Our purpose is to provide an exploratory statistical representation of initial teacher education as a complex system comprised of dynamic influential elements. More precisely, we reveal what the system looks like for differently-positioned teacher education stakeholders based on our framework for gathering, statistically analyzing, and graphically representing the results of a unique exercise wherein the participants literally mapped the system as they perceived it. Through an iterative series of inter-related studies employing cluster analysis and multidimensional scaling procedures, we demonstrate how initial teacher education may be represented as a complex system comprised of interactive agents and attributes whose perceived relationships are a function of nested stakeholder-dependent simplex systems. Furthermore, we illustrate how certain propositions of complexity theory, such as boundaries, heterogeneity, multidimensionality and emergence, may be investigated and represented quantitatively.
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Ludlow et al. (2017) studied this question.
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