The 5 biggest mistakes school districts make with student data (and how to avoid them)

In the right hands and with the right tools, student data can be immensely valuable for students and educators alike. 

But many school districts don’t use it to its fullest potential. They may have taken a few steps towards a data-driven school culture, but they’re making mistakes that are holding them back. 

Perhaps they’re focused on the wrong data, or they’ve adopted a platform without the processes and policies necessary to support it. Maybe they’re looking at the wrong metrics, using the wrong data model, or simply aren’t practicing data governance. 

Whatever the cause, they’re falling victim to some of the most common mistakes educators make with student data. Understanding those mistakes is the first step towards ensuring you don’t make them yourself. 

In this post, we’ll cover some of the biggest mistakes school districts are making with student data.

Zeroing In on the Wrong Data

Traditionally, decisions surrounding data collection and management in the education sector are made exclusively with outcomes in mind. Student and school information is collected and presented to leadership, where it’s typically used for passive metrics like attendance records, grades, and expenses. There’s little insight into why those metrics look the way they do, and how they came to be.

Data which might provide that context is either not collected or ignored. 

As the saying goes, no metric should ever be evaluated entirely in a vacuum. By examining collected student data against the backdrop of the broader institution, there’s a great deal more information that can be gained. These insights can then be leveraged to the benefit of both students and faculty.

With that said, there’s also such a thing as too much information. Just as you can’t really know the context of a particular metric if you don’t also evaluate the metrics it’s connected to, it can be difficult to make sense of a dataset that’s chock-full of redundant data points. There’s a sweet spot with both student data and how your school approaches it — one that must be informed by what you actually want that data to do.

Going in Without a Strategy

If you don’t have clear, ongoing goals for your usage of student data, it won’t matter how much information you collect. You won’t have any idea how that data should be analyzed, or what insights you should pull from it. You need to figure out your goals upfront, for both the short-term and the long-term. 

As noted by Teachers Pay Teachers, collected student data can generally be classified into one of the following three buckets. 

• Measuring Success: The data on which school districts — and truthfully, most people unfamiliar with data analytics — most frequently focused. Outcome data may include test scores, graduation numbers, remediation rates, or enrollment numbers.

• Monitoring Progress: Data such as attendance, homework completion rate, and classroom engagement allows a school to measure the progress it’s made towards a particular goal. It can also help predict outcomes, and determine whether the impact of a particular course of action is negative or positive. 

• Benchmarking Results: Also known as implementation data, this bucket is closely-related to outcomes. The difference is that outcome data is focused primarily on results, whereas implementation data is focused on determining whether or not an initiative succeeded or failed, and why. 

Data buckets aside, it’s also important to develop data models by which data can be  further organized and classified. Typically, this involves developing a high-level model that covers the major touchpoints of a student’s relationship with their school. This model can then be further subdivided into separate data models for assignments, attendance, transcripts, and so on.

In addition to modeling and success metrics, your data strategy should also establish the frequency with which students will be assessed. As you’ve likely gathered, this will likely necessitate broad changes to administrative processes, classrooms, and your overall curriculum. Otherwise, you’ll lose out on one of the most compelling benefits of digital transformation — efficiency.

Bogging Down the Flow

It’s an old story, and one not solely confined to education. An organization deploys an innovative new platform, backed by an aggressive strategy with clear, achievable goals. Then leadership ends up sabotaging the whole thing by failing to pivot and adapt. 

This inability to adjust can take many forms. 

Sometimes, it’s analog processes and policies developed well before automation became prominent. Rather than embrace something new, leadership attempts to adapt the old processes. Typically, the results of this endeavor are mixed at best. 

Other times, a district puts its entire data initiative into the hands of a few select delegates, failing to account for the fact that the insights gained by student data is valuable to everyone involved — including the students and their parents. This approach typically results in skewed insights as well, as stakeholders fail to adequately examine their inherent biases, viewing the data in terms of what it can do for them rather than what they can do with the data.

Silos. Silos Everywhere.

Failure to connect and integrate student data at every level of a school system doesn’t just interrupt the proper flow and utilization of data. It can also lead to the formation of data silos. With each user segment and department working on its own, duplication of work becomes a common issue — to say nothing of the expenses incurred by redundant processes and the time wasted as faculty members stumble through fragmented systems trying to find the information they need.

The solution here is simple. In addition to integrating your student information system with the rest of your infrastructure, you must ensure that all student data is stored in a central repository. Access to this data should be tightly controlled without diminishing the user experience.

Staying on the Surface Level

You have likely noticed a trend by now. Many of the mistakes we’ve covered are born out of erroneous assumptions and ideas about what student data is and how it can be used. In that regard, we’ve saved arguably the most common mistake for last. 

Too often, faculty and leadership look at averages rather than examining each individual student. Rather than asking what causes a particular student to perform well and why another student performs poorly, they focus on the peaks and valleys themselves. This is where the true value of student data — and of your overall student information system — becomes evident, as it can be leveraged to create personalized lesson plans and teaching strategies.

Focus on the Data That Matters with Edsembli

The right technology is only one side of the coin when it comes to embracing digital transformation. You need to understand what student data is, how it can be used, and how it’s modeled. Once you’ve figured out all that and adjusted your processes accordingly, Edsembli can help. 

With decades of experience in the education sector, we understand the needs of K-12 schools  — and our entire solutions portfolio reflects that. 

Book a demo or contact sales to learn more.