing   LACE  –  Onderwijsdagen,  #owd2015,  RoUerdam,  Netherlands  –  11  November  2015  
  6. 6. Why  envisioning  the  future  of  learning  analy2cs     l  We  are  interested  in  indica2ons   of  the  future  of  learning   analy2cs:   -  To  provide  guidance  for  policy   makers   -  To  help  coordinate  research     l  We  have  described  9  possible   futures  of  learning  analy2cs   (visions)   -  Conceivable  with  current   technology,  but  challenging  in   their  implica8ons   -  Developed  and  winnowed   down  within  the  project   6  LACE  –  Onderwijsdagen,  #owd2015,  RoUerdam,  Netherlands  –  11  November  2015  
  7. 7. We  are  carrying  out  a  'policy  Delphi'   7   l  To  solicit  informed  judgments  on  the  future  of   learning  analy2cs,  in  order  to  understand     -  The  underlying  trends   -  The  opinions  of  stakeholders  from  different  areas   l  The  visions  are  of  interest  in  themselves,  but  their   main  purpose  is  as  a  tool  for  elici2ng  and  thinking   about  beliefs  about     -  The  trends  which  are  driving  learning  analy8cs   -  The  implica8ons  of  those  trends   LACE  –  Onderwijsdagen,  #owd2015,  RoUerdam,  Netherlands  –  11  November  2015  
  8. 8. Today's  workshop   l  Share  the  visions:   l  h^ps://goo.gl/Elsx3x     l  The  main  purpose  is  to  generate  enlightening   conversa2ons  on   -  The  current  trends  in  learning  analy8cs   -  Where  those  trends  are  leading  to     l  We  would  also  like  to  include  the  points  from  your   conclusions  in  the  wider  study.     l  All  contribu8ons  will  be  anonymous     8  LACE  –  Onderwijsdagen,  #owd2015,  RoUerdam,  Netherlands  –  11  November  2015  
  9. 9. Three  stages  of  the  workshop   l  Stage  1:  Short  presenta8on  of  a  vision  (Doug)   l  Stage  2:  Rate  Vision  on  (Audience)   l   1.  ‘haalbaar’  =‘feasible’   l   2.  ‘wenselijk’  =  ‘desirable’   l  By  raising  your  hands!   l  Stage  3:  Capture  some  comments  on  each  Vision   l  Miriam  Brand  will  take  notes  on  ra8ng  results  per  vision   and  write  down  comments   In  total  7  minutes  per  Vision,  let’s  see  how  far  we  get  !!!   LACE  –  Onderwijsdagen,  #owd2015,  RoUerdam,  Netherlands  –  11  November  2015  
  10. 10. Vision  1:  2025,  LA  are  essen2al  tools  for   educa2onal  management   10  Pic  by:  Janneke  Staaks,  hUps://www.flickr.com/photos/jannekestaaks/14204590229/   •  A  wide  range  of  data  about   learner  behaviour  is  used   •  This  generates  good  quality,   real-­‐8me  predic8ons  about   likely  study  success     •  Learners,  teachers,   managers  and  policymakers   have  access  to  live   informa8on   •  You  don’t  have  to  wait  to   see  if  a  course  is  booming   or  failing  
  11. 11. Vision  2:  2025,  LA  analy2cs  support  self-­‐directed   autonomous  learning   11  Pic  by:  SparkFun,  hUps://www.flickr.com/photos/sparkfun/4536382170/   •  No  Curricula  anymore   •  Students  create  study   groups  that  decide  their   learning  goals  and  how  to   achieve  these   •  Analy8cs  support  info   exchange  and  group   collabora8ons   •  Teachers  become  MENTORS     •  Forma8ve  assessment  is   used  to  guide  future   progress  towards  learning   goals  
  12. 12. Vision  3:  2025,  analy2cs  are  rarely  used    in  educa2on   12  Pic  by:  Tara  Hunt,  hUps://www.flickr.com/photos/missrogue/94403705   •  Courses  that  are  automated   by  analy8cs  are  seen  as   inferior   •  Learners  have  realised  that   they  can  game  the  system   •  There  have  been  major   leaks  and  misuse  of   sensi8ve  personal  data   •  All  use  of  data  for   educa8onal  purposes  has  to   be  approved  not  only  by  the   learner  but  also  by  new   inspectorates.  
  13. 13. Vision  4:  2025,  classrooms  monitor  the  physical   environment  to  support  learning  and  teaching   13   •  Furniture,  pens,  wri8ng  pads  –   almost  any  tool  used  during   learning  –  can  be  fiUed  with   sensors.     •  Cameras  monitor  movements,   and  record  exactly  how  learners   work  with  and  manipulate   objects.     •  Informa8on  is  used  to  monitor   learners’  progress.   •  Teachers  are  alerted  to  signs  of   individual  learner’s  boredom,   confusion,  and  devia8on  from   task.   Pic  by:  Janneke  Staaks,  hUps://www.flickr.com/photos/jannekestaaks/14391223825/  
  14. 14. Vision  5:  2025,  most  teaching  is  delegated  to   computers   14  Pic  by:  Charis  Tsevis,  hUps://www.flickr.com/photos/tsevis/5470451264/   •  Development  of  enormous   datasets  containing  informa8on   about  hundreds  of  thousands  of   learners   •  It  is  possible  to  provide  reliable   evidence-­‐based   recommenda8ons  about  the   most  successful  routes  to   learning   •  Recommenda8ons  are  beUer   informed  and  more  reliable  than   by  even  the  best-­‐trained   humans  
  15. 15. Vision  6:  2025,  personal  data  tracking  supports   learning   15  Pic  by:  Lauren  Manning  hUps://www.flickr.com/photos/laurenmanning/7246212772   •  Sensors  gather  personal   informa8on  about  factors   such  as  posture,  aUen8on,   rest,  stress,  blood  sugar,  and   metabolic  rate.     •  This  data  helps  people  to   master  skills  as  swimming,   driving,  and  passing   examina8ons   •  Programmes  using  this  data   to  op8mise  learning  for   different  ages  and  courses  
  16. 16. Vision  7:  2025,  individuals  control  their  own  data   16  Pic  by:  Marcin  Wichary,  hUps://www.flickr.com/photos/mwichary/3014140238/   •  People  are  aware  of  the  importance   and  value  of  their  data.       •  Learners  control  the  type  and   quan8ty  of  personal  data  that  they   share,  and  with  whom  they  share  it     •  If  they  do  not  engage  with  these   tools,  then  no  data  is  shared  and  no   benefits  gained.     •  Most  educa8onal  ins8tu8ons  run   campaigns  to  raise  awareness  of   the  risks  and  exposure  of  data  
  17. 17. Vision  8:  2025,  open  systems  for  learning   analy2cs  are  widely  adopted   17  Pic  by:  Gideon  Burton,  hUps://www.flickr.com/photos/waking8ger/3157622608   •  ‘Open  learning  analy8cs’   established  by  the    Open   Learning  Analy8cs  Founda8on       •  Educa8onal  organisa8ons  see   learning  analy8cs  as  a  central   element  of  their  IT  provision   and  demand  access     •  All  tools  use  open  algorithms   standards  which  facilitate   transparency  and  independent   valida8on  
  18. 18. Provide  your  ideas  for  the  Future!   l  Don’t  forget  to  share  the   Visions  with  your  colleges  or   friends     l  We  are  keen  on  gemng  as   many  replies  to  make  a  rich   judgment  how  the  future  will   look  like     l  You  can  find  the  Visions  here:     h^ps://goo.gl/Elsx3x     18  
  19. 19. “The  future  of  Learning  Analy8cs”  by  Hendrik  Drachsler,   OUNL  was  presented  at  the  Onderwijsdagen  2015  in   RoUerdam,  Netherlands  11  November,  2015.     hendrik.drachsler@ou.nl       This  work  was  undertaken  as  part  of  the  LACE  Project,  supported  by  the  European  Commission  Seventh   Framework  Programme,  grant  619424.   www.laceproject.eu   @laceproject   19  

×