Can analytics help keep students from dropping out of school?

Higher education can be a great source of fulfillment and personal development. It’s also a powerful economic asset. According to the US Bureau of Labor Statistics, Americans with college degrees are roughly half as likely to be employed as those with only a high school diploma.

But getting there isn’t easy. Many enroll in higher education programs but drop out after facing academic or personal difficulties. One study concluded that as many as 54.8 percent of incoming undergraduate students won’t complete a degree within six years.

This is a problem, not only for educational institutions, but for society. Poor retention rates can mean employers will have access to a lower-skilled workforce and employees will have limited professional opportunities.

One way to help solve this problem is to identify students who are at risk. If educators know who is struggling, they can provide additional resources and support. At a larger institution, however, this can be a challenging task.

Understanding student information with IBM Analytics

Most schools already have access to a great deal of information about students, including high school grades, attendance information and participation metrics from online components of classes. IBM Analytics technology can help schools make the most of this raw data by gathering, analyzing and visualizing it in a way that is useful for educators. This enables schools to more accurately identify students who need help.

Here are three examples of cases where this approach is helping schools succeed:

1. The University of Florida uses IBM InfoSphere DataStage to extract, transfer and load data from multiple sources into IBM Cognos Analytics, which then helps monitor and predict student performance.

Here’s what Dave Gruber, Associate CIO of The University of Florida had to say about the solution: “Insights from IBM Cognos Analytics should enable us to implement more effective policies across the university. By helping us identify which students are at risk, it should help us intervene earlier and more effectively.”

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2. Finger Lakes Community College has used SPSS Modeler and IBM SPSS Statistics to achieve a 10 percentage point increase in retention rate for pre-nursing students.

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3. The Keller Graduate School of Management at DeVry University also uses IBM Analytics to track students. This has helped the school raise both persistence rates and NPS scores by 2 percent.

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Analytics is already helping solve serious problems for organizations of higher learning and society at large. Almost assuredly more colleges and universities will follow their lead.

To learn more about these technologies, visit the IBM Analytics website.