DeePENN Your Understanding of Data-Driven Decision Making in Education

Data-driven decision making has become a central focus in modern education systems, with the ultimate goal of enhancing student learning and achieving sustained improvement. To truly grasp the potential of data in informing educational strategies and actions, it's critical to understand how data should be collected, analyzed, and utilized. In this post, we’ll explore best practices, drawing on the pioneering work of Dr. Victoria Bernhardt and insights from my experiences as a NJ and NYC educator.

?The Power of Multiple Data Sources: Insights from Dr. Victoria Bernhardt, a recognized leader in the field of data-driven decision making, emphasizes the importance of using multiple measures to gain a comprehensive view of school effectiveness. I was introduced to her work as a second year principal in 2007 and her books and research really helped me to strategize how I used data to drive improvement at my elementary school. As a matter of fact, our school was taken off the persistently failing list and started showing significant progress for student achievement data in a very short time. I had the most amazing teachers at the Jackie Robinson School in Brooklyn, NY - as they bought into the framework and my philosophy. They helped me to put theory into practice. I implemented yearly Data Day meetings, data walls, daily comprehensive formative assessment practices, student progress reports which went home biweekly, and extensive analysis of all data concerning our school. My students had to know their data well!

?In her framework, Dr. Bernhardt highlights four (4) primary categories of data that should be considered:

?1. Demographic Data: Who are the students? This includes information like enrollment, attendance, ethnicity, and socioeconomic status.

2. Student Learning Data: How well are students learning? This involves standardized test scores, formative assessments, and grades.

3. Perception Data: What do stakeholders think? Surveys and feedback from students, teachers, parents, and the community provide valuable insights into the school environment.

4. School Process Data: What are the school’s practices and procedures? This includes instructional strategies, curriculum implementation, and other organizational structures. By looking at data through these lenses, educators and administrators can better understand the interconnections within their systems and identify areas of strength and opportunity.

Dr. Bernhardt’s approach ensures that decisions are not based on a single data point but rather on a rich tapestry of information, allowing for more targeted and effective interventions.? In my former district, I was affectionately known by some principals and teachers as “Dr. Data,” because I have been an advocate for holistic data-driven decision making; reinforcing the importance of integrating both quantitative and qualitative data to get a complete picture of school and student performance. While quantitative data, such as test scores, behavior incidents, reading levels, and attendance rates, provide hard numbers that can track trends over time, qualitative data—such as focus group findings, open-ended survey responses, and classroom observations (teacher practice and student engagement)—offers context and nuance that numbers alone cannot capture. I often reiterated, “Numbers tell you what is happening, but the stories tell you why it is happening.” I am also very focused on IMPACT, the so what of the actions or behaviors. For example, a dip in math scores (quantitative data) may prompt the question of why students are struggling. Qualitative data, such as teacher interviews, classroom observations, or student feedback, might reveal a lack of authentic student engagement with the curriculum or inadequate pedagogical support resources. Incorporating these different types of data ensures that educational decisions are both evidence-based and contextually relevant, allowing for solutions that are tailored to the unique needs of students and schools.

?Framing the Data Picture: From the student to the Central Office, in order to maximize the impact of data-driven decision making, it’s crucial to understand how data is layered across different levels within the education system. Each level—student, classroom, school, division, district, and central office—offers a unique perspective that contributes to a more holistic understanding of the educational environment. Allow me to take you through each of them:

1. Student-Level Data: This is the most granular level and includes individual student profiles, formative assessment trackers, students’ goal sheets, performance records, and behavioral data. It helps educators tailor instructional strategies and supports to meet specific student needs.

2. Classroom-Level Data: Aggregated student data (vertical and horizontal review of student performance) at the classroom level provides insight into how well students are meeting curriculum standards and where instructional adjustments may be needed. Teachers can use this data (checks for understanding are critical here) to identify patterns of student achievement and inform groupings, interventions, and differentiated instruction. As a former adjunct professor for CUNY teaching an Assessment in Education course for over ten years, I made sure to reinforce this with my pre-service teachers.

3. School-Level Data: School-wide data, such as climate surveys and overall academic performance, helps school leaders identify trends across grade levels and determine areas of focus for school improvement planning. Summative data plays a role but should not be the primary focus.

4. District-Level Data: Data at this level is crucial for ensuring consistency and equity across schools. It includes comparative analyses that reveal disparities between schools and helps prioritize resource allocation, in-school push in supports, and professional development.

5. Central Office Data: At the highest level, central office administrators use district-wide data to set policy, guide strategic initiatives, and ensure compliance with state and federal mandates. By considering data at each of these levels, educational leaders can paint a clearer picture of their school systems’ health and use this knowledge to drive continuous improvement.

?The Role of Progress Monitoring in Continuous Improvement

One of the most critical aspects of data-driven decision making is ongoing progress monitoring. Dr. Bernhardt and I both underscore that it’s not enough to simply collect and analyze data once; schools must implement a cycle of review, reflection, and refinement. When I first started as the Deputy Superintendent in Staten Island, this topic was the first professional development I conducted for the over 70 K-12 principals at one of our monthly meetings. Regularly monitoring data ensures that schools remain agile and responsive, adjusting strategies as new data emerges. For example, after implementing a new reading intervention, a school might monitor reading comprehension scores every four to six weeks. This is known as the Response to Intervention (RTI). If the data shows improvement, the intervention can be expanded. If not, the school can delve deeper into the data—perhaps looking at specific subgroups or cross-referencing with qualitative insights—to determine the root cause and modify the approach accordingly. Data is living and breathing and must be respected at all levels.

Final Thoughts: A Systems Approach to Data-Driven Decision Making

Data-driven decision making in education is not about using data to justify decisions; it’s about using data to inform all decision-making. By leveraging both quantitative and qualitative data and considering information across different levels, educators can build a strong foundation for continuous school and district improvement. The most successful teachers and principals know this secret. As educators, we must deepen our understanding of the complexities of data-driven decision making for the sake of the students whom we serve. Dr. Bernhardt’s model and my insights provide a blueprint for thoughtful data use that prioritizes student success at the core. When schools commit to using multiple sources of data and engage in ongoing progress monitoring, and deepen their understanding of multiple sources of data they then create a culture of evidence-based practice that fosters real and lasting change.

For more information on implementing these strategies or to discuss personalized approaches for your school community, feel free to reach out to me. Together, we can create a thriving educational environment where data is valued, respected, and used for continuous improvement. Visit deepennconsultingllc.godaddysites.com.

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