Over the past seven years, the Center for Universal Education (CUE) has researched educational initiatives that are growing around the world and found that they share at least one thing in common: each has proactively adapted and responsive to changing circumstances and contexts. Whether expanding to new communities, integrating into national systems, or responding to the global pandemic, each of these initiatives has had to modify, adjust or in some cases overhaul the design, the implementation or funding approach of an initiative.

So the question is not whether our environments will change, but how we adapt. In education, we have found that too often the adaptations made are not systematically planned or well documented, and the opportunity to learn from these modifications is lost. This happens for many understandable reasons, including the fact that those involved in the design and delivery of large-scale education programs often do not have the luxury of space and time to pause, reflect and correct the course based on new data and changes in the larger environment.

Adaptation monitoring tool

In order to respond to this reality, the CUE has just published an adaptation monitoring tool designed to help education practitioners plan, document and regularly learn adaptations in order to strengthen efforts to scale and sustain an initiative. .

The tool is based on the Plan-Do-Study-Act model used in improvement science and directly informed by the experiences and contributions of Real-time Scaling Lab partners. The tool is intended for use at various intervals throughout any scale-up process, with timely data collected and analyzed to inform rapid learning and decision-making. These are four simple steps repeated over time:

1. Identify what is the overarching scaling goal of the initiative and what key scaling factor or contributing factor to that goal will be at the center of any change.
2. Plan what adaptation will be tested to meet a challenge or opportunity related to this scaling engine and how it will be executed and measured.
3. Test adaptation over a short learning cycle — capturing any problems that arise, spontaneous changes made, and early results.
4. Reflect on the outcomes of adaptation, including what worked, what didn’t and lessons learned. Based on this learning, determine what changes to make to the model or strategy and what other adaptations to try, continuing the iterative learning cycle.

What does it look like in practice?

In the Philippines, the Department of Education (DepEd) has prioritized the effective delivery of teacher professional development (PDT) programs with the goal of improving the quality of education nationwide. One of the flagship programs is a blended teacher professional development course – Early Language, Literacy, and Numeracy (ELLN) Digital – offered to all Kindergarten to Grade 3 teachers nationwide starting in 2019. The ELLN course Digital combines independent, guided study of multimedia tutorials by teachers with collaborative learning through groups of teachers in school settings. Given the scale of PDT needs within the system, DepEd faced a major challenge in providing on-the-job training to around 300,000 K-3 teachers – how to maintain the quality of training while ‘ELLN Digital is evolving while ensuring that the approach is well suited to the various contexts of the country.

In response to this challenge, DepEd has partnered with the NGO Foundation for Information Technology Education and Development, Inc. (FIT-ED) to integrate “Plan-Do-Study-Act” improvement cycles in each school and division. These improvement cycles allow for rapid feedback loops to inform the continuous adaptation and course correction of the implementation of ELLN Digital at the school level, and the data should be aggregated across schools, divisions. and regions to inform the future deployment to more teachers and more schools. This iterative system-wide learning process was possible given the space, mandate and resources of government at the central level.

Over the past three years, a number of lessons have been learned from integrating an iterative adaptive learning cycle into the deployment of a national DPT program. These include:

• The need to understand scale-up readiness before deploying any new initiative.
• The critical importance of an enabling environment, including the political, cultural, economic, technological and institutional conditions of the local context.
• The centrality of fostering agency among implementers – in this case, teachers, principals and coaches – by empowering them to solve problems and make decisions, and by creating spaces for experimentation and collaboration.
• The challenge of building a critical mass of expertise at the local level through, among other things, professional learning communities for teachers and educational leaders collaborating with community members and other education stakeholders.

With so many unknowns in the world, one thing is certain: our environments are dynamic and constantly changing. Sustainable scaling must take these realities into account and be ready to respond and adapt. This requires fostering and strengthening adaptive capacity and the use of data for learning among the different stakeholders involved in scale-up. This tool, along with a suite of other complementary scaling resources, is intended to support these important efforts.

We welcome any ideas, suggestions or questions related to this tool. To share your experience or provide feedback for future editions, please email [email protected]

Note: This work was carried out with a grant from the International Development Research Center, Canada to the Foundation for Information Technology Development and Education (FIT-ED). The opinions expressed in this work are those of the authors and do not necessarily represent those of the International Development Research Center, Canada or its board of directors; or the Foundation for Education and Development of Information Technology.