Questions and Answers



Research: Question 1

Introduction

This section is organized around three categories of quantitative design: Experimental design, Co relational Design, and Cross Sectional Comparison Design. It is believed that the most important consideration in determining the suitability or a particular design or set of methods is the researcher's curiosity, that is, the question or problem that their research is devised to examine. Thus, designs and analytic techniques associated with one category of quantitative investigations are not inherently sounder than other types of investigations. Rather, appropriateness of a research design is determined by how well it addresses the researcher's question. As described in the following sections, each of the different types or quantitative research designs addresses different research questions and purposes (Apling, 2005).

Quantitative Approach to Special Education Research

In the quantitative research paradigm, researchers use the numerical expression of information for the purpose of summarization, classification, interpretation, and generalization. Fundamental principles of scientific inquiry such as sampling and population issues, validity and scientific control, probability and statistics, power, significance, and generalizability are all critical aspects of a quantitative research design.

Although quantitative research approaches share in common the formulation of words and observations into numbers, great variance exists within the paradigm regarding the designs and methods that researchers use to address their questions and test their hypotheses. The sample used in quantitative research is representative of the population to be analyzed. Probability consists of Simple Random Samples in which all units of the universe have the same probability of being included in the sample (Bruder, 2010). Proportional stratified-sample involves the units divided into strata, randomly selected within each stratum. Another type of sample is systematic samples which includes the application of a selection range to the units that constitutes the sampling frame.

On the other hand, there are sample clusters which are presented in groups. Moreover, non-probability is composed of stock units that have not been random relative to the size of the sample. Main statistical measure focuses on the analysis of the survey (Ratios, averages, etc.), and the level of analysis (global, sub-groups). Whereas, the magnitude of error is to have the values calculated in the sample. The probability is that these values or estimates have the desired sampling error. The three main quantitative study designs for special education research are Experimental Design, Co Relational Design, and Cross Sectional Comparison Design.

Cross Sectional Comparison Design

Cross-sectional comparison design (or Cross-sectional analysis) represent a host of research methodologies involving observations of a subset of a given population of items all, all or some at a given time. In cross-section comparisons, groups of different ages are compared against each other using independent variables. In statistics, cross sectional comparison follows a single dimension data set. Cross-sectional data, hence, will refer to the data collected by observing many subjects (such as individuals, firms or countries/regions) at the same point of time, or without regard to differences in time. Analysis of cross-sectional data usually consists of comparing the differences among the subjects. A Cross-sectional regression is a type ...