Open AccessVisualizing Teacher Education as a Complex System: A Nested Simplex System Approach
Author(s) -
Larry H. Ludlow,
Fiona Ell,
Marilyn CochranSmith,
Avery Danforth Newton,
Kaitlin Trefcer,
Kelsey Klein,
Lexie Grudnoff,
Mavis Haigh,
Mary Hill
Publication year - 2017
Publication title -
complicity
Language(s) - English
Resource type - Journals
ISSN - 1710-5668
DOI - 10.29173/cmplct26053
Subject(s) - multidimensional scaling , computer science , function (biology) , representation (politics) , complex system , exploratory research , artificial intelligence , machine learning , sociology , evolutionary biology , politics , political science , anthropology , law , biology
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.