Data Doesn’t Matter until It Makes Education Better for Each Student

Being “data rich and information poor” is simply not enough. Demands for accountability have increased—especially in education and policy—and the role of state and local educational agencies in shaping policies to provide high-quality learning opportunities for students is more pressing now than at any point in the past decade. And these policies depend on data.

Continuous improvement at all levels of the education system depends on data, and so does accountability for improved student learning outcomes. So how do state and local education agencies get there?

ESSA is only a start.

The Every Student Succeeds Act (ESSA) requires states to establish systems of accountability that highlight multiple measures of district, school, and student performance including standardized assessments, student growth, subgroup performance, and other indicators of student success and school quality. But if these systems do not accurately measure what matters most, shine light on disparities, or prioritize improving student outcomes for all students, then states can’t drive systemic change.

ESSA widened the scope of data used in state accountability systems to include measures beyond standardized assessments. Now state and local educational leaders will need to address data equity silos within and among agencies. Data sharing facilitates stronger goals and improves focus on policies that ensure educators closest to students can access the data they need—as long as they also have the time and skills to use it.

This type of change will require leaders to make intentional and targeted efforts to create a systemic culture and school/district accountability system where data is purposefully and routinely used to guide program, instructional, and organizational improvements. But do educators feel equipped to lead this change? When educational leaders from across the nation gathered at an ESSA Thinkers Meeting to talk policy, many reported feeling the increased demand but not having the capacity to make meaningful use of data. State and local education leaders are hamstrung without a data-driven culture that facilitates true change.

States that lead the way in effectively using data first help educators get comfortable with the idea of data and why it’s important and then shift the focus to empowering them to find, understand, and use data to improve teaching and learning. And where do you think they start? With district and school leadership. States with a strong data-culture tend to have leaders who lead by example and set expectations that decisions must be anchored in data.

Data culture needs to be developed—not applied—and that can’t happen in a silo. True data culture means involving people beyond the specialists at the center of your data practice so you can engage employees and achieve business engagement. Ultimately, this culture enables data to support your operations, instead of your operations doing the heavy lifting.

The experience of these leaders, and our own, suggests that you can’t import data culture and you can’t impose it. Most of all, you can’t segregate it. You develop a data culture by moving beyond specialists and skunkworks, with the goal of achieving deep business engagement, creating employee pull, and cultivating a sense of purpose, so that data can support your operations instead of the other way around.

Culture shift is essential.

Higher-quality learning opportunities start with a culture of data literacy. Until individuals are empowered to make more informed and equitable decisions about education-related policy, programs, and practices, transparency and accountability will remain out of reach. Data-driven decision-making and clear and concrete goals are worth striving for, but only if a culture shift is part of the strategy.

An effective data culture in which data-driven decisions are rooted in proficient data literacy helps leaders and educators better understand what they do know and uncover what they don’t know, making the invisible visible. It also helps remove the guesswork in understanding school and district performance, enabling leaders to effectively and efficiently address issues in educational policies, programs, and practices. After all, can a leader even measure improvement if he or she isn’t tackling the root cause of the problem? It’s highly unlikely.

When I talk about “empowering stakeholders” to use data to improve teaching and learning, I may make it seem as if this is an easy task to accomplish. It is not. No state can achieve this kind of change alone. Establishing efficient data use from the state to district level requires a range of responsibilities and skills.

This effort should start with state leaders who can drive the cultural shift by aligning policies and resources to support local educational leaders at the school and district levels. If the end goal is to establish data-driven cultures at the state and local levels (and it should be), then it makes sense to look to state leaders and policymakers to lead the way by creating the climate and conditions to ensure local leaders have the knowledge and skills necessary to find, interpret, and use data to improve practice.

Void of these skills, how can leaders see the big picture of how schools are performing and effectively meeting the needs of all students by providing the best education possible? Leaders need training across data analysis best practices to inform decision-making.

I have worked with a variety of leaders across the nation to address the issues of data equity, data literacy, and data culture. A nugget of advice (evidence-based, of course) I often give leaders to help them gain the best insights from their data is this: Employ an exploratory data analysis framework rooted in asking the right types of questions to help shape school improvements.

Multiple evidence-based frameworks are easily accessible via the internet, but I’ve found the most effective ones will suggest starting with the what and ending with the who. And in the middle are why and how. Putting it all together: what is the problem, why is it important, how are we going to solve it, and who will help us get there? Because the insights achieved from the analysis are only as good as the questions you ask and the order in which you ask them, the first two questions should be contextual in nature, while last two are procedural. A solid data analysis framework prevents leaders from, as the expression goes, putting the metaphorical horse before the cart.

Effective data analysis depends on strong research infrastructure.

In the words of Albert Einstein, “if you can’t explain it simply, you don’t understand it well enough.” I’d add that if you can’t explain it simply, it’s time to consider soliciting the support of someone—internally or externally—who has a quantitative bent. Generally, education leaders are not statisticians or psychometricians and, quite frankly, we should not hold them to that expectation.

Some state leaders have been more ambitious than others in establishing research partnerships to transform their education and accountability systems. While some are gradually building an infrastructure to facilitate research use, many others are pioneering a new path for the future use of research to help identify evidence-based intervention and to research and scale best practices for continuous improvement based on current studies.

Ultimately, the strength of a state’s research infrastructure rests on its ability to partner with high-quality, credible researchers. Strong partnerships that align researchers’ analytical skills with state-level policy expertise answer important questions about student and school performance. Leaders don’t have to make decisions in the dark, and students stay on track for high school graduation and post-secondary success.

Data’s potential impact within the educational system is immeasurable.

Used purposefully, data can help education leaders make better policy decisions and facilitate equitable education experiences and outcomes for students. States can draw on data to provide evidence-based tools and resources to district leaders who, in turn, should create the infrastructure for a research-driven data culture that provides educators the necessities for meeting the needs of students and teachers. As the use of data in the K-12 system increases, states are beginning to use data to track students’ employment, enrollment, and enlistment status beyond high school graduation resulting in significantly enhanced student performance outcomes.

Take a school district in Massachusetts, for example. To measure the impact of large-scale initiatives and standards-based curriculums, district leaders established a data culture that supported data-driven decisions that respond to challenges in programming, instruction, allocating resources, and professional development more proactively, rather than reactively.

A data culture that is systemic throughout all levels also keeps parents, the community, and other stakeholders in the loop about how schools, districts, and the state are serving students. In fact, a recent survey (Data Quality Control, 2019) showed that parents want better access to their student’s data; however, state and local educational levels have a responsibility to place data in a context that helps parents and other stakeholders understand what the data means and how to use it support their students’ learning and educational paths outside the classroom.

When working with school and district leaders in my former role as an assessment and data coordinator, I often encouraged them to reflect on their current data use practices within their school and district offices, respectively. More than not, I found that most leaders were not equipped with the tools necessary to meaningfully use data, hampering their ability to lead a data culture and make data-driven decisions to yield substantial improvement.

I responded by providing data-related professional development sessions for the leaders and, eventually teachers, across the district that were rooted in researched-based practices about how to create a data culture that guaranteed improve student performance outcomes by addressing the problem, collecting the right data, turning data into conversations, establishing a plan to address the problem, and identifying the appropriate stakeholders to execute the plan. However, I was careful to communicate that professional development would only do its job if the stakeholders were intentional about doing theirs by putting the knowledge and skills into play.

Data matters, but only if it is strategically and effectively used to improve the quality of education each student receives. And that starts with leaders.

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