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90-Day Improvement Cycle Handbook: Carnegie Foundation

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90-Day Improvement Cycle Handbook: Carnegie Foundation

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Bryk AERA Lecture on Improvement Science

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Bryk AERA Lecture on Improvement Science

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Managing for Change: Evaluation of the Networks for Improvement Initiative Funded by the Gates Foundation - first 2 years

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Managing for Change: Evaluation of the Networks for Improvement Initiative Funded by the Gates Foundation - first 2 years

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Gates Foundation Networks for Improvement Grant Program

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Gates Foundation Networks for Improvement Grant Program

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Networks for School Improvement (NSI) 2020 Update

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Your browser appears to be unsupported. Because of this, portions of the site may not function as intended.

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Book: Improvement In Action - Advancing Quality in America's Schools

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Book: Improvement In Action - Advancing Quality in America's Schools

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Improvement in Action Advancing Quality in America's Schools

Anthony S. Bryk

Request an Examination Copy

Improvement in Action, Anthony S. Bryk's sequel to Learning to Improve, illustrates how educators have effectively applied the six core principles of continuous improvement in practice. The book highlights relevant examples of rigorous, high-quality improvement work in districts, schools, and professional development networks across the country.

A must-read for educators who aim to put the principles for continuous improvement into action, transforming their organizations in the process. The six diverse case studies of successful improvement efforts provide vivid images of what it means to live the improvement principles. Taken together, the cases offer concrete, actionable insights into the core aspects of improvement work that can inform readers' pursuit of ambitious improvement goals. - Paul Cobb, research professor, Vanderbilt University

In Learning to Improve, Anthony Bryk boldly challenged educators to adopt and adapt modern, scientifically grounded principles of improvement. Now, in Improvement in Action, he offers six textured case studies that bring the theory to life in ways invaluable for anyone who wishes to accelerate toward profoundly better educational systems. In this, Bryk extends his legacy as one of the most important education change agents of his generation.- Donald M. Berwick, president emeritus and senior fellow, Institute for Healthcare Improvement

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Improvement in Action Advancing Quality in America's Schools Anthony S. Bryk Request an Examination Copy Improvement in Action, Anthony S. Bryk's sequel to Learning to Improve, illustrates how educators have effectively applied the six core principles of continuous improvement in practice.

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Carnegie Paper:  The Social Structure of Networked Improvement Communities

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Carnegie Paper:  The Social Structure of Networked Improvement Communities

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Sample Driver Diagram: Advanced Science Instruction

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Sample Driver Diagram: Advanced Science Instruction

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PPT from Study Group with Sample Driver Diagram revised 7/19 (view full post to edit)

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How do you use a Driver Diagram?  (Healthcare)

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How do you use a Driver Diagram?  (Healthcare)

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Learning Objectives: At the end of this activity, you will be able to:

Define the phrase "causal pathway."

Explain the relationship between a driver diagram and a PDSA cycle.

Discuss why driver diagrams are useful to quality improvement work.

Differentiate between primary and secondary drivers.

Description: If you're embarking on an improvement project, it's common to want to start testing changes right away. You have an aim, and you want to achieve it! But how do you know the change you are making will help you achieve your aim?

Enter the driver diagram. A driver diagram, explains Don Goldmann, MD, IHI's Chief Medical and Scientific officer, is a "simple, visual, somewhat intuitive display to help you understand where you're going with your work." Goldmann's latest Open School Short explains the purpose and value of a driver diagram - a tool that can help you with anything from losing weight to protecting your patients from infection.

After you watch the video, get more improvement knowledge from Goldmann in PDSA Cycles: From CLABSIs to Cucumbers.

1. What is the causal pathway and how does it apply to improvement work?

2. Why is it important to have a visual display of a system before embarking on improvement work?

3. What's the difference between a primary driver and a secondary driver?

4. Have you ever created a driver diagram at the beginning of an improvement project? Did you find it helpful?

5. Come up with your own personal improvement project - getting to work on time or losing weight, for example - and create a driver diagram with primary and secondary drivers. Did you find some changes you could test?

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A driver diagram, explains Don Goldmann, MD, IHI's Chief Medical and Scientific officer, is a "simple, visual, somewhat intuitive display to help you understand where you're going with your work."

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National Health System - Constructing a Driver Diagram

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National Health System - Constructing a Driver Diagram

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Driver diagrams are a visual display of team's ideas for what will "drive" or support the project aims. Driver diagrams are a type of chart with three or more levels.

These include:

An aim (the project's goal)

Primary drivers (High level factors that you need to consider or influence to achieve your aim)

Secondary drivers (Factors that underpin your primary drivers. Secondary drivers are linked to your project activities also known as 'change ideas')

Change ideas (These are the ideas for changes you plan to test to support achieving your aim; they can be linked to one or more secondary drivers)

Driver diagrams provide a 'theory of change' and fulfil a range of functions:

Support a team to explore what they think needs to be looked at in order to achieve their goal (aim)

Consider how factors are linked

Act as a tool to be able to summarise the project's change strategy

Support you to establish how you will measure your aim.

Remember that healthcare improvement projects function in a complex system, it is unlikely that a single person has a clear view of the entire system. When developing your driver diagram, enlist the support of team members who are familiar with the system you are trying to change. Remember you should always include service user input when developing your project.

Building a successful driver diagram:

Decide on your project's goal. This is your aim. Your aim should be specific and measurable. Refer to the section on Developing your aim for more information.

Identify high level factors and important areas that need to be considered to achieve your aim. These are your Primary drivers.

Secondary drivers are the 'influencers' of Primary drivers, you can establish your secondary drivers by identifying activities which influence your Primary drivers. Secondary drivers can link to one or more Primary drivers.

Consider your change ideas carefully. These are the ideas you will put in place to change the system. They will form your Plan-Do-Study-Act cycles (PDSA) and become part of your project plan.

Once you have your change ideas and a completed driver diagram you are ready to start testing your change ideas in PDSA cycles.

This template can be used to draft your driver diagram.

You might be interested in:

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These include: An aim (the project's goal) Primary drivers (High level factors that you need to consider or influence to achieve your aim) Secondary drivers (Factors that underpin your primary drivers.

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Institute of Education Sciences - Continuous Improvement Process Overview

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Institute of Education Sciences - Continuous Improvement Process Overview

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Presentation on how to construct a driver diagram for healthcare

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Carnegie Foundation for the Advancement of Teaching

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Learning to Improve Glossary | Carnegie Foundation for the Advancement of Teaching

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This glossary organizes a selection of key terms used in the book, Learning to Improve: How America's Schools Can Get Better at Getting Better, that

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Overall, we discussed that the plans seem:
1. Too broad
2. May be too scattered
3. Incorporated assessments but did not detail what should be done with the data (didn't specify how teachers would analyze the data, or how the student instruction would be organized following the assessments, except for general references to Saturday school, or pull out)
4. Missing reference to standards or curriculum

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I'm seeing action plans that appear to broadly define ELA baseline analysis and instructional planning.

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Focusing the action plan on the priority need and root cause

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Focusing the action plan on the priority need and root cause

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Bronx Collaborative's action plan seems too broad and doesn't include monitoring for completion of the steps, where Health Sciences and Olympia are more focused and do include monitoring

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A problem of practice may to to build alignment.  I see several alignment issues:
*Internal coherence (what is the theory of action?)
*Alignment with standards
*Alignment with specifically tested Regents skills (this can be aligned with standards as "assessed standards"
*A line of development that can be seen from beginning to end

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KQED: How to Plan and Implement Continuous Improvement in Schools

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KQED: How to Plan and Implement Continuous Improvement in Schools

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The basic tenets of the process involve understanding the problem, defining a manageable goal, identifying the drivers that could help reach that goal, and then testing small ideas to change those drivers. When done in a network, this cycle of improvement is expedited as various participants test different change ideas and share their findings with the group. Through a constant interplay of these elements a few change ideas will rise to the top and can be scaled across a system.
UNDERSTANDING THE PROBLEM
Many of the biggest problems of practice have been around a long time and aren't easy to solve. Too often when trying to improve something leaders jump to solutions before properly examining the problem. Understanding the problem requires valuing many types of knowledge. It means doing empathy interviews with participants in the system including teachers, staff, parents, and students. It involves bringing the best research literature to bear on the problem. And sometimes representing the processes involved in the problem can illuminate areas that are breaking down.

Biag said this stage is crucial and shouldn't be rushed. He's seen improvement projects that require up to a year of study to fully understand the problem, its root causes and the levers of change available to leaders. Often an improvement network will know it's time to move on when participants feel saturated -- they aren't turning up any new perspectives or information.

"Sometimes it's good to stop doing the research and try something," Biag said. Implementing some change ideas often helps inform the problem and may even necessitate that the team revisit and revise the problem statement.
DEFINE THE GOALS AND FOCUS COLLECTIVE EFFORT
Once the group has a "good enough" understanding of the problem it's crucial that they write a clear, succinct aim statement. It should be specific, measurable and focus on a challenging problem, but it should be doable.

The crucial question, Biag said, is "What's within your span of control and what's not? So when you act on this problem you aren't wasting your time on the things that aren't in your control."

He often sees people define the problem too broadly. If the problem is an achievement gap between student populations, a group might say the root problem is inequality or poverty. Those things may contribute to the problem, but they aren't within the control of teachers or principals or even districts to solve. A more manageable aim statement might be: "By June 2020 we're going to increase from 45% to 90% the number of male students enrolling in credit bearing math courses at community colleges."

"It has to be motivating enough for people to continue working on it for several months," Biag said about the reach goal. But it must be specific and concrete enough that the group can see if change ideas are helping progress towards the goal.

"While an aim statement can look deceptively simple, you need to build trust and get on the same page with everyone in your network to even agree on where to focus your efforts," Biag said. The network itself is important because it accelerates the pace of learning about potential solutions.

Once the aim is clear, the group brainstorms three to five primary drivers of the problem. These are the things the group believes provide the most leverage to meet the goal, and that are within the span of control. It's crucial to only have a few of these, not twenty, because the network must work on all of them in tandem. Staying focused allows for more progress.

After identifying the most important drivers, network participants brainstorm change ideas that might affect those drivers. "The word change is very specific to improvement science," Biag said. "It means an actual change in how you do work." In other words, the focus is on the process and results in action. Change ideas are not things like "more money" or "more staff." "It's an actual change of a process or the introduction of a new process," Biag said.
TEST AND BUILD EVIDENCE
Once the group has a good understanding of the problem, its root causes, what drives it and some ideas that will directly affect those drivers, it's time to start testing them. Carnegie uses a "Plan, Do, Study, Act" (PDSA) cycle for testing ideas. The changes should be fairly small and the tester collects data along the way. It doesn't have to be complicated data, just something to help analyze and track whether the change is moving the needle.

"Most schools and districts plan plan plan, then do, and then they never study," Biag said. He advocates that planning include a prediction because participants are more likely to compare a new strategy with the expected effect. If the change idea didn't function as expected there's a lot to learn there.

Many of the best change ideas come from looking at what Carnegie calls "positive deviants" -- the bright spots in a network. For example, if a network sets the aim of improving college readiness for English language learner students, when leaders are assembling their knowledge base they should talk to teachers who seem to be achieving better than average results with that population. Those teachers are "positive deviants" and networks should try to learn from the ways their practices differ from colleagues.

For example, High Tech High Charter Network leaders identified that they wanted to increase the number of African American and Latino males applying to four-year colleges. When they looked at drivers, they realized school attendance was lower for this group and hypothesized that the way teachers communicated with parents might be part of the issue. To try to eliminate variation in parent-teacher communication they tested a change theory that involved using a set of protocols for interacting with families.

They went through several iterations of the protocols, but when they hit on one that seemed to work they spread it throughout their network of schools. Now, when teachers meet with parents around achievement or discipline they all try to make it positive, share data about the student, and co-construct an action plan with the parent, among other things.

The key thing about working in a network is that different people can be trying different change ideas and sharing their data. "The idea is that you're not all working on all the same things at the same time," Biag said. "So you leverage the network, and the power of the network, to increase change ideas."

Some ideas won't work and will be abandoned. Others might seem promising, but more data is needed, so others in the network might try them too. Over time the change ideas that seem to really impact the drivers rise to the top.

"As you're testing and building evidence you're going to find ideas that work and then you can talk about spreading those ideas," Biag said.
SPREAD AND SCALE
Even with the best ideas implementation can be hard. Biag said leaders need to weigh several factors when thinking about how to spread an idea that seems to work. How costly will it be to implement? What are the consequences of failure? How reluctant are the people involved? How confident is the leader in the change idea?

For example, if the change is a parent meeting protocol and the leader doesn't think it's a great idea and that the cost of failure will be high, perhaps she only tests it on her sister first. But, if teachers are ready for the change and there's nothing to lose, then maybe the idea can scale up more quickly. This is where knowing one's own system and culture becomes important.

It's also worth thinking about who within the system needs to be on board for the plan to go well. Those folks can be powerful advocates if convinced that the change idea is a good one. "The best people are those who were pretty skeptical in the beginning and you were able to change them," Biag said.

Another strategy is to roll out the idea with those eager to try it and then demonstrate success to those who are more fearful. It's also necessary to be humble and willing to go back and test new ideas if the ones that seemed to work in the smaller group don't work when scaled. Perhaps the aim statement needs to change, or maybe the drivers aren't actually the most impactful.

"Our theory is possibly wrong and definitely incomplete; that's kind of a Carnegie saying," Biag said. He doesn't want anyone to think this process is linear, rather it's a cycle. And when people get comfortable with the cycle they build it into everything they do naturally. The biggest strength of continuous improvement is that it offers a path for systemic change, a way to build the capacity within the system, rather than building whole new systems.

"What we're trying to do is implement these tools and ways of thinking to empower people to engage in this work," Biag said. And that means having a bias towards action.

"You have to start before you feel ready. Your understanding of the problem will change over time and when you act on that problem the problem will change and so your understanding of that problem will change," Biag said.

People learn how to think about continuous improvement through the process of doing it. They get better at narrowing in on motivating, but achievable aim statements. They learn to include more voices in the information gathering stage. The "Plan, Do, Study, Act" cycles become second nature, and analyzing data gets less scary.

Perhaps one of the best parts of continuous improvement is that it helps empower those within a system to see themselves as the drivers of change. The ideas come from practice as does the data. And while data is often associated with accountability requirements, this improvement process offers practitioners the opportunity to think about and evaluate data that are important to their practice.

In this process, the data is only worthwhile if it shines light on whether the change is working. And when data is used this way, it's easier for educators to be transparent about what they're seeing. Improvement is not about judgement, it's a constant, normal aspect of professional life.

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How to Plan and Implement Continuous Improvement In Schools

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The basic tenets of the process involve understanding the problem, defining a manageable goal, identifying the drivers that could help reach that goal, and then testing small ideas to change those drivers. When done in a network, this cycle of improvement is expedited as various participants test different change ideas and share their findings with the group.

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Clinical Excellence Commission - Driver Diagrams

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Clinical Excellence Commission - Driver Diagrams

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A driver diagram is a simple, visual tool that will assist you to systematically plan and structure your improvement project. It will help you understand the logic of your project and where you are going with your improvement initiative. It is a living document that can be updated at every team meeting where drivers and change concepts can be discussed and agreed upon.

Overview

A driver diagram organises information on proposed activities so the relationships between the aim of the improvement project and the changes to be tested and implemented are made clear. A driver diagram is set out using columns consisting of:

An Aim Statement - outlining the project goal or vision. The aim statement is derived from the problem you are trying to address i.e. "What are you trying to accomplish?" (first questioned from The Model for Improvement)

Primary Drivers - are high-level factors that you need to influence in order to achieve the aim. They are improvement areas that must be addressed to achieve the desired outcome. Primary Drivers should be written as straightforward statements rather than as numeric targets.

Secondary Drivers - are specific factors or interventions that are necessary to achieve the primary drivers. They are targeted areas where you plan specific changes or interventions. Each secondary driver will contribute to at least one primary driver (drawn using 'relationship arrows'). They should be process changes that you have reason to think will impact the outcome (should have an evidence base). They should be necessary and (collectively) sufficient to achieve the aim. The secondary drivers are found by brainstorming the causes of the problem.

Change Ideas - are well defined change concepts or interventions to address the secondary drivers i.e. what exactly are you going to do to and how are you going to do it. Each change idea will contribute to at least one secondary driver (drawn using 'relationship arrows'). The change ideas address the question in The Model for Improvement "What change(s) can we make that will result in improvement?"

Prioritisation of Change Ideas - All change ideas need to be assessed to determine which ones you will test as a priority via a Plan Do Study Act cycle (PDSA). For each change idea, determine if it will have a high or low impact on the aim, and whether it will be easy or difficult to implement.

Measures

It is important that you measure the impact of your improvement project ie: How will you know if a change is an improvement? (the second question from The Model for Improvement). A driver diagram will help you determine outcome, process and balancing measures by focusing on

Summary

A driver diagram is a tool for planning an improvement initiative. It will help teams stay focused and on course when they are used as regular references for improvement work. A driver diagram will also help to define which aspects of the system should be measured and monitored to see if the changes and interventions are effective, and if the underlying causal theories are correct. A driver diagram should be updated regularly as the team acquires new knowledge and experience.

A driver diagram can assist in your improvement journey by:

Reinforcing the desired project outcome, or aim

Providing a simple visual tool for explaining the project's purpose and showing how the project activities will deliver that aim

Helping a group to explore the factors (drivers) that they believe need to be addressed in order to achieve a specific overall goal or result

Showing how the factors (drivers) are connected

Defining the key leverage points (drives) in the system

Acting as a communication tool to explain a change strategy

Linking the specific project activities and changes (the "How's") to key components in the system

Helping define how project progress and results should be measured and monitored

Facilitating stakeholder buy-in and commitment to the changes that the project will require.

Figure 1: Example of a completed driver diagram

Figure 2: Conceptual view of a driver diagram

Driver Diagram Webinars - An introduction to Improvement Science

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A driver diagram is a simple, visual tool that will assist you to systematically plan and structure your improvement project. It will help you understand the logic of your project and where you are going with your improvement initiative.

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The Six Core Principles of Improvement

1. Make the work problem-specific and user-centered.

It starts with a single question: “What specifically is the problem we are trying to solve?” It enlivens a co-development orientation: engage key participants early and often.

2. Variation in performance is the core problem to address.

The critical issue is not what works, but rather what works, for whom and under what set of conditions. Aim to advance efficacy reliably at scale.

3. See the system that produces the current outcomes.

It is hard to improve what you do not fully understand. Go and see how local conditions shape work processes. Make your hypotheses for change public and clear.

4. We cannot improve at scale what we cannot measure.

Embed measures of key outcomes and processes to track if change is an improvement. We intervene in complex organizations. Anticipate unintended consequences and measure these too.

5. Anchor practice improvement in disciplined inquiry.

Engage rapid cycles of Plan, Do, Study, Act (PDSA) to learn fast, fail fast, and improve quickly. That failures may occur is not the problem; that we fail to learn from them is.

6. Accelerate improvements through networked communities.

Embrace the wisdom of crowds. We can accomplish more together than even the best of us can accomplish alone.

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Carnegie Foundation Resource: Overview of Improvement Science in Education

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Carnegie Foundation Resource: Overview of Improvement Science in Education

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Carnegie Foundation for the Advancement of Teaching

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Addressing complex educational problems using positive deviance requires detective work. The task: to discover "outliers" who have succeeded under conditions where most others fail; uncover the strategies they use; and design opportunities to share those strategies.

Three up-and-coming networked improvement communities share common "messy" challenges and helpful advice at Carnegie's 2017 Summit on Improvement in Education.

Due to the evolving situation around COVID-19, the seventh annual Carnegie Summit was held as a virtual conference on April 1-3, 2020.

The Carnegie Foundation is pleased to join the University of Michigan School of Education and edX in announcing the creation of a new certificate program in improvement science and networked improvement communities.

This glossary organizes a selection of key terms used in the book, Learning to Improve: How America's Schools Can Get Better at Getting Better, that have formal meaning.

The Evidence for Improvement approach described in this paper is designed to enhance a network's internal learning processes and, in turn, lead to more positive impacts for educators and students. It has implications for improvement practitioners, evaluators, and funders.

Using ideas borrowed from improvement science, Learning to Improve presents a process of disciplined inquiry that can be combined with the use of networks to identify, adapt, and successfully scale up promising interventions in education.

This essay proposes science of improvement research and the idea of a networked improvement community as an alternative R&D method to create the purposeful collective action needed to solve complex educational problems currently faced.

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Our Ideas | Carnegie Foundation for the Advancement of Teaching

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Addressing complex educational problems using positive deviance requires detective work. The task: to discover "outliers" who have succeeded under conditions where most others fail; uncover the strategies they use; and design opportunities to share those strategies. Three up-and-coming networked improvement communities share common "messy" challenges and helpful advice at Carnegie's 2017 Summit on Improvement in Education.

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Carnegie Summit: Starting Strong: Tools and Processes to Launch your Improvement Journey

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Carnegie Summit: Starting Strong: Tools and Processes to Launch your Improvement Journey

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*Video: Carnegie Summit Presentation

*Slides: Tools and Processes to Launch Your Improvement Journey

*Tools to Use with Teams

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"Accelerating How We Learn to Improve" AERA 2014 Distinguished Lecture, Anthony Bryk

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"Accelerating How We Learn to Improve" AERA 2014 Distinguished Lecture, Anthony Bryk

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*Accelerating How We Learn to Improve
This article provides a helpful introduction to the history and logic that frames the value of improvement science for education.

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This article describes the use of the positive deviance approach to locate and learn from promising practices.

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Carnegie Foundation for the Advancement of Teaching

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Editor's note: A recent special issue of Quality Assurance in Education explores seven different improvement models being used in schools today. Beginning in February of this year, the Carnegie Foundation began publishing summaries of each of the models on the Foundation's blog, including process, examples, and pros and cons. The following post provides a summary of positive deviance. To learn more about this improvement method, please see "Positive Deviance: learning from positive anomalies," by Paul G. LeMahieu of the Carnegie Foundation, Lee E. Nordstrum of RTI International, and Dick Gale with the Institute for Teaching of the California Teachers Association. We hope that these summary blog posts will whet your appetite to delve more deeply into the journal itself.

Unlike the other improvement approaches described in this series, positive deviance (PD) is not a method with its own unique tools, principles, and behaviors, but rather an approach to improvement characterized by uncovering and adapting resources and activities used by organizations, communities, or individuals that succeed in the face of great odds. These outliers, or "positive deviants," manage to overcome complex problems and significant adversity where others who are similarly situated continue to struggle.

The method was first practiced in 1990, when the non-governmental organization Save the Children was invited by the government of Vietnam to create a program to address the problem of malnutrition in poor villages. Drawing on previous work by researchers at the Tufts University School of Nutrition, members of Save the Children visited the homes of children who were poor yet well-nourished ("positive deviants"), where they observed and identified hygiene and mealtime behaviors that seemed to be making a difference. They later shared these practices and strategies with other members of the community. The positive deviance approach has also been used to address problems such as neo-natal mortality, criminal recidivism, and many issues related to education.

Fundamentals of the Model

Rather than work to identify a problem, analyze the underlying causes, and implement effective practices, practitioners of PD assume that some individual or organization within the community has already done these things, either explicitly or intuitively. The role of PD is to conduct a strategic search to find and learn from these positive deviants.

Once the positive deviant, or outlier, has been identified, a PD team led by a facilitator conducts a thorough investigation into the outlier's behavior, using interviews and observation to identify which practices produce strong results. The team then determines how to spread this information to others who need it. There are four phases to the positive deviance process:

1. Defining the problem and the desired outcomes, and reframing the problem positively;

2. Determining the presence of positive deviants by using data collection and observation to identify similar organizations that appear to have overcome similar problems;

3. Discovering the uncommon and successful practices and strategies used by the positive deviants identified in phase 2 through inquiry methods;

4. Designing opportunities to spread knowledge in practice.

Two additional phases of work are sometimes included in the model: discerning or monitoring the spread of knowledge to others, and disseminating results to external audiences by amplifying success stories.

Positive Deviance in Action

Defining the Problem: This method is best suited to problems in complex social settings that appear to be intractable and therefore require sometimes profound behavioral or social changes. Problems are often first defined by the people they affect. When positive deviance is applied, it should reframe the problems in a positive manner. So, for example, rather than ask why so few academically at-risk students graduate from high school, ask instead what behaviors and strategies are used by the academically at-risk children who do persist until graduation. This approach focuses the community on identifying the positive deviants that exist in their midst.

Merced High School, a comprehensive high school in California's Central Valley, provides a partial illustration of the PD approach. In the 2008-2009 academic year, Merced High graduated only 80 percent of its seniors, below the national average. The reasons for Merced's low graduation rate were well known within the community and had resisted numerous change efforts: unemployment in January of 2009 was at 17 percent, with 60 percent of families living at or below the poverty level. The district had a high percentage of non-English speaking students, many of whom were responsible for caring for younger siblings and working to help support their families. And just 20 percent of students completed the courses required for admission to California's two university systems.

Problems are often first defined by the people they affect. When positive deviance is applied, it should reframe the problems in a positive manner.

Discovering Positive Deviants: The school applied to be part of a Positive Deviance Initiative led by the California Teachers Association's Institute for Teaching. Eager to get going, Merced High quickly trained a core team that began planning its strategy for identifying positive deviants, meaning students at high risk for dropping out who persisted despite their challenges. They discussed the challenges students face on the path to graduation and learned how to talk with students about these obstacles. In the spring of 2009, the team began conducting video interviews with at-risk students who were beating the odds to understand their experiences and learn about the strategies they used to keep up with their schoolwork.

Identifying Uncommon but Successful Practices: PD assumes that externally developed solutions imported into the community are not as effective as those that arise internally. Community members themselves enact and improve on the positive deviance approach. Through observation and discussion with various community groups (as well as through action techniques such as mapping and diagramming), the improvement team determines the practices and strategies that set apart the high achievers in the at-risk group.

The core PD group held regular meetings to discuss their initial findings and conducted additional student interviews, meeting with small and large groups of at-risk students. Then they opened up the PD project to all school staff.

PD places considerable weight on ensuring that all stakeholders are involved in the improvement process. Merced's core team held teacher leadership meetings and trainings, and organized a two-day summit for students. Potential solutions identified during this phase were vetted at a community engagement event that drew over 200 teachers, students, parents, and community leaders. Two key characteristics of successful students emerged from these efforts:

Involvement in school activities, such as sports, drama, band, and student government;

Relationships with teachers who provided support and encouragement during difficult times.

For a variety of reasons, the effort lost steam for several months. Staff from the Institute for Teaching visited the school at the start of the 2010 spring semester and re-booted the process.

Designing Opportunities to Spread Knowledge Through Practice: During this phase, the PD team tests promising solutions by providing opportunities for people who were not involved in the initial effort to practice the behaviors in a safe environment. While the initiative at Merced did not include a designing phase, Save the Children created an opportunity to spread knowledge through practice when they shared the positive deviants' successful hygiene and mealtime behaviors with other households in the community. Voluntary training sessions such as these (which both test and spread solutions) tend to start small and last long enough to ensure that the successful behaviors become common practice for participants, who then spread them throughout the greater community.

With input from the community, the PD team begins what's referred to as the discernment phase of deciding how to measure, monitor, and evaluate the effectiveness of the new practices.

Another aspect of positive deviance that breaks with other improvement models is that its findings do not easily morph into generalized knowledge. Whereas the other models in this series consider adaptability in their designs, PD assumes that every community has its own strategies, behaviors, and practices and that every community must therefore go through the entire PD process. In other words, the PD model does not de facto include dissemination, i.e., the spread of improvement knowledge produced by a local intervention to other contexts.

While there is no systematic way for spreading solutions outside their given context, the learning-by-doing, practice-based approach to sharing knowledge throughout a community is something most educators are familiar with. Additionally, the positive deviance method's focus on amplifying solutions that already exist may appeal to educators who are wary of yet another one-size-fits-all approach that doesn't account for local context. Viewed through that lens, PD may be an appealing choice with its emphasis on community involvement and ownership, and the empowerment of affected people to solve their own problems.

Sarah McKay is a former associate for research and communications at the Carnegie Foundation.

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Quality Improvement Approaches: Positive Deviance | Carnegie Foundation for the Advancement of Teaching

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Editor's note: A recent special issue of Quality Assurance in Education explores seven different improvement models being used in schools today. Beginning in February of this year, the Carnegie Foundation began publishing summaries of each of the models on the Foundation's blog, including process, examples, and pros and cons.