1. Research Design: Terms to Know

2. 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

3. 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

4. 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

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

6. 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

7. 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

8. 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

9. 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

10. 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