High School Dropout Rates in the Riverside Unified School District Chelsea Katsch, Sloan Sims, Tyler Spano, & Mary Krome Professor Joanna Bieri MATH 160: Math for Social Justice May 24, 2011

High School Dropout Rates in the Riverside Unified School District Abstract There are five public comprehensive high schools in Riverside City that are managed by the Riverside Unified School District (RUSD). For the purpose of this report, we have not included the publically run continuation high schools because they cater to alternative students, or any private schools. This report is an examination of the dropout rates from school year 20082009 within these separate high schools. We begin by offering a short background on the five schools, North, Poly, Arlington, Ramona, and King High Schools. The following sections focus on possible correlations to the dropout rates of students. We begin with a discussion of the relationship between the schools’ discipline and suspension rates and their dropout rates. The next chapter offers a view into the correlation between the economic background of students and their dropout rates. Finally, we compare the ethnicities of the students who drop out of high school with those of their teachers.

Introduction Perhaps the most important term in the entirety of this report is “high school dropout,” or just “dropout.” For a technical definition of “dropout,” see the Mathematical Introduction in this report. In simple terms, a “dropout” is someone who doesn’t finish high school. There are three key reasons why preventing high school students from dropping out is important. Current research points to several disturbing trends associated with high school dropouts. First, there is a correlation between arrest rates and high school dropouts. According to a report conducted in 2009 by the Center for Labor Market Studies at Northeastern University, about 1 in every 10 high school dropouts is currently in jail or juvenile detention. 1 High school dropouts are also costly to society, as explained in detail in a separate report co-authored by professors from Columbia University, City University, and Princeton University. Their report from 2007 finds that if someone graduates high school instead of dropping out, there is a net economic benefit of $127,000 per student, which is 2.5 times greater than the cost of providing the governmental aid and resources that high school dropouts traditionally require. 2 As the report summarizes, “…the costs to the nation of failing to ensure high school graduation for all America’s children are substantial. Educational investments to raise the high school graduation rate appear to be doubly beneficial: the quest for greater equity for all young adults would also produce greater efficiency in the use of public resources.” Lastly, there is a clear disadvantage to dropping out of high school in a society where the level of education is often indicative of amount of income. In general, a high school diploma allows individuals more opportunities in life. 1 To read the full report, titled “The Consequences of Dropping out of High School”, log onto http://www.clms.neu.edu/publication/documents/The_Consequences_of_Dropping_Out_of_High_School.pdf 2 It’s worth noting how the authors reach this conclusion. To quote their publication, “First, we identify five leading interventions that have been shown to raise high school graduation rates; and we calculate their costs and their effectiveness. Second, we add up the lifetime public benefits of high school graduation. These include higher tax revenues as well as lower government spending on health, crime, and welfare. (We do not include private benefits such as higher earnings). Next, we compare the costs of the interventions to the public benefits.” A full version of their report can be read online at http://www.cbcse.org/media/download_gallery/Leeds_Report_Final_Jan2007.pdf

The intention of this report is to add to the growing amount of research about the dropout rates in the United States. Specifically, we look for potential causes of dropout rates in public high schools in Riverside, California.

Background John W. North High School was started in 1964 and named after the founder of Riverside. The school offers the International Baccalaureate Program for its students, as well as advanced placement classes, AVID (a college preparatory course), and three California Partnership Academies (Education and Human Services Academy, Global Information and Technology Academy, and the Law and Protective Services Academy.) During the 2008-2009 school year, there were 2,512 students attending North High School. Ninth grade was the largest grade in North, with 774 students. The 10th grade had 614 students in it, and 11th grade was the smallest, with 525 students. There were 599 seniors at North High School. Polytechnical High School is the oldest high school in Riverside, having been founded in 1887. The school offers the AVID program to its students, as well as honors courses and advanced placement classes. Poly also has a “Newcomers Academy” that offers intensive language orientated classes for students who are new to the country and do not speak English. In 2008-2009, Poly’s student body was comprised of 2,837 students, with 769 students in the 9 th grade, 774 in the 10th grade, 673 students in 11th grade, and a senior class of 621 students. Arlington was founded in 1973. Some of the notable opportunities that the school offers for its students include Air Force Junior Reserve Officer Training Corps, AVID, and a program called Corporate Enterprise Opportunities (C.E.O.) Academy. They also are part of four separate community partnerships: the Regional Occupational Program, the Riverside Educational Enrichment Program, Riverside Against Drugs, and Keep Riverside Clean and Beautiful. There is a total of 2,218 students at Arlington High School. 780 of these students were in the 9 th grade, 553 were in the 10th grade, and 463 students were in the 11th grade. The 2008-2009 senior class had 422 students in it. Ramona High School first opened its doors in 1956, with its first class graduating in 1958. As with the other high schools in the Riverside Unified School District, Ramona offers the AVID program for its students. The school also boasts a nationally acclaimed band. 2,196 students attend Ramona High School, and the size of its grades has the largest variation out of the five high schools. In 9th grade alone, there were 823 students in 2008-2009. In 10th grade, there were 512 students, and 11th grade was the smallest grade, with only 376 students. The 12 th grade at Ramona had 485 students. The principal was Susan Mills, the only woman principal at the five schools in this study. Martin Luther King Jr. High School, commonly referred to as "King High School," is by far the newest high school in Riverside City. The school opened in 1999, with a total of 858 students in grades 9 and 10. Martin Luther King Jr. High School added grade 11 in 2000 and grade 12 in 2001. Enrollment at King High School has dramatically increased in the past several years as the population of Riverside has grown. As of the 2008-2009 school year, there were 3,055 students. 823 of those students were in the 9th grade, and 785 students were in the 10th grade. The 11th grade boasted 786 students, and the 12th grade had 679 students. Among the

variety of notable programs offered at Martin Luther King Jr. High School are AVID, Project Lead the Way (an engineering program), and a visual and performing arts program. The high school also offers three community partnerships for its students to learn from. They are the Regional Occupational Program, the Riverside Educational Enrichment Foundation, and the Riverside Sports Hall of Fame.

Mathematical Information The data collected in this report was collected from two different data bases. The first data base, Education-Data, has a direct partnership with the California Department of Education (CDE). The CDE collects and publishes all different types of data on different schools, districts, and countries. Education-Data does not change any of the data they receive from the CDE. Instead the site takes all of the information that it receives and publishes it in a way that it easy for the public to get data on any school in the state of California. The other data base that was used to create this report, DataQuest, is maintained by the California Department of Education itself. All of the numbers used in the site come directly from data gathered from the schools and districts across California. This means that our data could not be any more accurate. Information used throughout this report come directly from these two data bases for the 20082009 school year. The 2009-2010 data would have been used, as it is more current, but unfortunately none of the dropout rate data was available for this school year, thus we used the 2008-2009 school year data. During our research and report, only a few mathematical tools were used. In order to compare the different high schools within the district, all of our data had to be changed to percentages. This took some simple calculations. Another tool that was used within our report to demonstrate the differences between schools was graphs. Throughout the report, only two different graphs were used – pie and bar. It was felt that these graphs showed our data in the clearest way. The main term used throughout our report is the word “dropout rate”. This term needs to be defined so there is no question on the assumptions made when completing this report. The California Department of Education defines a child has dropped out when they were “enrolled in grades 7, 8, 9, 10, 11 or 12 at some time during the previous school year and left school prior to completing the school year and has not returned to school as of Information Day” or the child “did not begin attending the next grade (7, 8, 9, 10, 11 or 12) in the school to which they were assigned or in which they had pre-registered or were expected to attend by Information Day” 3 (Information Day is the day in which the data is compiled for each of the schools). For the purposes of our report, “dropout rate” is assumed to be the “1 year adjusted dropout rate”. The adjusted dropout rate has been defined as the “reported grade 9-12 dropout total minus reenrolled grade 9-12 dropouts plus Grade 9-12 lost transfers. The reenrolled dropouts are the “students initially reported as dropouts, but subsequently found to be enrolled in another California public school district” and the lost transfers are “students reported as having transferred to another California public school but not found enrolled in another California public school or students

3 California Department of Education, http://dq.cde.ca.gov/dataquest/gls_drpcriteria.asp.

reported as exiting for the summer, but not found enrolled in the fall”. The 1 year dropout rate formula is as follows: 1-year Rate Formula =

Numbers, Graphs, & Analysis Discipline and Dropout Rates Table 1: Discipline and Dropout Rates School

Enrollment

Dropout Rate

Suspensions Suspension as a % of Enrollment

JW North Ramona Poly Arlington King RUSD State

% of Suspensions for Violence and Drugs 30.4% 25.8% 28.6% 36% 40% -

2,512 4.5% 693 27.6% 2,196 4.1% 543 24.7% 2,837 2.8% 553 19.5% 2,218 2.7% 280 12.6% 3,055 2.0% 255 8.3% 42,344 6.1% 6,367 15% 6,102,161** 5.7% 757,045 12.4% * *** Not all agencies submitted data 4,5 We believe that the numbers of discipline cases related to dropouts are definitely correlated. When looking at the dropout rates compared to suspension rates, the rankings for each school correlate exactly

Table 1.1 School JW North Ramona Poly Arlington King

Dropout Rate 4.5% 4.1% 2.8% 2.7% 2.0%

Suspension Rate 27.6% 24.7% 19.5% 12.6% 8.3%

Graph 1: Suspensions and Dropouts These figures were shocking to our group because rankings for the schools are exactly the same, and one could infer that discipline rates directly influence dropout rates. The conclusion that we

4 California Department of Education, Dropout by Grade 2008-2009 5 California Department of Education, Expulsions, Suspensions, and Truancy Information 2008-2009

can draw from this set of information is that a certain type of student, one that is possibly troubled and involved in mischievous activities, is more likely to drop out than other types of students, who abide by the rules more often than the first type of student. This trend does not occur when looking at expulsions however.

Table 2: Expulsions and Dropouts School

Enrollment

Dropout Rate

Expulsions

Expulsions as a % of Enrollment .12% .32% .50% .09% .10% .12% .34%

JW North 2,512 4.5% 3 Ramona 2,196 4.1% 7 Poly 2,837 2.8% 14 Arlington 2,218 2.7% 2 King 3,055 2.0% 3 RUSD 42,344 6.1% 52 State 6,102,161*** 5.7% 21,039 *** Not all agencies submitted data 6,7 The expulsion rates per capita as a percentage compared to the dropout rates do not correlate.

Table 2.1 School JW North Ramona Poly Arlington King

Dropout Rate 4.5% 4.1% 2.8% 2.7% 2.0%

Expulsion Rate .12% .32% .50% .09% .10%

Graph 2: Expulsions and Dropouts We do not feel that these numbers are an accurate representation of discipline for the entirety of the schools being examined. Excluding Poly and Ramona’s expulsion figures, every school was within 1 student of each other, which does not reflect the schools different discipline cultures. Also we feel that Poly’s extremely high expulsion rate is something of an anomaly, and has special circumstances. The percentages, in our opinion, are more reflective of the schools’

6 California Department of Education, Dropout by Grade 2008-2009 7 California Department of Education, Expulsions, Suspensions, and Truancy Information 2008-2009

enrollment numbers than the expulsion figures. The truancy rate was another avenue that we decided to avoid.

Table 3: Truancy and Dropout Rates School Enrollment Dropout Rate Truancy Rate JW North 2,512 4.5% 30.28% Ramona 2,196 4.1% 45.37% Poly 2,837 2.8% 38.88% Arlington 2,218 2.7% 41.82 King 3,055 2.0% 33.05 RUSD 42,344 6.1% 30.49% State 6,102,161*** 5.7% 28.15% ** Truancy is defined as unexcused absences and tardies for more than three days *** Not all agencies submitted data 8,9 We felt that the truancy figures are not very reflective; they do not correlate when compared to the dropout rates.

Table 3.1 School JW North Ramona Poly Arlington King

Dropout Rate 4.5% 4.1% 2.8% 2.7% 2.0%

Truancy Rate 30.28% 45.37% 38.88% 41.82 33.05

Graph 3: Truancy and Dropout Rate The reason we did not feel that these numbers are accurate representations is due to the fact that some schools within the district have off campus lunch passes and others do not. This makes it much easier to simply not come back to school resulting in unexcused absences and tardies. Another reason is the difference in campus security between the schools. It might simply be easier to sneak out of certain schools than others. The final reason relies on teacher discretion. It

8 California Department of Education, Dropout by Grade 2008-2009 9 California Department of Education, Expulsions, Suspensions, and Truancy Information 2008-2009

is up to the teacher whether or not to mark a student tardy. We found this to be an inconsistent factor.

Economically Disadvantaged Youth Compared to Dropout Rates Table 4: Free/Reduced Lunch and Dropout Rates DROPOUT RATES 2.0% 2.8% 2.7% 4.5% 4.1% 5.7%

Martin Luther King Jr. High Polytechnic High Arlington High John W. North High Ramona High State Average

FREE/REDUCED LUNCH10 20.0% 40.2% 56.6% 63.0% 69.9% 57.3%

Table 4 shows the data for both the dropout rates and the percentage of students who received free or reduced lunch at the school. Students who are selected to receive free or reduced lunch are economically disadvantaged compared to their peers. These children usually face hardship at home due to their parent’s lack of financial security. Because of the struggles that students go through, dropping out may be a valuable option for these students. Thus, we compared the dropout rate to the free and reduce lunch rate in order to see if a certain high school that had a high free and reduce lunch percentage also had a high dropout rate. The results seemed to correlate. In the 2008-2009 school year, John W. North and Ramona High both had highest dropout rate and the highest percentage of students participating in free or reduced lunch. Also, Martin Luther King Jr. High had the lowest dropout rate along with the lowest percentage of students using free and reduced lunch. This may indicate that in the Riverside Unified School District, students who are at an economic disadvantage have a higher chance of dropping out from high school.

Graph 4.1: Dropout Rate (%) Graph 4.2: Free/reduced lunch (%)

Teacher and Student Ethnicities This section is devoted to comparing students and teacher ethnicities. It also includes the absolute value of the difference in percentage points of the teachers’ and students’ ethnicities. We use pie charts to demonstrate the various ratios of ethnicities. Following the presentation of this data is an analysis.

Arlington High Table 5: Race and Ethnicities of Students and Teachers at Arlington High RACE/ETHNICITY (% OF TOTAL)

TEACHERS STUDENTS DIFFERENCE IN PERCENTAGE POINTS (ABSOLUTE VALUE)

10 For the definition of free or reduced lunch, see Appendix A.

American Indian Asian Pacific Islander Filipino Hispanic African American White Multiple/No Response

0 1.2 1.2 0 20 5.9 71.8 0

0.5 2.7 0.4 1.8 57.7 6.6 30.2 0.3

0.5 1.5 0.8 1.8 37.7 0.7 41.6 0.3

Graph 5: Race and Ethnicities of Students and Teachers at Arlington High

John W. North High Table 6: Race and Ethnicities of Students and Teachers at John W. North High RACE/ETHNICITY (% OF TOTAL) American Indian Asian Pacific Islander Filipino Hispanic African American White Multiple/No Response

TEACHERS STUDENTS DIFFERENCE IN PERCENTAGE POINTS (ABSOLUTE VALUE) 1 0.4 0 5 1 0.8 1 1.3 21.6 57 7.2 15.8 68 19.2 0 0.6

0.6 5 0.2 0.3 35.4 8.6 48.8 0.6

Graph 6: Race and Ethnicities of Students and Teachers at John W. North High

Martin Luther King, Jr. High Table 7: Race and Ethnicities of Students and Teachers at Martin Luther King, Jr. High RACE/ETHNICITY (% OF TOTAL)

TEACHERS STUDENTS DIFFERENCE IN PERCENTAGE POINTS

(ABSOLUTE VALUE) American Indian Asian Pacific Islander Filipino Hispanic African American White Multiple/No Response

0 0.9 0.9 2.8 16.5 5.5 73.4 0

0.6 7 0.5 2.4 25.8 10.8 52.5 0.4

0.6 6.1 0.4 0.4 9.3 5.3 20.9 0.4

Graph 7: Race and Ethnicities of Students and Teachers at Martin Luther King, Jr. High

Polytechnic High Table 8: Race and Ethnicities of Students and Teachers at Polytechnic High RACE/ETHNICITY (% OF TOTAL) American Indian Asian Pacific Islander Filipino Hispanic African American White Multiple/No Response

TEACHERS STUDENTS DIFFERENCE IN PERCENTAGE POINTS (ABSOLUTE VALUE) 1 0.4 0.6 1.9 3 1.1 2.9 0.3 2.6 1 0.9 0.1 18.4 43.6 25.2 4.9 9.2 4.3 69.9 42.5 27.4 0 0.2 0.2

Graph 8: Race and Ethnicities of Students and Teachers at Polytechnic High

Ramona High Table 9: Race and Ethnicities of Students and Teachers at Ramona High

RACE/ETHNICITY (% OF TOTAL)

TEACHERS STUDENT S

American Indian Asian Pacific Islander Filipino Hispanic African American White Multiple/NoResponse

0 7.1 1.2 1.2 12.9 5.9 71.8 0

DIFFERENCE IN PERCENTAGE POINTS (ABSOLUTE VALUE)

0.5 1.5 0.5 0.5 63.9 6.8 25.9 0.3

0.5 5.6 0.7 0.7 51 0.9 45.9 0.3

Graph 9: Race and Ethnicities of Students and Teachers at Ramona High Graphs 5-9 show large differences between the ethnicities of students and their teachers at each high school. They do not, however, display the major correlations between the proportional relationship between ethnicities of students and teachers in relation to the dropout rates 11. We found that high schools with similar ethnicities of teachers and students had a lower dropout rate, while the opposite is true of high schools with disproportional student to teacher ethnicities. While we found this to be true in general, it did not hold fast in every example. The following table shows the sum of the percentage point difference in each school. This percentage point difference is the difference between the percentage points of each teacher and student with same ethnicity. For each school, the percentage point differences are added up. The higher the sum of these percentage points, the larger the difference between student/teacher ethnicities.

Table 10: Sum of Percentage Point Different and Dropout Rate %

Sum of percentage point difference Dropout Rate %

Arlington

North

King

Poly

Ramona

84.9

99.5

43.4

61.5

105.6

2.7

4.5

2

2.8

4.1

As you can see in Table 10, the results of these graphs are fairly similar. North High School has the highest dropout rate out of these five schools, with a rate of 4.5%. The school’s sum of percentage point difference is also one of the highest. The same is true of Ramona, which has the second highest dropout rate at 4.1%. This means that student and teacher ethnicities are not similar to each other, leading to the potential for students to feel out of place or uncomfortable in their educational environment. While it’s hard to measure cultural bias in the classroom, this data suggests a possible correlation. Also, students without teachers of the same ethnicity lack role 11 For the dropout rates by ethnicity see Appendix B.

models they can relate to within the context of their education. Conversely, King High School has the lowest sum of percentage points, along with the lowest dropout rate, at 2.0%. This shows that the school’s teacher and student ethnicities are proportional, which could have the long term effect of students staying in school longer. It’s also interesting to note that while the various ethnicities of students change from school to school, those of the teachers remain fairly common throughout the district. Since students within the Riverside School District are zoned for different high schools, this may be a reflection of the various populations in Riverside. Teachers, on the other hand, often are not from the neighborhoods or communities that they work in. Historically speaking, there is a precedent of teaching positions being available for white, middle class women who wished to work. At times, these positions were one of the only acceptable options for white middle class women in the workforce. Obviously, much has changed in the past few decades, but the data we have collected may reflect this legacy.

Average Class Size and Student/Teacher Ratio Table 11: Average Class Size, Student/Teacher, and Dropout Rate (%) SCHOOL

DROPOUT RATES (%)

AVERAGE CLASS SIZE*

Arlington

2.7

29.4

CERTIFIED STAFF STUDENT/TEACHER RATIO 24.1

North

4.5

30

24.1

King

2

30

25.9

Poly

2.8

30.4

23.6

Ramona

4.1

30.3

24.6

RANGE (Max-Min)

2.5

1

2.3

*Average class size is the number of students enrolled in classes divided by the number of classes. We also examined average class size along with student to teacher ratio at each of the schools, but found the result to be inconclusive. As demonstrated in Table 11, the difference in class sizes is not large enough to form a conclusion.

Conclusion

Through our research, we’ve found correlations to the dropout rates in the five public high schools in the Riverside Unified School District. Notably, schools with higher suspension rates also have higher dropout rates. In order to combat this, we recommend implementing incentives for positive behavior, and recognizing and rewarding positive behavior when it happens. In order to create a positive school climate, school administrators need to reinforce good behavior while creating the space for it to occur. By doing this, administrators are hopefully preventing the need for suspensions and therefore assigning less. We also found that schools with higher percentages of students receiving free or reduced lunch generally have higher dropout rates. Since this issue typically resides within the students’ family, we recommend that schools continue to be community spaces for the people they serve. Some schools have had success in this way by opening health clinics for their students, offering parenting classes, or even sponsoring parent and student functions to increase family involvement within the schools. The final correlation that we found was between the ethnicities of students in relation to those of their teachers. As stated before, schools that had proportional teacher to student ethnicities tended to have lower dropout rates and vice versa. We suggest that schools continue to look for caring and qualified teachers while keeping the implications of our findings in mind. That stated, it may help schools to recruit teachers of similar backgrounds, especially in terms of ethnicity, to their students. Schools can also provide whatever type of diversity training they deem appropriate based off the teachers they employ and the communities they serve. The final facet of our project looked at the average class and student/teacher ratio at these schools. Our results in this area were inconclusive. It’s important to remember that our findings only represent correlations, and not actual causations. With more time, it would be interesting to further investigate the relationship between teacher and student ethnicities. An in-depth analysis of this could include surveys of the students to determine if they felt the ethnicity of their teacher influenced their performance or attendance at school, or if there were other factors that the students deemed more important. In conclusion, there are many causes of dropout rates in high school, and countless factors that can influence them. We chose to focus on a few school-specific factors in order to increase understanding of those issues in particular.

Appendix A Eligibility for children to receive free/reduced lunches in the state of California. Data from The California Department of Education. Effective July 1, 2008 through June 30, 2009, participants from households with incomes at or below the following levels may be eligible for free or reduced-price meals or free milk. Note: The new income calculations are based on annual figures and the following formulas: Monthly = annual income divided by 12; Twice Per Month = annual income divided by 24; Every Two Weeks = annual income divided by 26; and Weekly = annual income divided by 52. All dollar amounts are rounded up to the next whole dollar. Table 12.1:Free Eligibility Scale; Meals, Snacks, and Milk Household Size

Annual

Monthly

Twice Per Month

1

$13,520

$1,127

2

$18,200

3

Weekly

$564

Every Two Weeks $520

$1,517

$759

$700

$350

$22,880

$1,907

$954

$880

$440

4

$27,560

$2,297

$1,149

$1,060

$530

5

$32,240

$2,687

$1,344

$1,240

$620

6

$36,920

$3,077

$1,539

$1,420

$710

7

$41,600

$3,467

$1,734

$1,600

$800

8

$46,280

$3,857

$1,929

$1,780

$890

For each additional family member, add:

+ $4,680

+ $390

+ $195

+ $180

+ $90

$260

Table 12.2: Reduced-Price Eligibility Scale; Meals and Snacks Household Size

Annual

Monthly

Twice Per Month

1

$19,240

$1,604

2

$25,900

3

Weekly

$802

Every Two Weeks $740

$2,159

$1,080

$997

$499

$32,560

$2,714

$1,357

$1,253

$627

4

$39,220

$3,269

$1,635

$1,509

$755

5

$45,880

$3,824

$1,912

$1,765

$883

$370

6

$52,540

$4,379

$2,190

$2,021

$1,011

7

$59,200

$4,934

$2,467

$2,277

$1,139

8

$65,860

$5,489

$2,745

$2,534

$1,267

For each additional family member, add:

+ $6,660

+ $555

+ $278

+$257

+ $129

A household of one means a child who is his or her sole support. Foster children are onemember households only if the welfare or the placement agency maintains legal responsibility for the child. Household is synonymous with family and means a group of related or unrelated individuals who are not residents of an institution of boarding house, but who are living as one economic unit sharing housing and all significant income and expenses. This scale does not apply to households that receive Food Stamps, Kin-Gap, Or FDPIR benefits or children who are recipients of CALWORKS. Those children are automatically eligible for free meal benefits. In the Adult Care Component of the Child and Adult Care Food Program, a household includes the adult participant and, if residing with the participant, the spouse, and any persons who are economically dependent on the adult participant. This scale does not apply to members of Food Stamp households, or recipients of Supplemental Security Income, Medicaid/Medi-Cal, or Food Distribution Program on Indian Reservations benefits. Those participants are automatically eligible for free meals.

Appendix B Dropouts by Ethnicity, 2008-2009 school year, data from Ed-Data Partnership http://www.ed-data.k12.ca.us/welcome.asp? Dropouts by Ethnicity, Grades 9-12 Ramona High School, 2008-09 Ethnicity

Enrollme nt

Adjusted 1-Year Dropout Rate2 School

American Indian or Alaska Native

11 Adjusted1 Dropouts1

9.1%

District 14.9%

Asian

34

1

2.9%

2.2%

Native Hawaiian or Pacific Islander

12

0

0.0%

10.1%

Filipino

10

0

0.0%

1.5%

Hispanic or Latino

1,404

62

4.4%

7.2%

Black or African American

150

9

6.0%

7.8%

White

569

15

2.6%

4.4%

Two or More Races

6

0

0.0%

0.0%

None Reported

0

1

**

**

2,196

89

4.1%

6.1%

Total 1

2 3

Total Reported Dropouts adjusted by removing Reenrolled Dropouts and adding Lost Transfers. Adjusted Dropouts divided by enrollment. Estimate of the percent of students who would drop out in a four year period based on data collected for a single year.

Dropouts by Ethnicity, Grades 9-12 John W. North High School, 2008-09

Ethnicity American Indian or Alaska Native

Enrollme Adjusted nt Dropouts1

Adjusted 1-Year Dropout Rate2 School District

9

0

0.0%

14.9%

Asian

125

0

0.0%

2.2%

Native

19

3

15.8%

10.1%

Hawaiian or Pacific Islander Filipino

33

1

3.0%

1.5%

1,433

76

5.3%

7.2%

Black or African American

396

14

3.5%

7.8%

White

483

19

3.9%

4.4%

14

0

0.0%

0.0%

0

0

**

**

2,512

113

4.5%

6.1%

Hispanic or Latino

Two or More Races None Reported Total

Dropouts by Ethnicity, Grades 9-12 Polytechnic High School, 2008-09 Enrollmen t Adjusted Dropouts1 American Indian or 10 0 Alaska Native Ethnicity

Asian

Adjusted 1-Year Dropout Rate2 School

District

0.0%

14.9%

85

2

2.4%

2.2%

8

0

0.0%

10.1%

26

0

0.0%

1.5%

Hispanic or Latino

1,237

59

4.8%

7.2%

Black or African American

260

7

2.7%

7.8%

Native Hawaiian or Pacific Islander Filipino

White

1,205

11

0.9%

4.4%

Two or More Races

6

0

0.0%

0.0%

None Reported

0

0

**

**

2,837

79

2.8%

6.1%

Total

Dropouts by Ethnicity, Grades 9-12 Arlington High School, 2008-09 Adjusted 1-Year Dropout Rate2

Ethnicity

Adjusted Enrollment Dropouts1 School

District

American Indian or Alaska Native

10

1

10.0%

14.9%

Asian

59

0

0.0%

2.2%

9

1

11.1%

39

0

0.0%

1.5%

Hispanic or Latino

1,279

37

2.9%

7.2%

Black or African American

147

7

4.8%

7.8%

White

669

14

2.1%

4.4%

Two or More Races

6

0

0.0%

0.0%

None Reported

0

0

**

**

Native Hawaiian or Pacific Islander Filipino

10.1%

Total

2,218

60

2.7%

6.1%

Dropouts by Ethnicity, Grades 9-12 Martin Luther King Jr. High School, 2008-09 Adjusted 1-Year Dropout Rate2

Ethnicity American Indian or Alaska Native

Adjusted Enrollment Dropouts1 School

District

17

2

11.8%

14.9%

215

3

1.4%

2.2%

Native Hawaiian or Pacific Islander

15

1

6.7%

10.1%

Filipino

73

1

1.4%

1.5%

Hispanic or Latino

788

32

4.1%

7.2%

Black or African American

329

9

2.7%

7.8%

1,605

12

0.7%

4.4%

13

0

0.0%

0.0%

0

0

**

**

3,055

60

2.0%

6.1%

Asian

White Two or More Races None Reported Total

Dropouts by Ethnicity, Grades 9-12 State of California, 2008-09 Ethnicity American Indian or Alaska Native

Adjusted Dropouts1

Enrollment

Adjusted 1-Year Dropout Rate2

15,950

1,327

8.3%

176,103

4,382

2.5%

Native Hawaiian or Pacific Islander

13,293

911

6.9%

Filipino

56,351

1,560

2.8%

Hispanic or Latino

935,076

65,201

7.0%

Black or African American

159,737

16,525

10.3%

White

609,533

22,753

3.7%

Two or More Races

51,593

663

1.3%

0

1,504

**

2,017,636

114,826

5.7%

Asian

None Reported Total

Works Cited Riverside Unified School District http://www.rusd.k12.ca.us/schools/SchoolIntro.aspx?sub=ss&cl=330 Education Data (Partnership with California Department of Education)

http://www.ed-data.k12.ca.us/welcome.asp? California Department of Education DataQuest http://dq.cde.ca.gov/dataquest/