In the education industry, data is king. It helps parents and family members decide where to place a student. It gives insight to teachers and school leaders about the health of their schools and opportunities for growth. It helps legislators understand the impact of policies. And most importantly, it helps us as adults, keep a pulse on the future: our children.
Although school data, like how well students perform in certain subjects, is much more available than it once was, presenting it understandably remains a challenge. Presenting school data effectively includes increasing simplification, creating clarity, and optimizing insights for the audience. For this article, we’re going to focus on the last factor: our audience and how to understand them.
The impetus for this article was the work we’ve done with our friends at Opportunity 180. Their product, School Scout Nevada, houses all public school data for the entire state of Nevada. We worked closely with them to launch School Scout in October 2024.
One Size Does Not Fit All
The mistake that many companies make in designing a platform for school data is assuming that a one-size-fits-all approach will meet everyone’s needs. I see this type of overgeneralization all the time, not necessarily with school data, but with data in general. I also see the opposite, which is overloading a data platform with features so cluttered that the interface is difficult to navigate.
The key to designing a successful school data platform lies in recognizing that your users are not a monolith group. They come to your product with different and distinct needs, questions, levels of literacy, and expertise. That’s why user experience (UX) is vital to the design process. UX isn’t just about crafting user-friendly interfaces, but about crafting experiences that cater to all the appropriate audience types.
Taking a Hands-On Approach
Audience identification should be a collaborative and in-depth process. With School Scout Nevada, we started by engaging with their internal team, identifying key stakeholders that specialized in different audience segments. These discussions were vital in identifying audiences’ unique needs and challenges. Our client also played a key role, sharing refined research they’ve been developing for years. This combination of staff expertise and collaboration allowed us to build a comprehensive understanding of the audiences.
Varying Needs of School Data Design
In the case of those audiences digesting school data, they are diverse and very distinct when compared to other industries.
They break down to:
- Parents (guardians, family members)
- Educators (teachers, administrators, school leadership)
- Policymakers (members of the legislature)
- Community Members (businesses and organizations invested in education)
Unlike industries with more uniform user goals, parents, educators, policymakers, and community members each have different objectives and levels of data literacy, ranging from granular classroom insights to county-wide trends. Additionally, education outcomes are not without some emotional weight, public accountability, and privacy considerations, which can add complexity to designing user experiences that are accessible, transparent, and actionable.
These audiences are:
Diverse and Interconnected
In education, the success of one group (e.g., students) often depends on the success of other groups (e.g., educators, parents). So unlike other industries, these audiences are not just customers, but active participants in the shared goal of educational progress.
Broad in Data Literacy
These audiences range from highly technical (policymakers and educators) to laypersons (parents and community members) in their ability to interpret school data. Policymakers and educators have experience interpreting large datasets, while parents probably do not. Additionally, policymakers and educators may use data terminology, such as “achievement gaps,” which might mean little and even alienate parents or community members.
Emotionally Invested
These audiences range from highly technical (policymakers and educators) to laypersons (parents and community members) in their ability to interpret school data. Policymakers and educators have experience interpreting large datasets, while parents probably do not. Additionally, policymakers and educators may use data terminology, such as “achievement gaps,” which might mean little and even alienate parents or community members.
