Making a Digital Difference in the Classroom With Data

Education in this country is changing rapidly, and not without controversy. Whether it's how often to test students, how early in the day school should start, or what curriculum and teaching methods are best, questions and concerns abound.

As always, the community of educators, parents, advocates and policymakers must make decisions about what to keep, what to expand, how to avoid programs or tools that lack value. Objective research results are a critical factor in making these decisions.

Until recently, these groups didn't always have information available to evaluate the many different ways to teach students and measure learning. But from K-12 through higher-ed, more tools and platforms are now churning out more highly detailed data than ever.

Because of this new data, research is a more valuable and desirable tool than ever. While personal information on individual students must be appropriately protected, much of this type of research does not require that level of detail. Aggregated or anonymized information provides a wealth of opportunity to gain insights into what works, what doesn't, and identify patterns of insights into educational outcomes. An important and timely Congressional hearing that took place on Capitol Hill last week addressed this very issue, as lawmakers pay more and more policy attention to student data and its responsible use.

For example, critics have long challenged the policies that focus on out-of-school suspensions as a disciplinary tool. An understanding had developed in recent years that suspending students was being applied inequitably, and did not actually improve student performance or retention. However, until recently, it was difficult to support these claims empirically - partly because of datasets that were limited to individual schools or districts, where the samples were too small, or too isolated from broader trends. But in 2014, the Center for Civil Rights Remedies was able to finally examine how suspension affects students' behavior and observe trajectories by combining longitudinal and administrative data. Information from across the country demonstrated high school suspensions did not improve school outcomes or deter future misbehavior.

In fact, students suspended from school are less likely than their non-suspended peers to obtain a high school diploma or obtain a bachelors degree, and are more likely to be arrested, become multiple offenders, and be sentenced to confinement in a correctional facility. These findings are now being used for a nationwide reevaluation of "zero tolerance" school discipline policies.

Even within a school district, data shows how they might reconsider their evaluation and selection processes to prevent unintentional bias. The Wake County (NC) Public School System wanted to increase low rates of enrollment in advanced math classes among female, black, Hispanic and low-income students. The district decided to use masked performance data, rather than teacher recommendations, to determine student eligibility. Including students' middle school grades and performance on standardized tests, they created a model predicting who would succeed in advanced math - and found that it identified many students who had not been previously been considered promising candidates. By promoting pupils based on this data, the district substantially improved overall rates of math acceleration among black, Hispanic, and low-income students, and raised female math acceleration to reflect their proportional enrollment in the district - all without impacting the successful completion rates.

These are just a couple examples of the many ways to demonstrate in concrete terms how new technology, data and analytical techniques can create better academic and performance outcomes for students. Moreover, it can empower students to be in more control of their academic destiny, and also allows them to turn data they generate into an accountability tool with the very system that educates them for anywhere from 12 to 16 to 20 years of their lives.

To illustrate the full scope of the value or research, and inform the public discussion on the best use of student data, the Future of Privacy Forum published a report, "19 Times Data Analysis Empowered Students and Schools", to demonstrate - through real life case studies and scenarios, including the examples above - how student data has been used smartly and responsibly to make a positive, impactful difference in student learning outcomes from kindergarten through college.

The study identifies 19 cases where data was successfully used to evaluate an education program, create a new learning or management strategy, or delve into equity and bias issues in the academic environment.

By highlighting actual data use and application in the education system from K-12 through post-secondary institutions, the study illustrates how students, educators, researchers and advocates are properly applying data analysis to encourage student success and retention, facilitate more effective instruction, advising and operation, and address bias and inequality issues.

To be useful and impactful, data about education processes and student often requires sharing information between schools, states, and organizations. In cases where this includes personal or sensitive information, privacy and security considerations are a foundational "must do." Every responsible researcher knows that the datasets they use must be collected, managed, stored, shared and deleted with sufficient privacy protections in place.

But, when properly used and implemented, it's clear from the report's findings that data in education has the potential to close multiple gaps in the classroom and schools and be a powerful tool in fulfilling the great promise of high quality education for every student in America.