Understanding and Mastering
Co-Constructed Learning Enhances Understanding
Adjunct Professor, Colorado Christian University
Adjunct Professor, University of Wyoming
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This newsletter is the eleventh in a series on complexity. Our informal
and formal educational systems, and our everyday life experiences, help
us learn to deal with the complexities of complexity.
Crossing a stream can be a very complex action.
Katie’s foot slipped on the mossy rock, plunging her into the stream.
The water was waist deep on me, nearly chest deep on her. She lurched
sideways, off balance. She reached out, grasping for anything, terror
on her face. The three other teenagers in the party didn’t see her
desperate moves. Each was wrapped up in a private world concentrating
on not being swept away by the cold mountain stream. Katie regained
questionable footing and staggered across, collapsing in a wet pile on
the bank. Our attention then had a laser focus. We not only didn’t hear
one another on this first stream crossing, we were barely aware of each
other. That stream crossing lesson had lasted less than five minutes.
Our wet miserable group then discussed what happened. Everyone had
slipped. The swift water was terrifying. Evan and Jon noticed that the
current broke when one person was slightly upstream, making it easier
for the downstream person. But tomorrow loomed, with a bigger stream
that we couldn’t avoid. Further, our food cache was on the other side.
The next morning we resumed the discussion. Jon suggested we move
slowly in pairs, holding on to each other. The larger person could
break the swift current by just being upstream. There was only one way
to find out, any error in our thought would have immediate negative
The memory of that first stream crossing remains more poignant than
hundreds of subsequent crossings. The lesson had no grades, no binders
with strategies, no lecture, no short review for a written test, and no
fake reality on a screen. We didn’t get to try it repeatedly. It was
real, and the lesson has stuck in fine-grained detail for
decades. The lesson was experienced with our minds and bodies
working together. It was a personal learning experience whose
solution was felt. It had personal rather than abstract consequences.
Here's what we learned by trial and error (and no fatalities). We could
project our thinking forward if we debriefed what had happened and
engaged in focused reflection that was guided by specific questions. We
envisioned ourselves in a similar type of situation, having to
determine what we were we going to do. We prospected or searched
out what we needed to do differently, and then had an authentic rather
than pretend practice with very real personal consequences, including
our personal comfort and safety. The combined experiences were then
assimilated into our personal history. The experience was far more
powerful and memorable than being tested on reading or hearing a
lecture. We encountered a complex situation in crossing a stream, and
by debriefing it we moved our understanding into a still more complex
In simple, linear relationships, a small change can produce a specific
result. Reality, however, is made of many complex relationships. As
things become increasing complex, more variables simultaneously
interact with each other, and predicting a specific result becomes
In complex equations, small perturbations can create very different and
more complex results. In the stream-crossing example, having one person
slightly upstream to break the current triggered a series of events
leading to more complex learning. This is an example of the popular but
poorly understood concept of "butterfly effect." Minute changes in
initial conditions often produce large differences later on. If the
initial conditions in a marble spiraling down a funnel change even a
tiny amount, the results change. Tilting the funnel ever so slightly or
using a marble with a different weight or size results in a completely
The same is true when considering the complexities of modern life and
the challenges we face daily. In solving complex problems, we need
other people to help us expand beyond our own paradigms, and schemas to
see more connections. Our assumptions and traditional linear thinking
may create roadblocks, becoming the perturbations that can drastically
change the result.
The blessing and challenge is that the social nature of complex problem
solving impacts both education and the corporate world. We need other
people to help us learn and grow neurologically, conceptually, and
developmentally. A key part of that learning growth is to respond
appropriately to feedback provided by the rapidly changing word.
Feedback loops impact complexity and modify the outcome. Just as in the
butterfly effect, complexity itself is an evolving equation.
Understanding the underlying problems and projecting them into new
situations has practical ramifications, especially for education and
management. What starts simply can be rapidly amped up in complexity.
Problems are solved when thought reaches a higher level of complexity,
grasping new relationships and new principles. The AH-HA moment is a
classic demonstration of such increasingly complex thought. Harvard's
Kurt Fischer found that the increasingly complex patterns of cognition
are best described through dynamic complexity theory (Fischer, 1980).
The theory is based upon robust cognitive neuroscience findings that
explain and predict how cognitive development progresses with age and
is significantly affected by environment using Vygotsky's Zone of
Proximal Development (1978). See also Chaliklin (2003) or Wikipedia's zone of proximal development
Figure 1: Skill Theory (Fischer, 1980)
Dynamic systems theory has a number of implications for learning,
whether in the classroom, field, or in a corporation. In complex,
dynamic systems, multiple variables that interact with each other change
responses. Rather than producing a simple linear pattern from cause to
effect, repeating patterns are created that fluctuate in scale. Some
are big, some are small. The same pattern can be found at very tiny
scales, such as tree branches forking into twigs, or a much larger
scale, such as the tree trunk forking into large branches. So too in
instruction where patterns repeat within a lesson design or in a whole
program. Consequently, a small change affecting the initial pattern on
a small scale can amplify the pattern on a much larger scale, the
butterfly effect. Fischer found that human thought and cognitive
development appears to have such patterns.
The primary take-away is that predictable patterns to the process of
learning and development occur even in highly complex
circumstances. Models of these processes are regularly created.
Having a model of learning, being intentional with instructional
design, and using meaningful feedback loops from the learning event at
multiple scales during problem analysis allows one to knowingly
influence complexity, as opposed to being at the mercy of it.
Feedback loops can be created at each level of complexity and involve
key players in the events or circumstances being analyzed, as
exemplified in the stream crossing. This means that a classroom or
corporation can insert specific feedback points to gather good data. In
the stream crossing, the guided reflection after the first crossing
yielded crucial data. The feedback loops at specific but multiple
points during the learning event yielded timely information and helped
to inform precise changes that facilitated achieving the learning goal.
Awareness of where the learning will go next helps teachers, trainers,
and corporate managers know how to use the data gathered from the
feedback. Additionally, understanding how specific feedback and the
data from it fit into the larger scheme of complexity allows for
greater implementation and integration of identified steps or proposed
To model these dynamic interactions, we conceive of the natural dynamic
of learning as a fractal spiral that connects distinct yet
interdependent brain processes in an intentional sequence. While each
step is connected in a dynamic, fractal manner, integrating and
building upon pervious steps, the sequence accommodates for natural
bottlenecks such as cognitive load and neural growth stabilization. The
spiral illustration shows how complexity, imbedded with different
instructional phases, leads to new, more complex solutions.
Figure 2: Co-Constructed Developmental
Each spiral with the sequential numbers represents an increasingly
complex learning event. Internal feedback loops (not shown in the
illustration) can link to any point from another to inform the
learning. Like the marble and funnel, such feedback loops can
potentially alter the path of learning, the players, and their actions.
In a learning event there are five numbered actions shown in the above
illustration. These are framing, activity, direct debriefing, bridge
building, and assimilation. Each is dynamically linked, and hence
highly adaptable to the changing circumstances. This means that the
five instructional actions, including a neurologically critical pause
that helps establish new linkages, are scalable. They work at any
level of complexity.
In the stream crossing, the students started at one scale, went through
all the phases of the learning event as a group and emerged with a
deeper and more complex understanding of how to cross a stream. Both
the leader and students co-construct the principles involved in complex
problem solving. Those principles were assimilated and used to inform
their actions in next learning event, whatever circumstances arose.
Understanding the nature of complexity, where a slight change in
multitude of variables can substantially change outcomes, allows for
the design of more effective learning events. Cognitive research
increasingly points to the role others play in our learning and
development and the need of others to help advance our thinking. This
creates obvious questions about the future of learning in a more
digitized world. What level of interaction and co-development can come
from a computer? What does this mean for isolated and individualized
computer-based training? What does it mean for business environments
where collaboration and analysis of the decision-making process are not
By developing a better understanding of the brain and how its dynamic
systems interact with their environment, we can design and deliver
better learning events in a highly complex world. Such intentional
designs can potentially reduce assumptions and guessing while
scaffolding better solutions to emerge in an uncertain world.
Chaliklin, S. (2003). The zone of proximal development in
Vygotsky’s analysis of learning and instruction. Retrieved
11/11/2013 from http://people.ucsc.edu/~gwells/Files/Courses_Folder/documents/chaiklin.zpd.pdf.
Fischer, K.W. (1980). A theory of cognitive
development: The control and construction of hierarchies of skills. Psychological Review, 87(6),
477-531. Retrieved 11/11/2013 from http://people.ucsc.edu/~gwells/Files/Courses_Folder/documents/chaiklin.zpd.pdf.
Piaget, J. (1950/2001). The psychology of intelligence. New
Vygotsky, L.S. (1978). Mind in society: The development of higher
psychological processes. Cambridge, MA: Harvard University Press.
is an adjunct professor in Colorado Christian
University's Business and Leadership school. She earned an Education
Masters from Harvard’s Graduate School of Education. Cruichshank’s work
stems from her years as an outdoor guide and Program Director at Solid
Rock Outdoor Ministries where research and practice came together. As a
licensed minster in the FourSquare Christian denomination, she is
currently the Director of the Gateway Collegium which oversees pastoral
continuing education and lay minister training. Cruickshank lives in
Laramie, WY with her husband Bob and their weimeraner Zoe. Jessie can
be contacted at firstname.lastname@example.org
Jeb Schenck, Ph.D
is an adjunct professor teaching neuroeducation
classes for the University of Wyoming. During his public school
teaching days he examined how neuroeducation theories actually
worked in real classrooms. His teaching skills, based upon
mind/brain theory, were acknowledged with many national honors.
His daughter, Jessi Cruickshank and he co-developed a new
experiential teaching theory, and started Knowa, a consulting firm to
help organizations to use instructional methods that create long
lasting learning. His wife, a TBI survivor, and he reside near
Yellowstone. All three of his adult children use aspects of mind/brain
theory in their own work. Jeb can be contacted at email@example.com
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