A Common Language for Improvement

When Gustavo Luna, Ed.M.’22, Ed.L.D.’25, first heard about the Data Wise approach, he was intrigued, if a bit cautious. The term “data” conjured images of massive spreadsheets, regression analyses, and, of course, test scores — helpful for researchers but not something educators could use in their everyday practice. But after taking a Data Wise course at the Harvard Graduate School of Education (HGSE) and working with special education professionals at a school in New York City, he saw how much untapped, useful information was hiding in plain sight.

One teacher he supported, who was working with a young student with behavioral disabilities, kept a log of how many seconds the student was able to hold a pencil each day. She was collecting data to track his progress, Luna realized; she just didn’t call it data. “Teaching is a practice. We never master it. Every school, every student is unique,” he says. “Knowing how to recognize, use, and, importantly, share data is what allows us to improve.”

Today, Luna is one of more than 200 certified coaches who are qualified to teach the Data Wise framework. He mentors other educators to use evidence from a wide variety of sources — from simple classroom logs to observational data — to better understand what is happening with learning and teaching in their classrooms so they feel empowered to make meaningful changes.

Understanding Data

Data Wise first took shape more than 20 years ago, as schools were just beginning to wade through an influx of assessment data required by the federal No Child Left Behind Act. Professor Richard Murnane convened a working group at the time of educators from Boston Public Schools and researchers from HGSE to discuss what it would take to make use of that data in service of improving instruction. Over the course of two years, the group realized that what schools really needed was step-by-step guidance on how to use all this new information.

Looking back, Senior Lecturer Kathy Boudett, then an HGSE postdoctoral student and current executive director of Data Wise, recalls, “Nothing I had done professionally before then felt so important. I knew we needed to figure this out.”

Not long after, the now-iconic Data Wise “swoosh” was born, outlining the eight steps of the Data Wise Improvement Process, and the core habits that support this work. It may look a bit complicated, but educators like Andrea Kayne, Ed.M.’90, will tell you it works.

“Suddenly, data was central to how administrators, teachers, and school counselors were being evaluated, but almost no one had the frameworks to contextualize that data, challenge it, collect their own, or act on it without fear,” says Kayne, who was program director of educational leadership at DePaul University at the time. “Data Wise was the answer I had been looking for — it created real professional learning communities: collaborative rather than competitive, empowering rather than punitive.”

Two decades later, the Data Wise Project has built an international network of certified coaches who have supported schools and systems from Oregon to Maryland and Illinois to Florida, as well as in countries such as Australia, Chile, and Brazil. More than 5,000 educators have attended the Data Wise Leadership Institute on Harvard’s campus or on-site in school districts.  

Led by Boudett, the team has released a host of new resources on the Data Wise website and is expanding professional learning opportunities to meet the evolving needs of schools and systems — with an eye to reaching even more educators in the coming years.

From Process to Purpose

As educators become savvier about data, the driving question behind the work has shifted from “How do we help educators make productive use of data?” to “How can we use a wide range of data to realize more equitable outcomes for students?”

And it’s not just about the technical use of data. “It's about getting teams of educators on the same page about what they see, what they want to improve and how, and then committing to doing it,” explains Lecturer Candice Bocala, Ed.D.'14, Data Wise research director.

That kind of collaboration is a rare antidote in a time of deep educator burnout and turnover. “Teaching can be really lonely,” Boudett says. “What we hear is that having this process allows educators to talk about work with colleagues in a way that's fun and exciting. They ask, ‘What can wfe do to really meet the needs of each of our learners? What are you trying?’ The framework deliberately connects educators to one another and to why they went into teaching in the first place.”

The result, she says, is that educators develop a common language for talking about improvement and decision-making. “Data Wise is meant to be done in teams,” Boudett says. “When you have multiple people looking at the same data, people will see different things, and the conversations about what to do about the evidence will be richer.”

As the network of coaches grows, they have helped the Data Wise framework itself evolve. One visible example is the “equity halo,” a series of reflective questions that now accompany each step of the swoosh, including “Whose stories do we tell/not tell? Are we measuring what matters?”

Coaches saw teams working through the steps, but they often struggled to examine longstanding inequities in schools and, as a result, missed the needs of the most marginalized students. One coach, Darnisa Amante-Jackson, Ed.L.D.’16, provided a critical insight: You can’t have separate lessons about the importance of equity; you need to integrate it at every step. Other coaches echoed that it was time to position equity at the heart of the process.

Those conversations directly influenced the third edition of Data Wise: Educators Collaborating So Each Learner Thrives, which was published last year in time for Data Wise’s 20th anniversary.  

A New Chapter

From its earliest days, Data Wise has been guided by this type of practitioner feedback. Its latest focus is creating local hubs of expertise — teams inside districts who can carry the work forward. In one local district, for example, Data Wise recently certified five district-level leaders who are now using data wisely in their own practice, supporting school teams in using the framework in their settings, and bringing school teams together to learn from one another about how improvement happens.

The project is also investing in new ways to reach educators. With the help of a recent philanthropic gift from Kayne, Data Wise is expanding its online offerings, including a free, asynchronous introductory module called Exploring Data Wise, launching later this year.

The new module — which replaces the massive open online course (MOOC) based on an earlier edition of the book — will ensure educators anywhere in the world can access an overview of the updated framework at any time. It gives teams a cost-free way to gauge how deeply their school or system is engaged in collaborative inquiry and to explore how Data Wise could be a resource if they choose to pursue more intensive professional learning.

“I invested in Data Wise because it works, because it is rigorous, and because it treats educators as professionals capable of deep inquiry,” says Kayne, who is now creating an edtech platform for international and independent schools. “Many of my former students, now working as principals and superintendents, speak about how central the Data Wise framework remains to their practice years later. That kind of staying power is not common in professional development. It tells you something real about the methodology. I see a gift to Data Wise as a gift with a very long half-life.”

One constant over 20 years, Boudett points out, has been educators' desire to improve outcomes. Coaches like Luna can attest that they are eager to change schools for the better and hungry for ways to do it well. As it evolves, Data Wise will continue to equip educators at all levels and around the world with a common language for turning data into action — and lasting impact.

“Deciding to use Data Wise doesn’t make the work easy. Working collaboratively to look at evidence of learning is hard, and looking honestly at your own practice is even harder,” Boudett notes. “But educators tell us that the ‘swoosh’ offers a roadmap, so when they hit bumps, they know where to check in and how to keep moving.”

Luna, pictured above running a Data Wise workshop at a Hopi school in Arizona/at a public school in New York City, credits Data Wise for helping his own team at Kern Tutoring, where he is founder and executive director, embrace a culture of continuous feedback and “small pivots” — both internally within the organization and in how they serve local school districts in California. Photos courtesy of Gustavo Luna.