By Matthijs Koopmans, Dimitrios Stamovlasis

This e-book capitalizes at the advancements in dynamical platforms and schooling by way of proposing essentially the most fresh advances during this region in seventeen non-overlapping chapters. the 1st half the publication discusses the conceptual framework of advanced dynamical structures and its applicability to academic techniques. the second one part provides a suite of empirical reviews that

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Extra resources for Complex Dynamical Systems in Education: Concepts, Methods and Applications

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Studies of classroom implementation of instructional reforms need to explore the depth of implementation and, therefore, these various dimensions of change. From a research perspective, depth of research includes research across the many dimensions of the implementation process. Implementation dynamics are both across time and across settings. Sustainability of reform extends the question of depth of implementation to understand change over time and across implementation sites (Freeman, Corn, Bryant, & Faber, 2015).

The opposite of linear is non-linear. The opposite of lineal is recursive” (Bateson, 1979/2002, p. 212). As Bateson contended, “lineal thinking will always generate either the teleological fallacy (that end determines process) or the myth of some supernatural controlling agency” (p. 56). W. Bloom tendency is to assign a singular cause to a particular effect. From the perspective of complexity and recursive thinking, when we see a particular effect, we may consider that the effect is due to the interaction of many different factors, relationships, and contexts.

Even some seemingly rigid object or stable process is undergoing continual change. One of Bateson’s (1979/2002) favorite examples, is the tight rope walker who is continually adjusting body and balancing pole positions in order to maintain balance. What may appear as stable, static, or rigid is actually undergoing continual change. Bateson (1979/2002) emphasized the importance of random variation and change as the characteristic of what he called the two great stochastic processes: (a) learning and (b) evolution.

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