Research Design: Terms to Know

Deductive logic Begins with one or more premises, then proceeds logically from these premises toward conclusions that must also be true Systematically gather data relevant to the hypothesis Statistically test and interpret the data to see if they support the hypothesis

Inductive reasoning Use specific instances or occurrences to draw conclusion Start from the data, begin to detect patterns and regularities, formulate some tentative hypotheses, end up developing some general conclusions or theories

Comparison: Deductive research Inductive research Scientific principles Moving from theory to data The need to explain causal relationships The collection of quantitative data Highly structured approach Researcher independent of what is being researched The request for generalization Inductive research Gaining an understanding of the meanings humans attach to events A close understanding of the research context The collection of qualitative data Flexible structure Researcher is usually part of the research process Less concern with the need to generalize

Different research strategies Experiment Survey Cross-sectional and longitudinal studies Case study Grounded theory Ethnography Action research

Triangulation The application and combination of several research methodologies in the study of the same phenomenon Methodological debate is necessarily pervasive in most fields of applied research. The undertaking of a research study requires great consideration as to the appropriateness and validity of any chosen method. The types of data sought, what is to be done with the data, available resources, time constraints, sampling capabilities, and skills of the researchers are some of the factors that contribute to the determination of what research methods are best for any given project. There are generally considered to be two methodological approaches to data collection and analysis: qualitative and quantitative. Qualitative researchers reject the idea that human behavior can be studied with the same methods as the natural or physical sciences, assuming that human behavior is always bound to the context in which it occurs, and, therefore, behavior must be studied holistically rather than through manipulation. Qualitative research is an intensely personal and subjective style of research. On the other hand, quantitative researchers strive for testable and confirmable theories that can explain how one set of variables is related to another. Quantitative research reduces human behavior to a set of finite characteristics that can be quantified and operationalized so that they can easily be tested. Over the past decade, there has been an increasing trend of blending quantitative and qualitative data within a study to provide a broader, deeper perspective. This approach is called methods triangulation. Both quantitative and qualitative research designs seek reliable and valid results. Data that are consistent or stable as indicated by the researcher's ability to replicate the findings is of major concern in the quantitative arena, while validity of the qualitative findings are paramount so that data are representative of a true and full picture of constructs under investigation. By combining methods, advantages of each methodology complements the other making a stronger research design with resulting more valid and reliable findings. The inadequacies of individual methods are minimized and more threats to internal validity are realized and addressed

Credibility of research findings How do I know what I know? Is the source reliable? Are the raw data reliable? Is the conclusion valid? Is it just some coincidence? Triangulation is a way help you make judgment

Validity and Reliability Think in terms of ‘the purpose of tests’ and the ‘consistency’ with which the purpose is fulfilled/met Validity and Reliability Neither Valid nor Reliable Reliable but not Valid Fairly Valid but not very Reliable Valid & Reliable

Validity and Reliability Validity is concerned with whether the findings are really about what they appear to be about Reliability mainly deals with “repeatibility” and consistency

Internal and External Validity Internal validity The extent to which its design and the data that it yields allow the researcher to draw accurate conclusions about cause and effect and other relationships within the data External validity The extent to which the conclusions drawn can be generalized to other contexts