Predictive analytics can help improve students' academic prospects.

Predictive analytics are key to keeping our kids in school

If data-driven decisions and predictive analytics can help students succeed in school, why aren't we leveraging data all the time?

High school graduation rates have reached record highs in recent years. Yet, one matter remains clear: there’s still a lot of work to be done. More than 1.2 million students drop out each year and the graduation-rate gap between low-income students and non-low-income students reaches double digits in nearly every state. We face an unfortunate reality where students of color, with disabilities, and in lower socioeconomic brackets have fewer resources and opportunities.

How can teachers, parents, and nonprofit organizations in the education sector work together to close the graduation gap? And how do we create more opportunities for all of our youth? The answer: data, technology, and compassion.

Related content: Can analytics help schools hire the best teachers?

The power of data-driven predictions

Traditionally, the education sector and student-focused nonprofits providing services like afterschool and mentoring programs, have relied on test scores and assessments to gauge student progress. However, these two factors alone can’t reliably show what else might contribute to a student’s academic success. Teachers are responsible for anywhere between 21 and 27 students per class and demand for after-school programs, particularly in low-income areas, has been rising since 2004.

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