Accommodating various learning styles

Complexity characterises the behaviour of a system or model whose components interact in multiple ways and follow local rules, meaning there is no reasonable higher instruction to define the various possible interactions.The stem of the word "complexity" - complex - combines the Latin roots com (meaning "together") and plex (meaning "woven").Contrast "complicated" where plic (meaning "folded") refers to many layers.A complex system is thereby characterised by its inter-dependencies, whereas a complicated system is characterised by its layers.Complexity is generally used to characterize something with many parts where those parts interact with each other in multiple ways, culminating in a higher order of emergence greater than the sum of its parts.

However, what one sees as complex and what one sees as simple is relative and changes with time.Warren Weaver posited in 1948 two forms of complexity: disorganized complexity, and organized complexity.Phenomena of 'disorganized complexity' are treated using probability theory and statistical mechanics, while 'organized complexity' deals with phenomena that escape such approaches and confront "dealing simultaneously with a sizable number of factors which are interrelated into an organic whole".The approaches that embody concepts of systems, multiple elements, multiple relational regimes, and state spaces might be summarized as implying that complexity arises from the number of distinguishable relational regimes (and their associated state spaces) in a defined system.Some definitions relate to the algorithmic basis for the expression of a complex phenomenon or model or mathematical expression, as later set out herein.One of the problems in addressing complexity issues has been formalizing the intuitive conceptual distinction between the large number of variances in relationships extant in random collections, and the sometimes large, but smaller, number of relationships between elements in systems where constraints (related to correlation of otherwise independent elements) simultaneously reduce the variations from element independence and create distinguishable regimes of more-uniform, or correlated, relationships, or interactions.Weaver perceived and addressed this problem, in at least a preliminary way, in drawing a distinction between "disorganized complexity" and "organized complexity".In Weaver's view, disorganized complexity results from the particular system having a very large number of parts, say millions of parts, or many more.Though the interactions of the parts in a "disorganized complexity" situation can be seen as largely random, the properties of the system as a whole can be understood by using probability and statistical methods.A prime example of disorganized complexity is a gas in a container, with the gas molecules as the parts.Some would suggest that a system of disorganized complexity may be compared with the (relative) simplicity of planetary orbits – the latter can be predicted by applying Newton's laws of motion.

Leave a Reply

Your email address will not be published. Required fields are marked *

One thought on “accommodating various learning styles”

  1. Lola thinks that living with her best friends (and one random assigned by Housing, who moves her things in and promptly disappears to the botany lab where she's the teaching assistant for Professor Nostradamus) is a wonderful idea for about twenty-four hours after move-in day.