Agriculture Reference
In-Depth Information
When interactions among participants take place on levels 2, 3, and
4, differences in problem definitions, motivations for engaging in the
project, individual interests and organizational missions, and ideologies
are exposed. The nature and the extent of the resulting higher order
learning depend on how the participants confront their differences and
the ways they are mediated. Interactions at the level of problem defini-
tion are the most common, and this is the type of learning that most often
occurs. Our 2008 study
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showed that a turnover in the teammembership
took place until all the participants reached congruency in their world-
views. Learning occurred mostly in problem definition and partially in
interpretive frame.
In summary, the disparate bodies of scholarship on learning can be
distilled down to this: learning takes place when key actors represent-
ing a range of interpretive frames, problem definitions, and core com-
petences engage in intense interactions around an issue, a problem, or
an idea. The question here is how to create an environment or a set-
ting in which this form of higher-order learning could occur. Clearly,
the type of interaction represented by acrimonious press reports, block-
ades, and secretive shipping practices is not the right setting. The pro-
cess of creating a GMO sector supplement, which involves represen-
tation and action by all stakeholders, ranging from GMO companies
to activist NGOs, could be an approach and a process in which higher
order learning could take place. In conceptual terms, the process could
be described as an experiment or, more specifically, a “Bounded Socio-
Technical Experiment” (BSTE), bounded by scope and time, but with
a wide range of inputs for inducing higher-order learning among the
participants.
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Halina Brown and Philip Vergragt 2008. Bounded Socio-Technical Experiments as
Agents of Systemic Change: The Case of a Zero-Energy Residential Building.
Tech-
nological Forecasting and Social Change
75: 107-130.
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See H. S. Brown et al., Learning for Sustainability Transition through Bounded Socio-
technical Experiments in Personal Mobility.
Technology Analysis and Strategic Man-
agement
15: 291-315 (2003).
