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Designing Social Learning Systems for Social Science Integration
Social learning is not a new idea or concept and its lineage can be traced in various literatures across social science branches including psychology, criminology, education and business studies. The concept is often linked to Bandura's work on social theory of learning (Bandura 1977) where individual learning takes place in a social context. Blackmore's (2007) review of social learning theories notes that social learning is likely to be interpreted and defined in accord with different theoretical traditions and interpretations. Of relevance to the discussion on natural resource managing, Blackmore also notes that social learning theory is part of the tradition of 'adaptive management' (Holling 1978) and is linked to Wenger's social theory of learning in communities of practice: defined as 'groups of people who share a concern, a set of problems, or a passion about a topic, and who deepen their knowledge and expertise in this area by interacting on an ongoing basis' (Wenger et al. 2002: 4–5; see also Wenger 1998).
With such origins and lineage it is perhaps not surprising that in the last decade there has been considerable attention from a range of authors in social learning for environmental managing (see Social Learning Group 2001) and in particular water resources (see, for example, Finger and Verlaan 1995; Daniels and Walker 1996; Woodhill and Röling 1998; Collins et al. 2007; Ison et al. 2007a, 2011; Pahl-Wostl et al. 2007; Pahl-Wostl et al. 2007, 2008; Mostert et al. 2007; Muro and Jeffrey 2008; see also Reed et al. 2010; Raadgever et al. 2012). The detailed distinctions and different interpretations of social learning by these authors are not rehearsed here.
Fig. 11.2 A heuristic for social learning. (a) Social learning in complex, uncertain and contested situations over time enables transformation through changed understandings and practices leading to concerted action by stakeholders. (b) The SLIM social learning heuristic depicts how six key variables interact to shape issues and particular situations. These variables include history, stakeholding, facilitation, institutions and policies, and epistemology (After SLIM 2004a; Ison et al. 2007a)
Instead, the definitions of social learning developed by the previously mentioned SLIM project were used as the conceptual and methodological basis of the case studies reported below. In the SLIM project, social learning came to be understood as one or more of four potentially inter-related processes:
(i) the process of co-creation of knowledge, which provides insight into the history of, and the means required to transform, a situation;
(ii) the convergence of goals (more usefully expressed as agreement about purpose or purposes), criteria and knowledge leading to awareness of mutual expectations and the building of relational capital;
(iii) the change in behaviours that results from the understanding gained through doing ('knowing') that leads to concerted action; and
(iv) ) arising from these, social learning is thus an emergent property of the process of transforming a situation (SLIM 2004c, d; see also Ison et al. 2007a; Collins and Ison 2009a, b).
Social learning is thus based on the process of multiple stakeholders socially constructing an issue in which their understandings and practices change so as to transform the situation of concern. This interpretation of social learning refers to collective learning – ie learning at the system level – in a social context compared to Bandura's individual learning in a social context
A diagrammatic depiction of the process of social learning is shown in Fig. 11.2. The axes represent the relationship between changes in the situation (s1–>s2 etc.) arising from changes in understanding and action and the process of transformation over time. The key elements relating to the transformation process are shown: starting context; institutions; facilitation; stakeholding and epistemological constraints.
Appreciating the starting context is important so as to become aware of legacies, framings and previous experiences of those involved which may have led to previous actions, divisions, conflict or opportunities for new practices in the current situation. The institutions element is broadly interpreted and concerns those aspects of a situation which enable or constrain behaviours and practices such as laws, regulations, policies, organisations, traditions and customs. The element titled as facilitation is also broadly interpreted and refers to people, activities and/or things which enable stakeholders to engage in conversations and inquiry. This can be a professional facilitator but it can also involve some intermediary object (see Steyaert et al. 2007) around which new debates and practices are focussed. Instead of the more usual reference to stakeholder, the heuristic specifically refers to stakeholding to note that individuals actively construct their stake and that this can be changed as a result of engaging with others in a social learning process.
The final element refers to epistemological constraints. In the original SLIM work (see SLIM 2004e) this was titled as 'ecological constraints' as it was noted that there were often diverging and competing understandings and conceptual models of ecology in many natural resource management debates. The SLIM researchers later reworked this, expanding the title of this element to 'epistemological constraints' or 'epistemology' to denote that all conceptual models and ways of knowing from any disciplinary branch (including social sciences) or praxis could constrain the way the situation is experienced and understood.
The key aspect of this diagram is that it is intended as a heuristic rather than prescriptive model of social learning – what occurs within each element and the configuration and 'weighting' of each will vary according to specific context.
Within a social learning paradigm a priority in research practice is to know how to create the circumstances for social learning to occur – ie designing a social learning system. The heuristic depicted in Fig. 11.2 reveals that in social learning, the inquiry moves away from routine or first order learning, by questioning starting assumptions and making sense of context, thus revealing the second order framings used by stakeholders in the situation as they engage with epistemological differences. A social learning system should enable those involved, whether social scientists, scientists, policy makers and practitioners, or any combination thereof, to question framings, norms, policies and objectives in interactive processes involving multiple stakeholders.
In emphasising social learning, integration of social science in policy-making becomes centred on a concern about designing social learning systems (see Ison et al. 2007b) for natural resource managing, as a way of integrating different disciplines within social science to enable contributions to policy processes.
The work undertaken as part of the SLIM project found that to create the conditions for integration to emerge, a social learning system should have the following characteristics:
• Systemic features
– Comprises elements or activities
– Exhibits connectivity
Fig. 11.3 Design for a social learning system in complex natural resource management situations (After Ison et al. 2009)
– Results in transformation
– Has emergent properties
– Is bounded in some way
• Design/designer features
– It is purposeful to those who participate
– It is not deterministic
– The 'designer' is aware that what is valid knowledge is contested.
This listing set out meta-level criteria for design that require more detailed interpretation in relation to specific contexts. One example of a how the meta criteria for design might be enacted as a social learning system is given in Fig. 11.3.
The design in Fig. 11.3 builds on the SLIM heuristic shown in Fig. 11.2 and sets out the key activities which can give rise to social learning. The first activity – clarifying purpose – emphasises the need for those involved in the design and process to be explicit about the purpose of engaging in the learning process. This is an iterative process which requires others to be engaged in the conversation (activity 2) and a (collective) appreciation of a range of stakeholders' views and perspectives (activity 3). As the process continues, new ideas, information and experiences can be introduced to help determine the situation more clearly and understand different framings. The exact means by which this is done varies according to context and need – in some cases a workshop bringing together social scientists and policy makers might be convened, in other instances, it might involve meeting with river managers on a river bank to understand their practices, concerns and framings of the situation. Methodologically, the aim is to enable conversations which enable participants to appreciate the multiple perspectives of those involved in the situation. The emphasis on appreciation is not just a requirement upon the researcher, but extends to all those in engaged in the learning system in that all participants 'sign up' or agree to this way of working.
Arising from the interplay and iteration of activities 1–4, issues and opportunities for progressing the situation begin to emerge and are refined over time (activities 5 and 6). This leads to developing agreement on a set of actions which can be enacted by individuals and/or organisations as appropriate. At this point, the performance of the learning system can be evaluated by recourse to a monitoring process (activity 8). The format of the monitoring process can again vary according to context, but to be consistent with the design of the learning systems, should have input from those involved in the process for determining performance criteria. This is particularly the case with the outputs from activity 3 which requires that the prior experiences of participants are valued in the learning process. Arising from activities 1–8, expected outputs of the learning system include changes in understanding, changes in relations between participants and new concerted practices as part of the transformation of the situation (see Fig. 11.2). It is in these outputs that integration of knowledges and integration of practices (as concerted action) emerges. Activities 9 and 10 relate to monitoring the performance of the learning system and its outputs and re-designing as appropriate.
The SLIM heuristic (Fig. 11.2) and the learning system show in Fig. 11.3 have been used in conjunction for researching and enabling social learning in various contested water resource situations by the author and colleagues from several institutions over the last decade. Aspects of some of this research in the UK, Australia and China provides some insight into the issues associated with designing social learning systems for progressing integration of social sciences into resource managing in different contexts.
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