Cetis13 Analytics and Institutional Capabilities - Intro
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Transcript of Cetis13 Analytics and Institutional Capabilities - Intro
Analytics and Institutional Capabilities
David SherlockMartin Hawksey (@mhawksey) Sheila MacNeill (@sheilmcn)
http://bit.ly/cetis13analytics
http://bit.ly/cetis13analytics
Outline Your dreams and reality Lightning talks Ranjit Sidhu (or SiD) (@rssidhu) Break
Simon Buckingham-Shum The Open University
@sbskmi
Jean Mutton University of Derby
@myderbi
Mark StubbsManchester Metropolitan University
@thestubbs
http://bit.ly/cetis13analytics
Breakdown: How is it stored, where is it stored, when can you get it?
http://bit.ly/cetis13analytics
EXCEPT: It’s just never enough..Which of your institutions data sources do you have access too?
“Most of it except the BI stuff”
“All of it except Moodle
“None”
“I don't have access to raw data”
http://bit.ly/cetis13analytics
Dream Soundbites “We gather enough xcri-cap data that we
can accurately model the UK courses offering, and find gaps, or overloading”
“We would like to provide learners with data that can help them make choices which improve their learning/opportunities”
“I would like to trace the impact of Library's resources and services”
http://bit.ly/cetis13analytics
Nightmare soundbites
IBM minority report style pre-crime uses... chucking people off courses before they fail as the indicators show they have a likelihood of failing.
A question I would like to address concerns accessing/using data simply because we can.
Some concerns from tutors that data as truth is de-personalising their relationship with students
http://bit.ly/cetis13analytics
Graphs can be a powerful way to represent relationships between data, but they are also a very abstract concept, which means that they run the danger of meaning something only to the creator of the graph… Everything looks like a graph, but almost nothing should ever be drawn as one.
Ben Fry in ‘Visualizing Data’
Tony Hirst: ‘all charts are lies’