Social Learning

Source Document: Justin Sharpe, Lucy Pearson, Sylvia Kruse, Thomas Abeling, Hugh Deeming, John Forrester, Åsa Gerger Swartling. 2015-3-31. Social Learning and Resilience Building in the emBRACE framework. Deliverable 4.3

The challenges presented to society by environmental hazards today are more complex than in the past and require new approaches to problem solving. Resilience requires particular change, and its careful management, to help living standards be maintained or transformed in face of a disaster, both in the short and long run. The emBRACE project is concerned with community resilience, and we take our definition of resilience from the latest Intergovernmental Panel on Climate Change (IPCC) summary report as being:

“The capacity of social, economic, and environmental systems to cope with a hazardous event or trend or disturbance, responding or reorganizing in ways that maintain their essential function, identity, and structure, while also maintaining the capacity for adaptation, learning, and transformation” (IPCC, 2014).

This definition closely links resilience with the capacity to adapt, where adaptive capacity refers to the aspect of resilience that reflects learning, flexibility to experiment and adopt novel solutions, and development of a generalized response to broad classes of challenges. This report proposes that social learning can potentially be employed to help prompt this required change in order to build resilience. Social learning has been defined in many ways but has evolved over time from being specifically about individual learning taking place in a social context, to be recognised as a, critical aspect to achieve sustainability in the context of social-ecological change (Armitage 2005, Diduck 2010) ecological sustainability (Reed et al, 2010 climate change adaptation (Pelling et al, 2015, May and Plummer 2011, O`Brien and Keefe, 2013), and resilience (Pelling, 2011, Krasny et al. 2010:) narratives and practice. Today researchers are engaging in social learning inquiry from many different perspectives including environmental education (Wals 2007), and natural resource management (Muro and Jeffrey 2008, Mostert et al, 2007, Pahl-Wostl et al, 2006, 2007, 2009).

The idea behind this suggested approach to social learning in the context of community resilience is that through facilitated social learning, knowledge, values and action, competences can develop in harmony to increase a group’s capacity to build disaster resilience. Shared learning amongst peers is believed to facilitate faster and deeper learning compared to that received through the dissemination of an instructor only (Joiner, 1989; Elwyn et al., 2001). This results in the potential for informal communities of practice functioning as vehicles for peer learning, facilitating resilience building (Pelling, 2008). Accompanying this potential are a number of practical questions: How can the dissonance created by introducing new knowledge, alternative values etc., become a stimulating force for learning, creativity and change? How can people transcend social norms and personal biases in order to enhance the flexibility of the social-ecological system and its ability to respond to change?

It is possible that this dissonance may be bridged by allowing for and encouraging reflective practices that can lead to transformative learning, which is defined as leading to a change in an individuals’ frame of reference, with potential consequences on the individual’s behaviour (Mezirow, 1991, 1995, 1996; Cranton, 1994, 1996). Frames of reference are defined as mental structures through which individuals make sense of personal experiences and that predetermine a person’s cognitive, emotional and behavioural responses to new experiences – in other words, filters that “shape and delimit our perception, cognition and feelings by predisposing our intentions, beliefs, expectations and purposes” (Mezirow 2006,p.26, cited in Vulturius and Gerger Swartling, 2013). It is proposed that through social learning it is possible to move beyond knowledge transfer (which may well be out-dated or unsuitable for general use) towards learning that evolves with the input of various actors (including those at community level), is adaptable and is able to reflect on what is effective as it develops. If successful, this type of learning should lead to communities that have evolved to be flexible, adaptive and strong enough to bear future shocks. This should be what is taken by the term resilience. It should not be an end state or goal but a desirable process through which communities of practice become confident and competent at identifying, analysing, reflecting and adapting their own schema of understanding and practices for living in an uncertain world.

Having said this, it is also recognised that there are resource constraints to such practices such as time, finances and human resources and so on. As a consequence, a working heuristic framework is required in order to allow resilience to be framed in a pragmatic way that allows for the development of learning over time, but not at the expense of current needs or concerns. The following graphic (figure 1) illustrates how community resilience is dependent upon learning (along with resources and capacities and appropriate effective actions), in maintaining essential functions in communities exposed to or affected by hazards. Of particular interest for this report is how learning is defined here to include phases that examine perceptions of risk and loss whilst also highlighting the importance of experimentation and innovation. Critical reflection is proposed as a mechanism through which to make sense of what is being learned before applying it to thinking or actions. As a consequence, although transformational learning may hold promise for the future development of community resilience it is bounded in this conceptualisation by the presentation of resilience as a form of maintenance. This perspective holds that developing resilience to future threats is still an abstract concept as the cycle is currently reactive rather than proactive, principally because the resources and capacities required to react to current threats are stretched due to financial contraints in the prevailing economic climate. This social learning framework, developed as part of the emBRACE project, attempts to address these realities while acknowledging social learning outcomes as potential elements of transformation and change that are desirable for adapting to and living with future disaster threats.

This report reviews the literature and case studies in the field of social learning and resilience, as well as the broader fields of social learning in the context of resource management and climate change adaptation, in order to begin to address the following research questions:

  • To what extent can social learning contribute to resilience building? And if so how?

  • How far does it contribute to existing gaps in the resilience literature?

  • What are the mechanisms for instigating social learning for building resilience?

  • What are some challenges that need to be overcome?

  • What are the limits of social learning for building resilience?

  • How can we begin to measure the effectiveness of social learning for building resilience?

  • What are the research needs?

  • What are challenges concerning social learning when dealing with natural hazards?

  • What capacities are needed for social learning to build resilience in the field of natural hazards?

  • What does social learning mean in the context of community resilience?

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Justin Sharpe, Lucy Pearson, Sylvia Kruse, Thomas Abeling, Hugh Deeming, John Forrester, Åsa Gerger Swartling. 2015-3-31. Social Learning and Resilience Building in the emBRACE framework. Deliverable 4.3

https://drive.google.com/file/d/0B9RBeBGSyVgFMkU4cUJlcXVneVU/view?usp=sharing

Introduction | Concepts | Methods | Case Studies | Reaching Out | Resources

Agent Based Modelling | Data Collection for Health & Social Services | Disaster Databases of Human Impacts in Europe | Disaster Footprints | Resilience Indicators | Social Learning | Social Network Analysis | Quantitative & Qualitative Methods