In the weeks leading up to our annual conference, Teaching, Learning, and Coaching, I’ll be posting interviews with the experts who will be presenting at the conference. The interviews will surface many different ways of looking at coaching, and like the conference itself, I hope they inspire, educate and provoke new thinking. I don’t agree with everything I hear in the interviews, but I am grateful for others’ thinking. We move forward by challenging our beliefs, and I hope you feel challenged too. You can keep up with the interviews by subscribing to this blog.
This week’s interview: Nancy Love
If you get the chance to see Nancy Love present, I highly recommend you go see her. Nancy, to my mind, is the world’s leading expert on data and coaching, and she is also a smart, fun, engaging, and kind presenter. She has presented at TLC several times, and I’m always grateful that she takes the time to share her ideas with us. I can’t wait to see her this year.
Nancy is Director of Program Development at Research for Better Teaching in Acton, Massachusetts, where she leads this education-consulting group’s research and development. She is the former Director of the Using Data Project, a collaboration between TERC and WestEd, where she led the development of a comprehensive professional development program to improve teaching and learning through effective and collaborative use of school data. This program has produced significant gains in student achievement as well as increased collaboration and data use in schools across the country.
Tell me about how you got involved in coaching
In the 1980s and 90s, I worked with a federally funded network of exemplary education programs to help schools implement programs that had been validated and documented on student achievement. Through professional development workshops and follow-up support training for trainers, we observed that in some schools the programs made a big difference for students, but in others it was as if the professional development efforts went down a black hole.
So, we started to study the conditions under which professional learning works and how to build more collective ownership, excitement, and accountability into school improvement. We realized that some critical ingredients were missing in our school improvement recipe, including teacher collaboration and data use. As a result, we examined a variety of professional development models, including coaching. Of particular interest to me were teacher teams and data use. This was around the time when data and accountability were the catchwords of the day. I was intrigued by that, but also concerned because, while I believed that effective uses of all kinds of data were vital to school improvement and equity, I worried that data were being misused, misunderstood, and under-utilized.
Later, I had the opportunity to lead a National Science Foundation-funded project to develop educators’ capacity to use data collaboratively, continuously, and effectively with a strong moral purpose – to serve students. We targeted teachers, leaders, specialists, and coaches with the assumption that they would take the work back to teacher teams, so their role was to facilitate collaborative inquiry using data and spread data literacy.
Originally, we didn’t have a name for those folks, but we ended up calling them data coaches.
In every case where we were able to document a positive impact on student achievement, behind the success story was the data coach. That is what launched me into the world of coaching, along with looking at multiple models for professional learning.
Tell me about your publications on coaching
During the 1980s and 90s I had the privilege to work with Susan Loucks-Horsley, one of the thought leaders in the field of professional development and school improvement, and to my surprise and delight, Susan asked me to join a team to author what turned into the book Designing Professional Development for Teachers of Science and Mathematics.
Then in 2002, Using Data, Getting Results was published by Christopher-Gordon, in which I offered a process and tools for collaborative inquiry teams with a major focus on equity. Although not explicitly about coaching, the resources can be useful for coaches, especially those who have worked with teacher teams. The book’s focus is on mathematics and science, and that was the catalyst for The Data Coach Guide, which was published in 2008, as an attempt to distill all that we had learned from training data coaches.
Then in 2009 Using Data to Improve Learning for All: A Collaborative Inquiry Approach was published. That publication summarized the approach in The Data Coach Guide, combined with stories from the field and a chapter on bringing cultural proficiency to collaborative inquiry as a core competency for data coaches. Most recently, I’ve been working on a new program called Coaching High Impact Teacher Teams: Four Steps to Improving Student Achievement about coaches guiding teams to 1) clarify the learning journey for students; 2) infuse formative assessments; 3) analyze formative assessments; 4) and take FIRME action (Feedback, Investigation, Reteaching/Regrouping/Re-engaging), Moving On, and Extension.)
What are some of the core ideas in your approach to coaching?
My core ideas about coaching have been shaped by three major influences: my experience of being coached myself; you, Jim Knight; and my work with data coaches and teams.
First, the kind of coaching that I am drawn to is primarily about listening deeply, believing that the person you are coaching has the creativity and resourcefulness to resolve his or her biggest problems, offering expertise sparingly and avoiding advice.
Second, you (Jim Knight) are a huge influence on my core ideas about coaching. I love the partnership principles as the moral fiber for coaching, especially a deep belief in equity and dialogue. I love the balance between dialogue and the goal-setting process and offering expertise in the learn part of the cycle while bringing in both the precision and the provisional nature of it.
Finally, over the last 15 years, I’ve been studying data and team coaching. Our core idea is that data coaches facilitate meaning making and dialogue around data, building that collective picture of current reality and not leaping to decisions before you are grounded in a shared vision. With that grounding in reality, skilled data coaches guide teams in setting goals, using logic-model thinking to plan for action, and then and taking action while using data to monitor progress.
Data coaching overlaps with the partnership approach (Jim Knight) in that we emphasize a kind of moral fiber. I was always moved by what Franklin CampbellJones said with regard to data: get ethical before you get technical. So data coaches are more concerned about having the passion to serve students and take on the tough issues around equity than about how technical they are in understanding the data.
Most recently, I’ve been thinking a lot about coaches’ role in facilitating teams and, like most of the field, have made a shift away from the focus on summative and-high stakes assessments to formative kinds of evidence. Like you and others, I believe that teams are most effective when they focus on the core practices of teaching, which is essentially about planning and executing superb lessons.
The core idea here is that the coach’s role is to facilitate deep learning, which includes taking action and reflecting and assessing the impact of the four high-leverage practices I referred to earlier. The way we describe the role of coaches and their work is that they are the lead learners, they’re the champions of the team values, they’re the impact, the equity advocates, the guardians of the professional culture and the problem solvers.
What distinguishes your approach to coaching from other approaches to coaching?
I think our focus on data coaching is unique. Our attention to cultural proficiency as a core competency for data coaches came early in our work. Specifically, I think our approach to data as a means of making dialogue and analyzing data with enough detail to pinpoint precisely what might be the best next step for both teachers and students is unique.
What have been some of your key learnings over the past few years?
One thing I’ve learned from observing teams is how important it is to balance accountability with support for teams through coaching. I have also come to realize that coaches don’t have to be the experts in all the practices. In fact, if the coach shows up as the expert, it may have a negative impact so that team members defer to the coach or don’t want to take risks because they don’t want to look bad in front of the expert. Also, the feeling of having to know everything sometimes puts a lot of pressure on the coach, so we find that coaches are relieved when we tell them that they don’t have to be the expert in all these practices but can play an important role as co-learners and in facilitating the learning of others.
What’s a good metaphor for what coaches do?
I was a gymnast, which made me think of the coach as spotter – you can take the leap but someone will catch you. Another metaphor would be the coach as a good friend; finally, using an adaptation of a quote by Susan Sarandon (from Shall We Dance?), the coach “as a witness to the good” – a professional witness to your life as a professional.
Since our conference theme is It’s All About the Kids, please tell me a little bit about the impact your work has had or can have on children
Back when we first piloted data coaching, we worked with a high-poverty school district in the mountains of Tennessee that took data coaching and data teams to new heights. Going on a districtwide campaign to close the gap between general and special education, they integrated special educators into teams, had mentors come in from the community, and made sure that special education was in place.
After a couple of years, they had doubled the percentage of students with disabilities who were passing the state test, literally eliminating the gap between special and general education. That was the first time that I had compelling evidence showing that the work around data coaching and collaborative inquiry was impacting children.
More recently, we have worked in a high-poverty, diverse district in the Boston area with coaches and teacher leaders, who did some of this formative work that I have been describing. Specifically, they focused on clarifying the journey for students, formative assessments, quick checks for every lesson, etc. They’ve just been recognized by the state of Massachusetts as a model turn-around school; in fact, there’s a video on the Department of Education website about what they’ve done. We’re really thrilled about that.
Tell me a bit about what you’re going to present at TLC
I’ll be presenting two sessions on analyzing student work that are “all about the kids.” In the first, participants will learn how to facilitate dialogue using a protocol called “criteria analysis,” where they use success criteria that have been clearly communicated to the kids. The power of this kind of analysis is that it makes it clear to teachers and students exactly what the next steps are and paves the way for feedback students can use to improve their work.
The second session engages participants with another kind of student work analysis called “error analysis.” Here participants will learn another dialogue process for making meaning together to uncover specific types of errors, such as misconceptions or flaws in reasoning.