Please provide at least 150-word response to each student response below to continue conversation and provide new information/content. Be sure to research/cite/reference sources in each discussion.
1st Post: Descriptive research is focused on studying a phenomenon that occurs naturally, with no interventions or manipulations. The researcher seeks to explore and describe phenomena without investigating cause-and-effect relationships. On the other hand, causal-comparative research is designed to explore cause-and-effect relationships without independent variable manipulation (Ravid, 2020).
A phenomenon observed at my workplace was the need for global training for marketing metrics. Each business group and many divisions had large PowerPoint decks that would be presented in lecture-style webinars. The webinars did not have embedded knowledge checks, polls, or other interactions. After the webinar, a qualitative survey was conducted to garner attendee feedback. A two-step approach was taken to evaluate the phenomenon. The first step was a qualitative survey asking the marketers to self-assess their knowledge and use of the metrics. The second step was a quantitative survey conducted to evaluate the marketers’ competency, and it was found that marketers had significant competency gaps in the metrics.
To rectify the situation, I built a branching course with a pretest of problem-solving scenarios with each metric. If the learner passed all the scenarios, their score would be posted to the LMS, and they could exit the course as completed. For scenarios that were not passed, the learner would complete the training branches for those metrics. A show it, try it, do it model was utilized. After completing the branches, summative problem-solving scenarios were presented, and detailed feedback was provided. On average, leaders rated themselves at a 4.5/5.0 proficiency level and demonstrated an 84% improvement from the pretest to the post-test.
2nd Post: United States hospitals experience high nurse turnover, especially among young RNs (Al Zamel et al., 2020). The current supply of nurses is not enough to meet increasing healthcare demands, which leads to decreased quality of care and increased mortality rates in healthcare. I could use a qualitative design to investigate which factors contribute to retention among Millennial or Generation Z nurses in acute care hospitals. My design would be like one described in Bibbin’s (2021) dissertation. My research question would be: What factors contribute to the retention of Generation Z nurses in acute care hospitals?
I could also employ quantitative methodology to investigate the retention of nurses in acute care hospitals. For example, I could compare turnover rates between Generation X and Generation Z nurses. I could ask a research question similar to Bennet’s (2020) study.
The research question would be: Is there a significant association between generational cohorts (Generation Z and Generation X) and nursing turnover?
My null hypothesis(H0) is: There is no significant association between generational cohorts and nursing turnover.
My alternative hypothesis (Ha1) is: There is a significant association between generational cohorts and nursing turnover.
My research questions will dictate my research design and the type of data I need to collect. The table below describes the differences between my potential studies.
3rd Post: There are several population sampling methods. The first sampling method is the simple random sample. Every member of the population has an equal and independent opportunity of being selected for the sample. The second sampling method is the systematic sample. This method determines the size of the population and the targeted sample size. Dividing the population by the sample size determines the value of K. To select the members of the population, every Kth member is selected. The third sampling method is the stratified sample. This method divides the population into subgroups, and a random sample is selected from each group. The fourth sampling method is the convenience sample. This is also called an incidental sample, and the group is typically chosen from the researcher’s classroom (Ravid, 2020).
The selected statistic is the parametric statistic. The data models are the t-test and analysis of variance. The t-test compares the means of two groups and is helpful for hypothesis testing. Does the hypothesis demonstrate that the process or treatment had a measurable effect on the population of interest? An example Bevans presents is comparing the petal length between two different species of irises in the same garden with the same environmental factors. The sample was 25 petals from each species. The t-test and null hypothesis test the differences (Bevans, 2020).