Causality In Complex Systems: The Role of Pattern Recognition

Processes of self-organization, adaptation, emergence, characteristics of complex systems, are regulated by causal principles and causal couplings that are not describable by a linear chain of causes and effects (Efficient Causality in Aristotelian terminology) and not defined in the deterministic framework. Simultaneity of causal interactions -where causes are at the same time effects- is of fundamental importance when studying systems characterized by negative and positive feedbacks processes and continually changing boundary conditions. Our research on student understanding of complexity indicates that students tend to utilize simple linear model of causality and establish a one-to-one correspondence between cause and effect which impedes a conceptual understanding of complex causal relations. Changes occur in reasoning when students are iteratively asked to recognize and describe patterns in data distribution and subsequently learn to identify these patterns as fundamental causal controls over system evolution and behaviour (Formal Causality in Aristotelian terminology).