Blog: STA630 GDB solution Spring 2012

True experimental design is better then Quasi experimental design because of its procedure. In true experimental design the two groups are selected for experiments , Though one group is selected for experiment but the information are recorded from both groups before and after the treatment . While this procedure is not adopted in the Quasi experimental.

True Experimental Designs

1-Pre-test-Post test control g roup design 2-Post-test-Only control g roup design 3-Solomon 4-G roup design.

True Experimental Design

1                    randomly formed g roups; g roups are pre-tested, one ***** receives a new or unusual treatment,
and both g roups are post-tested.

2                    2. Post-tested only control g roup design is a true experimental design involving at least 2 randomly formed g roups; one g roup receives a new, or unusual, treatment and both g roups are
post-tested.
Solomon 4-g roup design is a true experimental design that involves random assignments of
subjects to 1 or 4 g roups; 2 g roups are pre-tested, 2 are not; one of the pre-tested g roups and
one experimental treatment and all 4 g roups are post-tested.

Quasi-Experimental Designs

1) Non-equivalent control g roup design 2) Time serves design 3) Counter-balanced design

1                    Non equivalent control g roup design is a quassi-experimental design involving at lest 2 g roups, both of which are pre-tested; one g roup receives the experimental treatment, and both g

2                    Time series design is a quasi-experimental design involving 1 g roup which is repeatedly pretested, exposed to an experimental treatment and repeatedly post tested.

3                    Counter-balanced design is a quasi-experimental design in which all g roups receive all treatments, each g roup receives the treatments in a different order, the number of g roups equals the number of treatments, and all g roups are post tested after each treatment.

True and Quasi-Experimental Designs.

Barry Gribbons National Center for Research on Evaluation, Standards, and Student Testing Joan Herman National Center for Research on Evaluation, Standards, and Student Testing Experimental designs are especially useful in addressing evaluation questions about the effectiveness and impact of programs. Emphasizing the use of comparative data as context for interpreting findings, experimental designs increase our confidence that observed outcomes are the result of a given program or innovation instead of a function of extraneous variables or events. For example, experimental designs help us to answer such questions as the following: Would adopting a new integrated reading program improve student performance? Is TQM having a positive impact on student achievement and faculty satisfaction? Is the parent

the school's professional development program influencing teacher's collegiality and classroom practice? As one can see from the example questions above, designs specify from whom information is to be collected and when it is to be collected. Among the different types of experimental design, there are two general categories: true experimental design: This category of design includes more than one purposively created group, common measured outcome(s), and random assignment. Note that individual background variables such as sex and ethnicity do not satisfy this requirement since they cannot be purposively manipulated in this way. quasi-experimental design: This category of design is most frequently used when it is not feasible for the researcher to use random assignment. This article describes the strengths and limitations of specific types of quasi-experimental and true experimental design. 

QUASI-EXPERIMENTAL DESIGNS IN EVALUATION As stated previously, quasi-experimental designs are commonly employed in the evaluation of educational programs when random assignment is not possible or practical. Although quasi-experimental designs need to be used commonly, they are subject to numerous interpretation problems. Frequently used types of quasi-experimental designs include the following: Nonequivalent group, posttest only (Quasi-experimental). The nonequivalent, posttest only design consists of administering an outcome measure to two groups or to a program/treatment group and a comparison. For example, one group of students might receive reading instruction using a whole language program while the other receives a phonetics-based program. After twelve weeks, a reading comprehension test can be administered to see which program was more effective. A major problem with this design is that the two groups might not be necessarily the same before any instruction takes place and may differ in important ways that influence what reading progress they are able to make. For instance, if it is found that the students in the phonetics groups perform better, there is no way of determining if they are better prepared or better readers even before the program and/or whether other factors are influential to their growth. Nonequivalent group, pretest-posttest. The nonequivalent group, pretest-posttest design partially eliminates a major limitation of the nonequivalent group, posttest only design. At the start of the study, the researcher empirically assesses the differences in the two groups. Therefore, if the researcher finds that one group performs better than the other on the posttest, s/he can rule out initial differences (if the groups were in fact similar on the pretest) and normal development (e.g. resulting from typical home literacy practices or other instruction) as explanations for the differences. Some problems still might result from students in the comparison group being incidentally exposed to the treatment condition, being more motivated than students in the other group, having more motivated or involved parents, etc. Additional problems may result from discovering that the two groups do differ on the pretest measure. If groups differ at the onset of the study, any differences that occur in test scores at the conclusion are difficult to interpret. 

TRUE EXPERIMENTAL DESIGNS

likely to influence program outcomes, even with the best experimental design. Nor can the researcher necessarily be sure, without verification, that the implemented program was really different in important ways from the program of the comparison group(s), or that the implemented program (not other contemporaneous factors or events) produced the observed results. Being mindful of these issues, it is important for evaluators not to develop a false sense of security. Finally, even when the purpose of the evaluation is to assess the impact of a program, logistical and feasibility issues constrain experimental frameworks. Randomly assigning students in educational settings frequently is not realistic, especially when the different conditions are viewed as more or less desirable. This often leads the researcher to use quasi-experimental designs. Problems associated with the lack of randomization are exacerbated as the researcher begins to realize that the programs and settings are in fact dynamic, constantly changing, and almost always unstandardized.