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John Vivolo - Panel Presentation: Learning Analytics - Pocket Data Analytics – Getting Started with Practical In-Semester Course Analytics

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John Vivolo, Director, Online and Virtual Learning for New York University (NYU). Pocket Data Analytics – Getting Started with Practical In-Semester Course Analytics
Day 3

Learning Analytics Panel
Moderator: Dr. Jill Buban, Senior Director of Research and Innovation, Online Learning Consortium.
https://www.slideshare.net/alexandrapickett/olc-panel-presentation-learning-analytics
Panelists:
Patsy Moskal, Associate Director, Research Initiative for Teaching Effectiveness (RITE), University of Central Florida (UCF).
https://www.slideshare.net/alexandrapickett/patsy-moskal-panel-presentation-learning-analytics-examining-the-hype-and-reality-of-learning-analytics
John Vivolo, Director, Online and Virtual Learning for New York University (NYU).
Scott James, Data Scientist, PAR Framework, a division of Hobsons.
https://www.slideshare.net/alexandrapickett/scott-james-panel-presentation-analytics-in-higher-education-a-closer-look-at-online-learning


Open SUNY COTE Summit 2017 - Open SUNY Center for Online Teaching Excellence (https://commons.suny.edu/cotehub/)
Annual conference for the SUNY online teaching and learning community of practice.
March 8-10, 2017, Syracuse, NY.

Conference website: http://opensunycotesummit2017.edublogs.org/
Program: http://opensunycotesummit2017.edublogs.org/about/program/#.WMvhhP21vZs
Recordings: http://opensunycotesummit2017.edublogs.org/mediasite/#.WMvkv_21vZs
Materials: http://opensunycotesummit2017.edublogs.org/mediasite/#.WMvkv_21vZs
Open SUNY COTE: http://commons.suny.edu/cote/

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John Vivolo - Panel Presentation: Learning Analytics - Pocket Data Analytics – Getting Started with Practical In-Semester Course Analytics

  1. 1. Riding the Storm: Pocket Data Analytics – Getting Started with Practical In-Semester Course Analytics John Vivolo Director of Online and Virtual Learning
  2. 2. Order from Chaos •  Can  we  find  order  in  the  chaos  of  the  online  learning  data  storm?   •  Are  there  prac7cal  uses  of  course  analy7cs  to  improve  interac7on   and  performance  during  a  semester?  
  3. 3. 3 Types of Practical Analytics •  Time  based  -­‐  when  students  access  the  course  as  a   whole     •  Individual  assignments/content  -­‐  how  o<en  a  student   “hits”  an  assignment/content     •  Discussion  Board  how/when  are  students  ac7ve  in   discussion  boards  
  4. 4. Weekly   Analysis     Small   Data   Sets   Early   Interven7on   Understanding   student  paHerns   Improved  student   engagement     Improved  student   performance   Pocket Data Analytics: Getting Started
  5. 5. Course analytics can show when students are engaging with the course as a whole, individual content, discussion boards and other engagement tools. What is your goal once you see this data? a)  To  accommodate  student  schedules     b)  Influence  when  students  engage   c)  Avoid  the  “wait  and  see”  approach     d)  All  of  the  above   e)  None  of  the  above   f)  I  have  no  idea!    
  6. 6. Time-based Activity •  Days  of  the  week,  7mes  of  day,  weeks  of  the  month,  etc.     •  Analy7cs  can  influence  improvements  in  content   availability,  assignment  due  dates,  webinars,  virtual  office   hours,  etc.        
  7. 7. Course 1: Days of the Week Fully Online Course: 20 Students (One Week of Activity)
  8. 8. Course 1: Hours of the Day Fully Online Course: 20 Students (One Week of Activity)
  9. 9. Course #2: Days of the Week Fully Online Course: 25 students (One week of activity)
  10. 10. Course #2: Days of the Week Fully Online Course: 25 students (One week of activity)
  11. 11. Course 1: Days of the Week Fully Online Course: 20 Students (One Week of Activity)
  12. 12. Single Content Item (Video): One Week of Activity
  13. 13. Single Content Item (Video): One Week of Activity
  14. 14. Course # 1: Discussion Board Activity (One Week of Activity) M T W Th F S Su
  15. 15. Course # 1: Discussion Board Activity (One Week of Activity) M T W Th F S Su
  16. 16. Other Proactive Methods: “Alerts” •  A8endance  Alerts  Student/faculty  don’t  access  course       •  Assignment/Content  Alerts  Student  does  not  access  content     •  Due  Date  Alerts  Student  has  not  submiHed  assignment  (before/a<er)   due  date  
  17. 17. Questions? John Vivolo Director of Online and Virtual Learning Email: John.Vivolo@nyu.edu Twitter: @vivolojohn Linkedin: /johnvivolo Skype: john.vivolo  

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