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Early Warning Module Targets Dropout Levels

A new Early Warning Module from BrightBytes is designed to identify students level who are in danger of dropping out and warn their teachers as early as elementary school.

The module can identify 24 indicators across four domains — academics, attendance, behavior and demographics — that are triggers. With that knowledge in hand, schools and districts can intervene early to avoid eventual dropouts with actionable recommendations also provided by the tool.

BrightBytes representatives said more than 7,000 students in the United States drop out every day and an additional 19 percent of all high school freshmen do not graduate on time.

"Ensuring that students graduate is a complex, multifaceted challenge," said BrightBytes Co-Founder and CEO Rob Mancabelli. "We must properly identify at-risk students, connect these students to remediation services and ensure that those services are completed."

Mancabelli said his company's Early Warning Module can identify students at risk of dropping out with 40 percent more accuracy than other more traditional flag-based systems.

BrightBytes Chief Technology Officer Hisham Anwar also said the module is designed to protect student data privacy and security.

"We have an opportunity to pinpoint at-risk students, and do so through a 100-percent secure, zero-knowledge online environment," Anwar said.

The Early Warning Module is built on the company's Clarity platform in conjunction with Mazin Education, which has provided the algorithms necessary to identify at-risk students.

"By understanding the historical makeup at the student, building and regional level, the module accurately identifies students as early as elementary school," said Mazin CEO Mariam Azin.

About the Author

Michael Hart is a Los Angeles-based freelance writer and the former executive editor of THE Journal.

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