What is the dynamics of human behavior
Research / Complexity of Human Behavior
Without considering the theories of complex dynamic systems, psychological knowledge remains fragmentary and unconnected.
National Institute of Health (NIH), USA
complexity-research participates and initiates numerous research projects on the complexity of human behavior. The following list names some of these key research areas:
Since its founding at the end of the 19th century, academic psychology has represented a scientifically shaped image of man. Modern complexity research expands this perspective to include the aspect of complexity. Complexity is therefore not a contradiction to a scientific interpretation of human behavior. Complexity occurs even in simple mechanical systems when they consist of more than two coupled variables. Nevertheless, psychology has been very reluctant to take these new findings into account in its research - even though it has always emphasized that it is dealing with highly complex processes.
With his dissertation in psychology and the textbook on systemic psychology that followed, Guido Strunk gave a comprehensive overview of the possible applications of complexity research in psychology. He addresses problems of the conditioning paradigm as well as cognition, learning, perception, neural processes, and the experience of illness and health.
In the method part, he designs a comprehensive approach to systemic research into psychological processes.
In the early 1990s, Günter Schiepek initiated various projects to investigate social interaction processes with regard to complexity and chaos. Guido Strunk from complexity-research was involved in these projects right from the start, developed the evaluation and visualization software and managed, carried out and published numerous research projects in this area.
Studies on chaos in groups, the client-psychotherapist interaction and the dynamics in system games were made against this background. Some results have appeared, for example, in the textbook on synergetics in psychology published by Haken and Schiepek:
Strunk G., Haken H. & Schiepek G. (2006) Order and Order Change in Therapeutic Communication. In: Haken H. & Schiepek G. (Eds.) Synergetics in Psychology. Understand and shape self-organization: 462-516. Göttingen: Hogrefe.
Strunk G., Lambertz M., Bräuning G., Mittelmann K., Gees C., Welter T., Küppers G., Haken H. & Schiepek G. (2006) Dynamics and order change in creative problem solving in a work group. In: Haken H. & Schiepek G. (Eds.) Synergetics in Psychology. Understand and shape self-organization: 542-553. Göttingen: Hogrefe.
In a self-experiment, two psychology students were asked to record emotionally relevant events and to assess them in terms of anger, fear, joy and sadness. In each case, more than a thousand data points were recorded for a time series and analyzed by Complexity Research. The results show a highly complex process. A butterfly effect can be demonstrated, which is characteristic of chaotic processes. In addition, analyzes of the fractal structure of the data and changes in the butterfly effect show that psychological processes do not produce stable patterns but can switch between order patterns (phase transition).
Some results of this research project have appeared in the textbook on synergetics in psychology published by Haken and Schiepek:
Strunk G., Belker S., Nelle I., Haken H. & Schiepek G. (2006) Emotional dynamics as a “fingerprint” of personality. In: Haken H. & Schiepek G. (Eds.) Synergetics in Psychology. Understand and shape self-organization: 247-256. Göttingen: Hogrefe.
A central concept for describing human behavior is the so-called learning theory. In its foundations, it is in many cases still based today on the ideas of classical and operant conditioning. These approaches break down a learning process into a serial sequence of cause and effect. Feedback processes are faded out to the extent that the resulting processes can be interpreted as a linear-causal sequence of external and internal psychological events. Such processes are fundamentally not complex and also theoretically incapable of being complex.
Only when feedback processes are included as a theoretical possibility of self-regulation can a more complex form of behavior be described. This is already the case, for example, in the plan concept (TOTE concept) presented by Miller, Galanter and Pribram around 1960. But Piaget also described cognitive learning processes as self-organization processes.
In his Systemic Psychology, Guido Strunk examines the complex basics of learning processes in detail and contrasts the concept of phase transition, which describes change processes in the natural sciences, with learning. Numerous research projects are derived from this perspective, such as the following:
Strunk, G., Rose, M., Sender, T., Wagner, W. & Liening, A. (2014) Identification of phases of cognitive activation using methods of non-linear time series analysis, lecture held at: Annual Conference of the German Society for Economic Education, “Cognitive activation in economic education”, Oldenburg, Germany, February 24-27, 2014
Strunk, G., Rose, M., Sender, T., Wagner, W. & Liening, A. (2015) Cognitive activation as a process. In: Arndt, H. (Ed.) Cognitive activation in economic education: 60-74. Schwalbach: Wochenschau Verlag.
Strunk, G., & Liening, A. (2011) The balance between stability and change. Research models from synergetics open up new perspectives on organizational learning. Contribution submitted as a full paper at the DFTM conference Dortmund: TU Dortmund.
Liening, A., Strunk, G., & Mittelstädt, E. (2013) Phase transitions between lower and higher level management learning in times of crisis: an experimental study based on synergetics. Nonlinear Dynamics, Psychology, and Life Sciences 17 (4), 517-541.
The figure shows in three steps how the so-called potential landscape changes during a phase transition. The metaphor of the potential landscape identifies attractive system states as deep valleys and unattractive ones as high mountains or steep walls. In the attractor (a) the steep walls and the valley are clearly defined, the ball, which represents the system behavior, quickly rolls back into the attractor after a deflection. The catchment area of the attractor becomes flatter in the vicinity of the bifurcation point (b) and merges into a potential hill (so-called repellor) at the bifurcation point (c).
(More on this: Strunk, G. & Schiepek G. (2014) Therapeutic Chaos)
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