ko_1611_nov_2featurelead_art_gomezTackling challenging educational systems problems — and spurring effective collective action — requires a network designed for that purpose.

By Louis M. Gomez, Jennifer L. Russell, Anthony S. Bryk, Paul G. LeMahieu, and Eva M. Mejia

Educators are increasingly realizing that individuals working in isolation can’t adequately address the teaching and learning problems facing us today, whether it’s the individual teacher toiling alone in the classroom or the isolated school in a district. The fact is, the problems of achievement, attainment, and equal opportunity that educators grapple with today weren’t created by individuals. They were created by systems. And they won’t be addressed through isolated action.

Educators need to find ways to produce effective coordination among the many processes and actors that are part of the achievement equation. Faced with challenges of their own, many other sectors have turned to collective action networks — otherwise known in education as communities of practice (Lave & Wenger, 1991), professional learning communities (DuFour & DuFour, 2010; Hord, 1997), and design partnerships (Penuel, Coburn, & Gallagher, 2013). In large-scale engineering design, collective action has been responsible for creating the Boeing 787 Dreamliner; in software engineering, for developing the Linux operating system; and in health care, for solving the severe acute respiratory syndrome (SARS) puzzle. In education, our version of collective action is to help education systems and the individuals in them perform teaching and learning tasks better. Instead of teachers doing this in isolation, with their insights locked away in their local settings, the focus on networks is about releasing that nascent collective energy in education. The aim of network activity is to solve problems of practice more quickly by creating ways for more people to take advantage of the skill, expertise, and knowledge of many others. When the network is large, you can tap the creative efforts of many different people, increasing the odds that someone somewhere will figure out something better.

Here, we describe one particular network form — networked improvement communities (Bryk, Gomez, & Grunow, 2011; Bryk, Gomez, Grunow, & LeMahieu, 2015) — that can be of great value to educators as they tackle complex problems of practice.

Two kinds of collective action networks

But first, let’s look at collaborative arrangements more broadly. They’re not created equal. Leaders who want to take advantage of the power of networks to solve education problems have to pick and grow the right kind of network for the goals they seek to advance.

The kind of problem that educators face determines the kind of network they should build. Broadly speaking, we can divide the world of collective action networks into at least two kinds: sharing networks and execution networks. In a community whose overarching goal is sharing information, the coordination bar is set lower than in a community whose purpose is common action to achieve measureable improvements on a problem.

Sharing networks

In the education sector over the past decade or so, we’ve developed a great deal of experience in starting and maintaining sharing communities, like communities of practice. Members may engage in activities such as gathering and analyzing information about a problem, and individuals in the community may share solutions they’ve found. The raison d’être of sharing networks is to use collective energy to support individual action and agency.

One powerful example of a sharing community is the Math Forum (Herrick, 2009). In 1992, a visionary math educator named Gene Klotz recognized that math pedagogy needed to change. The research and practice community was learning that effective math pedagogy should be much more problem- and project-centered rather than involving a steady diet of worksheets, lectures, and drills. Yet teachers had few ways to access this pedagogy and associated materials. With support from the National Science Foundation, Klotz and his colleagues created the Geometry Forum, now known as the Math Forum (Renninger & Shumar, 2002; Renninger et al., 2004). These innovators saw great benefit in building a place where mathematics educators could talk about and share math ideas.

In many ways, sharing networks face what Nelson and Stolterman refer to as tame problems (2003). Tame problems are not necessarily easy. Tame problems may be complicated in that they may have lots of steps, take a long time to work through, and may even require some technical innovation along the way. However, these tasks tend to require less cooperation and coordination than execution networks, and they can usually be solved by selecting and applying a known algorithm.

For example, one tame problem in the math community was teachers’ lack of access to rich math problems. The Math Forum addressed this issue by identifying a sharing medium (the Internet) and creating easily accessible and structured materials — the Problem of the Week (PoW). PoWs are engaging math challenges designed to get students thinking, talking, and doing mathematics. Each PoW offers student and teacher materials, pedagogical assistance, and an opportunity for teachers to discuss the problems and their outcomes with one another.

The conditions and commitments of the Math Forum’s founding are straightforward. There was a visionary leader with a compelling idea — problem-based instruction — coupled to a persuasive information need and ready access to an audience. These are the primary ingredients necessary for a sharing network to emerge.

Execution networks

In execution networks, members collectively agree to accomplish some aim together — for example, raising achievement for some group of students by some specific amount by some specific time. We refer to a problem like that as a wicked problem. Execution networks — such as networked improvement communities (NICs) — are designed to tackle wicked problems (Mishra & Koehler, 2006). Because these problems don’t lend themselves to predetermined, straightforward procedures and simple social arrangements, they can lead to paralysis (Nelson & Stolterman, 2003).

Such paralysis has often led educators to recast wicked problems as tame problems. For example, when faced with the widespread failure of economically disadvantaged students to effectively engage with ambitious curricula, school districts have, on more than one occasion, dumbed-down those curricula, scripted them, and made them one-size-fits-all. They’ve taken a complex multicausal wicked problem and recast it as a straightforward one-dimensional implementation issue. Reframing the problem in this way avoids confronting the complexity embedded in the issue. When teachers are told to treat a wicked problem as a tame problem, they’re encouraged to ignore the multicausal nature of the failure. This leads, at best, to limited short-term progress for some and little long-term sustained improvement.

Tackling genuinely wicked problems requires social arrangements that encourage educators to appreciate the complexity they face and work toward the cooperation and coordination that sharing networks don’t typically afford. In contrast, NICs provide a social infrastructure that enables people to address wicked problems in a concerted manner. In sharing networks, improvement is a matter of individuals learning to improve their craft. Execution networks, on the other hand, are more akin to professional scientific communities.

Four defining characteristics of execution networks enable more effective common action to occur (Bryk et al., 2015). First, they rely on members adopting a well-specified common aim. Second, they’re guided by a common working theory of the problem and, in contrast to the sharing community whose members often have different theories and system views, NIC members have a shared view of the system that produces that problem. Third, NIC members use a common set of improvement methods to test and refine interventions and innovations. Taken together, these first three features create a common language for coordinating more effective collective efforts and promote consensus formation on specific research-based professional knowledge. Last, NICs are organized to diffuse innovations in an orderly way and promote ongoing learning about how to adapt interventions to the context.

NICs are an attractive arrangement to address wicked problems, in part because the pact among members is deeper and more binding than in sharing communities. The social arrangements in NICs allow people to do systems work where many parts have to work relatively seamlessly together. A NIC is purposefully structured to engage the close cooperation and systemwide coordination necessary to make headway on such problems.

Creating a NIC

On the basis of extensive qualitative research, Jennifer Russell and colleagues (Russell et al., in press) document the several domains of activity that need attention to initiate a NIC. They capture the key elements of NIC formation in a five-element framework (see Fig. 1). The framework divides the initiation activity into two broad domains: the technical underpinning that’s at the heart of improvement work and the social arrangements that enable people to work together.

The technical core

The inner technical core of the framework specifies the skills needed to accomplish the goal. At the center of the technical core is a problem of practice that’s articulated, documented, and explored through a theory of practice improvement that members understand and share. Members also share a common set of research tools and methods that allow them to explore the problem of practice. The work of the NIC on the problem of practice is further buttressed by a measurement system and analytics infrastructure. This aspect of the framework specifies the technical capabilities that must be in place for NIC members to collaborate for effective common problem solving. It also provides a setting that allows members to build a common language, which, in turn, enables the creation of important social structure.

Social participation

The outer rings of the framework provide the mechanisms needed to form social participation structures. The very outer ring addresses the idea that NICs require a shared culture among members. People have the will to stay the course in working toward an aim when they share common narratives for why they do what they do. For example, sports teams stick together in the lean times because they share stories about what makes the team and its approach to the game special. In a similar way, the framework suggests that common narratives and a common identity remind members what they value in the NIC, why they elected to become members, and why what they’re doing is more useful than how others might approach the issue. For example, a common narrative and identity would allow members to say that their network’s focus on problem-based math is superior to others’ focus on simple math drills.

The social substrate also encourages diverse actors to develop the will to engage in collective action on a commonly defined problem. Great leaders have figured out that it’s necessary for individuals from diverse settings to see that their identities have become bound to the problem at the center of the collective action effort. Decades of social science underscore the need to engage intrinsic motivation to get people to pay attention in sustained ways. From the perspective of the framework, aligning cultural norms, common work routines, and group feelings of identity promotes sustained attention.

k1611_1lead_gomez_fig1The second most outer ring in Figure 1 indicates that NICs need leadership resources and formal organization to advance their work. Beyond recruiting individual leaders with charisma, the NIC’s leadership has to decide which organizations and individuals to recruit. NICs need to select the right members who have the right sets of experiences to move the work forward in its early fragile stages. Further, NICs create organizational resources that identify the best research expertise from extant literature, and they develop a core analytic capacity to learn from the data and any results that members generate themselves.

A NIC takes off

Let’s look at the genesis of one networked improvement community, the Mathematics Teacher Education Partnership (MTEP) (LeMahieu, Edwards, & Gomez, 2015). W. Gary Martin, a leader in the mathematics education community, and Howard Gobstein, an executive vice president at the American Association of Public and Land-Grant Universities (APLU), are working to catalyze a NIC focused on the redesign of secondary mathematics teacher preparation programs (Martin & Gobstein, 2015). Their goal is to bring together university faculty and classroom teachers from participating school districts to meet the challenges of the Common Core State Standards for mathematics. In particular, they seek to develop strategies that help new teachers effectively and reliably implement ambitious Common Core learning tasks in their classrooms. This, then, is the problem of practice the members will come to share. The story of the formation of this partnership illustrates how catalyzing a NIC is different from forming a sharing community.

MTEP was conceived in 2011 at an APLU meeting that focused on the association’s aim to improve science and math teaching in secondary schools and at the beginning of college training. That APLU was the original convening agency is consistent with the framework shown in Figure 1. Among its 237 members are some of the nation’s leading higher education institutions. When APLU draws attention to improving secondary mathematics teaching, people listen.

The partnership didn’t begin as a NIC. At the start, it was a sharing network like the Math Forum. It was a loosely confederated collection of higher education institutions that had a shared interest in a set of mathematics education problems. In 2012, Martin and Gobstein encountered the networked improvement community idea. They realized that their loose confederation might have the social resources to form a NIC. For example, their partnership already had a process to identify and agree on major problem areas in secondary mathematics instruction. Martin and Gobstein realized they could build on common interests and preexisting social relations to ask some of their members to form a NIC. They drew together about 10 of their closest colleagues as a semiformal leadership team and began to think about how they could use the convening power of APLU and the social capital within their loose confederation to work toward forming a NIC.

The entire NIC comprised 38 higher education institutions and nearby local school districts. To coordinate and enhance the work, Martin and Gobstein came up with the notion of research action clusters (RACs) — that is, smaller subproblem-focused teams within the emerging NIC. Each cluster shared a commitment to developing common theory, illustrated in the driver diagram, shown in Figure 2 (Martin & Gobstein, 2015). The goal of the common theory is to tackle the aim by specifying what about the problem will be addressed by when. Moreover, each cluster would use the common theory to align itself with the subproblem most deeply felt in its locality. For example, one research action cluster focused on improving teacher retention rates in early-career secondary math teachers. This approach enabled each cluster to own a problem that was prominent for its local constituents; at the same time, its work would be coordinated within the greater NIC by a common theory.

k1611_1lead_gomez_fig2A look at its technical core

The innermost ring of the framework is its technical core; that’s where the NIC’s theory of practice improvement resides, along with shared research methods and its measurement and data analytics infrastructure. Martin, Gobstein, and their colleagues used driver diagrams as a way to visualize the cascade of actions that could, if the theory is on target, lead to the desired improvement. Martin and Gobstein encouraged members of the research action clusters to think through theory and represent their progress in these diagrams. The driver diagram that guides MTEP’s work is shown in Figure 2. In this way, they encouraged the NIC members as a collective to establish community norms anchored in research evidence and analytic arguments that could discipline theory and guide progress. With each cluster taking on some part of the large theory, members bond around this subset of common concerns.

k1611_1lead_gomez_fig3Martin and Gobstein also encouraged the research action clusters to use Plan-Do-Study-Act (PDSA) cycles as a common inquiry method (Cleghorn & Headrick, 1996). PDSA cycles are a disciplined way to engage in an improvement that guides iterative inquiry cycles. Each step in the four-stage process contains a set of actions. For example, in the Plan stage, where cluster members are testing a small innovation, they need to first record their prediction of what that innovation might result in before engaging in a change at the Do stage. When cluster members engage in common disciplined activity of this sort, it offers them an infrastructure that coordinates their activities and keeps them focused on the problem. The data that results from activity like this represent the first steps toward building common analytics and measurement systems. Martin and Gobstein were intentional about using these elements at the core of the framework. They realized at the start of the NIC that MTEP members were capable of sharing but needed help to move from sharing to common execution.

Collective action starts to take hold when diverse actors stop viewing a problem as someone else’s problem to worry about. In their book Switch: How to Change Things When Change is Hard, Chip and Dan Heath (2010) recognize how difficult it is to get people to start thinking in terms of “our problem.” In light of that fact, Martin and Gobstein realized that the work of the research action clusters would necessarily be slow and painstaking at the beginning. Organizers have to develop what historian, civil rights activist, and education reformer Charles Payne (2007, p. 243) refers to as a taste for “slow and respectful work.” Managers and designers must pay careful attention to cultivating an organizational ecology that supports members as they learn how to balance the complex concerns of collaborative work. For example, in the Mathematics Teacher Education Partnership, Martin and Gobstein realized that participants felt a tension between the tight problem focus of specific research action clusters and the broader concerns of the larger partnership. In response, in each of their large partnership meetings, they revisited their history, goals, and vision to keep the overarching purpose of the clusters in full view.

What complexity requires

Execution networks raise the bar for collaborative and coordinated work. Because they tackle wicked complex systems problems, they require more effort, and, specifically, a formal infrastructure that supports that work. Both sharing and execution communities are necessary. The important thing is for educators to decide which one of those networks works best for the goals they have in mind.

References

Bryk, A.S., Gomez, L.M., & Grunow, A. (2011). Getting ideas into action: Building networked improvement communities in education. In M. Hallinan (Ed.), Frontiers in sociology of education (pp. 127-162). New York, NY: Springer.

Bryk, A.S., Gomez, L.M., Grunow, A., & LeMahieu, P.G. (2015). Learning to improve: How America’s schools can get better at getting better. Cambridge, MA: Harvard Education Press.

Cleghorn, G.D. & Headrick, L.A. (1996). The PDSA cycle at the core of learning in health professions education. Joint Commission Journal on Quality Improvement, 22 (3), 206-212.

DuFour, R. & DuFour, R. (2010). The role of professional learning communities in advancing 21st-century skills. In J.A. Bellanca & R. Brandt (Eds.), 21st-century skills: Rethinking how students learn (pp. 77-95). Bloomington, IN: Solution Tree.

Heath, C. & Heath, D. (2010). Switch: How to change when change is hard. New York, NY: Broadway Books.

Herrick, M.J. (2009). The Math Forum: Measuring the aliveness of a community. In the proceedings of the 2009 Technology, Colleges, and Community Conference.

Hord, S.M. (1997). Professional learning communities: Communities of continuous inquiry and improvement. Austin, TX: Southwest Educational Development Laboratory.

Lave, J. & Wenger, E. (1991). Situated learning: Legitimate peripheral participation. New York, NY: Cambridge University Press.

LeMahieu, P.G., Edwards, A.R., & Gomez, L.M. (2015). At the nexus of improvement science and teaching: Introduction to a special section of the Journal of Teacher Education. Journal of Teacher Education, 66 (5).

Martin, W.G. & Gobstein, H. (2015). Generating a networked improvement community to improve secondary mathematics teacher preparation network leadership, organization, and operation. Journal of Teacher Education, 66 (5), 482-493.

Mishra, P. & Koehler, M. (2006). Technological pedagogical content knowledge: A framework for teacher knowledge. Teachers College Record, 108 (6), 1017-1054.

Nelson, H.G. & Stolterman, E. (2003). The design way: Intentional change in an unpredictable world: Foundations and fundamentals of design competence. Englewood Cliffs, NJ: Educational Technology Publications.

Payne, C.M. (2007). I’ve got the light of freedom: The organizing tradition and the Mississippi freedom struggle. Oakland, CA: Univ. of California Press.

Penuel, W.R., Coburn, C.E., & Gallagher, D.J. (2013). Negotiating problems of practice in research-practice design partnerships. National Society for the Study of Education Yearbook, 112 (2), 237-255.

Renninger, K.A. & Shumar, W. (2002). Community building with and for teachers at the Math Forum. In K.A. Renninger & W. Shumar (Eds.), Building virtual communities: Learning and change in cyberspace (pp. 60-95). New York, NY: Cambridge University Press.

Renninger, K.A., Shumar, W., Barab, S., Kling, R., & Gray, J. (2004). The centrality of culture and community to participant learning at and with The Math Forum. In S. Barab, R. Kling, & J. Gray (Eds.), Designing for virtual communities in the service of learning (pp. 181-209). New York, NY: Cambridge University Press.

Russell, J.L., Bryk, A.S., Dolle, J., Gomez, L.M., LeMahieu, P. & Grunow, A. (in press). A framework for initiation of Networked Improvement Communities. Teachers College Record, 119 (7).

LOUIS M. GOMEZ (lmgomez@ucla.edu) is a professor of education in the Graduate School of Education and Information Studies, University of California at Los Angeles, and a senior fellow at the Carnegie Foundation for the Advancement of Teaching, Stanford, Calif. JENNIFER L. RUSSELL (jrussel@pitt.edu) is an associate professor of education at the University of Pittsburgh and a fellow at the Carnegie Foundation for the Advancement of Teaching, Stanford, Calif. ANTHONY S. BRYK (bryk@carnegiefoundation.org) is president  and EVA M. MEJIA (mejia@carnegiefoundation.org) is director of network initiation and development at the Carnegie Foundation for the Advancement of Teaching, Stanford, Calif. PAUL G. LEMAHIEU (plem@carnegiefoundation.org) is senior vice president at the Carnegie Foundation for the Advancement of Teaching, Stanford, Calif., and on the graduate faculty at the University of Hawaii, Mãnoa.

R&D appears in each issue of Kappan with the assistance of the Deans Alliance, which is composed of the deans of the education schools/colleges at the following universities: George Washington University, Harvard University, Michigan State University, Northwestern University, Stanford University, Teachers College Columbia University, University of California, Berkeley, University of California, Los Angeles, University of Colorado, University of Michigan, University of Pennsylvania, and University of Wisconsin.

Originally published in November 2016 Phi Delta Kappan 98 (3), 8-15. © 2016 Phi Delta Kappa International. All rights reserved.