|
In every research project, the data you collect need to be arranged in a form that facilitates the interpretation of what those data mean from the perspective of your project. Organizing data usually involves two opposite, complementary operations-classifying and summarizing. Classifying consists of separating the contents of a mass of information into categories so the contents can be easily compared and contrasted. This operation is the focus of Classification Patterns. Summarizing--the reverse of classifying--consists of combining a conglomeration of information so the essence and implications of the material can be readily understood. Chapter 11 (Summarizing Information Verbally, Numerically, and Graphically) illustrates popular ways of abstracting and condensing data. Classification Patterns " What I need to know are the characteristics that a classification scheme should have in order to be accurate and efficient to use." One of the most fundamental attributes of human thought is people's propensity to arrange their experiences in terms of categories or classes. By assigning happenings to categories, people render life more comprehensible by revealing how certain events are similar to, and different from, other events. Classifying people, objects, and incidents enables us to compare and contrast our experiences and thereby construct an orderly mental map of reality that helps us cope with life's demands. The tendency--indeed, the necessity--to classify experiences derives at least partly from the limited capacity of the human mind to simultaneously comtemplate a multitude of variables. How many comparisons can be assimilated by those who seek an understanding of the patterns of comparisons? Writers on psychology such as Nobel laureate Herbert Simon believe that humans can simultaneously consider only a few items of information, perhaps fewer than four(depending partly on [how much is compressed into a comprehensible "chunk" of information]). For this reason, humans employ categorical ideas to think efficiently about what would be overly complex. ( Walberg, Zhang, & Daniel, 1994, p. 80) The practice of mentally grouping observations has apparently been a natural human function from earliest times. However, the business of rationally devising formal systems for classifying events is of more recent vintage. The science of classification, often called taxonomy or systematics, probably originated with the ancient Greeks, brought to fruition during the fourth century B.C.E. in the works of Plato and his student Aristotle. The product of systematics can be referred to as a taxonomy or, alternatively, as a typology, classification scheme, or codification system. In the field of biology, the theory of evolution proposed by Charles Darwin ( 1809- 1892) is a taxonomy for codifying the patterns in which the earth's multitude of life forms descended from common beginnings over eons of time. In chemistry, Dimitri Mendeleyev ( 1834- 1907) created the periodic table, a taxonomic system that not only equips chemists to classify known chemical elements but also to predict properties of as-yet-undiscovered elements. In the field of education, Benjamin Bloom ( 1913- 1999) and his associates created a widely used "Taxonomy of Educational Objectives" ( Bloom, 1956).Although we have waited until this point in the book to formally discuss the role that classifying plays in research, it should be apparent that decisions about how you intend to organize your data are profitably made at various steps of your project, from the early stage of defining your research problem through the ultimate stage of interpreting the results. But the reason we have placed this chapter under Stage III-B is because the matter of categorizing information is particularly important during the data-collection process. Your decision about how you are going to classify your data helps you identify the kind of information to collect.Because ways of adapting and creating classification schemes have already been discussed at some length in Chapter 5, the present chapter need not address such matters. Instead, the following presentation is limited to (a) examples of typical classification schemes and (b) key features of classification systems and implications those features may offer for students' thesis and dissertation plans.
|