data intensive university

The data-intensive universityGeorge Siemens, PhD

July 27, 2012Presented to:

American Association of State and College UniversitiesSan Francisco, CA

Assumptions

American intelligence communities are interested in your YouTube video, flickr uploads, tweets -- even your online book purchases -- and for over a year they've been laying down some serious cash to get a better look at all of them.

“…probably indicates that these sectors face strong systemic barriers to increasing productivity”

Kron, et al (2011)

“higher education finds itself on the verge of diving deeply into the analytical end of the education transformation pool”

Wagner & Ice 2012

“Analytics, and the data and research that fuel it, offers the potential to identify broken models and promising practices, to explain them, and to propagate those practices.”

Grajek, 2011

http://www.dataqualitycampaign.org/

A different way of thinking and functioning

What is a data-intensive university?

“A university where staff and students understand data and, regardless of its volume and diversity, can use it and reuse it, store and curate it, apply and develop the analytical tools to interpret it.”

Siemens, Long, 2011. EDUCUASE Review

Limited efficiency and productivity gains through piecemeal solutions

We collect enough data. We need to focus on connecting.

Multiple data sources:

Social mediaUniversity help resourcesLMSStudent information systemCourse progression, etc

Challenges: Broadening scope of data capture

- data outside of the current model of LMS - sociometer: Choudhury & Pentland (2002)

- classroom/library/support services,- quantified self

Timeliness of data (real-time analytics)

Principles of a systems-wide analytics tool

1. Algorithms should be open, customizable for context2. Students should see what the organization sees3. Analytics engine as a platform: open for all researchers and organizations to build on4. Specific analytics strategies and tools: APIs5. Integrate and connect with existing open tools6. Modularized and extensible

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Siemens, Long, 2011. EDUCAUSE Review

http://edfuture.net/

October 8-November 16, 2012

http://lakconference.org

gsiemens @gmailTwitterSkypeFBWherever

www.elearnspace.org

www.connectivism.ca

www.learninganalytics.net