Running Head: Free and Reduced Lunch STATE TEST SCORES … · 2014-09-02 · Free and Reduced Lunch...
Transcript of Running Head: Free and Reduced Lunch STATE TEST SCORES … · 2014-09-02 · Free and Reduced Lunch...
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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
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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.
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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
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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.”
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(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?
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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.
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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.
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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
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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)
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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
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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
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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:
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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
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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.
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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.
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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.
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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
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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
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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.
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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
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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.
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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
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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
Note significance = or < .25
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
reported in this finding is 3.9% indicating that this relationship is not practical. The p-
value, calculated at .00013, is lower than the Alpha level set at 0.25; consequently, there
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.
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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
Note significance = or < .25
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.
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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
Note significance = or < .25
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.
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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
Note significance = or < .25
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
reported in this finding is 6.87% indicating that this relationship is not practical. The p-
value, calculated at .00368, is lower than the Alpha level set at 0.25; consequently, there
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.
FreeandReducedLunch 27
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.
FreeandReducedLunch 28
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
FreeandReducedLunch 29
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
FreeandReducedLunch 30
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.
FreeandReducedLunch 31
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.
FreeandReducedLunch 32
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