Network learning outcomes in a programme

It is not straightforward to analyse learning outcomes in a programme characterised by adaptive co-management. Armitage et al. (2008) have given an overview of different definitions and typologies of learning, such as experiential learning; transformative learning; and social learning. They state that even within a particular framework there are multiple and sometimes contradictory definitions of learning. In this paper, we elaborate on social learning because of its explicit focus on the underlying multi-stakeholder participatory process that characterises policy programmes in integrated water management (Huitema et al., 2009; Pahl- between individuals and organisations in a programme (adapted from: Kjær, 2004; Rhodes, 1996). A governance arrangement as a structure refers to the design of patterns and mechanisms in which social order is generated and reproduced within the programme (adapted from: Voß, 2007).

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Wostl et al., 2007; Blackmore et al., 2007). Armitage et al. (2008) define social learning as a process of iterative reflection that occurs when we share our experiences, ideas and environments with others. Muro and Jeffrey (2008) have reviewed studies of social learning in participatory processes. They compare different definitions and conclude that ¨social learning requires the communication and interaction of different actors in a participatory setting which is believed to result in a set of social outcomes, such as the generation of new knowledge, the acquisition of technical an social skills as well as the development of trust and relationships which in turn may form the basis for a common understanding of the system or problem at hand, agreement and collective actions.¨ Most authors of social learning adhere to the same learning typology that distinguishes: single loop learning; double loop learning; and triple loop learning. These concepts have been developed by King and Jiggings (2002), Hargrove (2002) and Keen et al. (2005) and have been adopted and applied extensively in a variety of ways.

Table 7.1. Different interpretations for learning typologies: single, double and triple loop

learning Huntjens et al.,2011; Pahl- Wostl, 2009 Flood & Romm (1996)

Tuinstra (2008) Farrely & Brown (2011) Armitage et al. (2008) Single loop learning Refinement of established actions Do things right Instrumental learning adopting new knowledge to existing frameworks of objectives and causal beliefs Technical learning to achieve objectives Change actions and strategies Double loop learning Changing guiding assumptions / reframing Do the right things Change beliefs, norms and objectives Conceptual learning that reconsiders objectives Change values and policies Triple loop learning Regime transformation or paradigm shift in the structural context. Power imposing values and norms or vice versa Learning the ability to learn itself. Social learning for transformation from technical to conceptual Change governance norms and protocols that predicate single and double loop learning

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Table 7.1 illustrates what Muro and Jeffrey (2008) state as a lack of a consistent concept of social learning that complicates the task of defining common indicators to measure social learning as either a process or outcome. Moreover, none of the literature listed in Table 7.1 explicitly includes learning in individual programmes, or the learning that supports the adjustments of governance arrangements herein, but rather the learning in a sector (e.g. flood management) as a whole. Huntjens et al. (2011) and Pahl-Wostl (2009) classify the learning that contributes to changes of the regime as triple loop learning, referring to structural changes in the institutional context. Pahl-Wostl (2009) assumes that the learning in formal policy cycles, to which individual programmes belong, is restricted to single-loop learning. However, Van Herk et al. (2013c) showed that a programme adopting new paradigms of IFRM and new approaches for adaptive co-management will also foster double and triple loop learning. Such programmes can be considered large-scale experiments (Cook et al, 2004), even though they are not implemented with the aim to experiment or learn, but rather learning is instrumental to deliver specific policy objectives. All authors from Table 7.1 focus single loop learning on changing actions, or technical learning within existing frameworks, and not on changing governance arrangements within programmes or projects. The refinement or change of actions (single loop) and frames, values or beliefs (double loop) is also not positioned or evaluated within the framework of an individual policy or investment programme that delivers adaptation of physical or societal systems.

As the social learning literatures provide no unambiguous way to analyse learning outcomes of a programme, this paper uses theory on network learning from a different domain, namely health services (Knight and Pye, 2004). Literature on network learning – learning by a group of organizations as a group (Knight, 2002) – partly overlaps, but is also complementary to social learning theories. Policy and investment programmes in IFRM can be considered networks. A ‘whole network’ consists of multiple organisations linked through multilateral ties (Provan et al., 2007). IFRM involves interlinked organisations ranging from river basin authorities, to national governments, regional and local governments for spatial planning and urban water systems. Networks are often formally established and governed and goal directed rather than occurring serendipitously (Kilduff et al., 2003). Water management networks comprise multiple organisations with formalised roles and political mandates to manage amongst others: water quality; flood protection and drought. Knight and Pye (2004) analyse network learning as the change in network level properties, such as density and connectedness of organisations, structures and centralization in networks, or governance among a range of organisations. Based on a case study they classify learning outcomes into

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3 categories: interpretations; structures; and practices. Changes in ‘interpretations’ overlap with double loop learning and changes in ‘practices’ overlap with single loop learning. Changes in ‘structures’ partly covers triple loop learning, if referring to changes to institutional structures, but adds a new perspective in comprising changes to governance structures in a single programme. This research applies the classification of learning outcomes by Knight and Pye (2004) to integrated water management and defines its components as follows:

• Learning in terms of changing interpretations refers to the dominant philosophies or paradigms. In the scope of this research they are related to flood risk management, spatial planning, programme management or multi-level governance10.

• Learning outcomes in terms of changing structures are the patterns that are being (re)designed or that emerge from governing activities of social, political and administrative actors (Kooiman, 2003). These patterns also comprise the governance arrangements to manage a programme or project, in order to organise networks of actors and institutional frameworks.

• Learning in terms of practices comprises cognitive and behavioural learning related to working together in a programme or project on flood risk management and spatial planning.

7.3 Research approach

In exploring how learning in a programme that aims to adapt the physical system takes place, the research approach presented here aimed at analysing: (i) the learning outcomes of a programme; (ii) how governance arrangements within a programme have stimulated that learning; and (iii) how learning supports the adjustments of governance arrangements within a programme. Room for the River (RftR) has been selected as a case study for two reasons. Firstly, it has adopted an adaptive co-management approach to integrated water management and is a crucial step in the transition to ‘living with water’ (Van der Brugge et al, 2005; Van Herk et al., 2012b; 2013c). Secondly, Rijke et al. (2012b) show that the programme has an exceptionally high performance in terms of project output, stakeholder satisfaction, budget and time (Rijke et al., 2012b). Learning and programme adaptation have been identified as success factors (Rijke et al., in

10 _{The outcome of interaction among multiple actors from different sectors with}

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press). RftR has a long duration (1999-2015) that allows for much learning and requires adaptation to deal with ever changing internal and external complexities such as: changing stakeholder interests and configurations; new scientific insights; political and economic developments (Hertogh et al., 2008; Hertogh and Westerveld, 2010).

A combination of document analysis; face-to-face interviews (n=55); and observation at 3 training events (45 participants) and 2 political conferences (approximately 220 participants) have been used to analyse the learning outcomes in terms of interpretations, structure, practices (Section 7.2). First, we established the baseline for the learning outcomes at the start of the programme based on an extensive document analysis of formal policy and programme documents. Interviews with individuals who were involved with the initiation phase of the programme (n=10) were used to verify that baseline and further clarify the selection of governance arrangements or structures and practices to work with the new paradigms of river widening and co-management that were set at the start of the programme. The interviews were semi-structured and covered: the motivation for the programme objectives and river widening concept; the design of the RftR programme organisation and of activities for multi-actor collaboration and public participation. Section 7.4.1 describes the learning outcomes for the initiation phase of RftR.

Further semi-structured interviews were conducted to explore learning outcomes as changes in interpretations, structures and practices during subsequent stages of the programme. Questions were asked as to which changes occurred and what induced these changes. 31 interviewees were directly involved in the design and realisation stages of the program and 14 other interviewees held strategic positions at the levels of senior policy makers and decision makers. Interviewees represented a range of disciplines and organisations involved with the individual projects (i.e. waterboards, provinces, municipalities and Rijkswaterstaat, the executive arm of the Ministry of Infrastructure and the Environment that is responsible for the design, construction, management and maintenance of the main infrastructure facilities in the Netherlands) and the programme as a whole (i.e. the Room for the River programme Directorate, its mother organisation Rijkswaterstaat and the Ministry of Infrastructure and Environment). Interview transcripts were analysed using QSR Nvivo 9. Data was coded following the interpretations, structures and practices as found in the design phase. New codes have been added when new categories of learning outcomes emerged from the data. Observed changes have been verified through additional document analysis of meeting notes at all levels of programme governance and of periodic update

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reports of project teams to the Programme Directorate and from the Directorate to Dutch parliament. Section 7.4.2 presents the learning outcomes for the design phase of RftR.

Recurrently mentioned and similar learning outcomes and changes to interpretations, structures and practices have been clustered and analysed for interdependencies. We found mutual dependencies between the 3 types of learning outcomes and their evolution during the various stages of the programme. In Section 7.4 the learning outcomes have been presented and explained as clusters. This paper focuses on the learning outcomes at the network or programme level. For more learning outcomes, see Van Herk et al. (2013b) where the lessons from RftR that have been taken up by individuals, organisations and future programmes have been analysed and considered in terms of their contribution to a transition to IFRM.

Finally, we have analysed the interview data for governance arrangements that have stimulated learning and compared these with literature on learning strategies in adaptive co-management (e.g. Cook et al, 2004; Berkes, 2009; Huitema et al, 2009). From the interview data, we have inductively devised codes for QSR Nvivo 9 on these governance arrangements. These codes largely coincide with the institutional prescriptions for adaptive co-management of Huitema et al. (2009) and strategies to facilitate or improve co-management of Berkes (2009). In Section 7.5 we present the learning mechanisms that took place in RftR following the abovementioned theoretical ideas. This research provides empirical evidence and operational lessons as to how these theoretical prescriptions have been applied in a programme. A quantitative survey (n=151) has also been used to understand the importance of governance arrangements in terms of programme output and its contribution to a wider transition. Respondents were asked to rate success factors of RftR for its output and uptake in future programmes, using a five-point Likert- based scale, where 1. is very unimportant and 5. is very important. These success factors were previously deduced from the interviews and comprised: the urgency after the floods of 1993 and 1995; the programme objectives; its organisation; human factors such as leadership and trust; contextual factors such as political and economical developments. These results cannot provide evidence of a causal relationship between governance arrangements and learning and its impact on output and outcomes because: multiple factors influence the impact; governance arrangements have been continuously adjusted; and learning cannot be qualified and measured (Muro and Jeffrey, 2008). Nonetheless, the results provide insight into their relative importance of governance arrangements compared to other succes factors with e.g. the impact of the floods of 1993 and 1995 that scored an

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average of 4.3 out of 5. To validate the findings, we organised a network event to discuss the lessons learnt from RftR (approximately 150 participants that have been involved in the programme in various roles). The research at the level of a programme required the use of multiple sources of evidence and a validation from multiple perspectives.