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Chaos, complexity and complicatedness: lessons from rocket science
Author(s) -
Norman Geoff
Publication year - 2011
Publication title -
medical education
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.776
H-Index - 138
eISSN - 1365-2923
pISSN - 0308-0110
DOI - 10.1111/j.1365-2923.2011.03945.x
Subject(s) - parallels , chaos theory , argument (complex analysis) , complex system , chaotic , natural (archaeology) , epistemology , computer science , systems science , point (geometry) , science education , chaos (operating system) , management science , chaotic systems , cognitive science , artificial intelligence , psychology , mathematics , mathematics education , philosophy , economics , geometry , archaeology , computer security , history , biochemistry , operations management , chemistry
Medical Education 2011: 45 : 549–559Context Recently several authors have drawn parallels between educational research and some theories of natural science, in particular complexity theory and chaos theory. The central claim is that both the natural science theories are useful metaphors for education research in that they deal with phenomena that involve many variables interacting in complex, non‐linear and unstable ways, and leading to effects that are neither reproducible nor comprehensible. Methods This paper presents a counter‐argument. I begin by carefully examining the concepts of uncertainty, complexity and chaos, as described in physical science. I distinguish carefully between systems that are, respectively, complex, chaotic and complicated. I demonstrate that complex and chaotic systems have highly specific characteristics that are unlikely to be present in education systems. I then suggest that, in fact, there is ample evidence that human learning can be understood adequately with conventional linear models. Conclusions The implications of these opposing world views are substantial. If education science has the properties of complex or chaotic systems, we should abandon any attempt at control or understanding. However, as I point out, to do so would ignore a number of recent developments in our understanding of learning that hold promise to yield substantial improvements in effectiveness and efficiency of learning.