Running Head: economic Status in Relation to Student

Running Head: Socio‐economic Status in Relation to Student Achievement 1

RUNNING HEAD: Socio-economic Status in Relation to Student Achievement

DIFFERENCES IN SOCIO-ECONOMIC STATUS AREAS AND STUDENT

ACHIEVEMENT ON THE MATHEMATICS END OF COURSE EXAM

By

Jacob Dawson

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

61-683 Research Paper

Spring 2013

July 8, 2013


Abstract

This study was completed to determine if there was a significant difference in

student achievement scores on the End of Course Exam for Algebra 1 between schools

with a high free or reduced count compared to schools with a low free or reduced count.

Understanding students from high free or reduced areas is crucial when working with

these students. Understanding the importance of developing and maintaining

relationships proves to be important as well. Abraham Maslow’s hierarchy of needs

proves to be evident when working with students. If a student does not have their

physiological needs met or a sense of security, then they will not be able to perform at

the same rate as their peers who have all of these basic needs met. There were 50

random schools selected for this study. After the review of data, analyzing the t-test,

researching the study, and finding conclusions; it is evident that there is a discrepancy

between student achievement for schools with a high free or reduced rate compared to

those schools with a low free or reduced rate. Therefore, studies have proven that

students from a lower free or reduced area perform at a higher rate on standardized

assessments as opposed to students who come from a higher free or reduced area.


Introduction

Background, Issues and Concerns For a while now, there has been a growing phenomenon in school districts.

While the economy tends to fluctuate, there has been a growing rate of students who

are categorized as free or reduced lunch. There has been a trend of growth through the

past few years as more people do not have jobs. To combat this, there have been

major initiatives and incentives for teachers who work in districts with high free or

reduced percentages. For example, if a teacher works in a school district that has a

high free or reduced percentage then they get their student loans from the federal

government forgiven. Furthermore, there have been initiatives such as at-risk programs

and Response To Intervention programs implemented.

There has been an assumption that schools with a higher free or reduced

percentage tend to not achieve on end of course assessments as well as their peers in

schools with a lower free or reduced percentage. The study is to determine whether or

not a consistency exists between higher free or reduced percentage and lack of

achievement compared to same grade peers in a school with a lower free or reduced

percentage.

Practice under Investigation

The practice under this investigation will be looking at End Of Course examination

scores. Research will be done to determine whether or not there is a significant

difference between schools with a high free or reduced percentage compared to

schools with a low free or reduced percentage. This study will be looking at data


compiled from the Department of Elementary and Secondary Education (DESE). If

such a discrepancy does exist, then this study will provide an awareness of an issue in

student performance and schools can brainstorm and research techniques and

strategies to reach students in high free or reduced areas to enhance their

achievement.

School policy to be informed by study.

Every school district regardless of free or reduced percentages must meet Adequate

Yearly Progress. One of the elements for a district to meet Adequate Yearly Progress

in Missouri is through student performance on the Missouri Assessment Programs and

End Of Course assessments. If there is a significant difference between schools with

higher free or reduced percentages and schools with lower free or reduced

percentages, then school leaders in higher free or reduced percentages can take the

information and research different strategies and techniques to increase student

performance in their districts.

Conceptual underpinning.

There is a tendency to believe that learning is almost as of an assembly line. Educators

give students information, evaluate, and move them along to the next element.

However, Maslow proves this belief system inaccurate. According to Maslow, there is a

hierarchy of needs that need to be achieved prior to learning taking place. The levels

are physiological, safety, love/belonging, esteem, and self-actualization (Maslow, 1954).

Achievement does not take part until physiological, safety, love/belonging are met.

Students in low free or reduced districts tend to come from families who provide

physiological, safety, and love/belonging needs. Therefore, these students can focus


on learning. On the other hand, students who come from a higher free or reduced area

tend to not necessarily have those three levels met. For example, a child living in a

dangerous environment might fear for their safety or might be more worried about

feeding themselves before practicing their mathematics. While just down the road, a

child who is the same age as the previously mentioned child lives in a nice sub-division

were a loving family provides all the basic levels of needs and more focus for the child is

on the same mathematics that the other child is struggling to master. Depending on the

area of where a student is part of, different programs need to be implemented to allow

an equal playing field for achievement to take place.

Statement of the Problem

If there is a significant difference with student achievement between schools with higher

free or reduced lunch percentages and schools with lower free or reduced lunch

percentages, then school leaders of higher free or reduced lunch percentages need to

brainstorm and research techniques and strategies to give their students the

opportunities to achieve at the same level of same grade peers in schools with a lower

free or reduced percentage. Furthermore, building leaders need to give their teachers

the proper tools to educate students in higher free or reduced buildings a chance to

achieve at higher levels and potentially close the gap between the higher free and

reduced and lower free and reduced.

Purpose of the Study

If there is a significant difference with student achievement between schools with higher

social-economic status compared to schools with lower social-economic status, then


that information will be better used for schools in lower social-economic areas. Schools

in lower social-economic areas will be able to better identify the issue that is within their

district and be able to start brainstorming ways that teachers in these districts can reach

these students to maximize achievement.

Research Question

R.Q. 1--Is there a significant difference with student achievement between schools with

higher free or reduced lunch percentages compared to schools with lower free or

reduced lunch percentages?

Null Hypothesis

There is no significant difference with student achievement between schools with higher

social-economic status when compared to schools with lower social-economic status.

Anticipated Benefits of the Study

If there is a significant difference then districts in lower-social economic areas will be

able to identify the underlying issue within their districts and be able to invest in the

appropriate resources and training to try and bridge the gap. If there is no significant

difference then teachers in districts can eliminate this reasoning of poor student

achievement and research other possible issues.

Definition of Terms

DESE-Department of Elementary and Secondary Education


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

year in the subjects: Algebra I, Government, Biology, Geometry, English I, English II,

and Geometry

AYP-Adequate Yearly Progress; The No Child Left Behind Act (NCLB) of 2001 requires

all schools, districts and states to show that students are making Adequate Yearly

Progress.

IEP-Individualized Educational Program; an educational plan developed for students

with disabilities that includes a present level of performance and annual goals that are

mandated to be worked towards.

MAP-Missouri Assessment Program

Summary

A study was conducted to see if there was a significant difference in achievement

between schools with a high free or reduced lunch rate compared to schools with a low

free or reduced lunch rate. If the t-test does indicate a consistent discrepancy in

achievement between schools with a high free or reduced rate compared to ones with a

low free or reduced rate, then it is appropriate for districts to allocate resources to

educate their teachers on ways to reach these high needs students and in turn show

improvements on assessments. It is consistent that there is a difference in needs for

schools in high free or reduced areas compared to ones in low free or reduced areas.


After this study is concluded, if necessary, districts will be able to look into resources to

improve student achievement in these high free or reduced areas through teacher

training.


Review of Literature

No Child Left Behind now requires all students score proficient or advanced in

mathematics and communication arts by 2014. This was amended from the first law

where proficiency would be mastered in 2008. Other indicators that go into this formula

to ensure schools are meeting AYP are dropout rate and graduation rate. According to

the information from the state of Missouri regarding proficiency, there was no

modification or by-laws for students in low socio-economic areas. The law indicates

that every student is to score proficient or advanced by 2013-2014. (Missouri Growth

Model Application and Information, 2008)

However, when looking at assessment scores, it shows that schools with a

higher free or reduced number continually score less than schools with lower free or

reduced numbers. The question is why this is the case? As we look at research from

the article CONNECTING STUDENTS TO SCHOOLS TO SUPPORT THEIR

EMOTIONAL WELLBEING AND ACADEMIC SUCCESS , the authors discuss the

parallel between Maslow’s Hierarchy of Needs and student performance in high free or

reduced areas. One of the baselines to the hierarchy is a sense of safety and

immediate needs such as food and shelter. Schools that don’t allocate resources in

these areas have a tendency of seeing these students not perform as well on state

assessments. The reasoning behind this is the fact that these students come into class

hungry because they have not eaten breakfast. Or they may not be adequately

prepared because they spent all night watching their baby sister as opposed to studying

for a math test ( Sulkowski,Demaray,&Lazarus 2012).


However, according to the authors, there is a sign of hope for this epidemic. The

authors give recommendations and resources on how to start focus groups and

universal connections to ensure that each student has the ability and support to have a

connection with the school in which will turn into reaching their potential on achievement

assessments. It is imperative to understand that just presenting the information in a

variety of ways may not be enough to help these students. Giving them support and a

shoulder to lean on will show better results. (Sulkowski, 2012)

In another article that was researched, THE RELATIONSHIP BETWEEN SOCIO-

ECONOMIC STATUS AND LEARNING ACHIEVEMENT OF STUDENTS AT

SECONDARY LEVEL the authors researched different groups in a social class system.

First, the author pointed out the understanding of a definition for social class and what

categories would be reviewed to entail this information. The different categories were:

income, level of education, political prestige, and occupational prestige. (Akhtar & Khan

Niazi, 2011) Once the research was conducted then the researchers broke the

population into five groups. They were: upper, upper middle, middle, middle low, and

low. (Akhtar & Khan Niazi, 2011)

After the information was in the five subgroups, a study was conducted to see

how well each subgroup did in relation to student achievement. At the conclusion of the

study, it was concluded that students that come from families with a higher socio-

economic status tend to have higher levels of achievement than students who come

from lower socio-economic families. The research was overwhelming that there was a

significant difference of student achievement between students in a high socio-


economic environment to those who were in a low socio-economic environment. (Akhtar

& Khan Niazi, 2011)

Another researcher did a study regarding student achievement on mathematics

with two African American students of the same age and gender. The one difference

was that one came from a prosperous area and one came from a lower income area.

Rugutt (2010) concluded, with a lot of data to conclude his findings, that the student

from the more prosperous area did significantly better on achievement than the other

student.

Rugutt (2010) concluded from his findings that it is imperative for teachers to

understand where their students come from. Students from low income home tend to

not have the prerequisite abilities for higher level math than that of their peers.

Teachers even more than ever need to explore their students’ backgrounds and utilize

differentiated instruction to ensure that each one of their students has the chance to

excel on their assessment scores.

Jensen (2009) did a study regarding behavior patterns from people in a low

socio-economic area and how they react in scholastic situations compared to their

peers. Jensen notes, 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 (2009) gives a list of what is conditioned in a child’s brain and what can

be taught. She states that giving students mutual respect is the key ingredient to


fostering relationships with students from low socio-economic areas. (Jensen, 2009)

Teachers tend to believe that these students have behavior deficiencies; however,

these actions come from what is programmed in their brain before the age of four years.

Ruby Payne’s work is consistent with Jensen’s interpretations. Payne discusses

the rules of generational poverty in relation to the middle and upper classes. The

interpretation that best sums up her work is found under her hidden messages. That is,

for generational poverty, the driving force for making decisions is based on survival,

maintaining relationships, and entertainment. For a person in the middle class, the

driving forces for decision making are for work and educational achievement. (Payne,

2005).

Furthermore, Payne discusses behaviors that would inhibit learning, such as a

predisposition that it is okay for people to engage in fighting, arguing with an authority

figure, express angry, vulgar or inappropriate responses, and touch other people.

(Payne, 2005).

It is imperative for teachers to understand their constituents and offer alternative

ways to discipline students from low socio-economic areas because altering a behavior

takes more than one day, especially when the behavior has been developed through

circumstance. (Payne, 2005)

Another researcher looked at the comparison of dropout rate connected to the

area’s socio-economic status. The research then looked at what trends can be

manifested to decrease this trend of high dropout rate. (Bergeron, Chouinard, &

Janosz, 2011) The authors’ note the underpinning of a reduced dropout rate is a

positive student-teacher relationship. (Bergeron, Chouinard, & Janosz, 2011) The


authors believe the best way to combat this dilemma is to have teachers trained on how

to develop and maintain strong relationships with these students. This could be some

of these students only opportunity to develop a strong, professional relationship with a

teacher. Therefore, this area must be viewed as an opportunity and not a hindrance.

(Bergeron, Chouinard, & Janosz, 2011)

The final bit of information presented to show how districts are combatting a low

socio-economic status in terms of achievement is presented by Edwards, Smith, and

Todd. Their study took place at the Mooresville Graded School District in North

Carolina which was one of the lowest performing districts in the state. The main reason

for the district’s short comings was a high population of low socio-economic status.

(Edwards, Smith, & Todd, 2012) The district and community decided to provide every

student in the district with a laptop. The thought was to level the playing field for

disadvantaged students and students that come from a more prosperous home.

(Edwards, Smith, & Todd, 2012)

Their findings showed a 21% gain in assessment scores. Furthermore, the

demands of having that many laptops in a district provided students with a class that did

maintenance and other general housekeeping chores to the computers. (Edwards,

Smith, & Todd, Go Digital, 2012) It was noted as well that for the majority of these

students, these laptops were the first piece of technology in their families’ homes.

(Edwards, Smith, & Todd, Go Digital, 2012)


Research Methods

Research Design

A study was conducted to see if there is an achievement gap between students

who come from a low free or reduced lunch district to those who come from a high free

or reduced district on the End Of Course Algebra 1. The independent variable being

assessed was the free or reduced group and the dependent variable being assessed

was End Of Course Algebra 1 exams. If there is a significant difference found in

achievement from schools with a low free or reduced number compared to schools with

a high free or reduced number, teachers should be provided the proper training and

professional development to learn how to better reach these at-risk students and close

the achievement gap.

Study Group Description

Students from fifty randomly selected school districts in the state of Missouri who

have reported the End Of Course test scores from 2011-2012, disaggregated by a free

or reduced lunch percentage, were chosen as the group evaluated. All fifty schools

were broken up into two groups with one group being with a low free or reduced lunch

count and one with a high free or reduced lunch count.

Data Collection and Instrumentation

Data from DESE was collected to identify the scores of students from high free or

reduced districts and low free or reduced districts on the Algebra 1 End Of Course exam

from the 2010-2011 and 2011-2012 school years.


Statistical Analysis Methods A t-test was conducted to find if there is a significant difference in Algebra 1 End

Of Course exam scores based on socio-economic status. The source was broken into

two categories: schools with a high free or reduced lunch number and schools with a

low free or reduced lunch number. The mean, mean D, t-test, df, and p-value were

concluded from this test. The Alpha level was set at 0.25 to test the null hypothesis:

There is no significant difference in test scores of students from a high socio-economic

area compared to ones from a low socio-economic area on the Algebra 1 End of Course

exam.


Findings

A t-test was conducted to determine whether there was a difference in

performance on the 2010-2011 and 2011-2012 Algebra 1 EOC test based on a

school’s free or reduced rate. The following tables, graphs, and charts will depict the

organized findings based on raw data found on the Missouri DESE website during the

year 2013.

Chart 1

Test Analysis Results for 2010-2011 Proficient/Advanced Scores on Algebra 1 EOC

Source Mean Mean D t-Test df p-value

Low F/R Rates (25) 62.68

High F/R Rates (25) 55.56 7.12 2.06 48 0.05

Note: Significant when p<=0.25

Fifty randomly selected schools from across the state of Missouri were selected

to participate in this test. The reasoning for this test was to see if there is a significant

difference between End Of Course Algebra 1 scores based upon school’s socio-

economic status. Therefore, data from DESE report cards was used in determining

what the random school free or reduced rate was and then categorized into two groups.

Then, the researcher pulled the percentage of test scores who scored in proficient or


advanced on the Algebra 1 EOC exam for the 2010-2011 school year. The mean of the

schools with a low number of free or reduced rates was 62.68 and the mean for the

school’s with a high free or reduced rate is 55.56. The difference of the mean (Mean D)

between the two groups was 7.12. The t-test was 2.06 and df was 48. The null

hypothesis states there is no significant difference between End Of Course Algebra 1

scores based upon a school’s free or reduced rate. During the t-test, the p-value was

.05. Therefore, with the alpha level set at .25 and the p-value of the t-test being less

than the alpha level, the null is rejected and poverty does indeed have a significant

influence on a districts assessment scores.

Chart 2

The mean percentage for students scoring proficient or advanced in Algebra 1 in high

free or reduced areas was 54% while students from lower free or reduced areas taking

the same assessment was 64%. There was a ten percent difference in scores from the

two categories, which is significant.

EOC Algebra 1 Scores of Proficient/Advanced

Low F/R Rates

High F/R Rates


Chart 3

2010-2011 EOC Algebra 1 Scores

The four categories that students are categorized in are below basic, basic, proficient,

and advanced. The bottom two of these categories which does not meet the state

standards are below basic and basic. The top two of these categories are proficient and

advanced. When looking at the below basic/basic category, it notes that students in a

higher free or reduced rate had more students scoring in this category than students

from lower free or reduced areas. Looking at the proficient and advanced category, the

students in a higher free or reduced area scored an average of 54% while students from

lower free or reduced areas averaged a score of 64%. This states that there is a

significant difference between averages of scores from lower free or reduced areas

compared to averages of scores from higher free or reduced areas.

0%

10%

20%

30%

40%

50%

60%

70%

Below Basic/Basic Proficient/Advanced

High F/R

Low F/R


Chart 4

Test Analysis Results for 2011-2012 Proficient/Advanced Scores on Algebra 1 EOC

Source Mean Mean D t-Test df p-value

Low F/R Rates (25) 76.41

High F/R Rates (25) 63.32 12.96 3.80 48 4.13 E-4

Note: Significant when p<=0.25

Fifty randomly selected schools from across the state of Missouri were selected to

participate in this test. The reasoning for this test was to see if there is a significant

difference between End Of Course Algebra 1 scores based upon school’s socio-

economic status. Therefore, data from DESE report cards was used in determining

what the random school free or reduced rate was and then categorized into two groups.

Then, the researcher pulled the percentage of test scores who scored in proficient or

advanced on the Algebra 1 End Of Course exam for the 2011-2012 school year. The

mean of the school’s with a low number of free or reduced rates was 76.41 and the

mean for the schools with a high free or reduced rate is 63.32. The difference of the

mean (Mean D) between the two groups was 12.96. The t-test was 3.80 and df was 48.

The null hypothesis states there is no significant difference between End Of Course

Algebra 1 scores based upon a schools free or reduced rate. During the t-test, the p-

value was 4.31 E-4. Therefore, with the alpha level set at .25 and the p-value of the t-

test being less than the alpha level, the null is rejected and poverty does indeed have a

significant influence on a district’s assessment scores.


Chart 5

The mean percentage for students scoring proficient or advanced in Algebra 1 in high

free or reduced areas was 51% while students from lower free or reduced areas taking

the same assessment was 65%. There was a fourteen percent difference in scores

from the two categories which is significant.

2011‐2012 EOC Algebra 1 Proficient/Advanced Scores

Low F/R

High F/R


Chart 6

2011-2012 EOC Algebra 1 Scores

The four categories that students are categorized in are below basic, basic, proficient,

and advanced. The bottom two of these categories, which do not meet the state

standards, are below basic and basic. The top two of these categories are proficient

and advanced. When looking at the below basic/basic category, it notes that students

in a higher free or reduced rate had more students scoring in this category than

students from lower free or reduced areas. Looking at the proficient and advanced

category, the students in a higher free or reduced area scored an average of 51% while

students from lower free or reduced areas averaged a score of 65%. This states that

there is a significant difference between averages of scores from lower free or reduced

areas compared to averages of scores from higher free or reduced areas.

0%

10%

20%

30%

40%

50%

60%

70%

Below Basic/Basic Proficient/Advanced

Low F/R

High F/R


All of the findings in figures 1-6 answer the research question “Is there a

significant difference with student achievement between schools with higher free or

reduced lunch percentages compared to schools with lower free or reduced lunch

percentages?” Figures 1-3 dealt with performance during the 2010-2011 school year

and figures 4-6 dealt with performance during the 2011-2012 school year. The

assessment that was researched was the Algebra 1 End of Course Exam. All findings

from the data review answered the research question stating there is a significant

difference with student achievement between schools with higher free or reduced lunch

percentages compared to schools with lower free or reduced lunch percentages. There

was an increase in performance for schools with lower free or reduced lunch from 2010-

2011 to 2011-2012 whereas no gains were made for the schools in a higher free or

reduced area.


Conclusions and Recommendations

After concluding the study and research, it has been determined that there is a

substantive discrepancy between student performance on the Algebra 1 End Of Course

assessment for schools with a high free or reduced count compared to those of a low

free or reduced count. A t-test for the 2010-2011 reporting year indicated a p-value of

.05 and the t-test for the 2011-2012 reporting year indicated a p-value of 4.13E-4. Both

p-values were significantly below the alpha level of .25. Therefore, this rejects the null

hypothesis, and determines a significant difference in performance on the Algebra 1

End of Course Exam for schools in a high free or reduced area compared to those in a

low free or reduced area. This indicates that students who come from an area with a

lower free or reduced lunch rate, there tends to be a higher gain of achievement then

the students who come from an area with a higher free or reduced lunch rate.

The conceptual underpinning of theorist Abraham Maslow was supported

through the research and the study. The basis of Maslow’s Hierarchy of Needs is

physiological and then safety. Without these intricate parts of a child’s development,

they will not be able to reach self-actualization. The one most important element for

student success and failure is the teacher and what type of relationship is being

developed with students. (Bergeron, Chouinard, & Janosz, 2011) This indicates that a

sense of security within schools and authority figures can create a positive experience

with this population of students. Teachers must be adequately trained on how to

develop and maintain these unique relationships with students that come from a high

free or reduced setting.


It would be beneficial to continue this study with new data to ensure a trend. The

End of Course assessment results for the 2012-2013 reporting year are in and it would

be beneficial to see how these fifty random schools did. Also, it would be beneficial to

allocate some of the money in professional development to educate teachers on how to

understand the unique needs of these students. Then, the data from the 2013-2014

reporting year could be analyzed and see if these recommendations were beneficial or

not useful.

Another idea that would benefit this study is to select other random schools aside

from the ones previously selected in the state. This could give researchers more

information on a broader surface to see if there are consistencies. Finally, researchers

could select random schools from across the United States. This could dictate whether

or not this is a dilemma solely in the state of Missouri or across the country.

After concluding this study, it is proven that it is imperative for teachers to receive

training in how to work with students in a high free or reduced setting. The data has

shown that these numbers are on the rise. With a weaker economy and unemployment

on the rise, it is evident this problem will not go away. Therefore, districts must be held

accountable in educating their teachers in Ruby Payne’s work to ensure that these

students have the best opportunity possible. One thing is that these students cannot

control their environment; educators must accommodate them in the school setting to

allow them the opportunity to achieve at their potential, not their environmental potential.


References

Akhtar, Z., & Khan Niazi, H. (2011). THE RELATIONSHIP BETWEEN SOCIO‐ECONOMIC STATUS AND

LEARNING ACHIEVEMENT OF STUDENTS AT SECONDARY LEVEL. INTERNATIONAL JOURNAL Of

ACADEMIC RESEARCH, 956‐962.

Bergeron, J., Chouinard, R., & Janosz, M. (2011). The Impact of Teacher‐Student Relationships and

Achievement Motivation's Intentions to Dropout According to Socio‐economic Status. US‐China

Education Review B 2(1548‐6613), 273‐279.

Data, N. (n.d.). Eleven Facts About Poverty in America. Retrieved from Do Something :

http://www.dosomething.org/tipsandtools/11‐facts‐about‐education‐and‐poverty‐america

Edwards, M., Smith, S., & Todd, W. (2012, September/October). Go Digital. Learning and Leading with

Technology, pp. 12‐15.

Jensen, E. (2009). How Poverty Affects Behavior. Retrieved from ASCD Lead Teach Learn:

http://www.ascd.org/publications/books/109074/chapters/how‐poverty‐affects‐behavior‐and‐

academic‐performance.aspx

Payne, R. (2005). Understanding and Working with Students and Adults from Poverty. Poverty Series, 1‐

7.

Rugutt, J. K.‐A. (2010). Mathematics Learning Patterns Across Two Groups of African American Students:

A Multilevel Approach. International Journal of Learning, 17, 353‐371.


Sulkowski, M. L., Demaray, M. K., & Lazarus, P. J. (2012, May). Connecting Students to Schools to

Support Their Emotional Wellbeing and Academic Success. Communique, 40(7), 1; 20‐22.

Missouri Growth Model Application and Information. (2008, February 15). Retrieved from ED.gov:

http://www2.ed.gov/admins/lead/account/growthmodel/mo/index.html

District Report Cards. Retrieved from:

http://mcds.dese.mo.gov/guidedinquiry/School%20Report%20Card/District%20Report%20Card.

aspx

Documents

Running Head: economic Status in Relation to Student