Altus Dynamics Blog

Predicting Student Dropout Risks and Increasing Graduation Rates with Cloud Analytics [Case Study]

Posted by Cait Abernethy on Apr 11, 2016 10:00:00 AM

This post originally appeared on the Microsoft Customer Stories page.

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Keeping high school students engaged and excited about learning is harder now than ever before. But is it possible to predict whether students are at risk of dropping out of school? The Tacoma Public School district thinks so. Using predictive analytics tools based on Microsoft cloud technologies, the district is providing comprehensive data snapshots of student success indicators and has already helped to improve graduation rates from 55 to 78 percent.

And once teachers and principals can use the data model to predict dropout probability, they’ll be able to provide additional learning assistance early enough in the process to turn at-risk students around.

Not long ago, the reputation of public education in Tacoma, Washington, was as bleak as the gray skies that often blanket the city. A 2007 national study dubbed the 30,000-student Tacoma Public School district’s five high schools “dropout factories,” where many freshmen never made it to graduation. As recently as 2010, just 55 percent of the district’s high school students—well below the national average of 81 percent—earned their diplomas on time.

But administrators in the challenged district didn’t give up hope. Through their efforts, the graduation rate jumped from 55 to 78 percent by 2014. And today, the district is recognized nationally for its educational achievements.

So how was the dramatic turnaround achieved?

It started with a radical vision: What if teachers and principals had analytical tools to look at all the data surrounding a student and could then predict whether or not a student was likely to disengage and ultimately drop out? Armed with such tools, educators and administrators would be empowered to reverse the trend and help more students succeed.

“We have so much data in the district, and we wanted to get better at analyzing trends of student success,” says Shaun Taylor, the district’s CIO. “By using predictive analytics, we thought we would be able to intervene earlier and work closely with those at-risk students. Then we would be able to reach our ultimate goal: getting that graduation number close to 100 percent.”

 

To continue reading the rest of the article, please visit the Microsoft Customer Stories page.

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This Post Was Written By Cait Abernethy
Cait Abernethy is the Marketing Coordinator at Sparkrock and is excited about marketing trends, enthralled by technology of all kinds, and is interested in the ways local actions can have a global impact.
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