For this project, we choose to work on the Student Performance dataset from Kaggle.com. Our main question and problem statement was “The Student’s Performance Dataset this project focuses on students age 15-18. How does parental involvement and parental education affect a student’s GPA?” To do this, we took the average value for parental education and parental involvement for each range of GPAs. (4.0-3.5, 3.5-3.0, 3.0-2.5,2.5-2.0,2.0-1.5, and 1.0-0). Our overall hypothesis is that students who receive regular parental help with their schoolwork will have higher academic performance scores than those who do not, and this effect may be moderated by many demographic variables.
To analyze this dataset, we used the denotative reading method, where we looked at the data as literally as possible to observe a student’s GPA. To connect the methodological elements to the problem statement, using the variables, we looked at what demographic had the strongest connection to a high GPA.
By looking at averages of Parental involvement and parental education, we can conclude that parental involvement and education does not correlate with a student’s GPA. For parental education, no matter what the GPA was, all of the average values were between 2.6 & 2.8. For Parental involvement, there was a steady decrease as the GPAs ranges went down, but the decrease was small so we decided it wasn’t relevant enough to support our hypothesis.
We connected this to equality because it shows that you can be independent from your parents' education. Unfortunately, not everyone is born with equal parents but we think that this data shows despite that, that anyone can succeed if they put effort into their work.
Performance of students based on demographics specifically parental education and parental involvement.
Nate B, Qiqi C, Lia Y, Alyssa P.