For the past five years, I have co-directed the Deeper Learning Dozen, a community of practice of senior school and district leaders from school districts across North America (US and British Columbia) focused on district transformation to support equitable deeper learning for each and every young person and adult. Using innovative theory and practice from the field about communities of practice as spaces for collective learning and practice change; complexity theories such as Cynefin, emergence theory, emergent strategy, and the Six Circle Model; equity and racial justice work from the National Equity Project’s Liberatory Design process and Caroline Hill’s equiryXdesign; cutting edge performance assessment systems design from the work of the Assessment for Learning Project and the Center for Innovation in Education; and deeper learning pedagogy along with trauma informed classroom and school culture practices from such organizations as Lead by Learning, Engaging Schools, and Adaptive Schools, and the SoLD folks; we created innovative, playful, and powerful learning spaces for adults to challenge and support the development of their transformational leadership.
We focused our work in the community of practice on three principles: 1) (In)Equity is Structural, (2) Adult Learning and Student Learning are Symmetrical, and, (3) Leadership Accelerates Emergence.
Note: I wrote this essay in April of 2018 at the beginning of the work to create the Deeper Learning Dozen. I might change a few words around, but for the most part, it all still rings true.
Fullan (2016) and Elmore (unpublished) both tell us that systemic improvement will not occur simply from the development of individual teacher or leader capacity; it results from a strategic focus on the growth of collaborative capacity, the ability of adults to work together in sustained and complex interactions, focused on the ongoing improvement in the quality of their practice. That adult work must mirror the complexity of the interactions that they wish their students to experience in the instructional core, which Elmore refers to as “system symmetry.”
Elmore emphatically states that we must focus our effort on improvement in the quality of practice and experience in the instructional core first, and only much later on student achievement. Change in the instructional core will happen only if the kind of change in adult collaborative learning described above is strategically led in educational organizations. We believe that ongoing communities of practice in expanding dense social networks creates the kind of settings where this change in adult collaborative learning can occur.
What we need is an emergent and qualitatively different learning and leadership experience of participants that results in emergent and qualitatively different practices and actions.
The Learning Model:
Communities of Practice, the “curriculum,” that is, the focus of the collective learning, emerges in communities of practice through an inductive process of development:
The Growth Model:
We focus on the development of Collaborative Capacity and System Symmetry (“Quality first, then scale”). Communities of practice emerge and expand among an innovative core of people, with appropriate support and guidance. At their periphery, a community of engagement can be nurtured, people interested in the innovators’ work and potentially wanting to try out some ideas. Further “out,” a community of interest can develop that should be kept informed and increasingly engaged as they are ready (David Albury). See below for more on this idea of nested communities.
This raises the question of the need for more broadly distributed dense social networks, and ongoing networks, beyond periodic summer institutes and professional learning convenings, within which sustained relationships might develop, and teacher and leader professional growth and collaborative capacity building might occur and continue to develop. Social network theory, rethinking how community-based organizations can more effectively meet the needs of their communities, identifies key principles for network-driven improvement (Making Connections – Denver Social Network Project, 2007):
The Change Model
Implicit in both the ways in which “curriculum” (that is, the focus of the collective learning) develops in communities of practice and “growth” (scaling) occurs in social networks is the idea of emergence. Emergence is an inductive process of development, not a deductive one, that, to quote the work of Meg Wheatley and the Berkana Institute, “names, connects, nourishes, and illuminates,” “making visible the possibility of abandoning the old and jumping to the new.” This involves “hospice work, pioneering, and illuminating… and quietly protecting the space for those who are doing the pioneering work.” Inductive learning processes in social networks cannot be designed with pre-determined curriculum or assessed with pre-determined metrics for growth and impact. They must be facilitated with an eye to nurturing emergent ideas and involvements, that are “controlled and designed from the bottom-up,” where the focus of learning emerges in the social interaction of participants, and growth is driven by densely networked interactions of participants’ demands as they learn. This requires a fundamental change in the culture of learning from how educational organizations have traditionally structured or measured that culture…
This is why we quote Fullan et al. on Changing the Culture of Learning:
“The change lesson here is that we need to change the culture of learning not simply the trappings or structures. It cannot be done by policies or mandates. Transformation will only occur when we engage in the work of facilitating new processes for learning [our bolding here]. Once we have agreed on the [student] learning outcomes or competencies described earlier in this chapter, we need to provide rich opportunities to: work collaboratively; build new learning relationships; and learn from the work. No amount of pre-planning is better than the common experience of learning together while doing the work, because it builds capacity and ownership simultaneously. Simply put, we learn more from doing than thinking about doing so if we want deep learning we need to get started [our bolding here]. Thus, leadership for change is crucial—leadership that comes from all quarters” (Fullan, Quinn, McEachen, 2018 page 26).
What Fullan et al. are describing is exactly the paradigm shift that is needed and that communities of practice embedded in dense networks can provide. Thus, when we think about the learning environment we want to create, we are thinking about an emergent curriculum and emergent knowledge and skills shared within communities of practice, driven by the participants, and distributed through mutual exchange across wide networks of communities of practice that grow based on the demand of participants, not by any predetermined mechanism of control. The metrics are qualitative, not quantitative.
Terry Bailey, The Piton Foundation. Ties That Bind: The Practice of Social Networks.
Richard Elmore. Chapter Two: The Strategic Turn in School Improvement.
Fullan and Quinn. Coherence.
Fullan, Quinn, and McEachen. Deep Learning: Engage the World, Change the World.
Hi Howard, The Piton Foundation. Four Principles of Social Networks.
Meg Wheatley, The Berkana Institute. Our Theory of Change. http://berkana.org/about/our-theory-of-change/
Peggy Holman, Engaging Emergence
Beyond Communities of Practice and Social Networks, is the idea, developed by David Albury, of “nested communities.” Albury describes three nested communities that are the focus of different kinds of strategies, and have permeable boundaries between them: at the center, and involving the early adopters and increasingly apprenticing others into it, is a Community of Practice (the protected space of pioneers, in Wheatley’s terms). The next layer out is a Community of Engagement, where those who might want to try out some of the ideas of the pioneers as they see the pilots and prototypes happening. Further out is the Community of Interest, people who need to be kept in the information loop and in relation to the others, who may take awhile to adopt the new ideas, but must not be left out of the process.
There’s a blog about applying them in a school project in Australia here: https://www.innovationunit.org/thoughts/trapped-on-site-the-problems-of-scaling-powerful-new-practices-in-australian-schools-and-beyond/
And he wrote a little more about it here in a piece on healthcare: https://www.innovationunit.org/wp-content/uploads/2017/04/MYTHS-AND-MECHANISMS-1.pdf
(The “scaling innovation” frame is rather a different one from organization/system change, but there may be some interesting overlap).
Everywhere these days you see schools and non-profits being asked to prove that they are getting results by gathering and presenting data… tons of data. Foundations want to know that their investments are paying off. State and Federal Education Agencies want to assure that all children are learning. Businesses want minute to minute analytics and dashboards for their shareholders. We don’t seem to question this increasingly urgent push to having access to more and more data about every aspect of our work. And yet, as the data pile up, we feel more and more inundated with data, a veritable tsunami of data, and we wonder if we really can make sense out of it all, in any meaningful way.
Many non-profts and schools are facing an increasing feeling, and reality, of data overload. Teachers feel beat up with data. Particularly in public education, we seem to use data more as a hammer than anything else. And yet, almost everyone wants more data. Almost no one is asking, “To answer what questions?” Even harder, “What data do we really need to answer those questions?” And, “How would we know if those data actually answered our questions?” Let me make an emphatic point: That we have access to more data than ever does not mean that we can necessarily answer important questions about the effectiveness of our schools and other organizations any better, nor does it mean that we have to use, or even can use, all of those data for some important purpose.
As we now know (and many were saying all along), over a decade of time and huge sums of money were invested in No Child Left Behind, mostly on the questionable strategy that state standardized tests used for accountability would improve student achievement. This massive effort resulted in only modest gains in some places, while at the same time demonizing and demoralizing teachers and schools, and setting them up as targets of reform rather than putting that time and money into developing their professionalism and their professional associations’ capacity to raise their own standards of practice (as a recent article by Jal Mehta in the Harvard Ed Review notes). A similar frenzy seems to be gripping the foundation and non-profit world, to produce more and more data about the programs funded by the foundations. In a parody of this frenzy that is not too far from the truth, non-profits could end up spending more time reporting on their work than actually doing it. It is certainly true that many felt the hours and hours of test prep and testing that we did in education for NCLB, not to mention the narrowing of the curriculum just to focus on what the tests were supposedly measuring, represented a sad waste of time and distraction from real learning. This is not a sustainable system.
So am I saying that data are not useful? Absolutely not! Data can help provide a compass, guiding us with a north star and a bearing toward where we want to go. Data can act as a roadmap (as long as we remember that the map is not the territory!). Most important, data can serve as part of a reflective cycle of inquiry, a cycle of continuous improvement, at all levels in the educational system, and in our non-profits. However, we will want to consider carefully what questions we want to address and what data will meaningfully and effectively address those, as we shift toward a more balanced use of data. And we will want to explore what sorts of evidence we really need to address those questions. We will want to expand our notions of what counts as data at the same time that we are pruning back our massively overgrown data “tree.” And we will want to consider some ways that we think about and engage with data as well. It’s not just a technical question we are addressing.
So, first of all, we need clarity on our questions, and on who is asking them, and on their purposes. Are we exploring a classroom or other learning experience, or a whole school’s effectiveness? Are we looking at program effectiveness? Are we determining the extent to which organizational systems are well matched to program processes and desired outcomes or accomplishments? Are we examining leadership? Are we prototyping a new process or product?
And then, to borrow from Habermas, we might consider data to have a technical aspect, a social or practical aspect, and a critical aspect.
Some technical questions we will want to ask are:
Some social/practical questions we will want to ask are:
Some critical questions we will want to ask are:
If we work to become clear about the Theory of Action of our program or non-profit or educational project (how do we see the resources we have and our choices of what we do as leading to the outcomes or accomplishments we want?), then we have a solid place to begin to craft good questions about our work that can drive good choices of data to use in our assessment, in our quest for continuous improvement, using a cycle of inquiry. That inquiry provides a setting for us to engage as professionals in collecting useful data about our work, analyzing those, making meaning out of the analysis, choosing practices that will help us improve, fine tuning our work, and building a higher quality knowledge base to drive our practice. This embedded reflection and knowledge stewardship is at the heart of real improvement.
So, again, I ask, are you a fan of big data? If so, what is your question? Taking into consideration what I have said above, you may find yourself using less data, but getting more out of it. That would be sustainable.