Purpose

It’s not a stretch to imagine that child poverty within a school district can adversely affect student performance. As a former teacher, I can anecdotally say a child dealing with poverty at home is less likely to succeed within the standard expectations of a classroom. However, assumptions and stories are not facts.

This project seeks to explore the relationship between child poverty and College and Career Readiness (CCR) in Missouri School Districts. I’ve gathered performance data from the Missouri Department of Elementary and Secondary Education (DESE)ⁱ, and census.gov’s Small Area Income and Poverty Estimates (SAIPE)ⁱⁱ from 2019 to explore an introductory look at that relationship.

Guiding Question

What is the relationship between a school district’s College and Career Readiness (CCR) scoresⁱ and the percentage of children living in povertyⁱⁱ within that school district?

The Short Story

In each of the three CCR categories, we can see a decline in CCR as child poverty increases.

A Deeper Look

Notes on the Data

2019 Poverty Guidelines for Missouri

Household Size |	Poverty Guidelines
1	$12,490
2	$16,910
3	$21,330
4	$25.750
5	$30,170
6	$34,590
7	$39,010
8	$43,430

DESE’s College and Career Readiness scores are based on the percentage of graduating students that meet specific criteria within three categories:

• College Level Proficiency
• College or Career Path
• Assessment Scores

Within those categories, the districts’ percentage scores are divided into 4 determinations: “Target”, “Approaching”, “On Track”, “Floor.” For this project, “Target” indicates the district has met the standard for that category. “Approaching” indicates their score is just below meeting the state standard. “On Track” falls below that, with “Floor” being the lowest scoring determination.ⁱⁱⁱ

Note, the percentage range for each determination is different between categories. The determination percentage range for the indicated category can be found within the legends where applicable.

Analysis

Proficiency in College Level Courses

Definition: Graduates, “who earned a qualifying score on an AP, IB, or IRC assessments and/or receive college credit through early college, dual enrollment, or approved dual credit courses meets or exceeds the state standard or demonstrates required improvement” while still in high school (MSIP5)

Within this category, we see a large disparity between readiness scores. The lowest performing district shows only 3.7% of graduates meeting the state standard. The highest performing district earned a score of 103.1%. This is a performance difference of 99.4%.

Yet, this category also has the smallest steps between determinations. The determination of Floor only ranges from 0-4.9%. On Track shows the largest range of 38.8% before reaching the Approaching benchmark. From there, a district need only raise their score 3.8% to meet the state standard. To summarize, the jumps between determinations are 4.9%, 38.8%, and 3.8%.

College or Career Path

Definition: Graduates who are in college, the military, or on a career path directly related to their career education program within 6 months of graduating.

In contrast, we see the least disparity within the College or Career Path category with a high of 100% and a low of 58.9% for a variation of only 41.1%.

Indeed, when we look at the school districts within the highest 25% of child poverty, we see more districts meeting or approaching the state standard here than in any other category.

While two more districts are on target when testing for college level proficiency, college or career placement shows vastly more districts approaching the target standard making the likely hood of more districts meeting the target in the future much higher. Conversely, assessment scores leave significant room for improvement.

Assessment Scores

Definition: Graduates who scored at or above the state standard on any department-approved measure of college and career readiness test.

In the assessment category, we see the least number of districts meeting the state standard with only 189 hitting the target. Compare this to 310 and 285 districts meeting the state standard in College or College Level Proficiency and Career Placement respectively.

Recommendation

While many times correlation does not equal causation, further steps should be taken to investigate a causation link, including analyzing data from multiple years to further identify trends. If causation is found, identify what changes should be made within the current system to mitigate the effects.

Further Exploration

There are many other questions that arise when looking at this data as a starting point.

• Does enrollment size affect performance when determining the effect of poverty?
• What is the student to teacher ratio within each district?
  • Is there a correlation between teacher base pay and high student to teacher ratios?
• Is there a correlation between high performing teachers and districts with a lower poverty rate?
• How do demographics compare between high scoring and low scoring districts?
• Does our current system perpetuate under performance?

Process

By far the most difficult part of this project was sifting through DESE’s documentation to find complete and appropriate data. The only data that met that criteria was for the year 2019. Therefore, this project explored this relationship for only a single year: 2019.

After finding and compiling the data, I made a copy of each raw data file, normalized the district names across all sources, filtered each database to contain only information pertinent to this project while keeping data that might be useful for further analysis. I then verified that the resulting cleaned data was accurate to its source material and created a singular combined data table.

Of the original 553 reported districts from DESE, 95 districts do not have a year 12 (students graduating high school). Twelve more are charter or special school districts that do not have specific corresponding child poverty data from census.gov. Filtering out these districts leaves us with 446 districts.

More detailed process information can be found in the word document found at this link

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Endnotes

ⁱCollege and Career Readiness —“The district provides adequate post-secondary preparation for all students.
1. The percent of graduates who scored at or above the state standard on any department-approved measure(s) of college and career readiness, for example, the ACT®, SAT®, COMPASS® or Armed Services Vocational Aptitude Battery (ASVAB), meets or exceeds the state standard or demonstrates required improvement.
2. The district’s average composite score(s) on any department-approved measure(s) of college and career readiness, for example, the ACT®, SAT®, COMPASS®, or ASVAB, meet(s) or exceed(s) the state standard or demonstrate(s) required improvement.
3. The percent of graduates who participated in any department-approved measure(s) of college and career readiness, for example, the ACT®, SAT®, COMPASS®, or ASVAB, meets or exceeds the state standard or demonstrates required improvement.
4. The percent of graduates who earned a qualifying score or grade on an Advanced Placement (AP), International Baccalaureate (IB), or Technical Skills Attainment (TSA) assessments and/or receive college credit or a qualifying grade through early college, dual enrollment, or approved dual credit courses meets or exceeds the state standard or demonstrates required improvement.
5. The percent of graduates who attend post-secondary education/training or are in the military within six months of graduating meets the state standard or demonstrates required improvement.
6. The percent of graduates who complete career education programs approved by DESE and are placed in occupations directly related to their training, continue their education, or are in the military within six months of graduating meets the state standard or demonstrates required improvement.” DESE

ⁱⁱ “In addition, in order to implement provisions under Title I of the Elementary and Secondary Education Act as amended, we produce the following estimates for school districts: • total population • number of children ages 5 to 17 • number of related children ages 5 to 17 in families in poverty The estimates are not direct counts from enumerations or administrative records, nor direct estimates from sample surveys. Instead, for counties and states, we model income and poverty estimates by combining survey data with population estimates and administrative records. For school districts, we use the model-based county estimates and inputs from federal tax information and multi-year survey data to produce estimates of poverty.” (census.gov)

ⁱⁱⁱ DESE ranks these in the order of Target, On Track, Approaching, Floor. This wording often causes confusion about the rankings of the categories with “Approaching” inferring a closeness to the target. I have chosen to swap the order of the terms to eliminate that confusion.