Educators across the country are seeing a greater need to collect and use data to inform decisions as they work to help students. The pandemic severely disrupted our schools, and many districts used any student data they had to identify who was struggling and how to best provide support.

As districts continue to respond to the evolving circumstances of the pandemic, making the most of all available data to improve student outcomes remains critical to understanding the factors that most contribute to students’ success.

The power of using data is immense. When used properly, it can help districts make vital decisions about setting goals and providing targeted support for students. Whether you are new to data analytics in K-12 or a seasoned veteran, here are three practical ways to apply data to help drive better student outcomes.

1. Use Data to See a Holistic Picture to Identify and Support At-Risk Students 

Educators can and should use data to gain a holistic view of each student. One data point from a single observation never tells a student’s full story. Capturing a student’s academic, behavioral, attendance, and engagement data can provide a deep, informed understanding of who the student is, where they are succeeding, and where development is needed. Dashboarding data from different areas of interest can often illuminate trends and early warning signs, lending information to identify which students might need support.

A middle school in Mississippi sought to visualize data based on their homegrown at-risk model comprised of three categories: attendance, discipline, and grades. Each category had its own risk score ranging from zero to three. Combining all three categories generated a total possible risk score ranging from zero to nine. See chart Custom At-Risk Criteria below for reference. For attendance, missing five or six days of school would yield an attendance risk of two, trending toward high risk for absences. Assuming that same student missed no additional days of school, had no disciplinary events, and all of his grades were higher than 70, their total at-risk score would remain two.

Specifying a unique and multi-tiered rubric for each risk category provided a rich amount of information and a natural way to parse and analyze data. In this instance, school administration discovered that chronic absenteeism accounted for the most risk among their student population, with 97% of students having at least one risk point attributable to absences. Disciplinary events were overall negligible, with few overall risk points coming from this category. Risk based on low performance in the classroom revealed an interesting but troubling pattern. Though few students were at risk due to having low classroom grades, most students within this group had an overall high-risk score (an average of six). Moreover, this data revealed that students who were failing one classroom subject were usually failing at least one other subject as well.

Filtering and comparing results by grade level and other demographic factors allowed educators to see if differences emerged based on students’ current circumstances (e.g., experiencing homelessness or being in an after-school program). In other words, this data informed whether some students, more than others, were more or less frequently observed as overall high risk or high risk by particular categories.

A media friend was looking into a recent Vanderbilt study on six unidentified school districts across the state. The researchers found that “more students were chronically absent this fall than in previous years, and absenteeism increased the most among English Learners, students of color, and students who are economically disadvantaged.” I told her I was not concerned about the latest findings.

When pressed on the issue, I pointed out that the sample size was a little concerning. Only 6 districts were represented; my guess is they looked at the larger urban areas. I find the research misleading. There are 147 districts in the state, each with unique and distinct issues. If we rush in and try to apply a one size fits all solution to any issue, we would be making a mistake.

By failing to identify the six individual districts, the results from the research were problematic to me—as well as to other stakeholders and policymakers as well. The study has some interesting findings. It would be useful to those 6 unidentified districts. However, I am not certain there is a crossover for other districts.

One of the most powerful tools in fighting the COVID-19 pandemic has been data. Data analytics has informed what we can do, when we can do it, and has kept us safe. As more schools reopen their doors, data is also playing a vital role in ensuring they do so safely.

The Centers for Disease Control (CDC) issued key indicators for dynamic school decision making, which include measures of underlying community transmission as well as a measure of adherence to key mitigation strategies. While these indicators provide a solid foundation for establishing and maintaining in-person plans, they aren’t always inclusive of the data that parents, teachers, and staff need to feel comfortable about returning to the classroom.

To gain buy-in from these stakeholders and help inform plans as schools reopen, schools districts must also consider four under-the-radar-data points. Let’s take a look.

1. Access to high-speed internet

The pandemic and subsequent stay-at-home orders exposed a glaring inequity in access to high-speed internet in the home. An April 2020 survey, spearheaded by the U.S. Census Bureau, found that 3.7 million households with children had internet available “sometimes, rarely, or never.” This disparity is felt most acutely in rural America where only 65 percent of Americans have access to fixed internet.

Schools worldwide face difficult choices as they try to balance student and staff safety with their educational mission during the pandemic. All-remote learning eliminates the risk of an outbreak at the school, but at-home education doesn’t provide the most productive learning environment for everyone, and it can put at-risk students at a disadvantage for a variety of reasons.

Schools and districts are making decisions about their approach by taking into account factors like virus prevalence in their area and student and family needs. An August 2020 McKinsey report notes that in the U.S., about 75 percent of the 50 largest districts started this school year on an all-remote basis. Others returned to all in-person learning, and some had to shut down again due to outbreaks.

Some districts have adopted a hybrid model where online instruction alternates with in-person teaching in classrooms that have reduced class sizes and social distance protocols in place. Hybrid education can help schools address the needs of vulnerable learners, including younger children who are difficult to engage online, as well as low-income and special education students, along with English-language learners.