The design of any research study is critical in determining the degree to which the results of the research can be considered valid and reliable. There are degrees of assurance that are associated with different types of research design. The best approach is to use the method that controls for as many confounding variables as possible. The object of the research design is to eliminate all obstacles to the internal or external validity of the intervention that is under investigation. However, unlike in the physical sciences, we are working with human subjects that often make the elimination of extraneous variables very difficult. In education we also are dealing with other serious constraints including; time, money, and the rights of children resulting in less than perfect conditions in which to conduct research. Although the use the most rigorous experimental design is the goal of all research, it is important to remember that the best design is always the design that is feasible.

Hierarchical linear modeling provides a conceptual and statistical process based upon simple linear regression and multiple linear regression designed for investigating and drawing conclusions regarding the influence of phenomena at different levels of analysis. HLM is a type of regression model that is well suited for use with nested data enabling an analysis across hierarchical levels, whereas in simple linear and multiple linear regression analysis all effects are modeled at a single level. For example, in educational research, data is often considered as individual students nested within classrooms nested within schools (student > classroom > school > district). Education data sets typically select students from a group of schools and thus information about students are correlated (such that students from the same schools are similar in their traits). Adapted from Practical Assessment, Research, and Evaluation http://pareonline.net/getvn.asp?v=7&n=1

The implementation of a specific practice designed to meet a specific outcome.