- Published: November 14, 2021
- Updated: November 14, 2021
- University / College: Brown University
- Language: English
- Downloads: 40
Many different variables go into defining and predicting student success. Depending on which theorist you listen to, variables such as class size, teacher experience, teacher training, and home environment have a varying level of importance when it comes to predicting which students will be ready for college – or ready to graduate high school. While the truth is that there is not one single factor that will predict success (or failure) for any student, there are some factors that, over time, have been shown to deliver favorable outcomes more reliably than others.
One of these factors is socioeconomic status. Because relative wealth tends to mean more access to opportunities for enrichment and a higher attention to education as a priority, on the basis of a number of studies, I chose to compare mean family income and passing rate in the data provided. Except for the twenty-student Kelleys Island school district, which had a 100 percent passing rate despite a mean family income of only $19, 854 (Data), income had an extremely significant effect on passing rate. The only other two school districts with a passing rate above 90 percent were the two highest in terms of mean income.
For this project, I am comparing mean family income and passing rate, while acknowledging the effects of district size when producing a statistically significant sample. Mean family income ranges in this data sample from $18, 394 to $45, 723, while passing rates range from 33 percent to 100 percent. District sizes, in terms of student population, range from 20 to 36, 790. Size is an important factor, because districts that vary so widely in size will also vary in terms of administrative structure, teacher-to-student ratio, and class size.
I will produce a detailed analysis of the relationship between mean income and passing rate, and I may also look at the percentage of families on welfare, to see if that could be a contributing factor as well. It may be that tracking welfare recipients will not differ significantly from simply following income.
Works Cited
Data from selected school districts.
