Introduction:
“Without data, you’re just another person with an opinion.” — W. Edwards Deming.
So much of what I do in my career as an educator is based around the idea of being “data-driven”. As you’ll be able to tell by browsing my website, I am a huge proponent of utilizing data in education, but doing it the right way. In my experience, there seems to be a dominance of two schools of thought:
- Data should control every aspect of education
- Data dehumanizes students and takes away the power of personal relationships
In this article, I will attempt to explain why both of these viewpoints are wrong. There is a place in the middle where the true value lies. Education doesn’t have to be a guessing game, but it also doesn’t have to view students as numbers on a page.
Think of this as the manifesto of my blog. All my other articles point back to this one. So let’s unpack the idea of data-driven education and how it can be the key to unlocking the full potential of schools and improving student outcomes.
What Is Data-Driven Education?
In the modern classroom, data-driven education is an approach that utilizes gathered information to make informed decisions about teaching and learning practices. Yes, this means academic assessments and performance metrics but it certainly does not stop there. Here’s a rundown of some possible data sources (though the list is not exhaustive):
| Category | Data Type | Examples |
| Academic Performance | Formative Assessments | Exit tickets, quizzes, progress monitoring (e.g., DIBELS, MAP Growth) |
| Summative Assessments | State tests, end-of-unit exams, final grades, AP/SAT scores | |
| Benchmark Assessments | District-wide interim tests (e.g., i-Ready, NWEA, STAR assessments) | |
| Course Grades | GPA, letter grades, report cards | |
| Standards Mastery | Percent of students proficient by learning standard | |
| Behavior & Discipline | Incident Reports | Fights, bullying, vandalism, classroom disruptions |
| Discipline Referrals | Teacher-submitted behavioral referrals | |
| Suspensions/ Expulsions | In-school and out-of-school suspensions, expulsion records | |
| Attendance & Truancy | Daily attendance, chronic absenteeism, tardiness | |
| Student Demographics | Basic Demographics | Race/ethnicity, gender, grade level, age |
| Socioeconomic Status | Free/reduced lunch eligibility, family income proxies | |
| Language Status | English learner designation, home language | |
| Special Populations | IEP/504 status, gifted and talented, foster youth, homeless students | |
| Engagement & Climate | Student Engagement | Survey responses, participation in class, extracurricular involvement |
| Social-Emotional Learning (SEL) | SEL screener data, behavior rubrics, student self-reflections | |
| Climate Surveys | Panorama, YouthTruth, Tripod, local school climate surveys | |
| Family Engagement | Parent-teacher conference attendance, volunteer logs, family surveys | |
| Instructional Data | Teacher Observations | Walkthrough notes, instructional practice ratings (e.g., Danielson, CLASS) |
| Lesson Plans & Pacing | Alignment to standards, coverage tracking | |
| Professional Development Logs | Teacher participation in training, topics covered | |
| Operational Metrics | Enrollment & Mobility | Total students, mid-year transfers in/out |
| Staffing & Ratios | Student-teacher ratio, number of counselors, paraprofessionals | |
| Facilities Data | Classroom utilization, safety incidents, maintenance requests | |
| Postsecondary Readiness | College Readiness Metrics | FAFSA completion, AP/IB participation, dual enrollment |
| Career Readiness | CTE course enrollment, industry certifications, work-based learning | |
| Alumni Outcomes | College enrollment, persistence, employment post-graduation |
It is very important to distinguish that we are not just talking about assessment data. Often, when talking about a data-driven school, minds go straight to the idea of tests. Assessments provide valuable data on student learning, but that is only a small portion of what we’re talking about here.
At its core, data-driven education is the intentional use of data to inform teaching and learning decisions. It’s not about replacing the human touch in education—it’s about empowering educators with insights that help them teach more effectively and support each student more personally.
The key features of data-driven education include:
- Evidence-Based Instruction: Teaching strategies are selected and adjusted based on measurable student outcomes.
- Personalized Learning: Data helps educators tailor lessons to individual learning needs, ensuring students get the support or challenge they require.
- Continuous Feedback Loops: Teachers, students, and even parents have access to ongoing feedback that promotes growth and accountability.
- Proactive Intervention: Educators can spot warning signs early—like a drop in engagement or assessment scores—and intervene before students fall too far behind.
- School-Wide Alignment: Administrators use aggregated data to make informed decisions about curriculum, staffing, resource allocation, and professional development.
Benefits of Data-Driven Education
When schools harness data thoughtfully, they unlock a wide range of benefits that improve teaching, learning, and leadership across the board. Some of the most powerful outcomes include:
Improved Student Outcomes Through Targeted Instruction
One of the most powerful advantages of data-driven education is the ability to meet students where they are. With access to detailed data—such as quiz performance, reading levels, or math fluency—teachers can adjust lessons, group students strategically, and offer interventions that are tailored to individual needs. This level of precision supports both struggling learners and those who are ready to move ahead.
Real-Time Feedback for Students and Teachers
Years ago, students and parents had to wait weeks for report cards. Digital platforms now provide instantaneous feedback, helping students understand their strengths and areas for growth as they learn. For teachers, real-time dashboards can illuminate classroom trends, identify who’s falling behind, and guide next steps—all without needing to guess. This immediate insight fosters a culture of continuous learning and improvement.
Early Identification of At-Risk Students
Using predictive analytics and early warning systems, schools can spot red flags before they turn into real problems. Whether it’s a dip in attendance, sudden grade drops, or behavioral changes, data helps educators intervene early—sometimes before the student even realizes they need support. This proactive approach is a game-changer in closing opportunity gaps and preventing dropouts.
Better Resource Allocation and Strategic Planning
School leaders rely on data to make smarter decisions about where and how to allocate resources. Should a district invest more in reading specialists? Is a new curriculum improving outcomes? Which schools need extra support staff? Data provides a clear-eyed view of what’s working and what’s not, allowing for strategic planning grounded in facts—not assumptions.
Documented Perceptions from Stakeholders
Data collection instruments like school climate surveys, student perception surveys, and community listening sessions systematically gather information right from those that matter most. This data can be used to provide a learning environment that is most conducive to ensuring all needs are met.
Greater Accountability and Transparency
With more visibility into student performance and school operations, educators and administrators can demonstrate impact and drive trust. Parents, school boards, and communities are increasingly looking for transparency—and data provides the common language to explain progress, justify funding, and align everyone around shared goals. When done right, it doesn’t just hold people accountable—it empowers them to improve.
What Is the Wrong Way to Use Data?
One of the biggest threats to the success of data-driven education isn’t a lack of information—it’s using data the wrong way. Let’s take a look at some of the most common missteps and why they matter.
Data Rich, Information Poor
In my experience as a teacher and education consultant, I often find that schools are “Data Rich and Information Poor,” a term popularized in the 1983 book In Search of Excellence. Large amounts of data are being collected but many schools and educators have an inability to turn that data into meaningful and actionable insights. Having too much data can lead to data paralysis, which happens when educators are overwhelmed by dashboards, spreadsheets, and reports without knowing how to act on them.
This makes one wonder about the return on investment of collecting the data in the first place. For example, if a standardized assessment takes a lot of time away from instruction but isn’t producing data that the school regularly utilizes, then what’s the point? This is the reason data usage in schools sometimes gets a bad rap. Many view the data collection as intrusive…and maybe it is. Sometimes, that intrusion might be worth it if the return on investment is sizable. If it’s not, however, then it truly is a waste of time and resources.
Ignoring Context and Human Judgement
There is also the concern of taking humanity out of the learning process. It is important to remember that these are children, not just lines on a spreadsheet. They cannot be completely quantified. And the teachers are trained professionals who were passionate enough about student learning that they based their lives around it. Take their opinions into account. There is incredible value in building relationships and really understanding what drives students to succeed.
Over-Reliance on Test Scores
Standardized test results are just one snapshot of student learning—but when schools anchor every decision to test data, they risk narrowing the curriculum and missing the bigger picture. Overemphasizing test scores can reduce teaching to “test prep,” stifling creativity, critical thinking, and holistic learning.
Using Data to Punish Instead of Support
Data should be a flashlight, not a hammer. Unfortunately, when student or teacher performance data is used punitively, it creates a culture of fear instead of growth. For example, publicly shaming low-performing students or using data to unfairly evaluate teachers can damage morale, relationships, and trust.
Challenges with Data Literacy
I have built my career on the idea of education practitioner data literacy. I even wrote a dissertation on the topic. In it, I conducted a study of how data literacy is being taught to preservice teachers in teacher preparation programs. I’ll sum up the 200-page document for you in 2 words: it’s not.
OK, that’s not fair. Attempts are being made to prepare teachers in this topic, but it’s incredibly hard due to the preparation programs not knowing exactly what teachers will encounter in their careers. Schools utilize data at different levels and use different tools, so it can only be taught in generalities in college. Plus, the preparation programs have to prepare teachers of all disciplines and grade levels, so there is a lot of ground to cover there too.
Ultimately, educator data literacy is not good enough. Schools and districts need to take on more responsibility in developing a data literate workforce that can collect, analyze, and utilize data appropriately. This means professional development. The data that is being collected will not be used correctly if no one knows how to use it.
Conclusion:
Schools that embrace the power of data are seeing measurable improvements in student achievement, teacher effectiveness, and overall school operations. But it’s not just about collecting numbers—it’s about interpreting them with purpose.
Leaders set the tone. Principals, superintendents, and district leaders must model the use of data in their own decision-making—whether that’s planning professional development, tracking attendance trends, or evaluating new initiatives. When leaders walk the walk, it signals to staff that data use isn’t just a compliance task—it’s core to the school’s mission.
