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It’s time to learn about learning:
Where should the environmental and natural resource field go next?
1. Introduction
Questions around learning have piqued the interest of environmental policy and natural
resource management scholars over the past two decades. Researchers have asked: what
factors support our capacity for learning within our decision-making processes to govern
complex environmental problems? To what extent do governance processes designed for
learning result in better social and ecological outcomes?
Learning in environmental governance often refers to a process of acquiring, translating,
and disseminating new information among policymakers, managers, and key stakeholders
(Heikkila and Gerlak 2013), which can occur through different modes (e.g., sequentially
versus simultaneously) (Newig et al. 2016). Learning also refers to outcomes, such as
changes in beliefs and behaviors among governance actors (Leach et al. 2013) and the
adoption of new policies or programs (Heikkila and Gerlak 2013). It is through such
learning processes and outcomes, both at the levels of individuals and collectives, that
scholars see opportunities to develop more effective and robust environmental
management and governance, or more informed decision making under complexity
(Huntjens et al. 2011; Bodin and Crona 2011; Bos et al. 2013).
This Commentary reflects on the state of the scholarship on learning for environmental and
natural resource policy and governance. We argue that despite the proliferation of recent
research in this field, the multiple approaches to studying learning that exist remain largely
disconnected, which leads to missed opportunities for cumulative insight building.
Additionally, we argue that the current understanding of the individual and collective level
factors that shape learning in environmental governance is underdeveloped. To address
the limitations and improve both theory and practice, we offer recommendations for
‘learning about learning’. These include: an infusion of ideas from outside to advance the
field; more deliberate bridge building across the environmental and natural resource
learning research community; and engaged scholarship with governance institutions and
venues where we study learning.
2. What have we learned about learning?
The research on learning in environmental and natural resource governance has grown
rapidly in the past two decades (see Figure 1). This research has explored cases across
every continent, multiple levels of governance, and diverse environmental and natural
resource settings including water, forestry, fisheries, urban areas, agricultural
communities, energy, and biodiversity (see Gerlak et al. 2017).
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Figure 1: The number of learning and environmental management/governance documents
published per year in the Scopus database between 1990 and 2017
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Within this literature, a number of scholars focus on learning that occurs among the
individuals involved in a governance process – as identified through new knowledge or
belief change (e.g., learning about the nature of environmental issues) (Leach et al. 2013;
Pattison 2018). This research finds that the characteristics of individuals, such as their core
values or organizational affiliations, play a critical role in shaping learning. Some scholars
have begun to connect the cognitive and behavioral outcomes of learning, by examining
how new beliefs inform environmental management decisions (Measham 2009).
Researchers recognize that such learning can result in worse outcomes or the
reinforcement of existing beliefs or practices that are incorrect (Dunlop and Radaelli 2018).
Many studies emphasize organizational-level or collective level features of governance
processes that influence whether and to what extent learning occurs (e.g., Armitage et al.
2008; Lee and van de Meene 2012). One of the more influential bodies of literature that
focuses on learning for environmental governance in this vein is social learning theory
(Reed et al. 2010). Social learning refers to processes that involve active deliberation and
engagement by diverse actors in environmental governance, which can lead to new
understanding or shared meaning. Further, when such deliberation and engagement is
designed appropriately, it can increase adaptive capacity (Dana and Nelson 2012), build
trust and collaborative problem solving (Eakin et al. 2011), and result in better working
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We searched the Scopus database using search terms related to environmental governance and learning
drawn from previous research (Gerlak et al., 2017). From this search and subsequent analysis, we identified
2,218 documents which addressed learning in environmental management or related topics.
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relationships for stakeholders (Van der Wal et al. 2014). Social learning also emphasizes
the need for systems thinking, which can be enabled through more diverse participants
who understand different features of environmental issues (e.g., social, economic,
biophysical) (e.g., Ison et al. 2013). Such systems thinking is seen as essential to learning
about the complex dynamics of environmental systems.
While much of the learning literature in environmental and natural resource governance
looks at what fosters learning (e.g., participation, openness to different types of
knowledge), researchers also have identified factors that challenge learning. These include:
diversity of values, cognitive biases, and belief systems that make it difficult for groups to
create shared understanding or agree on collective strategies (e.g., Diduck et al. 2012), to
mitigate power differentials (Roome and Wijen 2006), or to sustain learning over time (e.g.,
Schusler et al. 2003) and across multiple jurisdictional or spatial scales (e.g., Gerlak and
Heikkila 2011). Learning in environmental governance can also be impeded by
institutional rules that constrain diversity in participation or decision-making processes, by
rules that limit access to information, or by rules that impede an open discussion about the
governance choices available (Heikkila and Gerlak 2018).
3. Critiques and limitations of the learning literature
Several scholars have examined the evolution of the conceptual debate on learning in the
environmental and natural resources governance literature, offering valuable critiques
(Blackmore 2007; Armitage et al. 2008; Reed et al. 2010; Rodela 2013; Gerlak et al. 2017).
These analyses acknowledge that learning scholarship lacks consistent theoretical and
empirical development of core concepts to guide empirical assessment. For instance, some
of the key terms, and theoretical strands, found in the literature include social learning
(e.g., Rodela 2013), collaborative multi-actor learning (e.g., Schmid et al. 2016), governance
learning (e.g., Newig et al. 2016), and policy learning (e.g., Radaelli and Dunlop 2013),
among many others. Moreover, each of these strands has its own key references, guiding
definitions, and analytical and methodological approaches. The divergence in the literature
may be explained by the diverse epistemologies and sub-fields of the research community.
Yet, the disconnected learning typologies and frameworks may impair our capacity to learn
across the sub-fields, and there is a distinct feeling that the wheel gets reinvented (Goyal
and Howlett 2018). What is needed is an explicit mapping of learning concepts, their
interrelations, and an attempt to gather as much empirical insights from all strands to
compare notes.
We also contend that research on the factors that foster learning or that shape learning
outcomes remains under-developed (Gerlak et al. 2017; Plummer et al. 2017). In
particular, empirical methods to establish causality (between particular learning activities
or processes and specific outcomes remain poor (Siebenhüner et al. 2016; Armitage et al.
2018). Part of this challenge stems from what cannot be easily measured – such as
precisely when and how individuals change beliefs. It is also challenging to observe “who”
or “what” is learning in studying environmental governance. For example, attempting to
draw insights about collective or group processes using measures based on the responses
of individuals (e.g., see Montpetit and LaChapelle 2015) may not always produce valid
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indicators of group-level outcomes. Another challenge involves the bounded timeframe
within which learning processes are often studied (Measham 2013). Learning as a process
is often conflated with changes in policies, decisions, or outcomes (Muro and Jeffrey 2012),
making it difficult to tease apart causal relationships.
Researchers have attempted to overcome these limitations. Some have established
quantitative approaches to measure learning and connect learning processes to outcomes
(Schmid et al. 2016; McFadgen and Huitema 2017; Armitage et al. 2018). Others have tried
to improve how the field conceptualizes the complexities of learning environments. Yu et
al. (2016) employ novel ways to measure factors, processes, and outcomes to establish
causality in a learning experiment. Heikkila and Gerlak (2018) offer a way to use the
institutional analysis and development framework to analyze how the rules of a
governance process enable or constrain learning. Despite these efforts, the learning
literature as it relates to the assessment of environmental and natural resource
management outcomes remains disconnected theoretically and conceptually, and with
room to enhance empirical rigor.
4. Taking our own advice: intentional learning about learning
Some of the weaknesses in the literature could be addressed by drawing on learning
perspectives from fields beyond environmental governance. What better way to start than
by looking at the way the education sciences have studied learning? For example, at the
individual level, researchers can learn from adult learning theory, which offers insights into
the role of imagination and reflection in learning (Dirkx 1998), social and cultural
perspectives, and non-learning at the individual level (Jarvis 2012). Similarly, social
psychologists offer critical insights into the ways in which emotion and cognitive biases can
shape decision-making, and thus potentially impede, or foster, learning (Kahneman 2011).
Scholars have begun to recognize the importance of building on these micro-level theories
to advance the learning scholarship (see Dunlop and Radaelli 2018). Such insights also
have been useful in understanding individual resistance to learning around issues such as
climate change (Kahan et al. 2012; Clayton et al. 2015), but more work is needed to connect
these insights on individuals to environmental governance processes.
In addition, we can draw lessons from organizational theorists about how knowledge can
be embedded and transferred within and across individuals and networks to advance our
insights around learning within a collective process (Argote 2013). From the disciplines of
business and economics, we can learn more about how knowledge is learned and shared in
firms through learning networks (e.g., Mariotti 2012; Gibb et al. 2017). Some
environmental scholars are beginning to think about learning at this more multi-level scale
(Diduck 2010). For example, Vinke-de Kruijf and Pahl-Wostl (2016) develop a framework
of multi-level learning that includes individuals, organizations, and network actors. So too
are scholars of policy change beginning to explore learning from both individual and
collective angles (Moyson et al. 2017). Nonetheless, we argue that environmental and
natural resource policy and governance scholarship around learning could benefit from
engaging with and learning from more well-developed learning literature.
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Of course, when drawing from other disciplines, it is possible to add to the cacophony of
concepts and terminology. Thus, it is important to find opportunities to bridge conceptual
and theoretical divides across the environmental and natural resource learning research
community, while still accommodating the rich insights from diverse disciplines that speak
to learning. To support these efforts, scholars may make explicit comparisons across
different learning frameworks, including those which may seem to be disparate, to guide
the conceptualization and identification of variables (e.g., see Pahl-Wostl 2009; Heikkila
and Gerlak 2013). The choices that scholars make in this respect should always be clearly
explained in order to advance the literature, which is often not the case (Gerlak et al. 2017).
It may also be valuable to develop a systems framework that accommodates insights on
learning from multiple disciplines and theories, and guides analysis at multiple levels,
while establishing shared conceptual guidance (e.g., akin to the Social Ecological Systems
Framework by Ostrom and colleagues ). This can enable more rigorous diagnoses of
learning in environmental governance across cases.
Practical limitations may limit opportunities to bridge the divides in the field. Simply
organizing panels at conferences or reading manuscripts are insufficient. These one-way
forms of communication do not engender the deeper learning needed to understand the
challenges, the tacit knowledge underlying research projects, and the operational tools
required to move a study from start to finish. Rather, we need to sit down face-to-face and
engage in the coproduction of knowledge across scholars and practitioners. One possible
path forward is demonstrated by the Virtual Learning Community (http://www.tias-
web.info/tias-activities/learning-community/), an international community of scientists,
policymakers, and practitioners with an interest in learning for sustainable development.
This virtual group organizes webinars, conference panels, and an online listserv to help
create synergies and identify cross-cutting issues. Intentionally designed research and
policy workshops can help us understand the commonalities and differences in research
findings based on comparative insights across contexts. Further, developing frequent
meetings among a group of established and emerging scholars, from multiple sub-fields
and countries, could help move the dialogue forward on how to improve our theoretical
foundations, while fostering innovation on empirical approaches. While there is no single
way to do this, scholars could start by seeking funding opportunities to build these types of
efforts. The U.S. National Science Foundation’s Research Collaborative Networks program
is one potential mechanism for such support. It offers funding for new collaborations to
support “coordination in research, training, and educational activities across disciplinary,
organizational, geographic and international boundaries”
(https://www.nsf.gov/funding/pgm_summ.jsp?pims_id=11691).
Finally, enhancing the coordination across the academic community needs to include
partnerships with governance institutions and venues where we study learning (see Bos et
al. 2013). Through engaged scholarship, we can create platforms that allow researchers
and practitioners to be part of co-learning. We can learn from the communities we engage
with, improve our research questions, and create trusting relationships that can improve
the likelihood that our research will be useable for governance. Some scholars of learning
in environmental governance are using tools of engaged scholarship (e.g., Bos et al. 2013;
