Are you using data-driven analytics as part of your continuous improvement efforts? Let’s explore key strategies and learn how using data-informed analytics is an empowering process to assist low-performing schools which are strategies that can work for any school district.
How do school leaders affect student achievement? Whether you are identified as a Low-Performing School or are a Blue-Ribbon District, you do it by developing and supporting effective teacher practices. It is also by implementing organizational management strategies focused on teaching for learning for all students. Administrators who have skills in curriculum and instructional leadership are better prepared to lead a building and/or district through school improvement efforts, including Low-Performing Schools.
Administrators need to have expert knowledge in curriculum processes and instructional strategies (‘talk the walk’) and have effective interpersonal skills and shared leadership strategies focused on building organizational capacity (‘walk the talk’) to improve student and staff outcomes.
Changes resulting in higher student achievement occurs because there is Structural Leadership which is using organizational design to promote maximum efficiencies and success. You also use Human Resource Leadership because as a principal or district leader, you foster the skills, attitudes, energy, and commitment to the shared vision, mission, and goals that have been set. Lastly, you use Data-Informed Leadership which emphasizes systemic data-use at three levels: at the school level, at the classroom level, and at the student level. Let’s explore more.
Using Data-Informed Analytics for Root-Cause Analysis
When overall performance falters at a school district, there can be so many reasons why. To avoid knee-jerk assumptions and pinpoint underlying root causes, administrators must rely on quality data and a sound data analytic strategy to correctly identify underperforming groups and/or subjects. We suggest the following steps within our Prism product:
1. Define your area(s) of inquiry. As an example, let’s begin with a benchmark assessment such as NWEA/MAP for both ELA and Math.
2. Narrow your focus using Eidex’s Analyzing Data and Data Chart Template. Because we want to dig deeper, we used our planning chart to focus our data analysis exploration into the Eidex Prism product. Here, we are going to use three different measures to triangulate our data. First, we are going to use the Measure of Met Proficiency by Subjects (ELA and Math). We notice that Math has a lower trend trajectory. We keep the Measure of Met Proficiency and now filter by buildings. Here we notice that some buildings made outstanding improvements while others have regressed.
3. Isolate the Problem Area. We determined Math requires an intervention. But at what grades? So, we continue to use the Met Proficiency measure and now filter by Grades.
We notice that grades 6-8 have significant regression. Yet, we want to isolate further, so we switch our measure to Achievement Quintile by our Target Grades of 6-8. Here we can see the percentage of students who fall into the Low and Low average quintile.
For our third measure, we now move on to Performance Indicator by Goal for these Target Grades. Based on what we are noticing, we determine that Real and Complex Numbers as well as Operations and Algebraic Thinking need curricular and instructional interventions. Are we there yet? No, let’s dig a bit deeper.
4. Student Level Analysis. As another filter, we can select the area of Low Performance in the goal area to target the identified students for interventions which you can be directly inputted in our 31a At-Risk module. This analysis prompts us to examine other data (such as MSTEP or local assessments) to ensure alignment of the results as triangulation between data is also important.
Let's review our steps so far. We started with our area of inquiry, narrowed our focus, isolated the problem area(s), and used student level analysis as we targeted identified students for interventions all by using our Eidex Prism software to highlight areas of strength and areas needing further attention.
5. Monitor and Adjust. The last step in the process is monitoring and adjusting to ensure that the interventions are working as intended using our 31a At-Risk module.
Our Eidex Prism 31a At-Risk module enables you to review post-intervention trend data by granularity levels and target groups as you analyze if the intervention made the expected change and was consistent with your target groups so you can determine your next steps.
RELATED: Using Data-Driven Analytics
Eidex Is Dedicated to Improving Low-Performing Schools – Strategies That Can Work for Any District
Eidex is developed by educators, for educators. We centralize the massive amounts of data your school system collects and organize it in engaging and action able ways. We make life and data easier, letting you focus on what really matters - student and school success. We understand the tough decisions you make every day.
As your partner in data, we work hard to provide an accessible, collaborative, and flexible system that gives you clear views at every level, from the state all the way down to individual students and teachers. We want you to see a complete picture within each school and student, as Prism turns granular data analytics into actionable insights. We have the tools you need.
If you’re ready to learn more about student and school data analytics and how Eidex can help, we’d love to talk with you! Please fill in the simple contact form on our site if you would like the template we mentioned, a quote, or a demo. You can also give us a call at (844) K12-DATA | (844) 512-3282.
References
Guiding Principles for Improving the Lowest-Performing Schools in Tennessee (2018, December). TN Education Research Alliance.