Educating the Whole Child: Combining SEL, CCR, and Early Warning Data

As data-driven decision making plays an increasingly important role in education, and particularly in student analytics, it’s important to have a holistic view of every student. Rather than keeping your data in disparate systems, it’s critical to consolidate it to support a whole-child approach. Early warning and intervention (EWI), college and career readiness (CCR), and Social Emotional Learning (SEL) programs often collect and use information in silos. However, to make a real impact, this information must be brought together for a complete view of students.

ASCD has been committed to the whole child initiative for almost a decade. David Griffith, ASCD Senior Director of Public Policy, has three main recommendations for SEL program development.

1. Start with the Child, Not the Measure

“Start off by identifying what is important for your education system to accomplish over time and the outcomes you want for your students,” he says. “Then use a backwards design process to identify measures, strategies, and the necessary resources to reach your goals.”

2. Commit to Continuous Improvement

“Measures should inform everything from policy actions and partnerships, to decisions about resources and supports, rather than just using them as a mechanism for punishing low-performing schools,” Griffith says.

3. Remember that Compromise Is Inevitable

“The perfect should not be the enemy of the good when it comes to multi-metric accountability. Systems should be able to take some calculated risks and experiment with new measures that they deem important as long as they commit to ongoing analysis and refinement of their measures—and are fair minded and sensible in their interpretation of results and how those results are used to evaluate schools and inform improvement,” he added.

While often the term whole child is synonymous with SEL, it’s important to acknowledge that SEL data in a silo does not give whole-child insight into student performance analytics. Griffith’s three recommendations go beyond how Social Emotional Learning data should be used, expanding into how to apply that data to all information and insights collected about a student. For example, using early warning information such as poor attendance and behavioral incidents in conjunction with SEL competency measurements can be used to inform a more effective intervention strategy.

So how can these separate systems and processes be brought together?

Holistic insights and collaboration are two key elements that enable successful data-driven decision making. To make these elements possible, administration and educators need a single source of information. To create holistic insights, educators often create spreadsheets that collect data from several sources. However, this process is extremely manual and takes time and effort away from interpreting and acting on the insights themselves.

Additionally, collaboration can be difficult if educators are individually creating their own spreadsheets. To provide educators the tools they need to be successful data-driven decision makers, technology and infrastructure need to be invested in to empower them with the insights they need to support their students.