module 3 dq 1 argument Rachel Within the article, College Major Choice in STEM: Revisiting…

module 3 dq 1 argument Rachel Within the article, College Major Choice in STEM: Revisiting…

module 3 dq 1 argument Rachel

Within the article, College Major Choice in STEM: Revisiting Confidence and DemographicFactors, by Moakler and Kim (2014), the researchers sought to determine how demographic factors, as well as academic and math self-efficacy, influenced a student’s choice to enter STEM fields. To address these questions, Moakler and Kim (2014) accessed a large data set (over 330,000 students from more than 600 colleges) collected in 2003 using stratified sampling techniques, and encompassing multiple data points collected on incoming college freshman at 4-year colleges. Ten independent or predictor variables of interest were identified in this study based upon the theoretical foundation of Social Cognitive Theory, Self-efficacy Theory, and Social Cognitive Career Theory. The ten predictor variables are parental income, parental education level, whether parents are working in a STEM career, student’s gender, student’s high-school GPA, combined verbal and math SAT scores, number of hours spent studying per week, academic confidence, mathematics confidence, and minority status. The dependent or response variable was whether the student declared a STEM major upon entering college. Three different logistic regression models were created to address the research questions and hypotheses, all of which were statistically significant, with confidence in mathematical and academic abilities and parents from STEM careers as the most influential predictors. Thus, this study is non-experimental (the researcher did not manipulate any of the independent variables), predictive (the logistic regression attempted to predict student’s choice to enter STEM fields), and retrospective (because it utilized historical data to explain or predict an outcome).

Many of the studies reviewed to date are quantitative. However, there is a mixture of experimental, quasi-experimental, and non-experimental studies. The majority are predictive or causal-comparative, although some are descriptive. Furthermore, there is a relatively equal mix of retrospective, cross-sectional, and longitudinal studies.

module 3 dq 1 argument Rachel Within the article, College Major Choice in STEM: Revisiting…

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