Monday, November 10, 2014

Factors Influencing Student Outcomes and How They Interact - 05 - Free and Reduced-Price Lunch

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 Students Eligible for Free or Reduced-Price Lunch

NCES reports on the percent of students eligible for free lunch or reduced-price lunch under the National School Lunch Program (NSLP).  This is the most commonly used proxy measure for student financial status within schools.

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).

Strong

  • There is a strong negative correlation between percent of students eligible for free or reduced-price lunch and percent of white students, a moderate positive correlation between the percent of students eligible for free or reduced-price lunch and percent of black students, and a weak positive correlation between percent of students eligible for free or reduced-price lunch and percent of Hispanic students.  There is no correlation between NSLP status and percent of students who are American Indian or Alaska native.  This indicates that states with larger percents of non-white students also have higher percents of students eligible for free or reduced-price lunch, and further that percent of black students is more predictive of free and reduced price lunch eligible students than is percent of Hispanic students.  
  • There is a moderate to strong negative correlation between percent of students eligible for free or reduced-price lunch and educational attainment in the state; indicating that states with lower percents of at-risk students have higher percent of people achieving high school diplomas and college degrees.  
  • There is a strong positive correlation between percent of students eligible for free or reduced-price lunch and poverty; indicating that states with higher percent of at-risk students (as defined largely by income level) also have higher poverty levels.
  • There is a moderate to strong negative correlation between percent of students eligible for free or reduced-price lunch and both personal and household income.  This holds true when income is adjusted for inflation (CPI2014) and state cost of living (RPP).  

Moderate

  • There is a moderate negative correlation between the percent of students eligible for free or reduced-price lunch and cost of living by state (RPP); meaning that states with higher cost of living have lower percents of student eligible for the National School Lunch Program's free and reduced-price lunch offerings.
  • There is a moderate positive correlation between the percent eligible for free or reduced-price lunch and percent taking the ACT and  and a weak negative correlation between the percent eligible for free or reduced-price lunch and the percent taking the SAT; meaning students from states with higher percents of free or reduced-price lunch participants are more likely to take the ACT and less likely to take the SAT. 
  • There is a moderate negative correlation between percent of students eligible for free and reduced-price lunch and education spending.  This is true for actual dollars and dollars adjusted for inflation (CPI2014) and state cost of living (RPP); suggesting that states with more at-risk students (largely due to poverty) also have lower per pupil spending.  

Weak

  • There is a weak positive correlation between the percent of students eligible for free or reduced-price lunch and period; indicating that a larger percent of students are eligible each year. 
  • There is a weak negative correlation between percent of students eligible for free or reduced-price lunch and percent of special education students; indicating that states with higher percents of special education students have lower percents of students identified for non-full-price meals. 
  • There is a weak positive correlation between percent of students eligible for free or reduced-price lunch and percent of students participating in ELL programs; indicating that states with higher percents of students identified as in poverty or otherwise at risk also have higher percents of students identified to receive English Language Learner services.  
  • There is a weak positive correlation between percent of students eligible for free or reduced price lunch and the student-teacher ratio; indicating that states with higher percents of at-risk students also have more students per teacher.  
  • There is a weak negative correlation between percent of students eligible for free or reduced price lunch and average teacher salary (raw and CPI2014),  but this correlation becomes non-significant when adjusting for regional price parity (RPP); suggesting that higher percents of at-risk students and lower teacher salaries are both related to lower state cost of living and not directly related to each other.  
  • There is a weak negative correlation between percent of students eligible for free or reduced-price lunch and spending on instruction as a percent of current spending, and no correlation between percent of students eligible for free and reduced-price lunch and spending on instruction as a percent of total revenue; indicating that states with higher percents of at-risk students have lower percents of current spending  going to expenses categorized as "instruction."  
  • There is a weak negative correlation between percent of students eligible for free or reduced-price lunch and population per square mile; indicating that states with lower percents of at-risk students have higher numbers of persons per square mile. 

None or Very Weak

  • No correlations with Students Eligible for Free or Reduced-Price Lunch yielded very weak or non-significant results.

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