Data-driven decision-making is increasingly recognized as a critical component of K-12 education, including enhancing personalized learning, improving assessment and feedback, optimizing resource allocation, and facilitating early intervention. These decisions are informed by analysis of various types of data, including academic performance, non-academic factors, program and systems data, and cognitive data. This analysis helps educators make informed choices that directly impact student learning and school effectiveness.
Despite the benefits, implementing data-driven decision-making in education is not without its challenges. School leaders and teachers may need more time, tools, expertise, and professional development to effectively collect, analyze, and interpret data. Additionally, there are the following differences: rich in data and data driven. Collecting data is essential, but it can increase pressure on educators who may already have responsibilities. A high-quality data management system that automates the collection and analysis process is key for institutions looking to transition to a data-driven model.
EdSurge recently spoke with: Becky MathesonDeputy Director of Innovation, Teaching and Learning. winnetka public schools, Illinois spoke about how school districts are supporting educators in effective and efficient data analysis and use. She has over 10 years of experience in district-level management positions with a focus on curriculum, instruction, and assessment, and has extensive expertise in building and refining data-based decision-making systems. Prior to her administrative role, Matheson was a middle school science teacher leading grade level teams and the science department. During this time, her interest in the relationship between student learning outcomes and data-based insights first emerged, guiding her approach to understanding student progress and informing future teaching strategies.
EdSurge: Why is data-based decision-making important at the classroom and district level in K-12 education?
Matheson: Data helps inform many instructional strategies, and this is especially important in a time when schools are being asked to do more and more. A balance between quantitative and qualitative data is important. When it comes to quantitative data, having a standard is invaluable. This allows you to compare student growth over time and track student achievement against benchmarks. That’s one way to find out where to shine your light.
Another approach involves analyzing student work samples and teacher feedback to get a more comprehensive picture of student needs. Previously, as a teacher, my main focus was on delivering content. However, today there is increasing recognition of the importance of dedicating more time to social-emotional learning and physical activity during the school day, and giving students more autonomy in their learning. Qualitative data is equally influential in this regard.
From a system or district perspective, it is very important to ensure consistency between grades and grade levels. Agreed datasets (universal screeners, common formative assessments with rubrics, projects students are working on, etc.) give us a way to tune the whole system so we can tweak the curriculum and where. You can figure out what you need to do. Do different things with staffing depending on student needs.
How do the dynamics of quantitative and qualitative data enhance the efficiency and effectiveness of educational decision-making processes?
The ready availability of quantitative data improves the efficiency with which professional learning communities (PLCs) come together. Being able to quickly group students by data can save a lot of time, allowing educators around the table to use their wits to analyze the meaning of the data, determine discrepancies, and identify when more information is needed. , we can discuss students who might benefit. Even from student services and grade level acceleration.
Qualitative data becomes useful once high-level programmatic matching occurs. A PLC allows teachers to view those student groups from a whole-child perspective. They are able to review samples of student work and identify areas of strengths and skills that need improvement, which helps us determine the appropriate support needed for each student.
How do you support teachers and staff to effectively collect, analyze, and use student data to inform instructional practices?
We foster a positive data culture and develop data literacy across the district. As a school district administrator, I view data as a starting point for asking questions to better understand what is and isn’t working, and ultimately towards an optimal student experience. I tell the teachers what I’m working on.
Increasing data literacy means talking not only about why you’re using data, but also how to use screening tools and what exactly the data means. We approach this with a combination of professional development and ongoing work-embedded support. The professional development part of it is messaging. This is why we’re moving in this direction as a district, these are the different tools and supports that we provide, and this is the value of data. Additionally, we have a team of coaches partnered with building administrators to help teachers use the tools, collect data, and understand what it means in their context.
Our district uses two data tools. One to analyze the data locally and the other to make the data readily available to teachers. Teachers often have to search multiple platforms to collect student data. They might use three different platforms for universal screening, one for attendance, and one to look at incident reports. Otus allows teachers to consolidate that data by going to the reports section of their student profile. Access all your information in one place. Currently, systems mainly store quantitative data. However, we are adding more qualitative data through various document uploads. For example, we are finishing up a review of our Stage 1 literacy curriculum. We plan to upload the results of the common formative assessments into the system and, in some cases, the actual assessments as well.
I also want to touch on the importance of community education around data literacy so that parents understand that when they receive assessment information, it is a snapshot in time. We aim to partner with families in our approach to data literacy. One of our goals this year was to increase parent communication about student learning. We sent all the evaluation reports home. This was valuable because it helped parents understand the different assessments, but each report looks different and uses different reporting methods, requiring another level of data literacy.
Next year I plan to use Otus with parents. Log in to one place for easy access to your test results. Different results in the data have different meanings. [test result] Visually represent data in a similar way.
What measures are you taking to continually monitor and evaluate the effectiveness of your data-driven practices?
There is a step-by-step process that starts at the school district level and ends at the classroom level. Three times a year, after he collects universal screening data, the first step is to meet with district administrators and building managers, where they review the system’s data. Some of the things I include in that meeting are the different activities and focus areas that the principal wants to work on in the building. Then, the following week, a building leadership team meeting, which includes principals and teacher leaders in the building, is held to review the data and determine areas of focus based on the school improvement plan. Finally, teams from each grade level meet to review the data. These team meetings involve not only the classroom teacher, but also the interventionist, special education teacher, and sometimes allied arts teacher. The district is fortunate to have this program in place three times a year. However, our immediate goal is to have more of these conversations.
Data-driven decision-making is similar to other evidence-based practices in schools, such as implementing a guaranteed and actionable curriculum and using assessment of the learning process. Data tells us how best to meet student needs and work toward maximum student outcomes. Actual analysis of data allows district and school leaders to support teachers, who in turn can support each student.
