In response to the feedback received on “Educational Funding and Student Outcomes: The Relationship as Evidenced by State-Level Data,” the KASB Research Department is working on a “Part II” which will dig further into other factors that impact student outcomes, and how funding impacts when these other factors are taken into consideration.
In this series of blog posts, I will describe the preliminary correlation analysis comparing these factors (independent variables) with each other in an attempt to show how closely tied to each other they are.
Today’s topic is Poverty
This study reviewed six measures of poverty; five measures of the percent of children at certain levels of poverty (50%, 100%, 150%, 200%, and 250%) as reported by the Anne E. Casey foundation in their annual Kids Count Data Book (based on U.S. Census data), and the percent of people with income below the poverty level in the past twelve months as reported by the U.S. Census bureau.
In terms of other independent variables, I will list the interactions in terms of the strength of the highest correlation between variables observed; Strong (+/- 1.0 to 0.5), Moderate (+/- 0.5 to 0.3), Weak (+/- .03 to 0.1), and None or Very Weak (+/- 0.1 to 0.0).
- There is a strong positive correlation between the percent in poverty and the percent eligible for free or reduced-price lunch, as would be expected.
- There is a moderate to strong negative correlation between poverty and teacher salaries; with higher percents of poverty tied to lower teacher salaries. This does not hold true, however, on the teacher salary amounts adjusted for regional cost of living (RPP); suggesting both poverty and teacher salaries are related to regional cost of living but not necessarily directly related to each other.
- There is a moderate to strong negative correlation between poverty and school spending; with higher percents of poverty tied to lower school spending. This holds true even with the funding amounts adjusted for regional cost of living (RPP); suggesting poverty and school funding may be directly related to each other.
- There is a moderate to strong negative correlation between poverty and educational attainment; with higher percents of poverty tied to lower educational attainment.
- There is a moderate to strong negative correlation between poverty and personal or family income; with higher percents of poverty tied to lower income. This holds true when the income amounts are adjusted both for inflation (CPI2014) and for regional cost of living (RPP).
- Poverty has a moderate negative correlation with RPP (regional price parity, or cost of living by state); suggesting that as the cost of living increases, the percent in poverty decreases.
- There is a weak positive correlation between the percent of students who are Hispanic and the percent in poverty, though this correlation is not as strong as that between the percent of students who are black and the percent in poverty. The percent of students who are white is negatively correlated with the percent in poverty, but again this is a moderate correlation. There is no apparent correlation between the percent of students who are American Indian or Alaska Native and the percent in poverty, though it is important to note that this population is very small in many states.
- There is a moderate negative correlation between poverty and spending on instruction as a percent of current spending per pupil; indicating that areas with higher poverty are putting a smaller percent of current spending towards instruction than those with lower poverty. There is no significant relationship between poverty and instruction as a percent of total revenue per pupil.
- There is a weak to moderate negative correlation between poverty and population per square mile; with higher percents of poverty tied to lower population density. This implies that there is more poverty in less densely populated states.
- Poverty has a weak positive correlation with period (or year); suggesting that the percent of the population in poverty is increasing over time.
- There is a weak negative correlation between the percent in poverty and the percent of children served under IDEA, which is somewhat counter-intuitive (unless the availability of services is perhaps a significant factor).
- There is a weak positive correlation between poverty and the student-teacher ratio; with higher percents of poverty tied to higher numbers of students per teacher, but this relationship is not statistically significant across all poverty measures.
None or Very Weak
- There is no significant correlation between the percent in poverty and the percent participating in programs for English Language Learners (ELL), which is contrary to the argument that students from homes where English is not the primary language spoken are more likely to also come from lower income homes.