Ecological Economics 77 (2012) 16–26

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Ecological Economics

j ourna l homepage: www.e lsev ie r .com/ locate /eco lecon

Surveys

An analysis of the methodological underpinnings of social learning research innatural resource management

Romina Rodela a,⁎, Georgina Cundill b, Arjen E.J. Wals a

a Education and Competence Studies, Wageningen University and Research Centre, Wageningen, The Netherlandsb Department of Environmental Science, Rhodes University, South Africa

⁎ Corresponding author at: Wageningen University8130, 6700 EW Wageningen, The Netherlands. Tel.: +3

E-mail address: rominarodela@hotmail.com (R. Rod

0921-8009/$ – see front matter © 2012 Elsevier B.V. Alldoi:10.1016/j.ecolecon.2012.02.032

a b s t r a c t

a r t i c l e i n f o

Article history:Received 13 December 2011Received in revised form 29 January 2012Accepted 29 February 2012Available online 29 March 2012

Keywords:Social learningNatural resource managementMethodologyMethods

This analysis is focused on research that uses a social learning approach to study natural resource issues. Wemap out the prevailing epistemological orientation of social learning research through the de-construction ofthe methodological choices reported in current social learning literature. Based on an analysis of 54 empiricalinvestigations of social learning and natural resources published after peer review, we investigated aspects ofresearch design that include data collection methods, evidence types and the researcher's role. We considerthese against different research-orientations (positivist, interpretive, critical, and post-normal). We discusswhich research-orientation appears most congruent with the overall commitment and premises of sociallearning studies. In line with initial expectations this study shows that positivist stances are hardly present,however research that follows a postnormal approach is less frequent than initially assumed. Instead,findings suggest that researchers using a social learning perspective to study resource issues tend to choosemethodologies that allow for in-depth descriptions, for meaning making and enquiry as a form of action.

© 2012 Elsevier B.V. All rights reserved.

1. Introduction

In recent years, the interest in social learning as a conceptual con-struct to be used for research and practice has increased substantially.As a result there is a rapidly growing body of literature and althoughthis literature has not agreed upon a definition the term social learn-ing is used with reference to a learning-based approach to environ-mental and/or resource management where reflective practice,utilisation of diversity, shared understanding and experimentationare seen as key features (e.g., Borowski, 2010; Garmendia and Stagl,2010; Rist et al., 2007; Schneider et al., 2009; Shackleton et al.,2009; Van Bommel et al., 2009). However, Reed et al. (2010) arguethat a lack of conceptual clarity and of a clear definition of sociallearning brings into question any evidence that learning has indeedtaken place. Muro and Jeffrey (2008) share this position, arguingthat the literature is vague about what exactly social learning is, andthat it offers limited empirical evidence on the role or effectivenessof social learning in participatory planning and decision making.Both papers, in raising questions about available empirical evidence,convey certain expectations about: i) the steps involved in knowledgeproduction and ii) validation (i.e. what counts as evidence) processes.This invokes an expectation for an iterative process of formulating and

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testing assumptions and definitions. In turn, this suggests that only cer-tain types of evidence can prove the effectiveness of social learning (i.e.,testable evidence). The authors of both papers, in raising questionsabout available empirical evidence, bring to the surface a lack of re-search into ontological and epistemological issues which is neededwhen it comes to questions of knowledge production and validation.

The aim of the research reported here was to map out the prevail-ing epistemological orientation of social learning research throughthe de-construction of the methodological choices reported in currentsocial learning literature. To this end we performed a systematic anal-ysis of selected empirical literature i.e. papers that report on/use so-cial learning in relation to empirical studies in practice, and havefocused on the choices made with respect to the study design, datasource and collection methods among others. Since we anticipated apredominance of post-normal approaches (e.g., Funtowicz andRavetz, 1993, 1999), we also accounted for the relationship betweenthe researcher and the phenomena under observation.

In order to develop a framework for analysing methodologicalchoices, Section Two reflects on knowledge production and validationpractices that seem to resonate most within the environmental man-agement and governance literature. There four typified categories arebriefly summarised. Section Three then details the method used to se-lect publications for this analysis and to extract and analyse data. InSection Four the results are presented and a discussion of how differ-ent strands of social learning literature treat knowledge productionand validation practices is provided. The last section providesconcluding remarks and links our results to possible future directionsin social learning research.

17R. Rodela et al. / Ecological Economics 77 (2012) 16–26

2. A Reflection on Practices of Knowledge Production

A journey through methodological choices acquires specific rele-vance when it is accompanied by a reflection on practices of knowl-edge production and validation. For this reason, we will brieflyoutline some of the philosophical considerations that seem to reso-nate most within the environmental management and environmentalgovernance literature. These considerations originate in the sociologyand philosophy of science, where by setting certain standards ofargumentation, researchers try to reflect on what constitutes scientif-ic research and how it evolves over time. Some of these insights haveentered the environmental management and environmentalgovernance literature, and contributed to raise questions about howresearch about the environment should be conducted and whichmethodology is best suited to investigate contemporary environmen-tal issues. Several important discussions of these issues can be foundwithin ecological economics; a field that has emerged from criticalconsiderations of the appropriateness of separating the study of eco-nomic systems from the study of ecological systems (Kastenhoferet al., 2011; Norgaard, 1985, 1989; Røpke, 2005; Tacconi, 1998). Eco-logical economics embraces a pluralistic approach and this allows forcritical considerations of current research practices and at the sametime offers space for reflections on how research about environmen-tal issues should be undertaken. Funtowicz and Ravetz (1990, 1994b)reflect on changes in contemporary scientific research by consideringwho takes part in knowledge production and validation and highlightthe idea of science as a socially distributed practice where, due to un-certainty and complexity associated with environmental issues, newquality criteria need to be integrated. Tacconi (1998) extends this toinclude the constructivist approach while Ramos-Martín (2003)makes a link to complex systems thinking. These authors highlightthe strengths and weaknesses of different research approaches inthe study of social–ecological systems.

Although it is not possible to talk about a clear-cut classification ofresearch approaches that currently characterise scientific research, itis particularly in relation to knowledge production and validation prac-tices that a distinction can be drawn between the positivist, the inter-pretative, the critical and the post-normal approach (Table 1). Beforegiving a brief description of each we must clarify that this is not anexhaustive list. Rather, the approaches listed are typified categoriesthat seem to resonatewithin the environmentalmanagement and envi-ronmental governance literature. Therefore, the position of positivism is

Table 1Summary of knowledge production practices (input sought in the writings of Funtowicz an

Dimension Positivist Interpretative

Basic goal In search of truth. In search of actors' interpreta

Build upon current knowledgebase and fill gaps in ourunderstanding

Provide a rich picture of thof a given issue by differen

The nature of knowledge Knowledge is universal Knowledge is contextual

Most used mode of inquiry Scientific method Phenomenological inquiry

Reasons for undertakingthe investigation

Finding evidence(discovery, curiosity)

Understanding

Type of evidence discussed Mainly quantitative Mainly qualitative

Researcher's role Neutral outsider Participant

Degree of interaction with otherresearch programmes

Lines are tightly policed:disciplinary differentiation

Lines are loose: inter-disci

Audience Peer community Peer community

that reality is given and exists independent from humans. A conse-quence of this position in research is the separation of the observerand the observed by using the scientific method that includes observa-tion, measurement, experimentation, as well as the formulation, test-ing, and modification of the assumptions initially stated (Guba, 1990;Kuhn, 1970; Norgaard, 1989). Rigour, quantitative analysis and controlover variables are the cornerstones of corresponding scientific methodsand the aim is generalisation of the research findings. Kuhn, (1970)challenged the idea of objectivity when asserting that scientists workunder theoretical frames that are superimposed on the phenomenaunder investigation. The positivist approach was challenged on addi-tional grounds, for instance; for its assumptions that reality is uniformand unchanging and that knowledge accumulated about an object canbe generalised to a wide range of cases (Norgaard, 1985, 1989), for itslimitations in managing complex systems that are characterised byhigh levels of uncertainty (see: Checkland, 1981, 2000; Ramos-Martín,2003; Vickers, 1965), and for rejecting non-scientific knowledge(Funtowicz and Ravetz, 1999). Several of these critiques are under-pinned by an ontological position that postulates that reality is sociallyconstructed and hence can take on multiple meanings.

The position of interpretative research is that reality is socially con-structed and cannot be captured by single interpretations that allobservers, or rather, participants in reality, share. Therefore, theresearcher's task is to unveil the interpretations that different groupshave of an object, phenomenon or issue. Interpretative research rejectsthe difference between subject and object and postulates that as we aremerged with our world, the way we go about understanding it is influ-enced by this condition (Heidegger, 1982). Thus, it is relevant to discernwhere the subject comes from in order to know how she/he goes aboutabstractions, rationalisations and theoretical constructions (Ricoeur,1981). This position assumes that knowledge is socially constructedand as such rather than testing assumptions, the researcher acts as anobserver seeking to identify the many interpretations available and tounderstand if and how these influence each other, and the object ofinterest. Many schools of interpretative research can be found and a de-tailed analysis of these is beyond the scope of this analysis. However, itmight be worth indicating differences among those cited by the ecolog-ical economics scholars mentioned above. For instance phenomenolo-gy, whose roots are in a philosophical movement that developed atthe beginning of the 20th century, evolved to include a range of inter-pretative methodological approaches discussed in detail by Moustakas(1994). These include ethnography, grounded theory, hermeneutics

d Ravetz, Kuhn, Moustakas, Ramos-Martín).

Critical Post-normal

tions of the world. In search of a transformations. In search of a negotiated agreement.

e interpretationst groups

Provide input for empoweringprocesses undertook bypractitioners

Provide scientific input for policyand decision-making

Knowledge is power Knowledge is multifaceted

Reflective inquiry Action research

Empowering Problem solving

Mainly qualitative Qualitative and quantitative

Learning agent, participant Advocate, participant

plinary Lines are loose:inter-disciplinary

Lines are open: trans-diciplinary

Peer community, practitionersand society

Extended peer community(stakeholders), policy anddecision-makers

18 R. Rodela et al. / Ecological Economics 77 (2012) 16–26

and empirical phenomenological research. These share several ele-ments such as the search for meaning and for first-person lived experi-ences and for this reason these frequently rely on qualitative data that isused to provide a rich picture, for example through the development ofcase studies based on in-depth interviews, life histories, text and narra-tive approaches (Alvesson and Skoldberg, 2000; Creswell, 1998; Wals,1993). But these methodological approaches also share the position thathuman experience and behaviours are part of the subject–object dialecticand seek an understanding of the wholeness of experience rather thanseeking to isolate a part of it (Creswell, 1998; Moustakas, 1994). Thesemethodological approaches do not aim for control upon pre-defined vari-ables, nor do these aim for generalisation or prediction (Wals, 1993).

A further approach that has influenced the environmental manage-ment and governance literature can be traced to the Frankfurt school ofcritical theory and has been most intensively influenced by Habermas'writings about deliberative democracy. This approach, which is often re-ferred to as critical research, also seeks to unveil the interpretations of re-ality, but often does so through the lens of power relations (Hart et al.,1994; O'Hara, 1996; Wilson and Howarth, 2002) oftentimes with a nor-mative purpose of overcoming power imbalances and social inequities.Several research methodologies are used to do this. Critical research, incontrast to the interpretative research which tends to engage innaturalistic inquiry (i.e. the study of phenomena in their natural setting),frequently integrates interventions in the study design e.g., participatoryworkshops. Such interventions are designed to study scholarly relevantquestions but it is not uncommon that these seek to fulfil further objec-tives, such as producing socially relevant outcomes and the empower-ment of those involved (e.g. Meppem and Bourke, 1999). In this, theresearcher's personal ambitions, values and ethical principles are not ex-cluded from the research inquiry but are rather seen as functional for theresearch process through which the researcher moves.

A post-normal approachwas first conceptualised by Funtowicz andRavetz (1993, 1994a, 1999) who identified features that they saw ascharacterising contemporary scientific research. Their interest is incurrent environmental challenges, which they see as being in needof urgent action. Funtowicz and Ravetz (1993, 1994a, 1999) arguedthat the ‘puzzle-solving’ approach (sensu Kuhn, 1970) to scientificresearch is inadequate for contemporary environmental and sustain-ability issues which are characterised by high levels of complexity,uncertainty and contestation (Peters and Wals, in press). A “post-normal” approach to research tends to be issue-driven, policy rele-vant, transdisciplinary and emphasises “issue improvement”. In relationto this last aspect,muchof contemporary post-normal researchers selectaction research as a mode of inquiry, where the researcher does notoperate alone under firmly defined disciplinary domains but is engagedin boundary crossing and collaborates with an extended communitywhose input is sought during problem formulation, or later, for thepurpose of knowledge validation. The researcher is exposed to, andrecognises the value of, different ways of knowing and knowledgethat can be used during the research process. Funtowicz and Ravetz(1990, 1993) defended the need for a new criterion for research out-comes; that of extended quality assurance. Quality of scientific researchcould be pursed through extended peer communities that take part inknowledge production and/or validation, but the researcher's personalambitions, values and ethical principles are also functional for qualityassurance.

Although these approaches to scientific research differ from oneanother in many ways, the last three (interpretative, critical and post-normal) seem to share some similarities (Table 1). For instance, theyshare the position that multiple interpretations of reality (co)exist,and favour qualitative data and cases studies instead of testable propo-sitions to be generalised. Also, these approaches allow for theresearcher to take on a different role, compared to a positivist tradition,as she/he moves between being a participant observer to a learningagent, or activist. It can be assumed, therefore, that the choices madeabout i) methodology and ii) researcher's role can help us understand

the epistemological base of the current social learning discourse, andit is on these two aspects that we base our analysis. Before discussingthe results, we provide a brief description of the methods used.

3. Methods

Selected literature was analysed with the aim of disentanglinghow it positions on aspects related to i) research methodology andii) the researcher's role vis-à-vis the observed. These two were bro-ken down into sub-questions that informed the development of acode-book used for the data extraction process (see: Annex I). Asimilar approach was used also by Kastenhofer et al. (2011). Sincewe were interested in questions of methodology, we focussed onlyon literature reporting on empirical studies.

We followed a number of steps for the retrieval of publications ofwhich some were similar to those undertaken for an earlier study(e.g., Rodela, 2011). That study had a different focus and covered amuch larger sample, i.e. 97 publications. To be included in the presentanalysis, papers had to meet two criteria: i) they had to be a peerreviewed publication; and ii) they had to be based on empiricalresearch in relation to social learning and natural resources. Paperswere excluded if they: i) used social learning superficially (i.e.mentioned the term but did not carry the concept through to theanalysis stage of the paper, and ii) reported on the same research(i.e. multiple publications), in which case only the most recent publi-cation was included. Two researchers searched through electronicbibliographic databases (Web of Science; SCOPUS). Abstracts of re-trieved publications were screened for relevance first and then laterfull papers were checked against predefined inclusion and exclusioncriteria.

3.1. Data Extraction and Analysis

A code-book was developed jointly by this research team and usedthroughout the data extraction process where individual studiesserved as data points. Data extraction was performed by two re-searchers who worked with a sub-set of 30 publications separatelyand later compared their coding results. This helped to identify dis-agreements in particular for content that was not overtly discussedin the selected literature (e.g. researcher's role). Disagreements suchas these can be handled by randomly selecting the coders' decisions,by asking an expert to serve as tie-breaker, or by discussing and re-solving the disagreements (Lombard et al., 2002). We chose toidentify differences in the interpretation of the two coders and soughta settlement over these. This was extended to the whole sample. Forcases where more than one code could be assigned to an item we choseto add additional columns (Annex 2). Once data were extracted wemirrored the results against the dimensions summarised in Table 1and discussed the anomalies that emerged during the data extractionprocess.

3.2. Limitations of this Study

Limitations to this type of method are known and have beendiscussed elsewhere (Petticrew and Roberts, 2006). For instance, by fo-cusing only on sources that allow a systematic retrieval of material(bibliographic databases) other written sources are excluded (e.g.,books, proceedings). Another limitation relates to some unavoidablesubjectivity entering the data extraction and data analysis process.With the aim to address the latter issue we took the followingmeasures: more than one person conducted the bibliographic search,a data extraction form was designed by an interdisciplinary teamand more than one person undertook data extraction on the samepapers. We recognised that it is difficult to argue for objectivitywhen the appraisal involves non-numeric or poorly described items.In this respect it makes more sense to speak about striving for

19R. Rodela et al. / Ecological Economics 77 (2012) 16–26

inter-subjectivity rather than objectivity. Thus, it is recognised that adifferent team of researchers might arrive at slightly differentconclusions than we did. The pool of authors contributing to thisresearch has expertise in different areas e.g., anthropology, education,and natural resource management. This we believe has benefited theprocess in terms of diversity of perspectives from which to interpretdata.

4. Results and Discussion

The review process started with an initial pool of 116 papers re-trieved as indicated above. The selection was narrowed to those pa-pers with an empirical focus, from which multiple publications ofthe same study and also publications which are not grounded in anempirical study were excluded. The final sample resulted in a totalof 54 papers reporting on empirical studies in practice published be-tween 1995 and 2010.

4.1. Methodological Choices

Twenty nine of the 54 papers reviewed declared an explicit interestin furthering our understanding of social learning, and used study de-signs meant to directly address questions about social learning. On theother hand, 25 studies reported on research that aimed to further theunderstanding of other phenomena e.g. the role of multi-stakeholderplatforms, and then within this context turned to social learning. Thisaspect emerged later during data analysis when we began to noticethat in several studies hindsight was used. It is relevant to clarify thatthis second group of studies are not evaluations since they do not usepre-defined criteria but are analyses of social learning opportunities,and related, in retrospect i.e., ex-post analysis. These studies drawupon past projects that have come through a full research cycle. Inthis we observed that several of these ex-post analyses were performedas a reflective exercise, or as an ad-hoc explanation, for whichsecondary data, reports or own experience was used. For instance,some analyses are mainly based upon hindsight where researchershave capitalised on past experiences and have compared in a lessstructured way how one, or more, past projects performed on sociallearning (e.g., Bouwen and Taillieu, 2004; McDaniels and Gregory,2004; Measham, 2009; Shackleton et al., 2009). Others haveintegrated reflections with the display of field data. For instance Millarand Curtis (1999) searched through interviews, collected for thepurpose of evaluating a project for pasture management, in order togain insight into participants' group-learning experiences, whileSchneider et al. (2009) integrated interview data with observationalnotes, collected for the purpose of project evaluation.

Social learning is a concept that has only recently attracted sub-stantial interest within the resource management community andan explanation for such ex-post analyses can perhaps be found in thetime lag that is involved in the prioritisation of research themes andfunding cycles. We could assume that during the early 2000s, whenseveral of these projects were submitted for funding, social learningresearch was not part of the mainstream natural resource manage-ment agenda, and perhaps not a priority for integration in researchproposals. Hence, when ideas around social learning began toconverge into a discourse in the mid 2000s, those with an interestin learning might have turned back to past projects and, as anexercise, tried to assess if, and how, social learning might have playedout in the research process or the systems of interest.

The way ex-post analyses are structured and the objectives theseaim to achieve can indicate some trends. Ex-post analyses can take onmany forms but two are of particular interest here. Ramos-Martín(2003) points out that in environmental economics ex-post analysesare used for the purpose of ex-ante predictions given that an underlyingassumption in environmental economics is that the physical system canbe described by a universal law, and hence, extrapolating past results

they can be used to model future trends. This type of ex-ante study ad-heres to the positivist approach to scientific research where the aim iscontrol over variables and prediction. However, Ramos-Martín (2003)highlights that when a different ontology is in place and the system isunderstood as evolving and changing then an alternative approach toresearch is needed and hence ex-post analyses would serve a differentpurpose than ex-ante predictions. Then, ex-post analysis can serve asa reflexive inquiry during which the research team tries to (re)describeand (re)interpret data, ideas and concepts by looking at past work withnewly accumulated tools and knowledge. Reflexive inquiry allows theintegration of more than one methodology and theoretical perspective(Alvesson and Skoldberg, 2000). In so doing, it can shed new light onpast environmental issues, perhaps highlighting aspects that wereoverlooked and in so doing generate new insight for future practice(Rapp Nielsen, 2010). In several of the selected papers, where researchtakes the form of an ex-post analysis, it is explained that the aimwas tobring together past experience in order to highlight the “lessonslearned” with specific interest in those aspects that were seen as keyelements for social learning. The presence of this type of inquiry, theemphasis on reflection and the interest in re-interpretation of past re-search suggests an ontological position where reality is seen as sociallyconstructed and taking multiple meanings.

However, ex-post analyses bring with them some challenges. Inparticular, questions have been raised about the ability of researchersto engage in the interpretation of their own interpretations i.e., thedouble hermeneutic, (e.g., Alvesson and Skoldberg, 2000; Lincoln,1995). We searched for strategies that the social learning literaturemight have used to cope with the double hermeneutic, but were un-able to identify any reference to this specific methodologicalchallenge. Selected papers do not give sufficient methodologicaldetail to help us understand if and how the interpretation bias washandled. Nor have they provided information that can help us to de-construct the methodological choices associated with reflexiveinquiry in greater detail. As highlighted by Alvesson and Skoldberg(2000, p.270), reflexivity is not an end in itself but a means to (re)de-scribe and (re)interpret ideas, “it is the ability to break away from aframe of reference”. Following from this, it is assumed that a reflexiveinquiry will be more fruitful when performed within an inter(trans)disciplinary team given that disciplinary influence, own worldviews,and personal stakes could be more easily identified and comparedto that of other team members. In so doing, the risk ofsubjective and arbitrary representations can be reduced. This studyfound that the majority of selected publications are indeed co-authored. Hence, we assume that these analyses benefited in thisway (e.g., Rist et al., 2007; Schneider et al., 2009; Shackleton et al.,2009).

In terms of data collection methods, the selected studiesfrequently employed interviews and observation for data collection.For instance, interviews with resource users or stakeholders areused in research reported in 37 papers, followed by participant obser-vation (26), text extraction from policy documents, reports and otherarchival material (22), and self-reported questionnaires (15). Choicesof sample selection indicate that non-random methods were chosenfor research reported in 36 papers (although several do not revealthis).

Two issued emerged during the coding of data collection methods.The first issue is that of multiple codes, as in several papers more thanone method is mentioned. This was handled by adding columns to theExcel file where this information could be stored (Annex II). The sec-ond issue relates to the detail of information that we initially hopedfor as it was not always reported in the papers. For this reason thenhave re-worded and clustered our codes (observation direct=3 andobservation unobtrusive=4; interviews structured=1 and inter-views semi-structured=2) into general ones as found within the se-lected papers (observation; interviews), then integrated into theExcel file.

20 R. Rodela et al. / Ecological Economics 77 (2012) 16–26

Hence, it seems that qualitative data is preferred and it can be as-sumed that it is so because it allows for in-depth understanding of theissue being investigated. On the other hand an explanation for thiscan also be found in the type of phenomenon under investigation.Learning as a process is not easily measured or captured with quanti-tative tools especially in relatively uncontrolled, somewhat messy,settings involving multiple stakeholders (Cundill and Fabricius,2009; van Mierlo et al., 2010).

The choice of study designs also suggests an interest in depth vs.breath; 22 publications report on a single case-study, 9 on multiplecase-study comparisons, and 2 on experiments, with the remainderbeing coded as reports/analyses of completed research. Large scalesurveys which allow for a certain degree of representativeness, andhence generalisation, are not reported in any of the selected papers.Hence, this study finds that in addition to the ex-post analyses thesocial learning research community is active in single case studies.Case studies allow for historical depth and a fine grained description.Case studies can be used for the identification of causal processes andtheory building. However, as Della Porta and Keating (2008) pointout, case studies are not very useful for testing hypotheses orestablishing relationships between variables. Case studies allow theproduction of context dependent knowledge. Therefore these, alongwith the earlier highlighted methodological choices, seem to indicatethat research reported in some of the selected publications is focussedon aspects other than testing and verifying the effectiveness of sociallearning. Rather, it seems that research tries to gather a deeper under-standing of learning processes and meaning making patterns, andthat often this is performed starting with own (researcher's) experi-ences in the field. As a consequence the process of knowledgeproduction does not follow an iterative process of formulating andtesting assumptions nor is it directed towards finding unequivocalevidence about the performance and effectiveness of social learningprocesses. This, as pointed out in the introduction, goes againstthe expectations of some commentators, and perhaps explains someof the criticisms that have been levelled at the social learningliterature.

It follows that the above described methodological choices signalthat social learning research adheres to a position that allows for mul-tiple interpretations of reality and accepts that context is important.However, contrary to our initial expectations (that social learningresearch was developing within a post-normal approach), thefindings suggest that it is rather tending toward the interpretativeand critical research agenda. A post-normal approach relies on trans-disciplinarity, that is, the opening up of the knowledge productionand validation process to an extended peer-community. However,the methodological choices identified suggest that this was the case inresearch reported only in a few publications. While social learningresearch is engaged in issue-driven research and seems to beinterested in socially relevant outcomes, it seldom integrates or reportson aspects of quality assurance. The next section helps to further disen-tangle this.

4.2. The Researcher's Role

Several scholars have already commented, as discussed above,that in contemporary scientific research there is a shift in the aspira-tions the researcher has as he/she chooses to take a different role vis-á-vis the researched (Funtowicz and Ravetz, 1993, 1999; Söderbaum,1999, 2011). From an impartial and value free observer the researchermoves into the role of a learning agent engaged in a reflexive inquiry,or that of an activist committed to issue-driven research.

Of 54 selected publications, 3 indicate that researchers haveacted as neutral outsiders, while 17 do not provide sufficient infor-mation about this aspect. On the other hand, 24 publicationsindicate that the researchers became involved with the phenomenaunder investigation and, for instance, took part in workshops where

they contributed to influence group dynamics either by facilitatingthe process, or becoming a participant observer (e.g., Blackstocket al., 2009; Garmendia and Stagl, 2010; Webler et al., 1995). Re-searches also report becoming involved with study participants inother ways. For example, 2 publications indicate that researchersacted as activists and undertook research activities in order toachieve (pre-identified) desirable outcomes, while 8 publicationssuggested that researchers were involved themselves in learningand in reflection which had important implications for the researchprocess (e.g. data analysis and interpretation) as well as for the re-searcher himself/herself (e.g. worldviews). For example, Toderi etal. (2007, p. 554) give an account of how, in reaction to someevent, the research team chose to rethink its role: “the agronomistsabandoned the expectation that the deployment of scientific datawould instigate linear and causative change, in favour of a willing-ness to explore social learning processes, joint reflection, and thefacilitation of the self-organisation of change among multiple stake-holders”. Not only did team members become committed tofacilitate change, but they themselves become part of a learningprocess and, as a result of interaction with other stakeholders,experienced a change in their own frames of reference. “The processincreasingly became a stakeholder-driven process and as such hadthe (unexpected) result of re-shaping the ongoing researchactivities of the research team. The team's development as reflec-tive practitioners was fundamental to the identification of newfactors influencing the system of interest, and to the identification ofnew boundaries to what needed to be included in the system in orderto improve the management of water quality” (Toderi et al., 2007,p. 561). A similar experience is mentioned by Millar and Curtis (1999)and Schneider et al. (2009). However, rather than focusing onreflexivity and considering how it influenced the worldviews of thoseinvolved, in these studies the focus is on knowledge co-productionbetween scientists and other stakeholder groups e.g. farmers, experts.Coding of this item was quite a challenging task as information abouthow researcher(s) positioned vis-á-vis the researched is not alwaysincluded and in several cases this was extracted from sentencesmeant to clarify other things that we regarded were useful to this endas well.

As already mentioned above, certain research approaches (e.g., in-terpretative and post normal) favour the involvement of stakeholdersand other social actors in the research process as it assumed theybring in new repertories of interpretation and in so doing contributeto amore rounded understanding of thephenomenaunder observation.However, only 6 publications out of 54 indicate that stakeholders wereinvolved in problem definition. Also, only 12 publications indicate thatdata collection and analysis was undertaken with a degree of stake-holders' involvement. Given that there are no general guidelines onhow to report on this aspect it could be assumed that some mighthave chosen not to write about this and thus a suggestion for future re-search is to bemore explicit when reporting onmethodological aspects.On the other hand, if we assume that papers have indeed reported accu-rately upon the research done then, froma post-normal perspective, theabove numbers could indicate that stakeholders are being given limitedspace for participation. This comes as a surprise, since the expectationfor a research agenda that prefers depth over breath and favours a vari-ety of repertories of interpretation is not only to be reflexive but alsoopen. Perhaps an explanation for what seems to be low involvementof stakeholders in problem definition, data collection and analysis,could be ascribed to institutional barriers that researchers encounterwithin their own departments, the funding bodies supporting the re-search, and the kind of publishing opportunities they are expected topursue. Stakeholders themselves might not have the time, the politicalsupport or the interest to contribute to the research process. Anotherexplanation might be that since social learning is an emerging researchtheme, problem definition very often remains within the domain ofresearchers, especially where the core goal of a study is to increase

Analytical item Coding

Study design Not applicable=0Case study=1Multiple-case study=2Experiment=3Longitudinal=4Reports/analyses of completed research=5

Data collection method Not applicable=0Interviews unstructured=1Interviews semi-structured=2Observation direct=3Observation unobtrusive=4Text selection=5Questionnaire=6Not revealed=8

Sample selection Not applicable=0Not revealed=1Random sampling=2Non-random sampling=3

Subjects involved in researchproblem definition

Not applicable=0Researcher alone=1Researcher+community=2Researcher+policy-makers=3Researcher+community+policy-makers=4

Subjects involved in datacollection.

Not applicable=0Researcher alone=1Community=2Researcher with community=3

Researcher's role Not revealed=0Neutral outsider=1Participant=2Learning agent=3Activist=4

21R. Rodela et al. / Ecological Economics 77 (2012) 16–26

understanding of social learning, which was the case in roughly 50% ofour sample.

This analysis exposes a tension. On the one hand, on the basis ofthe methodological choices being made by researchers, we find thatthe social learning discourse seems to be leaning toward the criticaland interpretivist approaches, while on the other hand there seemto be expectations about testable knowledge. The tendency of re-searchers not to disclose the methodological choices that they havemade makes it difficult to tease this trend out (Dillon and Wals,2006). However, we suspect that Kuhn's (1970) observations aboutthe role that paradigms have on how we engage and understandscientific research might help us to locate this tension. Kuhn (1970,p. 46) pointed out that: “Scientists work from models acquiredthrough education and through subsequent exposure to the literatureoften without quite knowing or needing to know what characteristicshave given these models the status of community paradigms”. The as-sumption that the nature of observation may be influenced by priorbeliefs and experiences of the scientist challenges the position thatscientists are neutral observers. This review has focused on a specificapplicative domain i.e. natural resource management. Although thisfield rapidly becoming interdisciplinary, we can assume that a major-ity of this community is constituted of scientists with training in thenatural sciences where a positivist approach to scientific researchdominates. This training would influence expectations and the wayscientists are engaged in borrowing practices from the social sciencesand humanities. If this is the case, then what we are seeing might wellbe the outcome of interdisciplinary cross-fertilisation that is in theearly stages of evolving its own methodological agenda. Although be-yond the scope of this study, an analysis of the disciplinary back-grounds of researchers would offer further opportunities for theinterpretation of the above results.

Therefore, rather than the alignment with a particular researchapproach our findings seem to indicate that social learning researchis moving between the interpretative, the critical and, to a lesser ex-tent, the post-normal, and is using methodologies and modes of in-quiry from all of these.

5. Conclusions

The present analysis focused on empirical research on sociallearning with the aim to reflect on aspects that pertain to the processof knowledge production and validation. There are expectations thatcurrent research should follow an iterative process of formulatingand testing assumptions and definitions about social learning (i.e.knowledge production) and should produce evidence (i.e. knowl-edge validation) about the effectiveness of social learning. In con-trast a great number of publications report on research that isseldom meant to evaluate the effects of individual variables e.g.learning, or to test what techniques, or interventions, can best leadto social learning. Rather, the literature explores social learning onthe basis of hindsight, own experiences, or uses empirical data ex-trapolated from activities meant to evaluate other processes, or con-cepts (e.g. participation). This mismatch between what analystsexpect to see in the literature on this topic, and what is actually pro-duced in practice, focuses attention on the existence (or absence) ofshared standards of evidence, argument and logic, and suggests thatsome of the current empirical research delivers content that is of adifferent form, and follows practices that differ, from what somewould expect.

This is tightly linked to questions of research design and, aboveall, to the ontological positions that guide the methodologicalchoices of those engaged in social learning research. Current sociallearning researchers are moving between more than one researchapproach, namely the interpretative, the critical and the post-normal, and are using methodologies and modes of inquiry from allof these. In natural resource management, much like in ecological

economics and other cross-boundary areas, researchers come froma wide spectrum of disciplines. They bring with them expertise,long years of specialised training and consequently expectationsabout knowledge production and validation which might not alwaysbe shared among others working in the domain of interest. Thiscould partially explain why criticism has been growing of theways in which social learning is approached (e.g. Muro and Jeffrey,2008; Reed et al., 2010). However, being more explicit about themethodological choices that are made should help to assuage thesecriticisms in the future.

We hope that this study will support researchers and practitionersin the selection of methodologies for studying social learning in naturalresource management. Above all, we hope that this study will help re-searchers, who are engaged with learning-based approaches, to bemore aware of the importance of reflecting on their ontological andepistemological positions and their associated methodological choicesand trade-offs.

Acknowledgements

The authors wish to acknowledge funding received from thefollowing bodies and/or programmes: the FP7-Marie Cure Actions-IEFof the European Commission (Romina Rodela), Rhodes Universitypost-doctoral fellowship and a SANPAD bursary (Georgina Cundill).The authors would like to thank Jarl Kampen and Peter Tamas forcomments on the code-book. An earlier version of this workwas presented on the 22th September 2011 at the “Researchinglearning professional development workshop” organised by theEnvironmental Learning Research Centre at Rhodes University. Theauthors would like to thank those in attendance at the workshop, inparticular Heila Lotz-Sisitka and Rob O' Donoghue for comments andsuggestions

Annex I. Code Book

, 4) *DC 5 *DC 6 *DC Sample Subjects Subjects Researcher's

22 R. Rodela et al. / Ecological Economics 77 (2012) 16–26

No. Paper Study *DC (1, 2) *DC (3

Annex II. Database Used for the Analysis

design interviews observation text questionnaire 8 notrevealed

selection invol.in res.problem

invol. indatacollection

role

1 Armitage, D.R., 2005. Community-based narwhalmanagement in Nunavut, Canada: change,uncertainty, and adaptation. Society & NaturalResources: An International Journal,18(8):715–731.

1 1 1 1 3 1 1 2

2 Blackstock, K., Dunglinson, J., Dilley, R., Matthews,K., Futter, M., Marshall, K., 2009. Climate proofingScottish river basin planning — a future challenge.Environmental Policy and Governance,19(6):374–387.

1 1 1 3 1 3 3

3 Bommel, S.V., Röling, N., Aarts, N., Turnhout, E.,2009. Social learning for solving complex problems:a promising solution or wishful thinking?Environmental Policy and Governance,19(6):400–412.

1 1 3 1 1 0

4 Borowski, I., 2010. Social learning beyond multi-stakeholder platforms: a case study on the ElbeRiver basin. Society & Natural Resources: AnInternational Journal, 23(10):1002–1012.

5 1 1 1 0 1 1 0

5 Bouwen, R., Taillieu, T., 2004. Multi-partycollaboration as social learning for interdependence:developing relational knowing for sustainablenatural resource management. Journal ofCommunity & Applied Social Psychology,14(3):137–153.

5 1 1 1 1 0

6 Brown, H.C.P., Buck, L.E., Lassoie, J.P., 2008.Governance and social learning in themanagement of non-wood forest productsin community forests in Cameroon.International Journal of Agricultural Resources,Governance and Ecology, 7(3):256–275.

1 1 1 1 3 1 3 2

7 Brummel, R.F., Nelson, K.C., Souter, S.G., Jakes, P.J.,Williams, D.R., 2010. Social learning in a policy-mandated collaboration. Journal of EnvironmentalPlanning and Management, 53(6):681–699

2 1 1 1 1 1 0

8 Cheng, A.S., Mattor, K.M., 2010. Place-basedplanning as a platform for social learning: insightsfrom a national forest landscapeassessment process in western Colorado. Society &Natural Resources: An International Journal,23(5):385–400.

1 1 1 3 1 1 2

9 Collins, K., Blackmore, etc. 2007, A systemicapproach to managing multiple perspectives andstakholding in water catchments: three UK studies

5 1 1 3 2 1 3

10 Cundill, G., 2010. Monitoring social learningprocesses in adaptive comanagement: three casestudies from South Africa. Ecology and Society, 15(3).

2 1 1 3 1 3 2

11 Daniell, K.A., White, I., et al. 2010. Co-engineeringparticipatory water management processes.Ecology and Society, 15(4):11.

2 1 1 1 3 1 1 3

12 Daniels, S., Walker, G., 1996. Collaborativelearning: improving public deliberation inecosystem-based management. EnvironmentalImpact Assessment Review, 16:71–102.

1 1 1 1 1 1 4

13 Davidson-Hunt, I.J., 2006. Adaptive learningnetworks: developing resource managementknowledge through social learning forums.Human Ecology, 34(4):593–614.

1 1 1 1 1 1

14 Dedeurwaerdere, T., 2009. Social Learning as a basisfor cooperative small-scale forest management.Small-Scale Forestry, 8(2): 193–209.

5 1 1 1 1 1 1 0

15 Durcot R. Gaming across scale in peri-urban watermanagement: contribution from two experiencesin Bolivia and Brazil. International Journal ofSustainable Development and World EcologyVolume 16, Issue 4, August 2009, Pages 240–252

5 1 1 1 1 1 1 0

16 Fernandez-Gimenez, M.E., Ballard, H.L.,Sturtevant, V.E., 2008. Adaptive management andsocial learning in collaborative and community-based monitoring: a study of five community-based forestry organizations in the western USA.Ecology and Society, 13(2).

2 1 1 1 3 1 3 0

Annex II (continued)

No. Paper Studydesign

*DC (1, 2)interviews

*DC (3, 4)observation

*DC 5text

*DC 6questionnaire

*DC8 notrevealed

Sampleselection

Subjectsinvol.in res.problem

Subjectsinvol. indatacollection

Researcher'srole

17 Frost, P., Campbell, B., Medina, G., Usongo, L.,2006. Landscape-scale approaches for integratednatural resource management in tropical forestlandscapes. Ecology and Society, 11(2):30.

5 1 1 1 1 0

18 Garmendia, E., Stagl, S. (2010) Public participationfor sustainability and social learning: conceptsand lessons from three case studies in Europe.Ecological Economics 69, 1712–1722.

2 1 1 3 1 3 2

19 Ingram, J., 2010. Technical and social dimensionsof farmer learning: an analysis of the emergenceof reduced tillage systems in England. Journal ofSustainable Agriculture, 34(2):183–201.

1 1 3 1 1 0

20 Keen, M., Mahanty, S., 2006. Learning insustainable natural resource management:challenges and opportunities in the Pacific. Society& Natural Resources: An International Journal,19(6):497–513.

5 1 3 1 1 0

21 Kendrick, A., Manseau, M., 2008. Representingtraditional knowledge: resource managementand Inuit knowledge of barren-ground caribou.Society & Natural Resources: An InternationalJournal, 21(5):404–418.

1 1 3 1 1 2

22 Kroma, M.M., 2003. Participation and socialleanring: farmer inno Gana. J. of InternationalAgriculture and Extension Education 10(1)

5 1 1 1 1 1 2

23 Kroma, M.M., 2006. Organic farmer networks:facilitating learning and innovation forsustainable agriculture. Journal of SustainableAgriculture, 28(4):5–28.

1 1 1 3 1 1 2

24 Kumler, L.M., Lemos, M.C., 2008. Managing watersof the Paraíba do Sul River Basin, Brazil: a casestudy in institutional change and social learning.Ecology and Society 13 (2).

1 1 1 3 1 1 4

25 Kuper, M., Dionnet, M., Hammani, A., Bekkar, Y.,Garin, P., Bluemling, B., 2009. Supporting the shiftfrom state water to community water. Ecologyand Society, 14(1).

1 1 1 3 1 1 3

26 Lebel, L., Grothmann, T., Siebenhüner, B., 2010.The role of social learning in adaptiveness:insights from water management. InternationalEnvironmental Agreements: Politics, Law andEconomics, 10(4):333–353.

2 1 1 3 1 1 0

27 Leys, A., Vanclay, J., 2010. Stakeholderengagement in social learning to resolvecontroversies over land-use change to plantationforestry. Regional Environmental Change:1–16.

3 1 1 1 2 3 2

28 Maarleveld, M., Dabgbégnon, C., 1999. Managingnatural resources: a social learning perspective.Agriculture and Human Values, 16:267–280.

5 1 1 1 1 0

29 Maurel, P., Craps, et al. 2007. Concepts andmethods for analysing the role of information andcommunication tools (IC-tools) in social learningprocesses for river basin management.Environmental Modelling & Software, 22,630–639

5 1 1 1 3 1 1 2

30 Mccrum, G., Blackstock, K., Matthews, K.,Rivington, M., Miller, D., Buchan, K., 2009.Adapting to climate change in land management:the role of deliberative workshops in enhancingsocial learning. Environmental Policy andGovernance, 19(6):413–426.

5 1 1 3 1 1 2

31 McDaniels, T.L., Gregory, R., 2004. Learning as anobjective within a structured risk managementdecision process. Environmental Science &Technology 38, 1921–1926.

5 1 1 1 1 0

32 Mclain, R.J., Lee, R.G., 1996. Adaptivemanagement: promises and pitfalls.Environmental Management, 20(4):437–448.

5 1 1 3 1 1 2

33 Measham, T.G., 2009. Social learning throughevaluation: a case study of overcomingconstraints for management of dryland salinity.Environmental Management, 43(6):1096–1107.

5 1 1 3 1 1 1

(continued on next page)

23R. Rodela et al. / Ecological Economics 77 (2012) 16–26

Annex II (continued)

No. Paper Studydesign

*DC (1, 2)interviews

*DC (3, 4)observation

*DC 5text

*DC 6questionnaire

*DC8 notrevealed

Sampleselection

Subjectsinvol.in res.problem

Subjectsinvol. indatacollection

Researcher'srole

34 Millar, J., Curtis, A., 1999. Challenging theboundaries of local and scientific knowledge inAustralia: opportunities for social learning inmanaging temperate upland pastures. Agricultureand Human Values, 16(4):389–399.

5 1 0 1 1 0

35 Mostert, E., PAHL-Wostl, C., Rees, Y., Searle, B.,Tabara, D., Tippett, J., 2007 Social learning inEuropean river basin management: barriers andfostering mechanisms from 10 river basins'.Ecology and Society, 12(1).

2 1 1 1 1 2 3 2

36 Nerbonne, J.F., Lentz, R., 2003. Rooted in grass:challenging patterns of knowledge exchange as ameans of fostering social change in a southeastMinnesota farm community. Agriculture andHuman Values, 20(1):65–78.

5 1 1 1 1 1 2

37 Pahl-Wostl, C., Hare, M., 2004. Processes of sociallearning in integrated resources management.Journal of Community & Applied Social Psychology,14:193–206.

1 1 3 1 1 2

38 Plummer, R., 2006. Sharing the management of ariver corridor: a case study of the comanagementprocess. Society& Natural Resources, 19(8):709–721.

1 1 1 1 1 3 2

39 Prell, C., Hubacek, K., Quinn, C., Reed, M.S., 2009.‘Who's in the network?’ When stakeholdersinfluence data analysis Systemic Practice andAction Research, 21:443–458.

5 1 1 3 1 3 3

40 Rist S., Chidambaranathan, M., et al. 2007. Movingfrom sustainable management to sustainablegovernance of natural resources: the role of sociallearning processes in rural India, Bolivia and Mali.Journal of Rural Studies 23, 23–37.

2 1 1 3 1 1 2

41 Rist S., Delgado, F., Wiesmann, U., 2003. The roleof social learning processes in the emergence anddevelopment of Aymara land use systems.Mountain Research and Development, 23(3),263–270. (SL emergent)

1 1 1 1 3 1 1 2

42 Satake A. et al. (2008) Comparison between perfectinformation and passive–adaptive social learningmodels of forest harvesting Theor Ecol 1:189–197

3 1 0 1 1 1

43 Schneider, F., Fry, P., Ledermann, T., Rist, S., 2009.Social learning processes in Swiss soil protection—the ‘From Farmer–To Farmer’ project. HumanEcology, 37(4):475–489.

1 1 1 1 3 2 3 3

44 Schusler, M.T., Decker, J.D., Pfeffer, J.M., 2003.Social learning for collaborative natural resourcemanagement. Society and Natural Resources,15:309–326.

1 1 1 1 3 3 1 2

45 Selin, S.W., Pierskalla, C., Smaldone, D., Robinson, K.,2007. Social learning and building trust through aparticipatory design for natural resource planning.Journal of Forestry, 105(8):421–425.

1 1 3 1 1 2

46 Shackleton, C.M., Cundill, G., Knight, A.T., 2009.Beyond just research: experiences from SouthernAfrica in developing social learning partnershipsfor resource conservation initiatives. Biotropica,41(5):563–570.

5 1 3 1 1 3

47 Sinclair, A.J., Diduck, A.P., 2001. Publicinvolvement in EA in Canada: a transformativelearning perspective. Environmental ImpactAssessment Review, 21:113–136.

2 1 1 1 1 1 0

48 Sinclair, A.J., Diduck, A.P., 2001. Publicinvolvement in EA in Canada: a transformativelearning perspective. Environmental ImpactAssessment Review, 21:113–136.

1 1 1 3 1 2 2

49 Standa-Gunda, W., Mutimukuru, T., Nyirenda, R.,Prabhu, R., Haggith, M., Vanclay, J., 2003.Participatory modeling to enhance social learningZimbabwe. Small-Scale Forestry, 2(2):313–326.

5 1 3 2 3 2

50 Steyaert, P., Barzman, M., et al., 2007. The role ofknowledge and research in facilitating sociallearning among stakeholders in natural resourcesmanagement in the French Atlantic coastalwetlands. Environmental Science & Policy,10(6):537–550.

5 1 1 3 1 1 2

24 R. Rodela et al. / Ecological Economics 77 (2012) 16–26

Annex II (continued)

No. Paper Studydesign

*DC (1, 2)interviews

*DC (3, 4)observation

*DC 5text

*DC 6questionnaire

*DC8 notrevealed

Sampleselection

Subjectsinvol.in res.problem

Subjectsinvol. indatacollection

Researcher'srole

51 Toderi, M., Powell, N., Seddaiu, G., Roggero, P.P.,Gibbon, D., 2007. Combining social learning withagro-ecological research practice for moreeffective management of nitrate pollution.Environmental Science & Policy, 10(6):551–563.

1 1 1 3 1 1 3

52 Todt, O., Muñoz, E., Plaza, M., 2007. Food safetygovernance and social learning: the Spanishexperience. Food Control, 18(7):834–841.

5 1 1 3 1 1 0

53 Umemoto, K., Suryanata, K., 2006 Technology,culture, and environmental uncertainty:considering social contracts in adaptivemanagement Journal of Planning Education andResearch, 25:264–274.

1 1 1 1 3 1 1 0

54 Webler, T., Kastenholz, H., Renn, O., 1995. Publicparticipation in impact assessment: a sociallearning perspective. Environmental ImpactAssessment Review, 15(5):443–463.

1 1 1 3 1 1 2

* Note: DC refers to data collection method as indicated in the Code book.

25R. Rodela et al. / Ecological Economics 77 (2012) 16–26

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