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Using Analytics to Intervene with Underperforming College Students (Innovative Practice)
Jan 20th, 2010
11:30 AM - 12:30 PM
Governor's Ballroom D (fourth floor)
Session Type: Concurrent Session
Data mining is typically associated with business and marketing. For example, Amazon uses people's past purchases to suggest books they might be interested in buying. Similarly, academic analytics can be used to identify and predict students who might be at risk, by analyzing demographic and performance data of former students. However, there is no clear consensus on how to intervene with current students in a way they will accept and not associate with academic "profiling." Why should students think they are exceptions to our rules? This panel presentation will share how three institutions are approaching this problem and provide an overview of related issues.
Live Video and slides from the presentation are being provided through the generous support of Sonic Foundry.
An archive of this video will be available after the session.
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