Using Big Data to Predict Online Student Success | Inside Higher Ed - 0 views
www.insidehighered.com/...predict-online-student-success
higher-education analytics learning big-data predictive
shared by George Bradford on 01 Feb 12
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Researchers have created a database that measures 33 variables for the online coursework of 640,000 students – a whopping 3 million course-level records.
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Project Participants American Public University System Community College System of Colorado Rio Salado College University of Hawaii System University of Illinois-Springfield University of Phoenix
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“What the data seem to suggest, however, is that for students who seem to have a high propensity of dropping out of an online course-based program, the fewer courses they take initially, the better-off they are.”
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Phil Ice, vice president of research and development for the American Public University System and the project’s lead investigator.
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The two-year college, which is based in Arizona, has a particularly strong online presence for a community college – 43,000 of its students are enrolled in online programs. The new tracking system allows instructors to see a red, yellow or green light for each student’s performance. And students can see their own tracking lights.
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It measures student engagement through their Web interactions, how often they look at textbooks and whether they respond to feedback from instructors, all in addition to their performance on coursework.
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The data set has the potential to give institutions sophisticated information about small subsets of students – such as which academic programs are best suited for a 25-year-old male Latino with strength in mathematics
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New students are more likely to drop out of online colleges if they take full courseloads than if they enroll part time, according to findings from a research project that is challenging conventional wisdom about student success. But perhaps more important than that potentially game-changing nugget, researchers said, is how the project has chipped away at skepticism in higher education about the power of "big data." Researchers have created a database that measures 33 variables for the online coursework of 640,000 students - a whopping 3 million course-level records. While the work is far from complete, the variables help track student performance and retention across a broad range of demographic factors. The data can show what works at a specific type of institution, and what doesn't. That sort of predictive analytics has long been embraced by corporations, but not so much by the academy. The ongoing data-mining effort, which was kicked off last year with a $1 million grant from the Bill and Melinda Gates Foundation, is being led by WCET, the WICHE Cooperative for Educational Technologies.