FACT2	  Learning	      Analy0cs	  Task	  Group	            (LATG)	  	            Update	  h>p://wiki.sln.suny.edu/display/...
Learning	  AData	  	  	                     BIG	    naly0cs	  Analy0cs	  
Let’s	  hear	  from	  you….	   •  0nyurl.com/factlatg13	  LATG	  Learning	  Analy0cs	  
Q1:	  What	  do	  you	  know	  about	  learning	   analy:cs?	   1.    A	  lot	   2.    A	  li>le	   3.    Unsure	   4.    ...
•  “the	  0mes	  they	  are	  a-­‐                   changing”	                      –  Bob	  Dylan	                  •  “...
1.  Iden0fy	  a	  STRATEGY	  and	  course	  of	  ac0on	  for	  further	      explora0on	  and	  implementa0on	  of	  Learn...
•  Learning	  analy0cs	  uses	  so_ware	  that	  collects	  and	  analyzes	      mul0ple	  data	  sets	  related	  to	  th...
Examples	  of	  uses…	  •  Persistence	  and	     reten0on	  (APUS)	  •  Intelligent/adap0ve	     tutoring	  (Carnegie	   ...
Q2:	  Use	  Learning	  analy0cs	  to	  evaluate	  student	  achievement	  of	  program	  and	  course	  level	  learning	 ...
Q3:	  Use	  Learning	  analy0cs	  to	  Iden:fy	  academically	  at-­‐risk	  students	  and	  no:fy	  students,	  faculty	 ...
Group	  Discussion	  WHAT	  DO	  YOU	  THINK	  ABOUT	  LA	  USES	  ?	  	  
Q4:	  Use	  Learning	  analy0cs	  to	  Provide	  automated	  feedback	  to	  students	  (ex:	  quiz/test	  feedback)	  1. ...
Q4:	  Use	  Learning	  analy0cs	  to	  Provide	  individualized	  learning	  paths	  to	  students	  based	  on	  pre-­‐en...
Q5:	  Use	  Learning	  analy0cs	  to	  Provide	  adap:ve	  learning	  paths	  to	  students	  based	  on	  performance	  i...
Group	  Discussion	  WHAT	  DO	  YOU	  THINK	  ABOUT	  LA	  USES	  ?	  	  
Q6:	  Use	  Learning	  analy:cs	  to	  customize	  course	  delivery	  to	  student	  learning	  styles.	  1.  In	  widesp...
Q7:	  Use	  Learning	  analy0cs	  to	  revise	  course	  content,	  ac:vi:es,	  assessments	  and/or	  course	  structure....
Group	  Discussion	  WHAT	  DO	  YOU	  THINK	  ABOUT	  LA	  USES	  ?	  	  
Where	  is	  the	  data?	  	  	  	  	                                                             Stand-­‐alone	          ...
Picciano,	  JALN	  	  v16	  no	  3	  Data	  Flow	  Examples	  
 	  	  	                              SPSS	             Iden0fying	  tools	  and	  services	  	  
•  Campus	  LA	  survey-­‐	  in	  process	      –  March	  Webinar	  to	  highlight	  uses	  &current	         thinking,	 ...
QUESTIONS?S?	                                     Clare	  Van	  den	  Bllink	                                     cv36@cor...
FACT2 Learning Analytics Task Group (LATG) Update
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FACT2 Learning Analytics Task Group (LATG) Update

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Chancellor Nancy Zimpher's presentation at the SLN SOLsummit 2013
by SUNY Learning Network on Feb 27, 2013
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The SLN SOLsummit 2013
February 27, 2013
Syracuse, NY

FACT2 Learning Analytics Task Group (LATG) Update
http://mediasite.suny.edu/mediasite/Viewer/?peid=7eb3c62bb4b745cb8147c74f8062afae1d
http://slnsolsummit2013.edublogs.org

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  • Image source: http://media.thelineofbestfit.com/wp-content/media/2013/01/Bob-Dylan-3.jpeg
  • Greg
  • Greg
  • Clare
  • Image source: http://www.ibiblio.org/team/history/pioneers/pres/03_bush.html
  • FACT2 Learning Analytics Task Group (LATG) Update

    1. 1. FACT2  Learning   Analy0cs  Task  Group   (LATG)     Update  h>p://wiki.sln.suny.edu/display/FACT/Learning+Analy0cs+Task+Group      
    2. 2. Learning  AData       BIG   naly0cs  Analy0cs  
    3. 3. Let’s  hear  from  you….   •  0nyurl.com/factlatg13  LATG  Learning  Analy0cs  
    4. 4. Q1:  What  do  you  know  about  learning   analy:cs?   1.  A  lot   2.  A  li>le   3.  Unsure   4.  What  is  learning  analy0cs?  LATG  Learning  Analy0cs  
    5. 5. •  “the  0mes  they  are  a-­‐ changing”   –  Bob  Dylan   •  “Technology  is  at  the  center   of…turbulence  in  our  0mes”   –  Tony  Picciano,  CUNY   •  “…collec0ng  traces  that   learners  leave  behind  and   using  those  traces  to   improve  learning”   –  E.  Duval,  LAK  2012  Belgium  The  Rise  of  “Big  Data”  
    6. 6. 1.  Iden0fy  a  STRATEGY  and  course  of  ac0on  for  further   explora0on  and  implementa0on  of  Learning  Analy0cs   across  SUNY.  2.  Provide  OPPORTUNITIES  for  SUNY  faculty  to  contribute   to  the  debate  and  best  prac0ces  on  Learning  Analy0cs.  3.  Iden0fy  TOOLS  (so_ware)  and  PARTNERSHIPS  (business,   organiza0ons)  inside  and  outside  of  SUNY  and   recommend  how  best  to  leverage  these.  4.  Iden0fy  and  share  best  PRACTICES  and  exemplary  uses  of   Learning  Analy0cs  across  SUNY.  5.  Collaborate  with  campuses  to  iden0fy  exis0ng  POLICES   and  laws  (FERPA,  HIPAA,  etc.)  and  recommend  addi0onal   polices  as  needed  to  ensure  the  appropriate  and  ethical   use  of  Learning  Analy0cs  within  SUNY     LATG  Task  Group  Charge  
    7. 7. •  Learning  analy0cs  uses  so_ware  that  collects  and  analyzes   mul0ple  data  sets  related  to  the  process  of  learning  to   predict  and  impact  student  success.     •  This  includes  data  collected  in  blended  and  online  learning   environments,  online  portals,  enrollment  data,  and  other   emergent  resources  connected  to  the  teaching  and   learning  experience.     •  Learning  analy:cs  can  be  used  to…     –  diagnose  student  needs,     –  provide  feedback  to  the  student,  faculty,  instruc0onal   developer,  and  advisor,     –  combine  with  data  from  other  learning  systems  to  generate   new  insights  about  learning  and  instruc0on.  Learning  Analy0cs  -­‐  Working  Defini0on  
    8. 8. Examples  of  uses…  •  Persistence  and   reten0on  (APUS)  •  Intelligent/adap0ve   tutoring  (Carnegie   Mellon)  •  Research  on  condi0ons   that  facilitate  learning   (CSU  Chico)   Learning  Analy0cs  &  Online  Learning  
    9. 9. Q2:  Use  Learning  analy0cs  to  evaluate  student  achievement  of  program  and  course  level  learning  outcomes?  1.  In  widespread  use        2.  In  limited  use                      3.  Not  in  use,  but  interested  4.  Not  in  use,  not  interested         Your  input:  learning  outcomes  
    10. 10. Q3:  Use  Learning  analy0cs  to  Iden:fy  academically  at-­‐risk  students  and  no:fy  students,  faculty  and/or  advisors.  1.  In  widespread  use        2.  In  limited  use                      3.  Not  in  use,  but  interested  4.  Not  in  use,  not  interested         Your  input:  learning  outcomes  
    11. 11. Group  Discussion  WHAT  DO  YOU  THINK  ABOUT  LA  USES  ?    
    12. 12. Q4:  Use  Learning  analy0cs  to  Provide  automated  feedback  to  students  (ex:  quiz/test  feedback)  1.  In  widespread  use        2.  In  limited  use                      3.  Not  in  use,  but  interested  4.  Not  in  use,  not  interested         Your  input:  learning  outcomes  
    13. 13. Q4:  Use  Learning  analy0cs  to  Provide  individualized  learning  paths  to  students  based  on  pre-­‐entry  condi:ons.  1.  In  widespread  use        2.  In  limited  use                      3.  Not  in  use,  but  interested  4.  Not  in  use,  not  interested         Your  input:  learning  outcomes  
    14. 14. Q5:  Use  Learning  analy0cs  to  Provide  adap:ve  learning  paths  to  students  based  on  performance  in  course.  1.  In  widespread  use        2.  In  limited  use                      3.  Not  in  use,  but  interested  4.  Not  in  use,  not  interested           Your  input:  learning  outcomes  
    15. 15. Group  Discussion  WHAT  DO  YOU  THINK  ABOUT  LA  USES  ?    
    16. 16. Q6:  Use  Learning  analy:cs  to  customize  course  delivery  to  student  learning  styles.  1.  In  widespread  use        2.  In  limited  use                      3.  Not  in  use,  but  interested  4.  Not  in  use,  not  interested       Your  input:  learning  outcomes  
    17. 17. Q7:  Use  Learning  analy0cs  to  revise  course  content,  ac:vi:es,  assessments  and/or  course  structure.  1.  In  widespread  use        2.  In  limited  use                      3.  Not  in  use,  but  interested  4.  Not  in  use,  not  interested         Your  input:  learning  outcomes  
    18. 18. Group  Discussion  WHAT  DO  YOU  THINK  ABOUT  LA  USES  ?    
    19. 19. Where  is  the  data?           Stand-­‐alone   LMS  Plajorm   Plajorm   Analy0cs   Analy0cs   Discrete   Analy0cs   Tools   Iden0fying  tools  and  services    
    20. 20. Picciano,  JALN    v16  no  3  Data  Flow  Examples  
    21. 21.         SPSS   Iden0fying  tools  and  services    
    22. 22. •  Campus  LA  survey-­‐  in  process   –  March  Webinar  to  highlight  uses  &current   thinking,  con0nue  dialogue…   –  Policy  considera0on  discussion   –  Evalua0on/demonstra0ons  from  vendors  •  CIT  2013  presenta0on  (May  2013)  •  Final  recommenda0ons  &  report  (May  2013)   LATG  Next  Steps  
    23. 23. QUESTIONS?S?   Clare  Van  den  Bllink   cv36@cornell.edu     Greg  Ketcham   greg.ketcham@oswego.edud  h>p://wiki.sln.suny.edu/display/FACT/Learning+Analy0cs+Task+Group      

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