The Student Success module not only identifies at-risk students as early as first grade in their academic career, but it also provides educators with the necessary tools to impact student trajectories in their postsecondary career as well.
SAN FRANCISCO (PRWEB) February 15, 2018
BrightBytes®, the leading end-to-end data management solution for education organizations, today, announced the rollout of the Student Success module, an expanded offering of their award-winning Early Warning module.
The BrightBytes predictive analytics solution (formerly known as the Early Warning module), which uses historical data and predictive analytics to individualize graduation risk analysis for students as early as first grade, will now provide insight into students’ readiness along the entire K-20 continuum in a new offering, the Student Success module. Developed in partnership with American Institutes for Research, one of the nation's largest behavioral and social science research and evaluation organizations, this robust solution will utilize two predictive models: one which identifies students at risk of not graduating from high school, and one that predicts students at risk of being unprepared for the challenges of postsecondary education.
The BrightBytes Early Warning module has already helped educators across the country improve graduation rates. After a 2014 statewide adoption, West Virginia reached a national high of 90% graduation rates. This improvement of nearly 5% is largely due to BrightBytes’ research-based predictive analytics module.
Traci Burgess, CEO of BrightBytes, explains, “Each student’s education journey begins before Kindergarten, and continues beyond graduation. The Student Success module not only identifies at-risk students as early as first grade in their academic career, but it also provides educators with the necessary tools to impact student trajectories in their postsecondary career as well. By preparing students to achieve after graduation, educators are developing a generation of individuals able to participate in a global economy and achieve greater equity in attainment gaps between socio-economic groups.”
AIR conducts and applies the best behavioral and social science research and evaluation towards improving people's lives, with a special emphasis on the disadvantaged. As the Student Success module was built, AIR provided valuable technical guidance in indicator definitions for the module’s expanded framework, and the team has worked closely to review the predictive models developed by analysts and researchers at BrightBytes. This partnership is instrumental to support BrightBytes’ mission to use research-based analysis to turn big data into big benefits for students.
“In order to help all students be college and career ready, educators and administrators need accurate, timely information that they can use to guide their decision making and instruction," said Susan Therriault, Managing Researcher at AIR. "We are excited about this partnership, which will allow us to scale the work we have done to help educators across the country prepare students for postsecondary success.”
About BrightBytes: BrightBytes, the leading end-to-end data management solution for education organizations, provides educators with the power to turn big data into big benefits for students. With the data integration platform, DataSense™, BrightBytes enables educators to cleanse, integrate, and bi-directionally manage complex data from multiple systems. The decision support platform, Clarity®, then analyzes and organizes meaningful data across research-based frameworks to deliver visualized, actionable information that drives student learning.
About AIR: Established in 1946, American Institutes for Research (AIR) is an independent, nonpartisan, not-for-profit organization that conducts behavioral and social science research on important social issues and delivers technical assistance, both domestically and internationally, in the areas of education, health, and workforce productivity.
Ken Goldstein 303-548-2136 ken(at)brightbytes(dot)net