Display Conceptual Framework Display There

¶ … Display Conceptual Framework Display There are a variety of different conceptual frameworks and theoretical models that come into play in an examination of global air and water pollution, and deciding which frameworks and models to use not only in examining but also in presenting the data on this subject can be complex.

Similarly, there are many different options for the visual presentation of these frameworks and for qualitative elements and data in general, and the varying efficacy of these different options in their impact on readers makes the selection of specific presentational designs essential when research needs to have a direct practical impact.

The following paragraphs will discuss the conceptual frameworks and visual data presentations that are deemed most suitable and effective for research specifically in the area of global air and water pollution and the role that information and communications technology can and do play in attempting to prevent, eliminate, and correct such widespread pollution.

Of the "explain and predict" techniques described by Miles & Huberman (1994), the technique deemed most useful for the defined research area is a map that can generalize certain narratives about the case, such as the creation of waste and pollution as well as the methods by which such waste is dealt with. Mapping these narratives can provide clear understanding of processes that have multiple steps and influences that interact in complex fashions, sometimes at multiple places within the process (Miles & Huberman 1994).

Due to the concrete complexity of pollution and its relation to information and communications techniques as well as the different conceptual frameworks that can be applied to this research, the visual mapping of various elements and processes in the research is believed to be an ideal method for presenting both data and theory.

One of the techniques that would be less useful in this specific application would be a visual representation of a hierarchical model, as in a series of relationships defined by interconnections in visually represented propositions (Miles & Huberman 1994).

Though this method is similar to the visual mapping described above and can itself be quite useful in many applications, the need to show hierarchical relationships is much lower in this research area than the need to properly illustrate process relationships and outcomes and to have these relationships and outcomes understood by the reader. Modeling associations is useful in many settings, especially in breaking down complex theories that are built on more abstract principles, but this really does not apply to the research situation at hand (Schensul et al. 1999).

Both the conceptual frameworks and the actual data and processes to be examined in this research are more concrete, and the researchers and readers will be better served by the process mapping advocated above than by the modeling association described here. There are no "explain and predict" techniques that.