Climate change adds considerable uncertainties and complexities to what are already multidimensional development challenges. These challenges are only likely to increase as the impacts of locked-in temperature rises are felt in countries most at risk, such as the Himalayan region, densely-populated deltas in Asia and much of Sub-Saharan Africa [1
]. While there is clear evidence that the current levels of investment into climate change adaptation and resilience building in developing countries is insufficient to meet rising needs [2
], investment into research and programme implementation continues to grow. However, effective responses are not just a question of resources: to date, the approaches that many of our organisations are taking have failed to address the complexity and the cross-scalar nature of the challenges that are triggered by climate change in the context of development [3
]. This is becoming increasingly recognised at different levels, from community-level organisations right up to international funding agencies, and is prompting new reflections on how to design programming that better reflects the complexity of the challenges it aims to tackle. Scaling up learning-centred programme design and delivery is now seen as an essential part of transitioning toward sustainable and climate-compatible development pathways [4
In response, much practical and theoretical work is being undertaken on the value of reflexive learning as a way of bringing together different knowledge to address the multiple dimensions of complex problems. One of the major themes in this work is better understanding how to take learning beyond the local or individual level into much wider networks of practice. The principles of resilience thinking warn us that organisations must become much more adaptive and dynamic in the ways that they anticipate, interpret and respond to unexpected change [4
]. As Boyd and Osbahr note:
Failure to incorporate reflexive learning in the process could manifest itself in misguided policy positions and an inability to assess the changing science of climate change, with serious consequences for practitioners and funding, and missed opportunities for sharing lessons for addressing climate change impacts.
This need to do things differently has been the subject of much recent discussion within the international development community in particular, but is not yet clearly reflected in most organisations working at the climate and development nexus. New initiatives from funders including the United States Agency for International Development (USAID) [6
] and the U.K. Department for International Development (DFID) [7
] and large programmes like the CGIAR’s research programme on Climate Change, Agriculture and Food Security (CCAFS) [8
] aimed at promoting learning-centred approaches to research and development serve to acknowledge this need and represent early actions towards new approaches. However, many approaches to date have been critiqued for their vagueness and normative treatment of learning. Armitage et al. [9
], for instance, argue that the growing popularity of these approaches among development agencies, researchers, government and non-governmental organizations signals that “greater specificity and clarity concerning the meanings and outcomes ascribed to learning is necessary” (p. 96). Along similar lines, USAID’s review of the literature on collaborating, learning and adapting (CLA) highlights the need to “expand the evidence base on the effect, impact and/or contribution of CLA practices to organizational effectiveness and development outcomes” [10
] (p. 12), while a recent World Bank report describes how learning processes continue to be viewed by many as “a rather insular or introspective exercise, relevant only to a small number of academics or development practitioners, instead of being a driver of social change towards increased impact” [11
] (p. 1). These critiques and the subsequent under-investment into systems and processes that follow from them can mean that while the value of learning processes is recognised on the surface, there is a lack of robust analysis and high level support to drive them to scale [12
Calls for a transition toward effective learning-centred models of programming, articulated above and elsewhere [12
], are particularly salient amid the growing number, size and complexity of programmes aimed at addressing climate change impacts and resilience in the context of development. In particular, the rise of multi-project programmes such as the four examined in this paper, as a model of programming has seen a widening range of collaborators brought together, often across great geographical distances, to work together toward ambitious common objectives [13
]. Buffardi and Hearn describe multi-project programmes as:
[T]ypically funded through a single mechanism and address a common, broad theme, such as community resilience or women’s empowerment. They are implemented across different locations by different organisations, and may target different population groups and employ different interventions, but are grouped together under a common set of high-level objectives, often under a single results framework. Importantly, there is an expectation of some level of interaction between the projects.
These multi-project programmes present novel opportunities and challenges for navigating and learning from complex problems, like climate change, particularly across scales. How, then, can learning processes avoid the pitfalls outlined above, whilst overcoming the challenges of distance, diversity, uncertainty and complexity that these modalities and challenges present? The reflections that follow draw on nested cases of large-scale learning processes with a view to providing new insights on this question.
The review and analysis that form the basis of this paper speak to some of these questions with the aim of providing lessons for future research and programming. We do so by:
Reviewing the theories that have shaped approaches to reflexive learning in large climate change and resilience-building programmes;
Conducting a comparative learning review of the design principles, challenges and lessons emerging from efforts to integrate reflexive learning processes into large, highly distributed climate change and resilience-building programmes for development.
We approach this second objective by drawing on evidence from four inter-related (or nested) programmes, all of which are seeking to integrate reflexive learning to inform their practice.
In this study learning processes are understood as cycles of action and reflection, that is, doing and thinking, performing and adapting, aimed at both improving and re-thinking practice. Our framing of learning, as we will discuss below, is influenced by Kolb’s [14
] model of experimental learning, which has significantly shaped thinking on reflective practice. By approaching this second objective as a learning review undertaken by people directly involved in the design and implementation of the four programmes under study, the authors see this paper as representing a dimension of reflective practice. As such, the paper may also serve to model how learning processes can be rendered more explicit and brought into wider forums as they unfold; keys to accelerating and expanding action in this field.
We begin by reviewing the case for learning in climate and development planning and programming and linking this to the increased focus on learning at the climate and development nexus. We review some of the dominant theories of learning within the current literature on climate change, resilience and development and identify theories that most closely reflect how learning is framed and supported in the four case study programmes. This review provides the backdrop for our analysis of the four programmes, identifying themes that have stood out across this set of cases. We conclude with a review of key points and questions for future research.
2. Learning as a Unifying Theme in Response to Complexity and Uncertainty
One of the clear challenges that climate change presents to decision-making is the increased uncertainty that it creates. This uncertainty can be attributed to a number of factors, including limits to the current “skill” of climate models and projections and the inherent uncertainties of non-climatic trends that influence GHG emissions and people’s climate vulnerability, such as population and economic growth, national development pathways and political will to take action [15
]. In specific decision settings (national or local planning, household decision-making, etc.), these factors combine to produce an ever-widening “envelope of uncertainty” that cannot be addressed solely through improvements in the climate sciences [16
]. As a result, many scholars and practitioners have shifted their attention toward strategies for how to best make decisions amidst these uncertainties, rather than trying to eliminate them [17
]. Approaches including adaptive management, resilience thinking, scenario planning and social learning have seen a rise in attention through this shift [18
The inherent uncertainty around the future impacts of climate change, paired with the high stakes it bears on decisions related to livelihoods and development are part of what makes it a so-called “wicked problem” for policy and planning. Wicked problems are characterised by their complexity, uncertainty and the divergence of viewpoints and strategies for responding to them. As such, Head argues, tackling such problems requires “new thinking about the multiple causes of problems, opening up new insights about the multiple pathways and levels required for better solutions, and gaining broad stakeholder acceptance of shared strategies and processes [...]. This requires organisational learning and cultural change” [21
] (p. 115). Along similar lines, Hurlbert and Gupta [22
] term wicked problems like climate change adaptation “unstructured problems”, characterised by the levels of disagreement on the values and norms associated with the issue and on the underlying science that defines it. In such problem settings, they argue, social trust and “triple loop” learning, learning that goes beyond error-correction to rethink underlying values, policies and norms, become key factors for structuring and understanding relationships between problems and solutions.
This appeal to collective reflection, iteration and learning as a means of engaging with complexity and uncertainty is a unifying feature in the literature on resilience [23
], adaptation to climate change [19
] and disaster risk management [26
]. To date, much of this literature has focused on learning which engages individuals and collectives (communities, households, governments, networks, etc.) who are managing or governing resources that are exposed to environmental shocks and stresses. As such, there is a strong emphasis on case-based studies of learning at scales ranging from communities to social-ecological systems [19
More recently, an emerging body of literature has gained prominence, examining the contribution of learning processes to the management and governance of climate change, resilience and sustainability research and programming [4
]. Variously described as “adaptive”, “iterative” and “organisational” learning, this analysis considers how learning, supported through monitoring, evaluation, research and dedicated learning processes, improves programme delivery and management. For Watkiss, Hunt and Savage [28
] the focus is on “the management of uncertainty over time, allowing adaptation to develop within a process of learning and iteration” with a view to maximising value for money, while Boyd and Osbahr note the role of learning processes to help “avoid mistakes from the past” [4
] (p. 631) and Gonsalves [29
] points to improved collaboration and innovation.
2.1. Theoretical Framings of Learning in Climate and Resilience Programmes
Building on our analysis and past reviews of the literature [30
], three theoretical framings of learning stand out as being widely used in the areas of resilience, climate change adaptation and environmental management, namely adult learning, organisational learning and learning in communities of practice. The framings span different units (or scales) of analysis, from individuals to organisations and wider networks, though the challenge of linking learning across these scales is a recurring theme within the literature [31
]. Across the framings, there are clear areas of intersection, and of tension, around the nature, process and site of learning; some within the field of adult learning, for instance, challenge the very notion of a “learning organisation” [33
Adult learning and adult education are themselves vast and dynamic areas of study, rooted in a concern for the ways that learning serves to strengthen individuals and societies. Its aims are instrumental, communicative and transformative, building from one of its founding thinkers’ assertion that “adult education will become an agency of progress if its short-term goal of self-improvement can be made compatible with a long-term, experimental but resolute policy of changing the social order” [34
]. One of the main features of adult learning is the central role of lived experience as a source and arbiter of learning [35
], with considerable focus on the ways that struggle (either individual or collective) and social action shape this experiential learning [36
]. Kolb describes learning as “the
major process of human adaptation” [14
] (p. 32) and, drawing on the work of Kurt Lewin and others, frames learning as a continuous cycle of actions and reflections that lead to changes in understanding and practice. These themes remain central to many of the learning-based approaches to resilience and climate change highlighted above. A critique of Kolb’s (and others’) models of reflective practice, however, is that it provides limited clarity on the nature of the reflection itself. This includes, for instance, whether it is best understood as an individual, cognitive process or an intersubjective, dialogical one [38
Organisational learning shares this interest in how cycles of experience and reflection lead to changes in individuals and collectives. Here, the organisation is the locus of change, with learning contributing to both improvements in current practice, as well as a rethinking of the organisation’s underlying assumptions amidst wider social change and uncertainty; what Argyris and Shön have famously termed “double loop” learning [40
]. Critics of organisational learning literature, however, argue that it assumes too much homogeneity in interests within an organisation and, in practice, focuses almost exclusively at the level of technical-economic learning [33
]. Field suggests that instances of effective learning are probably better described as “shared-interest-group learning”, which occurs at particular times and under particular circumstances where interests align [33
Departing from this critique of organisational learning is the work of Jean Lave and Etienne Wenger on communities of practice as sites of situated learning that engages actors who have a shared sense of belonging [42
]. For Wenger, communities of practice are at once “born of learning” [42
] (p. 230) and potentially powerful sites of social learning. The distinction between a communities of practice framing and a more formal organisational framing is captured in Wenger’s note that “the currency of these systems is collegiality, reciprocity, expertise, contributions to the practice and negotiating a learning agenda; not affiliation to an institution, assigned authority, or commitment to a predefined deliverable” [42
] (pp. 243–244). Membership in communities of practice is not uniform. Levels of participation differ, and the interaction between core, active and peripheral group members can stimulate and help transfer learning [45
]. With their emphasis on leveraging learning and innovation across organisations and networks (both formal and informal), communities of practice are seen to serve as beneficial collaborative structures for addressing complex and interdisciplinary problems like climate change adaptation [29
Communities of practice can be distinguished by three characteristics, which provide them with coherence and create the conditions for collective learning: a sense of joint enterprise; mutual engagement; and a shared repertoire of tools, stories and discourses that belong to the community (see Table 1
In the section that follows, we set out how these framings have provided a structure for the review of four programme case studies.
Iterative and learning-based approaches to climate change and resilience programming are increasingly being adopted in the context of international development. Paired with the rise of ever-larger “multi-project programmes” expected to deliver impacts at scale, this presents new opportunities and challenges for those who design, manage and implement these types of initiatives. While a significant body of case-based evidence exists for smaller scale and more localised learning initiatives, this paper has tried to contribute to the evidence base on much larger global multi-project programmes, where the task of developing a sense of coherence and collective endeavour can be daunting. We have also sought to draw out how nested programmes offer novel opportunities for learning to move across scales.
While the majority of the themes emerging from this review can be applied to international development programmes beyond the climate change and resilience focus covered here, the complexity and uncertainty of climate change creates an added impetus for having reflexive learning processes sit at the core of programme interventions. This, we argue, calls for a shift in thinking about programme design, with an increased focus on how to nurture emergent learning-oriented collaborations. Undertaking such a fundamental shift in programming approach over the scales of partnership explored in the cases above is no small task. As we have set out above, it involves changes in individual and institutional incentive structures; in programme design; in management principles and practices; and in resource allocations within programmes. It also requires a clear recognition of both the requirements for and the limits to learning-based approaches that are present in programmes of this scale. Drawing on the literature on communities of practice can offer important insights on the kinds of changes needed and the emergent model engagement that programmes might strive for.
Building on this last point, further applied research is needed to better understand these requirements and limits. We have argued, for instance, that nested programmes offer novel opportunities to scale up effective approaches within comparable contexts, but are there limits to the scale at which certain learning processes can be effectively applied? Can programmes reach levels of diversity and distribution that make the sense of joint enterprise impossible to establish? And if so, is this a signal for putting limits on the scale of learning-oriented programme design, or rather a call for altogether different approaches? As investment into research and action on climate change and resilience continue to scale up, these questions will grow ever-more pressing.