Complex Dynamical Systems Theory in Education: Is It a Paradigm Shift?

• In Event: Complex Systems Approaches to Studying Motivation and Learning in Social Contexts

Abstract

Objective
The purpose of this presentation is to discuss the significance of complex dynamical systems (CDS) theories for educational research.

Theoretical Framework
The field shows a growing interest in the applicability of CDS in education (Jacobson et al., 2019; Koopmans & Stamovlasis, 2016). CDS is often presented as an alternative to the traditional research paradigm, commonly referred to as the linear model, whose shortcomings are briefly noted below.

The Linear Model
Among others, the linear model typically relies on the following assumptions: (1) The ergodic assumption, i.e., homogeneity across subjects and random distribution of outcomes across the time spectrum. The latter part of this assumption is particularly problematic in educational research, which tends to rely on snapshots and benchmark measures rather than behavioral trajectories over time. (2) A sequential relationship between cause and effect, which ignores the recursive process through which variables mutually influence each other on an ongoing basis. (3) The independence of analytical units, such as when random samples of individuals are drawn from a population without understanding their systemic relationships. (4) Linear change, i.e., the assumption that changes in outcomes are proportional to changes in input conditions, disregarding the possibility of qualitative transformation and unpredictability.

A Few Essential Constructs in CDS
The assumptions of the linear model are too restrictive when complex and systemic processes are investigated, especially when it concerns phenomena such as these described in the session. Self-organization and emergence reflect processes through which coherence develops out of apparent random interaction between individual units, as may happen in classrooms when learning takes place. Self-organized criticality or the edge of chaos is defined as critical states occurring in systems if repeated exposure to certain input condition creates a tension that results in a sudden transformation. This state characterizes the propensity of systems toward change, a concept that has relevance, for example, in the field of educational reform. Autopoiesis is the ongoing self-realization of a system through interaction, requiring an analysis of the dependencies between units as well as their interactions. Autopoiesis predisposes systems toward self-preservation, a notion that has helped understand resistance to change in the educational system.

Methodological Considerations
To capture complex processes, several methodological responses are recommended. Researchers should use time series analysis and power spectra evaluate the dependency of given observations on previous ones, such that the longitudinal process gets captured. Behavior of individuals are analyzed in relation to one another and to higher level systemic manifestations, using such approaches as ethnography and social network analysis. Examples of both approaches are discussed in this session, i.e., daily high school attendance over multiple years (Koopmans, 2011) and school leadership in the face of conflicting bureaucratic pressures (Marion et al., 2012).

Significance
According to many, CDS represents a major paradigm shift (Fleener & Merritt, 2007). One way in which this statement is true for education is that CDS requires a major shift in our orientation toward research design and data collection. This presentation offers some pointers as to how we might bring this change about.

Author

• Matthijs Koopmans, Mercy College