Presentation by Andreas Schleicher Tackling the School Absenteeism Crisis 30 ...
Show me the data! Actionable insight from open courses
1. Show me the data!
Actionable insight from open courses
2. Analytics
“actionable insights through problem
definition and the application of
statistical models and analysis against
existing and/or simulated future data”
Cooper, A. 2012 – Cetis Analytics Series
What-is-Analytics-Vol1-No-5
30. Network effects
The social
network
diagrams can
be used to
identify:
• isolated
students
• group
malfunction
• users that
are
information
brokers
Hansen, D. L., Shneiderman, B., & Smith, M. (2010). Visualizing threaded conversation
networks: mining message boards and email lists for actionable insights.
32. Analytically cloaked
“Learning and knowledge creation is often
distributed across multiple media and sites in
networked environments. Traces of such
activity may be fragmented across multiple
logs and may not match analytic needs.”
Suthers, D. D., & Rosen, D. (2011).
A unified framework for multi-level analysis of distributed learning
34. In sample 41%
(n.103) emails
returned bio
% of
Total
Total Inputs
# Matched
# No Match
# Bad Input
Count
250
178 71.20%
72 28.80%
0
0.00%
35. In sample 41%
(n.103) emails
returned bio
% of
Total
API returns other
social profiles
Total Inputs
# Matched
# No Match
# Bad Input
Count
250
178 71.20%
72 28.80%
0
0.00%
36. • Detecting and Analyzing Subpopulations within
Connectivist MOOCs
• Retrospective investigation into learner
subpopulation detection within the connectivist
courses.
• Using free and open source tools we will
attempt to resolve activity data from multiple
sources to permit the analysis of any
engagement patterns.
Ferguson and Buckingham Shum (2012)'s Social Learning Analytics: Five Approaches defines five dimensions of social learning for which one could create instruments:social network analytics — interpersonal relationships define social platformsdiscourse analytics — language is a primary tool for knowledge negotiation and constructioncontent analytics — user-generated content is one of the defining characteristics of Web 2.0disposition analytics — intrinsic motivation to learn is a defining feature of online social media, and lies at the heart of engaged learning, and innovationcontext analytics — mobile computing is transforming access to both people and content.
Ferguson and Buckingham Shum (2012)'s Social Learning Analytics: Five Approaches defines five dimensions of social learning for which one could create instruments:social network analytics — interpersonal relationships define social platformsdiscourse analytics — language is a primary tool for knowledge negotiation and constructioncontent analytics — user-generated content is one of the defining characteristics of Web 2.0disposition analytics — intrinsic motivation to learn is a defining feature of online social media, and lies at the heart of engaged learning, and innovationcontext analytics — mobile computing is transforming access to both people and content.
Ferguson and Buckingham Shum (2012)'s Social Learning Analytics: Five Approaches defines five dimensions of social learning for which one could create instruments:social network analytics — interpersonal relationships define social platformsdiscourse analytics — language is a primary tool for knowledge negotiation and constructioncontent analytics — user-generated content is one of the defining characteristics of Web 2.0disposition analytics — intrinsic motivation to learn is a defining feature of online social media, and lies at the heart of engaged learning, and innovationcontext analytics — mobile computing is transforming access to both people and content.
Ferguson and Buckingham Shum (2012)'s Social Learning Analytics: Five Approaches defines five dimensions of social learning for which one could create instruments:social network analytics — interpersonal relationships define social platformsdiscourse analytics — language is a primary tool for knowledge negotiation and constructioncontent analytics — user-generated content is one of the defining characteristics of Web 2.0disposition analytics — intrinsic motivation to learn is a defining feature of online social media, and lies at the heart of engaged learning, and innovationcontext analytics — mobile computing is transforming access to both people and content.
Ferguson and Buckingham Shum (2012)'s Social Learning Analytics: Five Approaches defines five dimensions of social learning for which one could create instruments:social network analytics — interpersonal relationships define social platformsdiscourse analytics — language is a primary tool for knowledge negotiation and constructioncontent analytics — user-generated content is one of the defining characteristics of Web 2.0disposition analytics — intrinsic motivation to learn is a defining feature of online social media, and lies at the heart of engaged learning, and innovationcontext analytics — mobile computing is transforming access to both people and content.
Ferguson and Buckingham Shum (2012)'s Social Learning Analytics: Five Approaches defines five dimensions of social learning for which one could create instruments:social network analytics — interpersonal relationships define social platformsdiscourse analytics — language is a primary tool for knowledge negotiation and constructioncontent analytics — user-generated content is one of the defining characteristics of Web 2.0disposition analytics — intrinsic motivation to learn is a defining feature of online social media, and lies at the heart of engaged learning, and innovationcontext analytics — mobile computing is transforming access to both people and content.
Ferguson and Buckingham Shum (2012)'s Social Learning Analytics: Five Approaches defines five dimensions of social learning for which one could create instruments:social network analytics — interpersonal relationships define social platformsdiscourse analytics — language is a primary tool for knowledge negotiation and constructioncontent analytics — user-generated content is one of the defining characteristics of Web 2.0disposition analytics — intrinsic motivation to learn is a defining feature of online social media, and lies at the heart of engaged learning, and innovationcontext analytics — mobile computing is transforming access to both people and content.
What: Coursera MCQ dataWho: tutors
What: edXWho: Institutions/tutors
These trajectories are also a useful framework for thecomparison of learner engagement between different coursestructures or instructional approachesWhat: CourseraK-meansWho: Inst.
HeadacheSimply getting the data in a timely fashion
HeadacheDo you want a database table dump?Do you need to join datasets, merge results, cleanse
Ferguson and Buckingham Shum (2012)'s Social Learning Analytics: Five Approaches defines five dimensions of social learning for which one could create instruments:social network analytics — interpersonal relationships define social platformsdiscourse analytics — language is a primary tool for knowledge negotiation and constructioncontent analytics — user-generated content is one of the defining characteristics of Web 2.0disposition analytics — intrinsic motivation to learn is a defining feature of online social media, and lies at the heart of engaged learning, and innovationcontext analytics — mobile computing is transforming access to both people and content.