After Marilyn Darling's recent contributions to the list (LO27428), I was
intrigued to receive today my copy of the most recent "Systems Thinker."
Marilyn and Charles Parry present the opening article, "Emergent Learning
in Action: The After Action Review," which is followed Brian Hinken's,
"Working in High Leverage Zones with the Double-Loop Learning Matrix," a
case study based on John Shibley's work.
Reading them sequentially raised the following question: is the AAR
approach, which is described as dependent on iteration, focusing on one
event which is analyzed in what seems to me a very linear way (what was
supposed to happen? what actually happened and why? what are we going to
do differently or the same next time?) merely a well-developed version of
single-loop learning? That is, does it ever become self-referential and
recursive enough to ask double-loop questions like, "what are we doing
that causes this pattern to continue to happen? what beliefs do we hold
that cause us to value this intended outcome?" Or is the AAR approach, by
definition and design, self-limiting to the events/patterns level of
And, if the answer to the second question is, "yes," than is there another
step needed in order for deeper learning to emerge? if so, what would
that step be, and could it be done within the AAR paradigm?
Malcolm C. Burson
Director of Special Projects
Maine Department of Environmental Protection
"Malcolm Burson" <email@example.com>
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