running head: free and reduced lunch state test scores … · 2014-09-02 · free and reduced lunch...

FreeandReducedLunch 1

Running Head: Free and Reduced Lunch

INFLUENCE OF FREE AND REDUCED LUNCH STUDENT POPULATION ON

STATE TEST SCORES AND THE ACT.

By

Shawn Fowler

Submitted to

Educational Leadership Faculty

Northwest Missouri State University Missouri

Department of Educational Leadership

College of Education and Human Services

Maryville, MO 64468

Submitted in Fulfillment for the Requirements for

61-682 Research Paper

Spring 2014

July 18, 2014


ABSTRACT

This study was completed to discover if there is a significant relationship in

students that receive free and reduced lunch and students that do not receive free and

reduced lunch on state tests and the ACT. The state tests include the Algebra 1, Biology,

Language Arts 10 and Government. Although various learning and teaching styles are

also influences on test scores this study will focus on the free and reduced lunch student

population and it’s direct relationship to socioeconomic status. The results of this study

discovered that students that do not receive free and reduced lunch scored significantly

higher than students that do receive free and reduced lunch. After compiling and

reviewing the data from this study, performing research and reviewing literature there is a

need that has to be addressed by school districts and communities. Lower socioeconomic

students are not performing as well as higher socioeconomic students.


INTRODUCTION

Background,issuesandconcerns.

School districts across the state have diverse student populations with various

rates of free and reduced lunch. Test scores can also vary among school districts. There

needs to be a concern in the educational community about how these two topics are

related. Most high schools in the state of Missouri administer the Biology, Algebra 1,

Government and Language Arts10 EOC tests and in the future the ACT and this study is

designed to investigate socio-economic status and its possible effect on student’s test

results. The school district studied has a 53% free and reduced lunch rate. The research

widened and investigated four different content areas EOC tests scores and the ACT and

compared them with the actual free and reduced lunch percentages of students. The

research links poor test results to low socio-economic status and investigated methods of

intervention and remediation. Although the actual test result is important it is not as

important as student success and the ability to score well on tests in order to advance into

college or career readiness regardless of socioeconomic status. The research was

designed to assist low income students achieve their dreams and give them an

opportunity to succeed.

Practice under investigation.

The practice under investigation will be looking at EOC and ACT performance

results. This investigation determined if there is a significant relationship in various EOC

and ACT test scores based on socio-economic status. This study used the disaggregated

data provided by the School District investigated, the Department of Elementary and


Secondary Education (DESE) and if there is a relationship, what interventions can be

made to assist some students in achieving higher test scores and student success.

Schoolpolicytobeinformedbystudy.

Every school district in the state of Missouri must meet certain standards on EOC

tests and beginning in the 2015 school year all students must take the ACT, so if there is

a significant relationship in test scores based on socio-economic status teachers should

make sure they are knowledgeable of their student’s socioeconomic status so they are

able to reach all students regardless of status.

Conceptualunderpinning

Each student has a unique and specific background. One specific difference

among students is there socio-economic status. This difference in backgrounds among

students influences different values and what is considered important in their lives. The

different values may lead to various learning styles. Educators have the responsibility to

teach all of their students and become familiar with instructional methods and strategies

in order to achieve the goal of student success.

This study is designed to investigate the relationship in test scores between free

and reduced lunch students and non-free and reduced lunch students. According to Ruby

Payne, “achievement levels of affluent students regardless of race were similar.” (Payne,

2005, p.2) The levels of achievement of non-affluent students were also similar. This

study investigated the relationship between these similarities. There are many researched

reasons for this relationship such as, “poor children are prone to developmental delay and

damage, to drop out of high school, and give birth during the teen years.” (Payne, 2005,

p.4) “Poverty prone children are more likely to be from single parent households.”


(Payne, 2005, p.4) She also established that, “poor inner city youths are seven times more

likely to be the victims of child abuse or neglect than are children of high social and

economic status.” (Payne, 2005, p.4) Students of low socioeconomic status face a variety

of obstacles outside of the classroom.

Statement of the Problem If there is a relationship between the four content EOC student test results and

ACT test results, does socio-economic status influence those results? If there is a

connection administrators and teachers need to know. How do administrators and

teachers connect with students in need and how do they improve student test scores to

benefit student success.

Purpose of the Study The purpose of this study was to investigate if socioeconomic status has a strong

effect on academic performance on one content area over another and the ACT. The

information gained from this study will give teachers and administrators a better

understanding of methods and strategies to assist students who may be in need in order to

improve student test scores.

Research Questions.

RQ 1: Is there a significant relationship in student achievement on the Biology, Algebra

1, Government and Language Arts10 EOC tests and the ACT between students from

higher socioeconomic status compared to students from lower socioeconomic status?

RQ 2: If socioeconomic status does affect all or particular test scores what changes in

instruction may need to occur to improve their test scores?


Null Hypothesis

Ho: There is no significant relationship in student achievement in Biology, Algebra 1,

Government and Language Arts 10 or the ACT between students from higher

socioeconomic status compared to students from lower socioeconomic status.

Anticipated Benefits of the Study

The result of this study will inform teachers and administrators about which subjects may

be affected by student socioeconomic status. This information will allow teachers and

administrators to modify instruction in order to reach student needs, which allow for

student success on state tests.

Definition of Terms

AYP- Annual Yearly Progress- The No Child Left Behind Act, instituted in 2000, sets

certain goals for school districts to achieve to show student performance. One factor is

test scores on the EOC tests in high school and the MAP test in elementary school.

DESE- Department of Elementary and Secondary Education

Differentiated Instruction- changing instruction to fit needs of different groups of

students so every student is able to master the skills and objectives associated with the

course objectives.

EOC- End of Course Exam- test given in the state of Missouri at the end of certain

courses created in 2009

Free and Reduced Lunch- A method to verify a student’s socio-economic status

Socio-Economic Status- A measure of an individual’s or family’s economic and social

position based on education, income, and occupation.


Summary

A study was conducted to see if there was any relationship between various EOC

and ACT test results based on socioeconomic status. If the Descriptive Analysis and

Correlation Analysis tests conclude that there were any significant relationships,

educators may need to differentiate instruction in order to reach all of their students to

ensure that all students have a chance for success, regardless of background. Educators

also need to become aware of different student value systems that may lead to student

success. After this study is completed, educators can benefit by investigating student

performance data in order to develop certain instructional methods through professional

development.


REVIEWOFLITERATURE

TheEndofCourseAssessments(EOC)wereusedinthisstudy

becauseallstudentsarerequiredtotakethesestatetestsregardlessofany

differences.Therehavebeenmanystateteststoassessmasteryofaparticular

contentthroughouttheyears.Eachtesthashadavalidpurpose.ThecurrentMAPas

statedbytheMissouriDepartmentofEducationstates “The Missouri Assessment

Program assesses students’ progress toward mastery of the Show-Me Standards which

are the educational standards in Missouri. End-of-Course assessments are taken when a

student has received instruction on the course-level expectations for an assessment,

regardless of grade level.” (DESE, 2014, p. 1) This means that prior to each EOC the

students should be prepared by the high school to succeed on the test. The American

College Testing assessment was also used because students that choose to attend college

are typically required to take this test. “The ACT® college readiness assessment is a

curriculum- and standards-based educational and career planning tool that assesses

students' academic readiness for college.” (ACT, 2014, p. 1)

There is a strong relationship between poverty, low socioeconomic status and free

and reduced lunch (F/R Lunch) student population. A working definition of poverty is

“the extent to which an individual does without resources.” (Payne, 2005, p.7)

This is an interesting definition because it is not solely based on finances or

income but rather available recourses and actions. The current poverty level within the

Unites States is an income of “$23,550 for a family of four.” (2013 Poverty Guidelines,

2013, p. 1) and the current level to receive F/R Lunch is set at an income of “43,568 for a


family of four.” (Free and Reduced Lunch Guidelines, 2013-2014, p. 1). This data

confirms that every family of four below the poverty line is receiving F/R Lunch.

The current application has a baseline income of “$44,123 for a family of four”

(National School Lunch Program, 2014, p. 1) in order to receive benefits such as F/R

Lunch. It is safe to assume that families and students that receive F/R Lunch are within

the realm of needing assistance based on state and national assistance programs.

Assistance is on a slide and scale format and the closer to the top dollar amount of

income the less assistance provided. This data confirms the strength in the relationship

between poverty, low socioeconomic status and receiving F/R Lunch.

According to Abraham Maslow, “healthy human beings have a certain number of

needs, and that these needs are arranged in a hierarchy, with some needs (such as

physiological and safety needs) being more primitive or basic than others (such as social

and ego needs).” (Burton, 2013, p. 2) “Maslow called the bottom four levels of the

pyramid ‘deficiency needs’ because a person does not feel anything if they are met, but

becomes anxious if they are not. Thus, physiological needs such as eating, drinking, and

sleeping are deficiency needs, as are safety needs, social needs such as friendship and

sexual intimacy, and ego needs such as self-esteem and recognition. In contrast, Maslow

called the fifth level of the pyramid a ‘growth need’ because it enables a person to ‘self-

actualize’ or reach his fullest potential as a human being. Once a person has met his

deficiency needs, he can turn his attention to self-actualization; however, only a small

minority of people are able to self-actualize because self-actualization requires

uncommon qualities such as honesty, independence, awareness, objectivity, creativity,

and originality.” (Burton, 2013, p. 3)


There is a strong relationship between poverty level and the bottom four levels.

Students that grow up in poverty are only concerned with the bottom four levels that are

made up of survival, safety, relationship and esteem needs. These concerns may not allow

them to achieve the top level of growth creativity, problem solving skills and basic

acceptance of facts. This image was placed in the research paper to state the importance

that if students are worried about meeting their basic survival needs how can they

possibly grow and succeed academically? Students in poverty are not distressed about the

content in class but rather possibly surviving the day.

Maslow’sHierarchyofNeeds(Burton, 2013, p. 1)

“Maslow’shierarchyofneedsmaybecriticizedforlackingscientificproofbut

noonecanarguethefactthatstudentsmusthavebasicneedsmetintheirlives


beforetheycanbeexpectedtobeconcernedabouttestsandacademic

content.”(Burton, 2013, p. 3)

ThisstudyinvolvestheACTtomeasureacademicsuccessandpreparedness

ofstudents.Thefactisthathighersocioeconomicstatus(SES)studentsperform

betterontheseteststhanlowerSESstudents.StudentsoflowerSEShavedifferent

needsandvalues.Povertyisrelative.“Ifeveryonearoundyouhassimilar

circumstances,thenotionofpovertyandwealthisvague.Povertyorwealthonly

existsinrelationshiptoknownquantitiesorexpectations.”(Payne,2005,p.2)

Thecycleofpovertyandgenerationalpovertyisatremendousobstacleand

maynoteverbesurpassedbystudents.“StudentswhoareraisedinalowerSES

needtoseethelightofbreakingtheirpersonalcycleanditistheresponsibilityof

parentsandteacherstomakesurethatthesestudentsunderstandtheobstaclesand

theassistancetoovercomethem.“(Payne,2005,p.37)

OnestepinthebreakingthecycleistodowellonthestatetestsandtheACT

inordertogivethemtheopportunitysurpasstheirinitialsituation.Everylevelof

socialclassdistinctionhasitsownsetofrulesandguidelines.Teachersneedto

understandthatstudentsoflowSEShaveaparticularsetofvaluesandrulesand

theymaynotknoworunderstandhowtoworkorsocializeoutsideofthese

boundaries.“Thesehiddenrulesaretheunspokencuesandhabitsofagroup.

Distinctcueingsystemsexistbetweenandamonggroupsandeconomicclasses.”

(Payne,2005,p.37)

TheproblemthatexistsbetweenschoolsandlowSESstudentsisthatschools

andteachersteachwithasetofmiddleclassrulesandstandardsandthepopulation


oflowSESstudentsisrising.Thisdifferenceofrulesandvaluescanbeanobstacle

forlowSESstudentstoovercome.

Thegrowthandlearningthatstudentsperformarenotonlypartoftheir

currentsituationbutcanbetheresultofgeneticsandtheirearlyyouth.“The

prevailing theory among psychologists and child development specialists is that behavior

stems from a combination of genes and environment. Genes begin the process: behavioral

geneticists commonly claim that DNA accounts for 30–50 percent of our behaviors, an

estimate that leaves 50–70 percent explained by environment.” (Jensen, 2004, p. 1)

The environment we grow up in influences the ways we learn and develop. Early

relationships with parents and caregivers also influence personality, which can either be

secure and stable or unsecure and unstable. This personality can control learning and

confidence in them. “Socioeconomic status forms a huge part of this equation. Children

raised in poverty rarely choose to behave differently, but they are faced daily with

overwhelming challenges that affluent children never have to confront, and their brains

have adapted to suboptimal conditions in ways that undermine good school performance”

(Jensen, 2004, p. 2)

Thereexiststhesimplefactthatpovertyinfluencingstudentachievementhas

beenaroundforalongtime.ThetablebelowdisplaysfamilyincomeandSATscores.

“Ever since the Coleman report in the 60s and the controversial book The Bell Curve by

Herrnstein and Murray in the 1990’s dozens of studies keep finding the same thing:

socio-economic status is correlated with student achievement.” (Wiggins, 2012) Also

from Wiggins:


Family Income Critical Reading Mathematics

0$ – $20,000 433 461 $20,000 – $40,000 463 481 $40,000 – $60,000 485 500 $60,000 – $80,000 499 512 $80,000 – $100,000 511 525 $100,000 – $120,000 523 539 $120,000 – $140,000 527 543 $140,000 – $160,000 534 551 $160,000 – $200,000 540 557 More than $200,000 567 589 (Wiggins, 2012)

Students who grow up in poverty have different brains than students who grow up

in a higher SES. “The effects of poverty on any human being are truly staggering. In

short, the kids are different because their brains are different. Our neurons are designed

by nature to reflect their environment, not to “automatically” rise above it. Areas of the

brain that are affected by chronic exposure to poverty include those responsible for

working memory, impulse regulation, visuospatial, language and cognitive conflict.”

(Noble, et al. 2005, p. 2).

“Evidence suggests children of poverty are more likely to have different brains

via four primary types of experiences. They are: 1) exposure to toxins, 2) chronic stress,

3) chronic exposure to substandard cognitive skills, and 4) impaired emotional-social

relationships. While not every single low SES child will experience all of these factors,

the majority will.” (Jenson, 2009p. 1)

A positive influence and learning environment can change a young person’s


working of the brain. “We know that children of poverty often have suboptimal brains

and we know that brains can change for the better. It takes quality schools and quality

teaching. Average teachers working well at a great school climate (collaborative,

committed, focused, mission-driven, etc.) can succeed. Or, high-performing teachers at a

school with an average climate can succeed. But the reality is that low SES kids will

expose the weakest links in the education you provide. In short, it’s the ability of each

school staff to understand not just “what it takes” but also be “able and willing to deliver”

the factors that actually drive positive change.” (Jensen, 2009m p, 1) Students that are

raised in a lower SES can succeed but it takes the people around them to assist in their

success.


Research Methods

Research Design

Aquantitativestudywasconductedtoseeifanyrelationshipsexistedin

studenttestresultsinAlgebra1,Biology,LanguageArts10andGovernmentEOC

testsandtheACT.Theindependentvariablewasstudentsocio‐economicstatus

basedonstudentsreceivingF/RLunchandthedependentvariableswerestudent

EOCtestandACTresults.Iftherelationshipisfoundtobesignificantthenvarious

strategiesneedtobeimplementedinordertoachievestudentsuccess.

Study Group Description Students in the high school investigated who have completed the Algebra 1,

Biology, Language Arts 10 and Government and EOC tests and the ACT disaggregated

by socio-economic status were evaluated. The school district investigated has a 93%

White population with the other 7% being Black, Latino or Asian. The district also has a

total of 541 students. The district also has a 10% student population on an IEP with 1% of

the students being on a 504 plan. With a 93% White student population there only is a 1%

ELL student population.

Data Collection and Instrumentation Archived data from DESE and the studied school district was collected to identify

raw scores on the Algebra 1, Biology, Language Arts 10 and Government EOC tests and

the ACT from the 2012-2103 school year.


Statistical Analysis Methods Two statistical tests were conducted to find if there is a significant relationship in

Biology, Language Arts 10, Government and Algebra 1 EOC tests and the ACT based on

socio-economic status. The source was broken into 2 groups, students on free and

reduced lunch and students who are not. The descriptive analysis will be conducted to

measure the data and create a summative analysis of the raw data. The correlation

analysis will also be conducted to measure the relatedness of the various test scores on

whether students receive free and reduced lunch assistance. The null hypothesis states

that there is no significant difference in student achievement in Biology, Algebra 1,

Government and Language Arts 10 between students from higher socioeconomic status

compared to students from lower socioeconomic status.


Findings

A descriptive analysis and correlation analysis were conducted to decipher

whether there was a relationship in performance on the Algebra 1, Biology, Language

Arts 10 and Government EOC tests and the ACT from the 2012-2103 school year based

on a student population receiving or not receiving F/R Lunch. The following tables and

graphs will depict the organized findings based on the statistical raw data found on the

Missouri DESE website and information provided by the investigated school district.

There is one year of data.

Figure 1

Descriptive analysis results for the Algebra 1, Biology, Language Arts 10,

Government and EOC tests scores.

Grade Algebra 1 EOC Biology EOC Language Arts

10 EOC Government EOC

Mean 3.66 3.99 3.75 3.55

Maximum 5.00 5.00 5.00 5.00

Minimum 2.00 2.00 2.00 2.00

Median 4.00 4.00 4.00 4.00

Standard Dev. 0.80 0.74 0.87 0.84

Figure 2

Mean scores for the Algebra 1, Biology, Language Arts 10 and Government EOC

for the F/R Lunch student population

Algebra 1 EOC

Biology EOC L/A EOC

Government EOC F/R Lunch

Mean Scores 3.59 3.81 3.55 3.38 Yes


Figure 3

Mean scores for the Algebra 1, Biology, Language Arts 10 and Government EOC

for the non F/R Lunch student population

Algebra 1 EOC

Biology EOC L/A EOC

Government EOC F/R Lunch

Mean Scores 3.77 4.09 3.89 3.68 No

Figure 4

Bar Graph displaying the mean scores for the Algebra 1, Biology, Language Arts 10

and Government EOC comparing the non F/R Lunch student population to the F/R

Student population

All students who were eligible to take the following EOC tests were selected for

this study to determine if there is a relationship between F/R Lunch and non F/R Lunch

students in the Algebra 1, Biology, Language Arts 10 and Government EOC. I removed

the variability for randomness for this study. In this study there were 224 F/R Lunch

0.000.501.001.502.002.503.003.504.004.50

AlgebraEOC BiologyEOC English1EOC GovernmentEOC

AverageEOCscoresbasedonFreeandReducedLunch

FreeandReduced

NonFreeandReduced


students and 259 non F/R Lunch students for a total of a 483 students in the population.

This results in a 46% F/R Lunch student population. The school district studied has a

slightly higher F/R Lunch student population when considering all four schools. When

analyzing the data of the Algebra 1, Biology, Language Arts 10 and Government EOC

scores the F/R Lunch student population scored considerably lower than the non F/R

Lunch student population in every category. The scale of the results is scored with a 5

being the highest score and a 0 being the lowest score. The non F/R Lunch students

scored the highest in the Biology EOC with a score of a 4.09. The non F/R Lunch

students also scored the highest in the Biology EOC with a score of a 3.81. The non F/R

Lunch students scored the lowest in the Government EOC with a score of 3.68. The F/R

Lunch students also scored the lowest in the Government EOC with a score of 3.38. The

largest difference between F/R and non F/R students in EOC scores was in the Language

Arts 10 content area with a difference of .34. The smallest difference between F/R and

non F/R students in EOC scores was in the Algebra 1 content area with a difference of

.16. Non F/R Lunch student population had a maximum score of 5 in each content

category and had a minimum of 2 in each content category. F/R Lunch student population

had the same scores. Each student population scored a 4 as the median in each content

category. Although there are some similarities of scores this data does show that there is a

significant relationship as a whole between F/R Lunch and non F/R Lunch student

populations and their test scores.


Figure5

DescriptiveanalysisresultsfortheACT

Non F/R F/R

Mean 23.23255814 20.8285714

Maximum 33 30

Minimum 14 15

Median 23 20

Standard Dev 3.878007216 3.92

Figure6

Bar Graph displaying the mean scores for the ACT comparing the non F/R Lunch

student population to the F/R Student population

19.5

20

20.5

21

21.5

22

22.5

23

23.5

NonF/RLunchF/RLunch

AverageACTsoresbasedonFreeandReducedLunch


AllstudentswhochosetoparticipateandcompletetheACTduringthe2013‐

2014schoolyearwere selected for this study to determine if there is a relationship

between F/R Lunch and non F/R Lunch students in the ACT. I had to consider the

variable of randomness for this portion of the study because I could not control who

participated. All students regardless of class level were selected for this study. I only used

the composite score for this study. In this study there were 35 F/R Lunch students and 86

non F/R Lunch students in this study for a total of a 121 total student population. This

results in a 29% F/R Lunch student population. When analyzing the data of the ACT

scores the F/R Lunch student population scored considerably lower than the non F/R

Lunch student population in the composite score. The scale of the results is scored with a

36 being the highest score and a 0 being the lowest score. The non F/R Lunch students

scored an average of a 23.2, a maximum score of 33, a minimum score of 14 and a

median score of 23. The F/R Lunch students scored an average of 20.8, a maximum of

30, a minimum of 15 and a median of 20. This demonstrates that the F/R Lunch students

have the potential to score high on the ACT. The raw data did show however that there

were 7 other scores of at least 30 among the non-F/R Lunch students and there was only

an additional single score of 28 within the F/R Lunch students. This data is confirmed

when the mean was analyzed. The non-F/R Lunch students had a mean 2.4 points higher

than the F/R Lunch students. There are a few students who scored well on the ACT from

the F/R Lunch students however the number of students is low. If 3 of the highest scoring

students were removed from the data the difference would be more significant. This data

is also a concern. Simply, the F/R Lunch students scored considerable lower on the ACT

than the non-F/R group.


Correlation analysis displaying the raw data for each of the Algebra 1, Biology,

Language Arts 10 and the Government EOC scores and the ACT scores

Algebra 1 EOC

Table 1:Correlation Study Free or Reduced Lunch and Algebra I EOC

N Mean r R² p-value Free or Reduced Lunch 179 37% Algebra I EOC 179 3.59 0.0984 0.97% 0.04736

Note significance = or < .25

After collecting the information from 179 F/R Lunch students and their Algebra 1

EOC scores, a correlation matrix was completed to test the null hypothesis to find if there

is a significant relationship between F/R Lunch students and their Algebra 1 EOC results.

The null hypothesis states that there is no significant relationship in student achievement

in Algebra 1 between students from higher socioeconomic status compared to students

from lower socioeconomic status. The data collected for F/R Lunch reveals the mean was

37%. The data collected for Algebra 1 EOC scores displays the mean was 3.59. The r

value, or correlation coefficient was 0.0984 and the R2,or practicality was 0.97% with the

p value as 0.04736. A fair degree of relation the r value must be above .39 therefore this

correlation coefficient of, 0.0984, shows that the relationship is weak. For a relationship

to be considered practical the practicality level must be higher than 10%; the practicality

reported in this finding is 0.97% indicating that this relationship is not practical. The p-

value, calculated at .04736, is lower than the Alpha level set at 0.25; consequently, there

is a significant relationship between F/R Lunch and the Algebra 1 EOC scores. After

compiling these relationship indicators, the null hypothesis will not be rejected. There is a

weak, not practical but significant relationship between F/R Lunch student population


and Algebra 1 EOC scores.

Table 2:Correlation Study Free or Reduced Lunch and Biology EOC

N Mean r R² p-value Free or Reduced Lunch 148 30% Biology EOC 148 3.81 0.1986 3.9% 0.00013


After collecting the information from 148 F/R Lunch students and their Biology

EOC scores, a correlation matrix was completed to test the null hypothesis to find if there

is a significant relationship between F/R Lunch students and their Biology EOC results.

The null hypothesis states that there is no significant relationship in student achievement

in Biology between students from higher socioeconomic status compared to students

from lower socioeconomic status. The data collected for F/R Lunch reveals the mean was

30%. The data collected for Biology EOC scores displays the mean was 3.81. The r

value, or correlation coefficient was 0.1986 and the R2,or practicality was 3.9% with the

p value as 0.00013. A fair degree of relation the r value must be above .39 therefore this

correlation coefficient of, 0.1986, shows that the relationship is weak. For a relationship

to be considered practical the practicality level must be higher than 10%; the practicality



is a significant relationship between F/R Lunch and the Biology EOC scores. After

compiling these relationship indicators, the null hypothesis will not be rejected. There is a

weak, not practical but significant relationship between F/R Lunch student population

and Biology EOC scores.


Table 3:Correlation Study Free or Reduced Lunch and Language Arts 10 EOC

N Mean r R² p-value Free or Reduced Lunch 171 35% Language Arts 10 EOC 171 3.55 0.1994 4.0% 0.00014


After collecting the information from 171 F/R Lunch students and their Language

Arts 10 EOC scores, a correlation matrix was completed to test the null hypothesis to find

if there is a significant relationship between F/R Lunch students and their Language Arts

10 EOC results. The null hypothesis states that there is no significant relationship in

student achievement in Language Arts 10 between students from higher socioeconomic

status compared to students from lower socioeconomic status. The data collected for F/R

Lunch reveals the mean was 35%. The data collected for Language Arts 10 EOC scores

displays the mean was 3.55. The r value, or correlation coefficient was 0.1994 and the

R2,or practicality was 4.0% with the p value as 0.00014. A fair degree of relation the r

value must be above .39 therefore this correlation coefficient of, 0.1994, shows that the

relationship is weak. For a relationship to be considered practical the practicality level

must be higher than 10%; the practicality reported in this finding is 4.0% indicating that

this relationship is not practical. The p-value, calculated at .00014, is lower than the

Alpha level set at 0.25; consequently, there is a significant relationship between F/R

Lunch and the Language Arts 10 EOC scores. After compiling these relationship

indicators, the null hypothesis will not be rejected. There is a weak, not practical but

significant relationship between F/R Lunch student population and Language Arts 10

EOC scores.


Table 4:Correlation Study Free or Reduced Lunch and Government EOC

N Mean r R² p-value Free or Reduced Lunch 205 42% Government EOC 205 3.38 0.1861 3.46% 0.00007


After collecting the information from 205 F/R Lunch students and their

Government EOC scores, a correlation matrix was completed to test the null hypothesis

to find if there is a significant relationship between F/R Lunch students and their

Government EOC results. The null hypothesis states that there is no significant

relationship in student achievement in Government between students from higher

socioeconomic status compared to students from lower socioeconomic status. The data

collected for F/R Lunch reveals the mean was 42%. The data collected for Government

EOC scores displays the mean was 3.38. The r value, or correlation coefficient was

0.1861 and the R2,or practicality was 3.46% with the p value as 0.00007. A fair degree

of relation the r value must be above .39 therefore this correlation coefficient of, 0.1861,

shows that the relationship is weak. For a relationship to be considered practical the

practicality level must be higher than 10%; the practicality reported in this finding is

3.46% indicating that this relationship is not practical. The p-value, calculated at .00007,

is lower than the Alpha level set at 0.25; consequently, there is a significant relationship

between F/R Lunch and the Government EOC scores. After compiling these relationship

indicators, the null hypothesis will not be rejected. There is a weak, not practical but

significant relationship between F/R Lunch student population and Government EOC

scores.


Table 1:Correlation Study Free or Reduced Lunch and ACT

N Mean r R² p-value Free or Reduced Lunch 35 7.2% ACT 35 20.83 0.2621 6.87% 0.00368


After collecting the information from 35 F/R Lunch students and their ACT

scores, a correlation matrix was completed to test the null hypothesis to find if there is a

significant relationship between F/R Lunch students and their ACT results. The null

hypothesis states that there is no significant relationship in student achievement in ACT

between students from higher socioeconomic status compared to students from lower

socioeconomic status. The data collected for F/R Lunch reveals the mean was 7.2%. The

data collected for ACT scores displays the mean was 20.83. The r value, or correlation

coefficient was 0.2621 and the R2,or practicality was 6.87% with the p value as 0.00368.

A fair degree of relation the r value must be above .39 therefore this correlation

coefficient of, 0.2621, shows that the relationship is weak. For a relationship to be

considered practical the practicality level must be higher than 10%; the practicality



is a significant relationship between F/R Lunch and the ACT scores. After compiling

these relationship indicators, the null hypothesis will not be rejected. There is a weak, not

practical but significant relationship between F/R Lunch student population and ACT

scores.


Conclusions and Recommendations

Theresultsofthisstudyindicatedthatthereisasignificantrelationshipin

theAlgebra1,Biology,LanguageArts10andGovernmentEOCandACTtestscores

betweennonF/RLunchandF/RLunchstudentpopulationsforthe2013‐2014

schoolyearatthehighschoolstudied.Althoughtheremaybeafewindividual

studentscoresimilaritiestheaverageofthetwostudentpopulationsdisplayeda

significantdifference.TheF/RLunchstudentpopulationsscoredconsiderably

lowerontheseteststhanthenonF/RLunchstudentpopulation.Theoverall

analysisofthedataledtoarejectionofthenullhypothesis.

The purpose of this study was to investigate if socioeconomic status has a strong

effect on academic performance on one content area over another. The scores were higher

in the content areas of Algebra 1 and Biology and lower in the content areas of Language

Arts 10 and Government. One reason for this result may be the fact that both Language

Arts 10 and Government involve challenging reading comprehension that students from

low SES may struggle. Algebra 1 and Biology involve more concepts, procedures and big

ideas which students from a low SES background may have a better understanding. Both

math and science can also involve a more “hands on” approach, which may lead to a

better understanding.

A current teaching strategy involves the use of close reading and teaches students

how to analyze and breakdown challenging texts. Developing useful and purposeful

reading strategies needs to be a part of every teacher’s daily instruction. Teachers need to

expose students to a higher text complexity in order for students to grow and be

successful when faced with a more rigorous text, possibly on an EOC or ACT test.


Another positive teaching strategy involves the use of Common Formative

Assessments (CFA). This is the use of a simple check for understanding procedures for

the students. If this type of assessment is used often a teacher may be able to alter any

misconceptions and also be able to change instruction in order to meet the needs of all

students. Teachers may also use the strategy of pre and post testing, which is often the

same test. If a pretest is given to assess the major topics of a unit, the teacher may learn

of any background knowledge students may already possess. The use of the post test will

check for growth in knowledge rather than the data a final summative assessment will

provide. Sometimes a small positive gain in knowledge is as important as the final test

result.

Theresearchinvestigatedtheeffectsofsocioeconomicstatusonstudenttest

scoresbecausetheeffectsofpovertymayhaveanadverseeffectonstudent’slives.

Theseadverseeffectsmaylimitfutureopportunitiesforthesestudentswhenthey

havesomanyobstaclesintheirlives.Ibelievethateverystudentshouldhavean

equalopportunitytofindsuccessinschoolandlife.Whencomparingtheconceptual

underpinningtotheresearchfindingsthereisasignificantrelationshipbetween

SESandstudenttestresults.Thereisplentyofevidencethatstudentsinpoverty

findsuccesswhengiventheopportunitybutstudentsalsomayfallbythewayside

whenopportunityslipsbecausetheydonotknoworunderstandhowtofind

success.Unfortunatelythelaterhappensmuchmoreoften.Thistopicisofpersonal

interestbecausethestudentswhodofindsuccesswhenstartinginpovertyarethe

greateststoriesandthestudentsthatarerememberedthemostoften.Educators

needtopositivelyinfluenceallstudentsbutunderstandthatstudentsthatcome


fromlowersocioeconomicstatusmayhaveadditionalneedsthatallpeoplethat

touchtheirlivesneedtobemadeaware.

The data in the Review of Literature comparing SAT scores in critical reading and

mathematics and household income. This data is related to the data in my study. The

choice to use this graph to display critical reading and mathematics scores is important

because of the strong correlation these two topics have to the new Common Core State

Standards. If these new CCSS are going to be used in the future of our instruction we

need to look into why there is such a difference between students in poverty and those

that are not? And then how can we fix the current problem of assisting students in

poverty score better on these standardized tests.

The analysis of the raw data and investigation of student scores there are some

low SES students that perform well on these tests. For instance, there were a few low

SES students that scored 28 and 30 on the ACT and had a higher minimum score than the

high SES students in the ACT. In each of the EOC categories the low SES students

scored a maximum of 5 and a minimum of 2, mirroring the high SES student scores. The

difference in Algebra 1 EOC scores was only .16. This set of data proves that there are

extremely competitive and capable students within the low SES student population, the

problem is that there are only a few of these students. Students who grow up in poverty

are exposed to stresses and values that are different than students who do not grow up in

poverty. Because of these stresses students who grow up in poverty have a different set of

values, habits and behaviors. “If children are under stress, the ways they respond are

remarkably similar,” she says. “They get sad, distracted, aggressive, and tune out.” That

is what she saw in the high-poverty schools she visited. Chaos reigned. The most


disruptive children dominated the schools. Teachers didn’t have control of their

classrooms — in part because nothing in their training had taught them how to deal with

traumatized children. Too many students had no model of what school was supposed to

mean. “These were schools that were not ready to be schools.”

(Nocera, 2012, July 27)

The fantasy of removing poverty and living in a world of equality is just that, a

dream. The community, family and school can assist students in achieving more in their

lives. After all isn’t that why we are all in the field of education. Low SES students can

perform well and achieve their dreams but it may have involved athletics. These students

were great athletes who scored well enough to get into college and then they blossomed

into mature adults and took advantage of their new success. These students are few and

far between. There are also many low SES students that fail because they did not

understand how to take advantage of their opportunity. As a community we need to

remove students from their generational poverty and provide them an opportunity to

succeed. “Two things that help one move out of poverty are education and relationships.”

(Payne, 2005 p. 3)

As an educational community we can provide each of these concepts to all

students. Also; “Four reasons one leaves poverty are: It’s too painful to stay, a vision or

goal, a key relationship, or a special talent or skill.” (Payne, R 2005 p.3) Building

relationships with students is one of the most important responsibilities of education.

Regardless of SES, each student deserves a role model and an opportunity to dream and

achieve and if this assists students to move forward in SES then awesome.


As an educational community it is our job to prepare all students to compete in a

global world economy. We are preparing students for jobs that may not yet exist, that is

why all students should be able to critically think and problem solve. We need to develop

more specific professional development to achieve this. Professional development should

educate teachers in more teaching strategies to be able to reach all students. The concept

of differentiated instruction is a good start of assisting students with lower abilities.

Educators need to build a stronger support system in the earlier grades so that low SES

students have the chance to have their brains reflect optimistic qualities and give them the

opportunity to experience positivity outside of their homes. Schools must do a better job

of involving the parental support system. Students spend relatively equal time at school

and at home. It would do no good to only have quality education only at school and then

lose all of the work once they go home. Families need to support, grow and be involved

with their children and students. Parents need to be quality teachers as well just within the

home.

There needs to be more research done in the area of instructional strategies to

assist students in need. How do we develop better methods to reach low SES students?

The gap between performance of low SES students and high SES students needs to be

minimized. All students regardless of status should have the chance to do whatever they

wish and it is our job that they receive that opportunity.


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