by M Van Epp · 2016 · Cited by 9 — social learning catalyse adaptive responses to climate change? IIED Working Paper. IIED, London. pubs.iied/17390IIED. ISBN 978-1-78431-428-6.
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Working Paper November 2016Climate change Keywords: Social learning, monitoring and evaluation, community- based adaptation, community-based natural resource managementSolving ‚wicked™ problems: can social learning catalyse adaptive responses to climate change? Marissa Van Epp and Ben Garside
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International Institute for Environment and Development 80-86 Gray™s Inn Road, London WC1X 8NH, UK Tel: +44 (0)20 3463 7399 Fax: +44 (0)20 3514 9055 www.iied.org @iied www.facebook.com/theIIED Download more publications at www.iied.org/pubs About the authors Marissa Van Epp is an independent researcher working on social learning, monitoring and evaluation and climate change adaptation. Ben Garside is a senior researcher in IIED™s Shaping Sustainable Markets research group. E-mail: email@example.com Produced by IIED™s Communications Group The Communications Group works to position IIED for impact and in˜uence by communicating with the right people, in the right way, at the right time. We work to three objectives: putting audiences ˚rst; creating content for impact; and enabling best practice in communications and marketing. The Group has been working with the CGIAR Climate Change, Agriculture and Food Security Research Program, and others, to explore the effectiveness of social learning methodologies in addressing complex global challenges, through the Climate Change and Social Learning initiative (CCSL, https://ccsl.wikispaces.com). Solving ‚wicked™ problems is the culmination of this work, and collects and analyses evidence on where effective social learning is occurring and how such an approach can contribute to tackling problems such as climate change and achieving better development outcomes. Acknowledgements IIED and the authors would like to thank all the initiatives who participated in or adopted the social learning M&E framework used in this study, for their strong interest in this work and their efforts in data gathering. The ˚ve initiatives are: the African Climate Change Resilience Alliance (ACCRA) in Uganda; the Bolsa Floresta Program (BFP) in the Brazilian Amazon; the Collaborative Adaptation Research Initiative in Africa and Asia (CARIAA); the Political Action for Climate Change Alliance (PACCA) in Uganda and Tanzania; and the Potato Park-International Potato Centre-ANDES Agreement for the Repatriation of Native Potatoes in Peru. In addition, special thanks to the Climate Change, Agriculture and Food Security (CCAFS) programme at the Consultative Group on International Agricultural Research (CGIAR) for their support in funding this work. Published by IIED, November 2016 Van Epp, M and Garside, B (2016) Solving ‚wicked™ problems: can social learning catalyse adaptive responses to climate change? IIED Working Paper. IIED, London. http://pubs.iied.org/17390IIED ISBN 978-1-78431-428-6 Printed on recycled paper with vegetable-based inks.
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www.iied.org 3Social learning approaches can catalyse knowledge co-creation and action, so have the potential to help solve complex ‚wicked™ problems such as climate change and food insecurity. This working paper synthesises evidence from ˜ve diverse initiatives employing social learning approaches in response to such problems using the Climate Change and Social Learning initiative™s monitoring and evaluation framework. It ˜nds initial evidence that key factors in social learning approaches can lead to clear learning outcomes with resulting positive changes in values and practice. Links to longer-term development outcomes are also evident in several completed initiatives. Contents Summary 41 Introduction 62 Framework for analysis 83 Methodology 10 3.1 Peer assist and data collection 10 3.2 Analysis and indicator scoring 12 4 Case studies and ˜ndings 14 4.1 African Climate Change Resilience Alliance (ACCRA) 15 4.2 Bolsa Floresta Program (BFP) 17 4.3 Collaborative Adaptation Research Initiative for Africa and Asia (CARIAA) 23 4.4 Policy Action for Climate Change Adaptation (PACCA) 25 4.5 Potato Park Project 27 5 Synthesis and discussion 29 5.1 Engagement 30 5.2 Iterative Learning 32 5.3 Capacity Development 34 5.4 Challenging Institutions 36 5.5 Looking across the four dimensions at social learning 38 6 Revising the framework 41 7 Conclusions and next steps 43 Appendix A. CCSL M&E Framework 46 Appendix B. Process Guide 49 Appendix C. Diagrams 53Acronyms 58 References 59
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4 www.iied.org SOLVING ‚WI CKED™ PROBLEM S: CAN SOCIAL LEARNING CATALY SE ADAPTIVE RE SPON SES TO CLIMATE CHANGE? Summary Social learning approaches can catalyse knowledge co-creation and action, so have the potential to help solve complex ‚wicked™ problems such as climate change and food insecurity. This working paper synthesises evidence from ˜ve diverse initiatives employing social learning approaches in response to such problems using the Climate Change and Social Learning initiative™s monitoring and evaluation framework. It ˜nds initial evidence that key factors in social learning approaches can lead to clear learning outcomes with resulting positive changes in values and practice. Links to longer-term development outcomes are also evident in several completed initiatives. Complex or ‚wicked™ problems often cannot be adequately addressed using traditional ‚top-down™ approaches. Social learning- oriented approaches offer a potential solution by calling on the knowledge of multiple stakeholder groups, and encouraging knowledge sharing and integration and the co-creation of new knowledge. Social learning is more than just group learning; it has an agenda for wider change. It encourages stakeholders to work together to implement and test solutions through iterative cycles of learning, action and re˚ection. Spreading the learning from this iterative process to wider stakeholder groups and networks allows for change on a larger scale. Institutional openness and support for such approaches is crucial for realising the potential for change. Working in partnership with ˜ve initiatives, this working paper applies the Climate Change and Social Learning initiative (CCSL) monitoring and evaluation framework to assess the impacts of social learning approaches. The only tool of its kind, it is structured to track the processes that are more likely to foster social learning across four key dimensions: engagement, iterative learning, capacity development and challenging institutions. It can also be used to explore links between process activities, learning outcomes, and resulting changes to values and practice. This paper gathers results from across these dimensions as a ˜rst step in testing whether and in which contexts the progression from process to outcomes holds true. The evidence collected across the ˜ve initiatives identi˜es key processes that have enabled social learning outcomes and, in some cases, development outcomes. The ˜ve initiatives are: The African Climate Change Resilience Alliance (ACCRA), which integrates climate change adaptation into national monitoring and evaluation (M&E) frameworks in Uganda across community, district and national levels The Bolsa Floresta Program (BFP), which integrates forest conservation with community-driven development projects in the Brazilian Amazon The Collaborative Adaptation Research Initiative in Africa and Asia (CARIAA), which is an early stage global research programme aiming to integrate social learning approaches into programme design The Political Action for Climate Change Alliance (PACCA) in Uganda and Tanzania, which is an early stage programme seeking to foster multi-stakeholder learning alliances The Potato Park-International Potato Centre-ANDES Agreement for the Repatriation of Native Potatoes in Peru (referred to as the ‚Potato Park project™), which works to repatriate native potatoes and carry out collaborative research between the International Potato Centre (CIP) and indigenous communities in the Peruvian Andes. We found that across the dimensions of change, most of the initiatives progressed from process (where the indicator scores are highest), to learning outcomes (with slightly lower scores) and to value/practice outcomes (which had the lowest scores). More samples are needed, but these initial ˜ndings appear to con˜rm our hypothesis that a successful social learning- oriented approach would result in a clear overarching progression from processes to learning outcomes to value/practice outcomes. Conversely, we ˜nd where there is little or no process, there are weak outcomes Š again in line with our hypothesis. When looking at the process indicators in each of the four dimensions, we found engagement to be the strongest. The strongest aspects of engagement were found to be fostering champions and leaders, trusted facilitation, and inclusive and active participation. Based on our limited sample size, no individual dimension of social learning appeared to be an accurate predictor of the likelihood that an initiative™s process- related efforts would (or would not) result in positive outcomes. The results do however demonstrate the interconnected nature of the four dimensions. Engaging
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www.iied.org 5institutions is crucial if they are to be challenged and capacity development was found to be one way to do so. Facilitation, crucial to iterative learning, can also be used to ensure that capacity development takes place during group re˚ection and evaluation moments. Where social learning did occur and the programme/ project had reached a stage where development outcomes could be observed, social learning™s positive contribution was clear. Where indicator groups in the framework were not achieved Š for example where there was a lack of engagement over a sustained period, the absence of multiple re˚ect and act cycles, or no attempt to challenge institutional barriers Š outcomes appeared sub-optimal. Some of the completed projects provide examples of improved development outcomes. In the Potato Park project, for instance, joint research and action by farmers and scientists resulted in potato varieties being successfully repatriated to Potato Park communities, increasing potato biodiversity in the Park to one of the highest rates in the world, with improved incomes for Potato Park communities. Again, the sample size was small, which makes it dif˜cult to robustly assess the contribution of social learning to development outcomes, but these initial ˜ndings are encouraging. Key ˜ndings and conclusion At this early stage, our analysis indicates that programmes and projects employing approaches that incorporate key factors from each social learning dimension are most likely to see positive changes among stakeholders in relevant understanding, relationships and norms. Programmes and projects that emphasise all four dimensions are most likely to see the crucial changes in values and practice across stakeholders and wider groups that can lead to improved development outcomes. Our evidence indicates that programmes and projects that incorporate the following ‚who, what, when and how™ of effective social learning are most likely to see positive changes: Who Š carry out stakeholder research and target speci˜c stakeholder groups to ensure active participation, including those traditionally seen as ‚external™ stakeholders. Take a bottom-up approach to tailor capacity development activities and foster buy-in. Aim for inclusive collective learning. Capacity development and support helps groups/institutions lower on the power ladder to challenge those higher up. What Š involve bene˜ciaries and decision makers in design. Soft skills and concepts are as important as technical capacity development Š for example collective learning about the process of enabling social learning. Foster institutional openness to and support for social learning-oriented processes. When Š engage stakeholders and start capacity development early to enable broad participation in the project design. When and how often re˚ection occurs; more frequent re˚ection moments foster better social learning. How Š improve engagement by using experienced and trusted facilitators. Participation should be continuous. Use different styles of capacity development: learning by doing, as well as facilitation, can build soft skills. Re˚ection moments should be structured and planned-in. Learning needs to be captured and shared. Project/programme structures and planning processes need to be ˚exible to adapt to the results of learning. Integrate challenging of institutions to initiatives; challenging through champions and from the inside can be effective. In addition, we identi˜ed some recommendations for initiatives taking a social learning-oriented approach: Monitor learning. Monitoring the implementation and results of social learning can ensure that it can be adjusted to the evolving context and needs of a programme/project Learning leaders. An individual who is internal to the programme/project can champion and manage learning processes and monitoring Institutionalise learning. The learning leader should not hold the social learning banner alone. Rather, champions of social learning need to spread their knowledge to wider networks within that institution to be effective Enable action. Challenging institutions is important because more powerful institutions often control the resources, structures and decision making that enable or constrain action in projects/programmes. Institutions should put decision-making power and resources behind social learning processes to enable follow-up action. Taken together, these form a ˚edgling evidence base on the potential for social learning-oriented approaches in climate change adaptation and food security activities to improve development outcomes. IIED aims to build on this evidence base, focusing on the role of social learning processes in planning and implementing appropriate strategies for adapting to climate change and better managing climate uncertainties.
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6 www.iied.org SOLVING ‚WI CKED™ PROBLEM S: CAN SOCIAL LEARNING CATALY SE ADAPTIVE RE SPON SES TO CLIMATE CHANGE? 1 Introduction The people who are most vulnerable to the impacts of climate change and food insecurity ever more urgently need solutions. These intertwined issues have been described as ‚wicked™ problems because of their complexity, evolving nature, lack of clear solutions and plurality of perspectives (Carlile et al. , 2013). Solutions that are planned and implemented using traditional ‚top- down™ approaches are not suf˜cient to cope with these multiple challenges. Social learning-oriented approaches offer a way to identify potential solutions to the complexity of climate change by calling on the knowledge of multiple stakeholder groups and encouraging them to share and integrate that knowledge in their understanding, and create new knowledge together. Social learning is more than just group learning; it has an agenda for wider change. The de˜nition of social learning guiding this working paper is from the Climate Change and Social Learning initiative (CCSL): 1 Social learning approaches help facilitate knowledge sharing, joint learning and co-creation experiences between particular stakeholders around a shared purpose, taking learning and behaviour change beyond the individual to networks and systems. Through a facilitated iterative process of working together, in interactive dialogue, exchange, learning, action and re˚ection and ongoing partnership, new shared ways of knowing emerge that lead to changes in practice. A social learning approach can bring together stakeholders at different levels, with different values and perspectives, to ˜nd common ground in de˜ning a complex challenge such as climate change adaptation and its potential solutions. It encourages them to work together to implement and test solutions through cycles of learning, action and re˚ection. Spreading the learning from this iterative process to wider groups and networks allows for change on a larger scale. Social learning approaches often come up against institutional barriers in moving from collective learning around a problem to achieving action and change. In social learning, ‚institutions™ refers not only to the formal, bricks-and-mortar sense of the term (government bodies or research institutes), but also to the informal and intangible sense (local community organisations or cultural practices). These barriers can be related to decision making and resource allocation being made by external institutions who are not participating in the learning processes, or through rigid and often bureaucratic ˜xed project cycles. They can also be related to power imbalances and politics between institutions within and across hierarchies, such as community to local government to national government. Institutional openness to and support for social learning approaches is crucial for realising their potential for change. Institutions need to have structures and systems that allow ˚exibility in planning processes, as well as adequate resources, to accommodate the 1 The Climate Change and Social Learning initiative (CCSL) is a working group investigating how social learning-oriented approaches can improve institutional processes and effectiveness and lead to better development outcomes in the context of climate change. More information about the group, as well as resources on social learning, can be found on the CCSL wiki page at http://ccsl.wikispaces.com .
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8 www.iied.org SOLVING ‚WI CKED™ PROBLEM S: CAN SOCIAL LEARNING CATALY SE ADAPTIVE RE SPON SES TO CLIMATE CHANGE? 2 Framework for analysis The CCSL M&E framework was developed in 2014 through a participatory approach. Organisations and initiatives interested in social learning were brought together at a workshop hosted by the International Institute for Environment and Development (IIED) in London in June 2014. Drawing on practical experience, as well as on a body of research conducted by members of the CCSL initiative, workshop participants followed a social learning-oriented process to come to a consensus on the key elements of social learning. These were areas where you are likely to ˜nd processes that encourage and support social learning Š engagement or capacity development, for instance. The main output of the workshop was a shortlist of these elements that was used to develop indicators, and then re˜ned and expanded by CCSL members into a full M&E framework including indicators. 3 The resulting framework was developed around four areas Š or dimensions Š of social learning: 1. Engagement. Outreach to and involvement of individuals and groups as part of the problem de˜nition and learning process. Engagement as part of good social learning targets women, youth and other marginalised groups. 2. Iterative learning. Collective or group learning that occurs continuously or cyclically to co-create knowledge. 3. Capacity development. The development of an individual™s or group™s knowledge and skills. In social learning this is not limited to a one-way transfer between two parties (eg researcher to farmer), but instead is multi-directional and involves multiple parties (eg farmers to researchers, farmers to farmers, researcher to farmer, and so on). 4. Challenging institutions. Active questioning of institutional practices and values, potentially leading to institutional change. In social learning, ‚institutions™ refers not only to the formal, bricks-and-mortar sense of the term (eg government bodies or research institutes), but also to the informal and intangible sense (eg local community organisations or cultural practices). The relationship between these four dimensions, social learning and the hypothesised impact of a social learning- oriented approach is illustrated in a simple theory of change diagram in Figure 1. As shown, the dimensions can be both key processes in, and outcomes of, good social learning. The overarching theory of change is that a combination of iterative learning, capacity building, engagement, and the challenging of systems and institutional barriers and norms (process indicators) may lead to more effective co-learning and the co-creation of solutions to ‚wicked™ problems Š or social learning. 3 Additional details on the development of the framework can be found in Van Epp, M and Garside, B (2015) Monitoring and Evaluating Social Learning: A Framework for Cross-Initiative Application. CCAFS Working Paper no. 98. CGIAR Research Program on Climate Change, Agriculture and Food Security (CCAFS). Copenhagen, Denmark.
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www.iied.org 9Effective social learning should lead to different ‚learning change outcomes™ that can be tracked (learning outcome indicators). Learning change outcomes can be normative (related to norms), relational (involving relationships) or cognitive (focused on knowledge) (Lebel et al. , 2010). Together, these can generate changes in values and practice occurring across individuals, networks, institutions and systems (value/practice outcome indicators). The anticipated overall result is evidence of these changes having a positive impact on sustainable development with increased impacts where change at the institutional/system level also occurs (impact indicators) (Van Epp and Garside, 2015). To monitor progress in each of the four thematic dimensions of social learning Š engagement, iterative learning, capacity development and challenging institutions Š the framework uses 30 ‚essential™ indicators. These are spread across the progression from tracking process for each dimension, to learning outcomes and then to value/practice outcomes. This progression from process to learning outcome to value/ practice outcome is referred to as the ‚dimensions of change™. Table 1 below summarises the structure of the framework, outlining where the indicators ˜t in the matrix comprised of the four thematic dimensions and the three dimensions of change. Indicators are numbered within each dimension of change. The full CCSL M&E framework can be found in Appendix A. Of the 40 total indicators, 30 are considered essential for monitoring and 10 are considered non-essential. That said, even the essential indicators do not necessarily represent the only or required elements of a social learning-oriented approach. Rather that they are common elements of social learning-oriented approaches that have been used by a variety of programmes and projects. 4 The framework is a tool for assessing the extent to which these elements occur, analysing how and why each of them contributes to social learning in different contexts, and exploring the links between social learning and any changes in values and practice that positively impact climate resilience and development. Figure 1. A theory of change for social learning SO CIAL LEAR NINGENGAGEME NT IT ERA TIVE LEAR NINGCAPACI TY DE VELOPME NT CH ALLE NGI NG INSTITUTION SBETT ER AND MORE SUSTAINABLE DE VELOPME NT OUT COMES Table 1. CCSL M&E framework structure PROCESS (P) IN DICA TO RS LEAR NING (L) OUT COME IN DICA TO RS VAL UE/P RAC TICE (V) OUT COME IN DICA TO RS Engagement P1ŒP4 L1ŒL3 V1ŒV2 Iterative learning P5ŒP9 L4ŒL6 V3ŒV6 Capacity development P10ŒP13 L7ŒL9 V7ŒV8 Challenging institutions P14ŒP17 L10ŒL12 V9ŒV11 4 More information can be found in Harvey, B et al. (2013) Social learning in practice: A review of lessons, impacts and tools for climate change. CCAFS Working Paper no. 38. CGIAR Research Program on Climate Change, Agriculture and Food Security (CCAFS). Copenhagen, Denmark.
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10 www.iied.org SOLVING ‚WI CKED™ PROBLEM S: CAN SOCIAL LEARNING CATALY SE ADAPTIVE RE SPON SES TO CLIMATE CHANGE? 3 Methodology 3.1˚Peer assist and data collection Following the development of the CCSL M&E Framework, a call was issued to identify climate change adaptation and food security initiatives using a social learning-oriented approach that were interested in monitoring and evaluating the impact of that approach. These initiatives were invited to pilot the framework through a ‚peer assist™ process, which worked with each initiative to adapt the framework indicators and the methods for gathering results to each initiative™s context. The ˜ve initiatives chosen to take part in the peer assist process received support from a CCSL member at IIED in a) understanding the framework, b) tailoring the indicators to their speci˜c programme or project, c) thinking around how to integrate the framework into any existing or future M&E systems, d) choosing appropriate methods for collecting evidence against the framework, e) analysing the evidence and f) writing a case study report. 5 A process guide was developed to help participating initiatives think about how to use the framework Š this can be found in Appendix B. Data collection methods considered are summarised in Table 2. Methods were chosen in dialogue with the initiatives and tailored to each case study™s context. Process- based network mapping was found to be an especially useful tool for eliciting information about processes from community-level project dialogues. This method, which produces process ‚net-maps™, allows users to retrospectively track the step-by-step processes between stakeholders as a project evolved. 6 This method was ˜rst used successfully with BFP, and later with other case studies. Stories of change, outcome mapping and policy change analysis were not used by any of the case studies. This was for two reasons: they were not part of existing methods being used by ongoing initiatives, and they tend to be more time and resource intensive and require longer timeframes for implementation. Evidence was collected by members of the initiatives, with two exceptions. Evidence for CARIAA was primarily collected by the authors due to staff turnover in the programme, and for BFP the authors conducted ˜eldwork alongside BFP staff working with local organisations in the Brazilian Amazon. The peer assist and associated data collection approach had several limitations. The evidence gathered to populate the framework depended on what stage an initiative had reached at the time of data collection. For those initiatives applying the framework retrospectively with limited resources for additional data collection or ˜eldwork, this was often not ‚hard™ evidence and was sometimes based on a limited number of stakeholders™ experiences. In all cases, however, the authors provided a critical review through peer assist, challenging the assessment where appropriate. For ongoing initiatives that applied the framework at or near the beginning, the work had not progressed enough to make a connection between evidence collected and development outcomes by the time of publication. For these case studies, the value/practice indicators are less populated, re˚ecting work in progress rather than lack of effort. 5 With the exception of CARIAA, for which data collection, analysis and case study write-up was carried out by a CCSL member at IIED in consultation with CARIAA. 6 See the work of Eva Schiffer on Net-Map Toolbox and the Process Netmap variant: https://netmap.wordpress.com/process-net-map .
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www.iied.org 11Table 2. Data collection methods METHO DOLOGY DESCRIP TION PROCESS INDICA TO RS LEAR NING OUT COME INDICA TO RS VAL UE/ PRAC TICE OUT COME INDICA TO RS Participant observation An informal, qualitative way of capturing individual participants™ thoughts and feelings at a given moment. Observations could be recorded in personal journals, for example Focus group discussions A more formal, qualitative way of capturing participants™ thoughts and feelings in a group setting at a given moment Surveys/ questionnaires A way to collect data from larger groups of people in a format that can be quantitatively analysed Social network analysis and process network mapping Social network analysis aids assessment of the nature of the networks relevant to the project/ programme and participants. A variant of this, ‚process network mapping™, facilitates participants™ illustration of the process followed and the actors involved, revealing not only relevant networks but also a timeline of interactions, processes and outcomes (indicated by bracketed tick marks) Community self- assessment Enables a community to collectively re˚ect on a given topic, eg needs, transformation, social differentiation, and existing processes and cultural practices Stories of change, stakeholder portraits and follow-up interviews Three qualitative tools to help researchers track participants™ transformations Š changes in knowledge, beliefs, attitudes, actions, and so on Š over the duration of a project/programme Outcome mapping Allows project designers to systematically outline the anticipated steps/pathways for bringing about the desired changes (outcomes) of the project. This is ideally done prior to or at the beginning of a project/programme, and is revisited at key stages to aid re˚ection Policy change analysis Helps to determine the success of a project/programme based on the extent to which it in˚uences policy (measured by, for example, citations)
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