Educators use predictive analytics to help at-risk students

Data is woven into every aspect of our lives. Though you may not be familiar with the math or algorithms that govern predictive analytics, their impact can nevertheless be seen and felt in education.

What if there were a way to harness this intelligent technology and use it in classrooms? What if data about students’ habits, patterns, and performance could be used to predict which of them are at risk of falling behind their classmates, and to empower teachers to intervene and help prevent that from happening? Thankfully, some schools are already doing that.

Predictive analytics in action

Enterprising school districts and education leaders are having marked success with predictive analytics in K-12 schools. For example, Tacoma Public Schools had its reputation tinged with a graduation rate of 55 percent, as recently as 2010. The district launched the Whole Child Initiative, a program leveraging predictive analytics technology to identify patterns of disengagement that empower educators to intervene earlier and with higher impact.

The Tacoma school district now has a world-class data system for teachers to use, enabling them to see how students are performing in the classroom, including additional factors such as attendance, discipline, and behaviors that can affect achievement. The data insights and analysis helped change the conversation for educators regarding how to think about students’ progress and how to sustain success. More importantly, it resulted in dramatically higher graduation rates, reaching as high as 85 percent in 2016 – above the national average.

Current data practices fall short

Data is already at the center of teaching and learning. Districts rely on data benchmarks to track growth across students’ academic careers. When it comes to helping students who are at risk, educators do the best they can to create personalized learning plans based on the available data.

Some educators are good at gathering data, but not necessarily at using it to its full potential. Learning platforms and technologies such as Student Information Systems collect numbers and data about each student, but these systems are siloed and don’t provide a holistic picture of various components that affect student success.

In fact, a 2015 study showed that more than two-thirds of teachers do not feel that the data and the tools they rely on are effective for guiding instruction and helping students. And with student-to-teacher ratios growing and performance expectations (of students, teachers, and schools overall) increasing, pressure is mounting to do more with the information available, more quickly, to impact more students.

Rich data analysis, however, is time-consuming and labor-intensive. Given the demands of an educator’s job, it’s nearly impossible to manually analyze data for each student to discern meaningful patterns. And it must be done quickly enough to intervene in time to improve an at-risk student’s performance and set them on a new path toward lifelong success.

Providing emerging technologies to educators

Predictive analytics platforms can help. With real-time access to vast amounts of student-related information, these solutions help uncover meaningful patterns and predict future outcomes by providing the horsepower to slice, dice, and analyze data sets in a fraction of the time against manual calculations.

Other industries, particularly retail, have proven the value of predictive platforms by making shockingly accurate predictions of consumer behavior and are paving the way for the same technology to help create targeted plans to help all students succeed.

Machine learning software, such as Microsoft’s Azure Machine Learning, looks for patterns in large amounts of data. These solutions provide a 360-degree view of a student, offering custom data displays to help teachers and students identify and resolve learning gaps faster. It can even predict future behavior to alert faculty so they can intervene, before learning gaps become classroom performance issues.

As with other industries, big data and predictive analytics have enormous potential for transforming education and leveling the playing field for all students. Start exploring how predictive analytics could impact your school through Azure Machine Learning and Dynamics 365. If you are ready to schedule a discovery call and learn how this could work in your school, send an email to, or contact your local Microsoft representative.

An infographic showing six ways your student information systems could improve.