19 Times Data Analysis Empowered Students and Schools: Which Students Succeed and Why?

Abstract

Thoughtful use of education data has tremendous potential to improve and address inequities in America’s education system. Scientists better understand how the brain incorporates new information and skills. Educators have a more accurate sense of student progress and potential risk for dropping out. Students and teachers use more detailed information about their strengths, weaknesses, and individual academic performance to diagnose and address learning gaps. Schools can correlate patterns with failing or dropping out, and intervene early with at-risk students. Districts and schools can use data to allocate resources and create institutional reform to better meet student needs in a world where students take increasingly personalized or non-traditional paths to graduation. Today, companies use new technologies and analytical approaches to provide more personalized services to customers; municipalities streamline allocation of city resources; and doctors can make more precise diagnoses. Until recently, educators did not have much information available to generate new insights about the learning process, student success, or optimal institutional management. However, education — both K-12 and higher ed — is now catching up as newly created digital learning tools and platforms generate an abundance of highly detailed data that can help parents, teachers, administrators — and ultimately students — make more informed choices. With this data, we can finally observe patterns during instruction, across classrooms, between schools, and over time to create a more complete understanding of which students succeed and why. The ability to compare administrative, academic, demographic, and social information from various sources at last provides a means to examine the full multiplicity of factors that contribute to student success. Examining student trajectories over time shows how well students are prepared for the next steps in the learning process. They can identify ways to facilitate application and transition between school levels and into the workforce. To provide useful insights, research about long term education and career success often requires sharing information — sometimes including sensitive data — across schools, between states, and over time. The student data used in this research must be collected, used, and deleted with sufficient privacy protections. Appropriate policies, well-tailored laws, best practices, and genuine enforcement mechanism minimize the privacy risks, and ensure the best outcomes for students. This report highlights the ways that newly available technology, data, and analytical techniques can create better educational outcomes. It presents concrete examples from Pre-K through higher education of how education data can be used to benefit students, the education system, and society-at-large. The cases here illustrate how students, educators, researchers, and advocates apply data analysis to encourage student success and retention, facilitate more efective instruction, advising, and administration, and ameliorate inequalities. Data-driven education has the potential help bridge the achievement, retention, and discipline gaps so that all students can enjoy a high quality education and achieve career success.