Information Age Education
   Issue Number 125
November, 2013   

Understanding and Mastering Complexity:
Co-Constructed Learning Enhances Understanding 

Jessie Cruickshank
Adjunct Professor, Colorado Christian University
Jeb Schenck
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.

The Event

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 consequences.

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.

The Explanation

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 level.

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 exceedingly complex.

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 different pathway.

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 changes.

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.

Co-Constructed Developmental
Teaching Theory

Figure 2: Co-Constructed Developmental Teaching Theory

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 allowed?

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

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

Piaget, J. (1950/2001). The psychology of intelligence. New York: Routledge.

Vygotsky, L.S. (1978). Mind in society: The development of higher psychological processes. Cambridge, MA: Harvard University Press.


Jessie Cruickshank 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

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

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