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Educators can use data sources to examine COVID learning loss and the educational divide

A data-driven look at COVID learning loss

Educators can use data sources to examine COVID learning loss and the educational divide

Students across the country have missed months of school due to COVID-19 and are entering another year that’s shaping up to be anything but normal. While the full impact has yet to be determined, the fear is that the COVID learning loss experienced during the pandemic could widen achievement gaps for those students furthest from opportunity.

While the education system strives to provide all children with fair, equitable access to high-quality education, the sudden switch to distance learning during the pandemic has turned the spotlight on persistent inequities among students.

Related content: Study shows major learning loss for grades K-2

Some schools had ongoing interaction with families from day one. Other schools had little or none at all. Some families had internet access, computers, and the ability to work from home while supporting their child’s online learning. Others did not. Some schools provided packets for distance learning. But any type of learning – virtual or with a packet of materials – left to untrained (but well-meaning) parents is less effective in supporting students who are already behind and need targeted support.

The Collaborative for Student Success estimates in its report “The COVID-19 Slide” that U.S. students will return to school in the fall of 2020 with only 70 percent of the learning gains in reading relative to a typical school year. Additionally, in mathematics, students are likely to show even smaller learning gains, returning with less than 50 percent, and in some grades, nearly a full year behind what we would observe under normal conditions. While we will not know the full implications of COVID learning loss until after the crisis ends, these early projections are alarming.

For students from families that have been hardest hit by the economic impact of the coronavirus pandemic, the loss of resources and opportunities to learn go well beyond a traditional summer break and only serve to widen the achievement gap.

New data for the new normal

When dealing with the COVID slide, it’s not enough to anticipate that students will be behind one grade level on average. It will be necessary to capture the extent of each student’s learning loss and how it manifests across different groups.

That will require integrating data that has never been analyzed together before, such as:

● School opening and closing dates
● Available and implemented online and blended learning programs, including interventions
● Student access to online programs, devices, broadband internet, and other connectivity data
● Student and parent surveys
● Formative and summative assessment data

Once collected, data can be parsed, compared, and analyzed to help make better, more informed decisions that benefit systems, schools, and individual students alike. Valuable diagnostic information about past practices and predicted success probabilities for students at various academic milestones will help leaders to make proactive, sound choices for the future.

Educators can use these data sources to explore COVID learning loss among student groups in various ways, including:

● Identifying whether specific student groups experienced more COVID learning loss than other student groups, to target interventions and relief funding.
● Identifying any differences in patterns of COVID learning loss across different grades and subjects, which could inform strategies about how to help students regain ground.
● Incorporating data based on access to online learning environments, online learning usage, hybrid learning opportunities, and data about school closures. Program evaluation results could inform resource allocation to mitigate the impact of the pandemic and support strategic decisions about what instruction might look like during future interruptions.
● Identifying successful exemplars among schools that may have implemented strategies that limited COVID learning loss or limited inequities in COVID learning loss.
● Identify whether differences between expectations and actual results align with past trends. For example, if certain student groups were more likely to fall short of expected performance from 2018-19 to 2020-21, were these same patterns present in comparisons from previous years, such as from 2016-17 to 2018-19? These results could help to separate out the potential impacts of the pandemic and could identify additional patterns in student achievement data that could inform instructional approaches and allocation of resources.

The future of education

Right now, we are not only seeing the transformation of our educational system, we are actively making the decisions that will shape the future of education for children across the country. In this new and rapidly evolving environment, it is imperative that schools, districts, and states uncover and address unbalanced educational opportunities. While data analysis itself may not guarantee equitable outcomes, using data to make proactive decisions and more strategically distribute resources can illuminate a clear path forward in the face of this pandemic.

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