Read Chapter 8 Clarifying Quantitative Research Designs by Susan K. Grove , review the algorithms for the different research designs.
· You are going to compare two groups of students (school team or no school team). This is like having an intervention group and a control group.
· Select (and cite) the correct quantitative algorithm from your text that will aid you in identifying the research design you should use.
· State the quantitative research design and the algorithm you used in this decision.
· Explain your choice.
· What type of sampling will you do to reach the highest level of research design (experimental?). Select a quasi-experimental or experimental sampling method.
· What method did you select and why?
Research Design Selection for Comparing Two Groups of Students
In conducting a study to compare two groups of students, specifically those involved in a school team versus those not in a school team, it is important to select an appropriate quantitative research design that will provide meaningful insights. The quantitative algorithm that will aid in identifying the research design to use in this scenario is the "True Experimental Design" algorithm as outlined by Susan K. Grove in Chapter 8 of her book, Understanding Nursing Research: Building an Evidence-Based Practice.
Quantitative Research Design:
The quantitative research design recommended for this study is a Quasi-Experimental Design. This choice is based on the "True Experimental Design" algorithm provided by Grove, which suggests that when random assignment is not feasible, a quasi-experimental design is a suitable alternative for comparing groups and inferring causality.
Rationale for Choosing Quasi-Experimental Design:
The nature of the study, where students cannot be randomly assigned to school team or no school team due to ethical or practical reasons, aligns well with the characteristics of a quasi-experimental design. This design allows for comparison between groups while controlling for some variables, although it lacks the randomization element present in true experimental designs.
Sampling Method for Experimental Design:
For reaching the highest level of research design, considering an experimental design, the sampling method selected would be Stratified Random Sampling. Stratified random sampling involves dividing the population into subgroups (strata) based on certain characteristics and then taking random samples from each stratum.
Rationale for Selecting Stratified Random Sampling:
Stratified random sampling is chosen for its ability to ensure representation from different subgroups within the population, such as students in school teams and those not in school teams. This method helps in reducing sampling bias and increasing the precision of estimations within each subgroup.
In conclusion,
by employing a quasi-experimental design with stratified random sampling, this study comparing two groups of students can achieve a robust research design that balances practical considerations with methodological rigor.