Advancing Data-Informed Student Support in K-12 Education

Sarah Singer brings more than 10 years of education experience to her role at PowerSchool. She now helps K-12 education agencies create strategic plans for building a data-driven environment.  

Sarah entered Portland Public Schools in 2007 as a Broad Resident in Urban Education, a national and highly selective two-year management development program that recruits and trains emerging leaders for senior management positions in public education. She went on to serve as the Senior Advisor to the Chief Academic Officer. Later, she oversaw the Research, Evaluation, Assessment, Administration, and Analytics Departments in the district.  

Data-informed practice is first and foremost a mindset. What follows is a journey guided by self-reflection and the drive to improve. These practices are about inquiry. Educators ask one question, leading to a multitude of others, all in the name of learning about student needs and strengths to support their overarching success.  

As educators, we don’t often categorize the kinds of questions we ask. But the types of questions we ask are critical. If educators disproportionately only ask certain kinds of questions, and not others, this may be an indicator that your organization’s data culture and systems need further nurturing.  

Considering asking these three types of questions system-wide:  

What has happened with this student? Why?  

These analyses help uncover the root cause of why a student may be struggling. In understanding the cause, educators need access to holistic data. PowerSchool Student Analytics allows educators to review data including academic, behavioral, social and emotional, attendance, and more in one place. They can do so in the moment to support the inquiry-driven process discussed above.  

What will happen to this student if we don’t intervene?  

Machine learning or other methodologies can help educators identify students at risk before it’s too late. For example, the PowerSchool Risk Analysis K-12 early warning system identifies students at risk for graduation using an algorithm based on district historical data and factors that matter most in your system.  

What is the right course of action to take with this student?  

This is where data becomes actionable, ideally through preventative and proactive frameworks like Multi-Tiered Systems of Support (MTSS). PowerSchool’s MTSS solution allows educators to identify and track student needs with an extensive range of inputs, implement and monitor interventions, and review the efficacy of their MTSS framework for continuous improvement.     

In working with school districts over the years, including my own, I’ve seen several patterns emerge. Sometimes districts jump into action without understanding the root cause, undervaluing descriptive analysis. Sometimes districts languish in the descriptive analysis phases, and as a result “analysis paralysis” plays out rampantly within the district’s culture. Regardless, it’s important to reflect. Ask if your district is embarking on all three types of analyses. Is there a healthy amount of descriptive analysis coupled with actionable analysis? Is your District even using predictive analysis? Lastly, do you have the right data systems to support educators with all three types of analyses?  

Asking these important questions can help you gauge where your organization is along its data-culture journey. It’s a great place to start when looking for ways to better support students, and to see if your district is making the most of the technology tools you already have.  

Advancing data-informed student support in K-12 education starts with ensuring that educators are equipped to ask the right questions and interpret the answers in a way that meaningfully impacts student success. Whether it’s through descriptive, predictive, or prescriptive analyses, the goal remains the same: to understand and support each student’s unique journey.