As covered in the Assess Module, you can start your project by collecting information (e.g., through a violent extremism assessment or risk assessment) to inform your design and implementation. While this is a necessary first step, it is equally important to continue this learning throughout the duration of the project and to adapt when necessary to ensure that the project remains effective and relevant. This is true of most development work, but it is particularly true of projects that address violent extremism (VE). Adaptation is necessary to account for changing VE and conflict dynamics and their high degree of complexity.
The complexity inherent in P/CVE projects is of two types: issue complexity and contextual complexity.
Issue complexity means issues are being highly context-specific so that you can’t simply transfer solutions from one context to another. It also means issues are multi-faceted; activity components interact in unpredictable ways, making it difficult predict how a particular activity will affect results—and therefore requiring ongoing observation.
What are some factors that contribute to the complexity of violent extremism and the need for P/CVE projects to integrate learning and adaptation?
- VE actors are quick to shift their rhetoric, strategies, foci, and modes of operation. Programming must keep up but can do so only if it is informed by up-to-date monitoring and analysis of VE dynamics.
- When VE occurs in conflict-affected environments, the context is likely to be particularly volatile. Staying abreast of changes in the context will be a particularly important task for local organizations.
- Tracking how national-level or structural factors relate to the local level, where most projects are likely to occur, is critical to understanding how the VE landscape may be shifting.
- Host government responses may also shift quickly, and the interaction between those responses and VE activity must be tracked and its impact understood.
- P/CVE is still an emerging field and lacks an evidence base—particularly data on practices that have proven effective in different contexts.
Adapted from: Source
Contextual complexity may affect a project even if the issue itself is not complex. In fragile and conflict-affected states or in humanitarian emergencies, even addressing “simple” problems requires adaptation.
Learning can take many forms and serve different purposes. Learning includes your approach and related actions to collect and analyze data related to the issue on which you’re focusing, the activities you’re implementing, and the context in which they take place, in order to generate lessons that you can feed back into your programming (the “adaptation” piece of learning and adaptation).
This resource highlights the importance of learning to inform adaptation in development programming. It also explains the two types of learning you can undertake:
Identify one or more connected activities (for example, a youth-led magazine that covers issues related to young people confronting violent extremism in their community) and carry out learning exercises during implementation to assess progress and identify lessons learned. This learning will ideally lead to changes and adaptations to the approach and activities. For example, the training program for the youth-led magazine might reveal that radio is more likely to reach its youth audience, and therefore the program may decide to add that component to its approach.
Implement more than one activity or sets of connected activities at the same time (for example, a youth-led magazine paired with a separate activity to form citizenship clubs in schools to promote non-violence and community engagement) and conduct learning actions to assess progress and identify lessons learned. By implementing two approaches at the same time and analyzing the results of both, you can understand which approach works best and make any necessary adjustments.
Use both sequential and parallel learning
Don't look at these types of learning as separate or mutually exclusive – they describe the underlying methods you could use for developing your learning approach. In practice, you could conduct learning activities that advance both sequential and parallel learning at the same time.
Adaptation refers to what you do with the data you’ve collected and the learning you’ve generated; it refers to actions your project will take in response to what you’ve learned. According to The Asia Foundation’s Strategy Testing: An Innovative Approach to Monitoring Highly Flexible Aid Programs, three reasons usually drive development projects to adapt. We have revised these reasons to apply to P/CVE projects.
Tactical adaptation refers to tweaking activities in response to monitoring information or feedback. This type of adaptation usually focuses on improving project and implementation performance or on better engaging communities or beneficiaries in planned activities.
Strategic adaptation refers to more profound course correction, in response to learning or feedback that questions the appropriateness of the project’s approach and planned activities. For example, this might be learning that leads to changes in the project’s outcomes, adding or removing activities, or changing the target group.
Adaptive management is a broad framework for approaching learning and adaptation in development projects. It involves monitoring, learning, and gathering feedback as you implement a project. Even more importantly, it involves making adjustments and course corrections in response to this learning. USAID defines adaptive management as “an intentional approach to making decisions and adjustments in response to new information and changes in context.” As such, adaptive management is not about changing goals during implementation; it is about changing the path being used to achieve the goals in response to changes. Refer to this USAID document for more guidance on adaptive management.
Later in this module we will look in more detail at USAID’s and other organizations’ models for applying learning and adaptation and adaptive management frameworks.