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Education Data Quality and Completeness

By Kevin Shane / January 10, 2017

With the recent push toward heavily relying on education data, it’s extremely easy for schools to just get caught up in the whirlwind without slowing down to map out their options. It’s extremely easy for schools to fall into a few different traps. Some schools have a wealth of data and no plan to use it. Schools need a data map; there needs to be a plan in place from day one. Other schools have goals that could be supported by data, but they aren’t collecting the relevant data. These scenarios cause problems when making that initial push toward fully utilizing data. Data needs a use, availablity, completeness, and alignment with goals.

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When laying out an improvement plan and data goals for the first time, there are a few steps schools can use to make the process easier:

  • Start small. Schools shouldn’t begin by trying to use every piece of data they have. There are thousands of data points that most schools have access to, but that doesn’t mean that all of them have to be used right away.

  • Start with something you know needs to be improved. Attendance? Behavior? Test scores? Pick one thing that can be improved and start with that.

  • Start with something that can snowball into using other data. For example, once you’re beginning to understand how to use your attendance data, you can add in student socioeconomic data to see if/how they are related.

These are all things that can be completed when schools make sure that their data is high quality and complete. Data quality and data completeness are two issues that many schools face when utilizing their data for the first time.

Data quality can refer to many different aspects of data. Here, however, I’m going to use the general definition that data quality refers to how well the data matches its intended purpose. When evaluating data quality for schools, there are two ways to approach the problem. Schools can look at the data they already collect and see how it can be used to solve a problem, or schools can look at a problem and evaluate what data they need to collect in order to gain insight into how to solve that problem. Both approaches can be effective and both can help improve schools. Schools will almost always collect a core set of data, e.g. attendance, grades, and behavior, so this data can be used fairly easily and relates to many problem schools may face. In several cases, this data can be used to support goals the school has, but school leaders should always be aware of whether or not the data they are using can be improved in any way or if they can collect additional data to support goals.

Data completeness goes hand-in-hand with data quality, and it refers to whether or not all of the necessary data is collected and available in whatever data resource schools use. For example, if attendance is a priority, do schools have access to data showing who is present, absent, tardy, suspended, excused, unexcused, etc. on a daily basis? Is this data available to be broken down daily/weekly/monthly? If a school decides to focus on test scores, are all of the relevant scores available? Is historical data available or only the most recent tests? How long does it take to get the scores? If data isn’t updated in a timely manner, it ends up not being useful because the data isn’t complete when teachers could use it.

When making the commitment to put education data into your school plans, data quality and data completeness need to be considered. Don’t rush forward with incomplete, non-relevant data that doesn’t fit your goals. This is a waste of time for everyone involved. If you need help evaluating your data, just ask! Complete our quick survey to get a team member to reach out to you.

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Topics: EdTech, Data, Metrics, Analysis, Data Analysis, Education Data, School Data

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