Technology Enhanced Learning at the University of Minnesota
 


Technology Enhanced Learning at the University of Minnesota

« Outbreak at WatersEdge - A Public Health Discovery Game | TEL Home | Gartner: E-learning Market Pushing Toward Open Source »

June 03, 2008

Using CMS reports for data mining

Colleges Mine Data to Predict Dropouts - Chronicle.com

John P. Campbell's data mining project at Purdue is featured in the Chronicle this week. I first heard about this project at Educause Midwest in 2007; the project is much further now. Campbell and his colleagues are able to notify students when the data indicates the student is struggling, and students are responding.

From the article: "Purdue researchers found that students in the moderate-risk (yellow light) group who received the e-mail messages did better in the course than did their counterparts in a control group. Most of the students identified as being at highest risk (red light) still did not rectify their situations or take advantage of campus resources, however."

The middle range of students is a big group - if this type of system can help them, then it certainly has promise.

I wonder how successful this program would be if students were more widely aware of it. Would they find it intrusive? Would they try to game the system by logging in more or clicking around the discussion area in order to make it seem like they are more engaged? What do you think?

Trackback

Post a comment

(If you haven't left a comment here before, you may need to be approved by the site owner before your comment will appear. Until then, it won't appear on the entry. Thanks for waiting.)




Feedback | Notice of Privacy Practices

The University of Minnesota is an equal opportunity educator and employer.
The views and opinions expressed in this page are strictly those of the page author. The contents of this page have not been reviewed or approved by the University of Minnesota.