In her New York Times Bestseller The Life-Changing Magic of Tidying Up, Marie Kondo describes organizing as “the act of restoring balance among people, their possessions, and the house they live in.” Through her KonMari Method, which consists of first discarding items that fail to bring you joy and then completely organizing your space, Kondo claims that you’ll never revert to clutter again.
In addition to the normal array of messy cubicles and cluttered desktops, many schools and districts have their own unique organizational challenge: data clutter. Part of the issue is that data organization is quite possibly the least-sexy conversation topic in education reform. At its root, though, persistent data clutter is the result of a knowledge gap—the people making the decisions about data aren’t familiar with the data itself or how it’s organized. Ask yourself:
Is your student information stored across multiple databases in SQL tables built ad-hoc as the data became available?
Is there only one person at your organization who knows how your data is collected and organized?
Do you expect your teachers to parse through dozens of student data reports to inform their classroom instruction?
If your answer to any of these questions is “Yes” or “I don’t know” or “Let me ask our data person,” then you could have data clutter.
Data clutter can prevent schools and districts from fully accessing the student data that they’ve spent countless hours and dollars collecting. It can neuter their ability to connect their data to third-party vendor applications, such as learning management systems, data administration tools or online learning platforms—and vice-versa. It can also waste significant amount of teacher time that could be better spent planning for or delivering instruction. Indeed, both physical and digital clutter have a significant impact on employee productivity and quality of work. In a worst-case scenario, I’ve seen data clutter completely halt a multi-million dollar state-level education data collection project after the loss of a single employee.
Given these barriers, how can schools and districts address their issues with data clutter?
1. Create a comprehensive data strategy
When it comes to beginning any decluttering effort, Kondo is clear: “If you tidy up in one shot, rather than little by little, you can dramatically change your mindset.” Before adopting a data model or making wholesale changes to your current data collection efforts, it’s essential for an organization to determine the purpose of and approach for its efforts. By crafting a comprehensive data strategy first, schools and districts can deliberately select the data they want to collect, how they want to store it, and determine what information to share with teachers, staff, and parents. Within this framework, they can make informed decisions about how to gather data and when to implement their new approach.
When it comes to organization, Kondo has two rules: “store all items of the same type in the same place and don’t scatter storage space.” Poor data organization—such as storing data in multiple databases or in flat files or creating ad-hoc data tables—can severely limit the accessibility and usefulness of the student information. Oftentimes this is caused by a single employee needing instant access to newly available data, without concern for how the data may be used in the future. If the employee leaves, the lack of data structure or documentation may prevent the state or district from accessing certain information for months.
The simplest way to alleviate this risk is to adopt a data model to standardize how student information is organized at the school, district, or state level. This enables district and school staff and third party vendors to better access student data without requiring constant configuration or expensive development work. There are many education data models available, such as Common Education Data Standards (CEDS), Schools Interoperability Framework (SIF 3.0), and the Ed-Fi Data Standard. When selecting one, it’s important to consider the following questions:
Does this data model align with the intended outcomes of my comprehensive data strategy?
Is this data model supported by my Student Information System and other data-focused vendors, including assessment providers and vendors that provide tools to support teacher accountability, graduation tracking, and state level reporting?
Does this data model have the technical documentation necessary to handle employee turnover?
By answering these questions, a state or district can find a data model that best meets its needs without having to recreate the wheel.
3. Make your student data accessible
Teachers and administrators often have to wear multiple hats throughout a school day; why add data scientist to the list? In addition to thinking about how student data is organized on the back-end, it’s equally important to consider how it’s presented to the end user. There are many data visualization tools on the market, including Qlik and Tableau. Some states and districts may also opt to build their own custom visualization tools based on their individual needs.
No matter the approach to data visualization, it’s important that the front-end solution of any data effort is designed as thoughtfully as the back-end. As Kondo notes, “By eliminating excess visual information that doesn’t inspire joy, you can make your space much more peaceful and comfortable.” Kondo is referring to the visual layout of a home, but this sentiment is true for data systems, as well. By limiting available reports to those that are deemed necessary, states and districts can implicitly set expectations for what data elements the teachers and administrators are responsible for monitoring at any given time.
In her concluding chapter, Kondo states that “one of the magical effects of tidying up is confidence in your decision-making capacity.” The same can be true for education organizations that deliberately design and implement a comprehensive data strategy. Schools and districts can not only save significant amounts of time and money, but can also effectively utilize their student data to allocate resources, improve classroom instruction, and implement programs to help enable student success. And maybe even find some joy.
Owen Willis is a consultant at UPD Consulting, where he specializes in implementing edtech data solutions for districts and states. He has worked on several projects that involve implementing the Ed-Fi data model; UPD Consulting has an ongoing relationship with the Ed-Fi Alliance and the Michael and Susan Dell Foundation.
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