The Use of Data to Improve Outcomes and Equitability

The Use of Data to Improve Outcomes and Equitability

Oct 19, 2021, 3:32:20 PM Tech and Science

After-school programs have been an essential part of education since they were first created. They have not only helped to improve education outcomes, but they have also helped improve access to education for minorities. Yet, a lot of this judgment was based on crude metrics and anecdotal observations. As Youth Today reports, recently, after-school programs have been using data to measure outcomes and equity. Unfortunately, although many positives were discovered, holes in the services provided by after-school programs were also found.


One discovery was that graduates of middle school programs often did not have sufficient options in high school. So, many of these graduates were underserved or unserved as they advanced to high school. Such a discovery is a good thing because it has allowed many afterschool programs to up their game and meet the needs of those high school students. 


We are living in an increasingly data-driven world, and decision-making has benefited. After-school programs have helped. Decision-makers in after-school programs have been able to use data to evaluate their offerings better, and determine how they can better meet the needs of the youth. Improvements rely on measurement. As Bill Gates has been fond of saying, you have to “measure what matters”. By regularly measuring outcomes, equitable access to after-school programs becomes more attainable.


There are critics of what has been called “the cult of measurement,” which argues that the focus on numbers and measurement of outcomes has inadvertently taken away focus from the stuff that matters, which has exacerbated outcomes. Data is not, as we are often led to believe, objective. There’s a saying in computer programming, “garbage in, garbage out.” In other words, the data that goes into a model defines the output of that model. If, for instance, a modeler uses biased data, then the outcome will lead to biased results. In addition, assumptions by the modelers can lead to flawed definitions of what constitutes success or failure. For instance, success is often defined as an ability to do well on a test, even though a more holistic view would suggest that passing an examination is not the ultimate goal of education.


In addition, even if we assume that a data-driven decision-making framework is perfect, many communities lack the training or resources to implement it. The Youth Today article promotes a data-driven approach without effectively addressing the potential flaws of such a model. As is often said, a man with a hammer in his hand only sees nails. A data-driven approach must be aligned with other tools to ensure that outcomes are genuinely improved and equitable access to education is achieved.


There are certainly merits to using data. Often, our subjective judgment is riddled with biases, and we often do not have the computing power to find meaningful insights. We need data to guide us where our experience cannot. The data use framework drafted by the Every Hour Counts coalition of advocates for after school programs and activities is indeed a helpful tool. Together with other tools, we should use data to ensure improved outcomes and equitability are achieved. 



Published by Jacob Maslow

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