What Schools Can Learn from Their Data Analysis Tools

School districts are increasingly turning to artificial intelligence (AI) tools to help them make sense of the vast amounts of data they collect on students. However, before schools can start leveraging these AI-powered insights, they need to establish a robust data governance policy. This is particularly important in K-12 education, where federal and state regulations require districts to protect personal information and online activity.

According to Microsoft’s Jubelirer, a strong data governance policy begins with purpose. It involves identifying the exact problem that needs solving and then following standard best practices for collecting, storing, and using student data. This includes limiting access to authorized staff only, using aggregated or de-identified data wherever possible, maintaining strong security controls, and being transparent with families about how their child’s data is used.

In Weehawken Township School District in New Jersey, superintendent Eric Crespo has implemented a comprehensive data governance policy that governs the entire lifecycle of student records. The district worked closely with a law firm to develop this policy, which was then approved by multiple levels of stakeholders. This includes students and their parents, who must fill out an authorization form before accessing the district’s network for the first time.

The policy also emphasizes transparency, privacy, security, human oversight, and accountability. As Crespo notes, it serves as a ‘rulebook’ that outlines who gets to see student data, how it is stored, and which vendors are allowed to interact with it. He likens this approach to giving approved vendors a ‘key to exactly one room in the house,’ rather than granting them unfettered access.

When it comes to leveraging AI tools for business, human expertise remains essential for interpreting results and making informed decisions. Jubelirer stresses that technology should help educators evaluate information more effectively while keeping people at the center of every decision. This is particularly important when reviewing insights from large data sets, as each school has its own unique culture and context.

Crespo echoes this sentiment, noting that human judgement is crucial for avoiding bias in AI-powered analysis. He warns against relying too heavily on single data points, saying ‘the first line of defense is refusing to let any single data point make a decision on its own.’ By striking the right balance between technology and human oversight, schools can unlock the full potential of their data analysis tools.