Predictive analytics is exploding and disrupting postsecondary education. With the success it’s had there, experts say predictive analytical tools show even more promise for K-12 schools. School districts are collaborating with universities to create new models and tools to evaluate and improve student performance. Predictive analytics is enhancing education everywhere.
What is Predictive Analytics?
Quite simply, predictive analytics is used to make predictions about future events. It uses several techniques such as statistics, modeling, machine learning, data mining, and artificial intelligence to analyze current data and make future predictions. Historical and transactional data hold patterns that can be found and used to identify future opportunities and risks. By applying predictive analytics to schools, educational institutions can interpret big data to benefit students.
When predictive analytics are used, schools have the data at hand to become significantly more proactive when it comes to the success of students. Instead of relying on annual reports, they can look forward, anticipating outcomes and behaviours based upon data. These patterns can help schools make better decisions.
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Predicting Graduation with Predictive Analytics
It is the goal of every school to educate their students and hand them a diploma when their high school journey is completed, but, unfortunately, not every student will walk across that stage. If schools use predictive analytics, they can help students stay on track to graduate by evaluating indicators starting in elementary. If these indicators are showing negative results, the school can intervene and help get the student back on track.
Statistical analysis uses a combination of actionable indicators to predict an outcome that needs improvement or school attention. These indicators can include course grades, extracurricular involvement, suspensions, attendance, and course level. Less obvious data can also be used like classroom observations and non-cognitive components. Each student can be evaluated by these indicators and can then be grouped into categories needing no intervention, medium intervention, or high intervention to succeed.
Real World Use of Predictive Analytics
Several schools districts in the States are making the jump into predictive analytics to assist their students; the Hamilton County school division is one of them. This district evaluated test scores, attendance, student demographics, and other information to predict the likelihood of graduation. From these indicators, the district identified changing issues that contribute to the risk of students dropping out in different grades.
Since the Hamilton County school division started using predictive analytical tools, they have seen great results. In the four years since the tools were first used, the graduation rate within the school district has steadily increased. In the first year of implementation, the graduation rate was 70.9%. In the fourth year, it rose to 80.2%. The student dropout rate also fell during the four year period from 6.4% to 1.8%. The Hamilton County school division’s use of predictive analytics significantly influenced student success and helped more high school students reach that graduation milestone.
Predictive analytics may seem like a big, unattainable idea, but it really isn’t. This method of predicting outcomes can be used for school divisions to better monitor students and help them if necessary. If schools are looking for ways to increase student performance, raise their graduation rate, and lower their dropout rate, employing predictive analytics is a viable option.
