Cetis13 Analytics and Institutional Capabilities - Intro

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Analytics and Institutional Capabilities David Sherlock Martin Hawksey (@mhawksey) Sheila MacNeill (@sheilmcn) http://bit.ly/cetis13anal

Transcript of Cetis13 Analytics and Institutional Capabilities - Intro

Analytics and Institutional Capabilities

David SherlockMartin Hawksey (@mhawksey) Sheila MacNeill (@sheilmcn)

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CC-BY By marinephotobankhttp://www.flickr.com/photos/19378856@N04/2037098785/

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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

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Questionnaire

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Break Down: Who wants to do what, what data do they get to do it

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Breakdown: How is it stored, where is it stored, when can you get it?

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Breakdown: Role and access to data without request

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Breakdown: Role and analytics expertise

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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”

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Obligatory wordle: Our dreams

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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”

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Obligatory wordl: Our Nightmares

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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

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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’

IMAGES + STORIES ON THE FUTURE OF LEARNING ANALYTICS...

Participants choose images and add stories/comments on Learning Analytics, tagging them: Dream / Nightmare / Fairydust

http://lanoirblanc.tumblr.com/