Data-driven decisions are increasingly recognized as a critical component of K-12 education, enhancing personalized learning, improving assessment and feedback, optimizing resource allocation, and encouraging early intervention. These decisions are based on analysis of various types of data, such as academic achievement, non-academic factors, program and systems data, and perception data. In turn, this analysis helps educators make informed decisions that directly affect student learning and school effectiveness.
Despite the benefits, implementing data-driven decision making in education presents challenges. School leaders and teachers may need more time, tools, experience, and professional development to effectively collect, analyze, and interpret data. Furthermore, there is a distinction between being rich in data and data driven. Data collection is essential, but it can increase pressure on educators who may already be overburdened with responsibilities. High-quality data management systems that automate collection and analysis processes are key for institutions looking to shift toward a data-driven model.
Recently, EdSurge spoke with Becky MatisonDeputy Superintendent of Innovation, Teaching and Learning at Winnetka Public Schools, Illinois, about how their district supports educators in effective and efficient data analysis and use. With over 10 years of experience in district-level administrative roles focused on curriculum, instruction, and assessment, he has extensive experience building and refining database decision-making systems. Prior to her administrative duties, Mathison was a high school science teacher and led grade level teams and the science department. During this time, her interest in the relationship between student learning outcomes and data-driven insights first emerged, guiding her approach to understanding student progress and informing future educational strategies.
EdSurge: Why is data-driven decision making important in K-12 education at the classroom and district level?
Mathison: Data can help inform many instructional strategies, which is especially important in the current era when more and more are asked of schools. The balance between quantitative and qualitative data is essential. In terms of quantitative data, having something normalized is invaluable. It allows you to compare a student's growth over time and also observe her achievement against benchmarks. That's one way to figure out where to focus our light.
Another approach involves analyzing samples of student work and teacher feedback, offering a more holistic view of student needs. Previously, as a teacher, the main focus was delivering content. However, today there is a growing awareness of the importance of dedicating more time during the school day to social-emotional learning and physical activity and of providing students with more autonomy in their learning. The qualitative data remains equally impressive in this regard.
From a system or district perspective, ensuring consistency across grade levels is really important. Agreed upon data sets (whether universal assessments, common formative assessments with a rubric, or projects that students are working on) give us a way to calibrate across the system so we can determine where we might need to make adjustments to the assessment plan. studies or do things differently with staffing because of student needs.
How do the dynamics of quantitative and qualitative data improve the efficiency and effectiveness of educational decision-making processes?
Having readily available quantitative data increases the efficiency of joining professional learning communities (PLCs). If you can quickly group students by data, that can save a lot of time so educators around the table can use their brainpower to analyze what the data means, determine inconsistencies, identify when more information is needed, and discuss students. who could benefit. from student services or even grade level acceleration.
Once that high-level programmatic match is made, qualitative data comes into play. In the PLC, teachers can look at those groups of students from a whole-child perspective. They can review samples of student work and identify areas of strength or skills that need improvement, which helps us determine the appropriate support each student needs.
How do you support teachers and staff to effectively collect, analyze, and use student data to inform their instructional practices?
We foster a positive data culture and develop data literacy across the district. As a district administrator, I let teachers know that I view data as a starting point to ask questions to better understand what is working and what is not, and ultimately work toward an optimal student experience.
Developing data literacy means talking not only about why we use data, but also how to use discovery tools and what exactly the data means. We address this with a combination of professional development and ongoing support embedded in the job. The professional development part is the messaging – this is why as a district we are heading in this direction, these are the different tools and supports that we will provide them and this is the value of data. Then, we have a team of coaches partnered with building administrators to help teachers use the tools, collect data, and understand what they mean in their context.
Our district uses two data tools: one to analyze data locally and the other to make data available to teachers. Too often, teachers have to search across multiple platforms to collect student data. They could use three different platforms for universal control, another for assistance and another for incident reports. oto has allowed us to merge that data so that a teacher can go to the reporting section of a student's profile and access all that information in one place. Currently, we have mainly quantitative data in the system. However, we are adding more qualitative data with different document uploads. For example, we are concluding a review of the level one literacy curriculum. We have plans to upload the results of common formative assessments into the system and possibly even upload the actual assessments.
I also want to mention the importance of community education about data literacy so that parents understand that when they receive assessment information, it is a snapshot in time. Our goal is to partner with families in our data literacy approach. One of our goals this year was to increase communication with parents about student learning. We send home all our evaluation reports. It was valuable because it helped parents understand different assessments, but each report looked different and used different reporting methods, requiring another level of knowledge of the data.
Next year we plan to use Otus With parents. They will be able to log in to one place and access their test results more easily. The different data results will break down the meaning of each (test result) while visually representing the data in a similar way.
What steps do you take to continually monitor and evaluate the effectiveness of data-driven practices?
We have a tiered process, starting at the district level and going to the classroom level. Three times a year, after collecting universal screening data, our first step is to meet with district and building administrators, where we analyze the system data. Part of what I include in that meeting are different activities or focus areas that principals may want to address in their buildings. Then the following week, there is a building leadership team meeting, which includes the principal and building teacher leaders, where they review the data and determine areas of focus given their school improvement plan. Finally, each of the grade level teams meets to review the data. At these team meetings, there will not only be classroom teachers, but also interventionists, special education teachers, and sometimes related arts teachers. We are fortunate as a district to have this system three times a year. The goal, however, is to have more such conversations in the meantime.
Data-driven decision making is similar to other evidence-based practices in schools, such as having a viable and guaranteed curriculum or using assessment for learning processes. Data informs us how best to respond to student needs and work to achieve the best outcomes for students. Really analyzing the data helps our district and school leaders support our teachers so they, in turn, can support every student.
