In the current educational climate, school administrators face a dual challenge: navigating the post-ESSER funding landscape and managing an overwhelming amount of data generated by digital learning systems.
With budgets tightening in the post-ESSER era, every dollar spent on educational resources must be justified with demonstrable returns. Simultaneously, school leaders are bombarded with data on everything from student engagement to attendance, making it harder to focus on what truly drives student success.
Now more than ever, principals and school-based administrators need to lead with data strategically. This is not about tracking every available metric—it’s about aligning data with the goals and objectives set forth in the district’s strategic plan and the School Improvement Plan (SIP). This alignment is key to ensuring that data informs meaningful decisions that improve teaching, learning and overall school performance. Below are some best practices for leading with data.
Align data with strategic priorities
Every data point you collect should connect to your school or district’s objectives. As budgets become more constrained, it’s more important than ever to focus on data that directly measures progress toward specific goals.
For example, if your SIP emphasizes increasing literacy rates among English language learners, your data should focus on tracking reading proficiency and engagement for this student group. While collecting unrelated data might offer interesting insights, it can also divert valuable time and resources away from what truly matters—gaining the insights necessary to drive progress toward your key objectives.
Know what data matters
With so many metrics available, it’s crucial to know what matters most. Administrators should focus on actionable data—data that helps measure progress toward SIP goals and informs the teaching and learning environment in the school:
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- Student Performance Data: Monitoring both quantitative and qualitative student data is crucial for administrators to drive school improvement. This includes standardized test scores, formative assessments, course grades, class participation, teacher observations, and input from students and parents. For example, improving math proficiency, tracking assessments, participation, and teacher feedback throughout the year helps monitor progress. By analyzing this data, administrators can identify gaps, implement targeted interventions, and align efforts with school goals.
- Student Engagement Data: Engagement metrics from LMS platforms and other digital resources can reveal how often students interact with content, complete assignments, and participate in collaborative activities. This can be particularly helpful in understanding the level of student engagement with interventions designed to improve academic performance.
- Student Behavioral Data: Attendance, discipline records, and other behavioral data offer crucial context for understanding student readiness to learn. For example, a student experiencing a significant drop in academic performance, alongside an increase in tardiness and absences, may be struggling due to factors outside the classroom. This information can help explain why certain academic interventions are not achieving the expected results, as external issues may be affecting the student’s ability to engage and learn effectively.
- Teacher-Related Data: Monitoring key teacher-related data—such as performance, professional development, school culture, and related metrics—is vital for administrators to ensure instructional quality aligns with school goals. These data points help identify areas where teachers need the most support, enabling administrators to tailor professional development and enhance the overall teaching environment. By consistently tracking this information, administrators can make informed decisions that positively influence both student outcomes and school culture.
Streamline data collection
Knowing which data is important is only half the battle; the next challenge is collecting it consistently and efficiently, including working with partners to ensure the right data is shared to inform decision-making:
- Choose the Right Tools. LMSs and student information systems (SISs) are valuable tools for collecting data on student performance, attendance, and engagement. However, it’s crucial to select tools that integrate seamlessly with your district’s existing systems and are user-friendly for teachers and caregivers. When data collection becomes a cumbersome process, it undermines the effectiveness of the entire system.
- Establish Clear Data Protocols. Consistency in data collection is key. School leaders should establish clear protocols that outline how data should be collected, at what intervals (weekly, monthly, or quarterly), and who is responsible for inputting the data. Consistent data collection ensures that the information you gather is reliable and can be compared over time.
- Protect Data Privacy. Data privacy in schools refers to the protection of students’ personal and educational information from unauthorized access, misuse, or sharing. This is crucial as schools collect and store a wide range of sensitive data, including academic records, personal identification details, health information, and even behavioral data. Ensuring this data is kept private and secure is essential to safeguarding students’ identities and their right to privacy. Several laws govern how schools collect, manage and share student data. In addition to the Children’s Online Privacy Protection Act and the Family Educational Rights and Privacy Act, many states such as California and Colorado also have their own data privacy laws.
Use data to prove resource effectiveness
With shrinking budgets, proving the effectiveness of educational resources is essential. Administrators need to show that the tools they invest in are improving student outcomes:
- Set Clear Benchmarks. SIP goals should have clear, measurable benchmarks. For example, if your SIP focuses on raising math scores by 10% for the school year, you need to track data that measure incremental growth in math proficiency
- Monitor Trends Over Time. One-time data snapshots don’t provide enough information to make informed decisions. Administrators should monitor trends over months or semesters. If a new reading intervention is implemented, reviewing and monitoring the intervention activities and data collected through the implementation in addition to the literacy scores during the school year could be used to assess its effectiveness.
- Gather Qualitative Feedback. In addition to quantitative data, actively seek qualitative feedback from teachers and students. For instance, if teachers report a math tool is cumbersome to implement, that insight can help explain why the tool may not be showing the expected results.
Prove ROI to stakeholders
Proving there is a return on investment (ROI) is essential for justifying budget expenditure. Stakeholders—including school boards, parents, and the community—want to know how new resources are meeting the desired results and ensuring student success:
- Calculate ROI. Start by comparing the cost of a resource with its measurable benefits. For example, if a $20,000 reading program leads to a 10% increase in reading scores, compare that to other programs to assess its value. Prioritize high-impact investments with the best returns.
- Highlight High-Impact Investments. Focus on resources that provide significant benefits for their cost. For instance, a low-cost professional development program that significantly boosts teacher effectiveness might offer a better ROI than a high-cost tech tool with limited results.
- Communicate Results. Create clear, data-driven reports to communicate the effectiveness of school resources. Show how investments have led to improvements in key metrics such as academic achievement, engagement, and behavior.
Foster a data-rich—not data-overload—culture
Leading with data has a clear goal to provide actionable insights that help improve instruction and learning:
- Provide Actionable Data. Provide educators with the data they need to adjust instruction effectively. For example, instead of providing generic engagement data, offer insights into student progress toward mastery of state standards, allowing teachers to adjust their instruction to better support student learning.
- Facilitate Collaborative Discussions. Encourage regular collaboration among teachers to discuss data trends and instructional strategies. Grade-level or department meetings are great opportunities to analyze trends and share best practices.
- Invest in Professional Development. Ensure that teachers receive ongoing professional development on how to use data in the classroom. Providing regular training on how to analyze and apply data ensures that teachers are equipped to make data-driven decisions.
