English Language Acquisition Grants Under the No Child Left Behind Act: Analysis of State Grant Formula and Data Options

The number of limited English proficient (LEP) students enrolled in K-12 education increased by 60.8% from the 1994-1995 school year to the 2004-2005 school year, while total student enrollment increased by 2.6% over the same time period. Given this tremendous growth in the LEP student population and the likelihood that Congress will consider legislation to reauthorize the Elementary and Secondary Education Act of 1965 (ESEA), as amended by the No Child Left Behind Act of 2001 (NCLBA; P.L. 107-110), during the 110th Congress, this report examines the formula used to provide grants to states under the English Language Acquisition program, authorized by Title III of the ESEA. This program provides grants to states to help ensure that LEP and recent immigrant students attain proficiency in English. Much of the debate surrounding the reauthorization of this program has focused on the data used to determine how many LEP and immigrant students are in each state, as these data are the basis upon which grants are determined.

This report examines the American Community Survey (ACS) data that the U.S. Department of Education has used to calculate state grants since FY2005. It also analyzes state-reported data that could potentially be used to calculate these grants. Differences in LEP and immigrant student counts based on the different data sources are compared, revealing substantial differences in student counts for some states depending on the data source used. FY2007 grants are calculated using both the ACS and state-reported data to examine the potential differences in state grant amounts depending on the data source used. The differences in student counts that exist between the ACS and state-reported data are reflected in the differences in estimated state grant amounts, as some states would receive substantially more or less funding if state-reported data were used to calculate grants rather than the ACS data. Consideration is also given to the drawbacks of using either the ACS or state-reported data and possible alternative strategies for determining state grant awards (e.g., averaging the student counts from the ACS and state-reported data) are discussed.

This report will be updated as warranted by legislative action.

English Language Acquisition Grants Under the No Child Left Behind Act: Analysis of State Grant Formula and Data Options

June 29, 2007 (RL34066)

Contents

Tables

Summary

The number of limited English proficient (LEP) students enrolled in K-12 education increased by 60.8% from the 1994-1995 school year to the 2004-2005 school year, while total student enrollment increased by 2.6% over the same time period. Given this tremendous growth in the LEP student population and the likelihood that Congress will consider legislation to reauthorize the Elementary and Secondary Education Act of 1965 (ESEA), as amended by the No Child Left Behind Act of 2001 (NCLBA; P.L. 107-110), during the 110th Congress, this report examines the formula used to provide grants to states under the English Language Acquisition program, authorized by Title III of the ESEA. This program provides grants to states to help ensure that LEP and recent immigrant students attain proficiency in English. Much of the debate surrounding the reauthorization of this program has focused on the data used to determine how many LEP and immigrant students are in each state, as these data are the basis upon which grants are determined.

This report examines the American Community Survey (ACS) data that the U.S. Department of Education has used to calculate state grants since FY2005. It also analyzes state-reported data that could potentially be used to calculate these grants. Differences in LEP and immigrant student counts based on the different data sources are compared, revealing substantial differences in student counts for some states depending on the data source used. FY2007 grants are calculated using both the ACS and state-reported data to examine the potential differences in state grant amounts depending on the data source used. The differences in student counts that exist between the ACS and state-reported data are reflected in the differences in estimated state grant amounts, as some states would receive substantially more or less funding if state-reported data were used to calculate grants rather than the ACS data. Consideration is also given to the drawbacks of using either the ACS or state-reported data and possible alternative strategies for determining state grant awards (e.g., averaging the student counts from the ACS and state-reported data) are discussed.

This report will be updated as warranted by legislative action.


English Language Acquisition Grants Under the No Child Left Behind Act: Analysis of State Grant Formula and Data Options

The number of limited English proficient (LEP) students enrolled in K-12 education increased by 60.8% from the 1994-1995 school year to the 2004-2005 school year; total student enrollment increased by 2.6% over the same time period. Given this tremendous growth in the LEP student population and the likelihood that the 110th Congress will consider legislation to reauthorize the Elementary and Secondary Education Act of 1965 (ESEA), as amended by the No Child Left Behind Act of 2001 (NCLBA; P.L. 107-110), this report examines the formula used to provide grants to states under the English Language Acquisition program, authorized by Title III of the ESEA. This program provides grants to states to help ensure that LEP and recent immigrant students attain proficiency in English. Much of the debate surrounding the reauthorization of this program has focused on the data used to determine how many LEP and immigrant students are in each state, as these data are the basis upon which grants are determined.

This report begins with a general overview of the English Language Acquisition program, focusing specifically on the state grant formula. This is followed by a detailed analysis of the American Community Survey (ACS) data currently used by the U.S. Department of Education (ED) to calculate these grants, as well as state-reported data that could potentially be used to calculate these grants. The third section of the report compares student counts based on ACS data and state data and examines differences in estimated FY2007 state grants if state data were used as the basis for determining the awards. The report concludes with an examination of some of the drawbacks of using either the ACS or state-reported data for determining state grants and other possible alternative strategies for calculating state grants.

English Language Acquisition State Grants

Title III, Part A of the ESEA authorizes formula grants to states to ensure that limited English proficient (LEP) students and immigrant children develop English proficiency.1 Prior to determining state grant allocations, statutory language provides for several reservations of funds. These include reservations for national activities, for schools serving Native American and Alaska Native students, and for the outlying areas.2 After reserving the required funds, grants to the 50 states, the District of Columbia, and Puerto Rico are determined based on the state's proportional share of LEP students and immigrant students relative to the U.S. population of LEP students and immigrant students.3 These shares are then weighted, with a higher weight (0.8) being assigned to the state's population of LEP students and a lower weight (0.2) being assigned to the state's population of recent immigrant students. No state can receive a grant less than $500,000. The grant to Puerto Rico cannot exceed 0.5% of the total available for state distribution.

Data Availability

In determining the number of LEP and immigrant students in an individual state and in the United States, statutory language directs ED to use "the more accurate" of (1) data available from the American Community Survey (ACS), or (2) the number of children being assessed for English proficiency as required under Title I of the ESEA.4 In practice, ED has been using the ACS data to make state allocations since FY2005. Title III grants for a specific fiscal year have been based on ACS data from two years prior. For example, FY2007 grants are based on the 2005 ACS data. According to testimony provided by Cornelia Ashby, Director of Education, Workforce, and Income Security Issues at the Government Accountability Office (GAO), ED has not used state data because it believes the state data are incomplete.5 For example, ED noted that for the 2004-2005 school year, not every state provided data, and some data included only partial student counts.6

American Community Survey Data

ED obtains the relevant ACS data from the U.S. Census Bureau. The LEP student count is based on the population aged 5 to 21 who reported speaking a language other than English at home and speaking English less than "very well." The number of immigrant students is based on the number of individuals aged 3 to 21 who reported entering the United States during the two years prior to the survey or during the survey year. For example, for the 2005 ACS, individuals entering the country in 2003 or later were counted as recent immigrant students. According to GAO, these questions were developed for the 1980 census to "obtain information needed about current language use and limited English language proficiency as a result of legislation such as the Civil Rights Act of 1964, the Bilingual Education Act, and the Voting Rights Act."7 These questions have not been modified since their inception. Thus, they were not designed specifically for Title III purposes.

Tables 1 and 2 provide the ACS counts for LEP and immigrant students, respectively, used by ED in determining state grant amounts for FY2005, FY2006, and FY2007. Few states had relatively stable LEP student counts from 2002 to 2003 and 2003 to 2004 (Table 1). It was more common for states to experience substantial increases or decreases in their number or percentage of LEP students across the various ACS administrations. For example, the number of LEP students in Arizona declined by over 16,000 students from 2002 to 2003 but increased by nearly 21,000 students from 2004 to 2005, while the number of LEP students in Texas decreased by almost 58,000 students from 2002 to 2003 and increased by almost 25,000 students from 2003 to 2004. In other states, the change in the estimated number of LEP students may have been relatively small, but because some states serve small numbers of LEP students, changes in their student counts can result in large percentage changes. For example, the number of LEP students in Arkansas increased by about 8,000 students from 2002 to 2003 and decreased by about 5,000 students from 2003 to 2004, resulting in percentage changes in student counts of 59.9% and 21.6%, respectively. Although the number of immigrant students identified through the ACS is smaller then the number of LEP students, similar patterns were found in the immigrant student counts across years (Table 2).

Table 1. LEP Student Counts from the 2003, 2004, and 2005
American Community Surveys

State

ACS 2003 (FY2005 Grants)

ACS 2004 (FY2006 Grants)

ACS 2005 (FY2007 Grants)

Change from 2003 to 2004

Change from
2004 to 2005

Number

Percent

Number

Percent

Alabama

15,225

14,970

18,745

-255

-1.7%

3,775

25.2%

Alaska

5,500

5,090

4,225

-410

-7.5%

-865

-17.0%

Arizona

117,530

101,140

121,895

-16,390

-13.9%

20,755

20.5%

Arkansas

13,635

21,800

17,095

8,165

59.9%

-4,705

-21.6%

California

1,050,180

1,075,825

1,097,205

25,645

2.4%

21,380

2.0%

Colorado

66,865

60,430

61,675

-6,435

-9.6%

1,245

2.1%

Connecticut

28,080

33,020

33,165

4,940

17.6%

145

0.4%

Delaware

6,030

7,015

8,355

985

16.3%

1,340

19.1%

District of Columbia

5,835

2,950

3,490

-2,885

-49.4%

540

18.3%

Florida

231,710

235,830

234,505

4,120

1.8%

-1,325

-0.6%

Georgia

93,155

78,495

85,275

-14,660

-15.7%

6,780

8.6%

Hawaii

10,565

12,945

14,230

2,380

22.5%

1,285

9.9%

Idaho

12,485

12,550

9,860

65

0.5%

-2,690

-21.4%

Illinois

176,630

182,210

182,730

5,580

3.2%

520

0.3%

Indiana

57,500

70,380

40,740

12,880

22.4%

-29,640

-42.1%

Iowa

17,370

12,900

16,015

-4,470

-25.7%

3,115

24.1%

Kansas

15,965

17,160

21,115

1,195

7.5%

3,955

23.0%

Kentucky

16,565

17,580

17,160

1,015

6.1%

-420

-2.4%

Louisiana

18,740

15,235

14,165

-3,505

-18.7%

-1,070

-7.0%

Maine

2,590

3,865

3,535

1,275

49.2%

-330

-8.5%

Maryland

38,640

39,900

47,550

1,260

3.3%

7,650

19.2%

Massachusetts

77,685

59,785

64,815

-17,900

-23.0%

5,030

8.4%

Michigan

72,320

49,255

62,675

-23,065

-31.9%

13,420

27.2%

Minnesota

44,530

48,180

39,575

3,650

8.2%

-8,605

-17.9%

Mississippi

7,410

4,775

7,870

-2,635

-35.6%

3,095

64.8%

Missouri

28,600

19,950

21,765

-8,650

-30.2%

1,815

9.1%

Montana

1,515

2,920

2,185

1,405

92.7%

-735

-25.2%

Nebraska

14,100

12,460

14,935

-1,640

-11.6%

2,475

19.9%

Nevada

48,730

58,010

38,540

9,280

19.0%

-19,470

-33.6%

New Hampshire

5,905

5,195

5,000

-710

-12.0%

-195

-3.8%

New Jersey

121,360

100,680

107,955

-20,680

-17.0%

7,275

7.2%

New Mexico

40,205

27,690

28,805

-12,515

-31.1%

1,115

4.0%

New York

388,795

332,065

275,230

-56,730

-14.6%

-56,835

-17.1%

North Carolina

65,600

73,710

70,970

8,110

12.4%

-2,740

-3.7%

North Dakota

2,190

2,095

1,700

-95

-4.3%

-395

-18.9%

Ohio

42,860

48,885

48,005

6,025

14.1%

-880

-1.8%

Oklahoma

31,570

20,575

21,085

-10,995

-34.8%

510

2.5%

Oregon

37,755

43,100

49,910

5,345

14.2%

6,810

15.8%

Pennsylvania

61,600

75,935

74,245

14,335

23.3%

-1,690

-2.2%

Rhode Island

17,865

11,875

12,130

-5,990

-33.5%

255

2.1%

South Carolina

16,155

15,525

22,940

-630

-3.9%

7,415

47.8%

South Dakota

4,055

2,855

4,065

-1,200

-29.6%

1,210

42.4%

Tennessee

25,595

33,180

28,635

7,585

29.6%

-4,545

-13.7%

Texas

603,105

545,330

570,145

-57,775

-9.6%

24,815

4.6%

Utah

19,215

20,590

21,050

1,375

7.2%

460

2.2%

Vermont

1,585

1,140

1,900

-445

-28.1%

760

66.7%

Virginia

53,935

52,640

57,440

-1,295

-2.4%

4,800

9.1%

Washington

58,840

59,350

78,270

510

0.9%

18,920

31.9%

West Virginia

2,465

2,320

3,250

-145

-5.9%

930

40.1%

Wisconsin

44,275

39,665

38,855

-4,610

-10.4%

-810

-2.0%

Wyoming

1,780

1,885

2,130

105

5.9%

245

13.0%

Total

3,942,395

3,792,910

3,828,805

-149,485

-3.8%

35,895

0.9%

Source: Table prepared by CRS, June 2007, based on data provided by the U.S. Department of Education (ED), Budget Service.

Note: The American Community Survey (ACS) is administered by the U.S. Census Bureau. The Census Bureau provides ED with specific data runs from the most recent ACS to enable ED to calculate Title III grants.

Table 2. Immigrant Student Counts from the 2003, 2004, and 2005
American Community Survey

State

ACS 2003 (FY2005 Grants)

ACS 2004 (FY2006 Grants)

ACS 2005 (FY2007 Grants)

Change from 2003 to 2004

Change from
2004 to 2005

Number

Percent

Number

Percent

Alabama

10,500

10,195

7,710

-305

-2.9%

-2,485

-24.4%

Alaska

1,705

2,415

965

710

41.6%

-1,450

-60.0%

Arizona

20,670

35,400

35,660

14,730

71.3%

260

0.7%

Arkansas

3,485

6,545

4,680

3,060

87.8%

-1,865

-28.5%

California

238,495

229,805

251,275

-8,690

-3.6%

21,470

9.3%

Colorado

18,920

14,840

16,835

-4,080

-21.6%

1,995

13.4%

Connecticut

10,255

10,725

10,670

470

4.6%

-55

-0.5%

Delaware

1,525

2,520

2,495

995

65.2%

-25

-1.0%

District of Columbia

2,125

1,665

1,285

-460

-21.6%

-380

-22.8%

Florida

105,365

100,595

93,535

-4,770

-4.5%

-7,060

-7.0%

Georgia

21,285

25,045

36,945

3,760

17.7%

11,900

47.5%

Hawaii

3,635

5,145

6,645

1,510

41.5%

1,500

29.2%

Idaho

5,730

3,360

5,010

-2,370

-41.4%

1,650

49.1%

Illinois

36,390

43,520

35,965

7,130

19.6%

-7,555

-17.4%

Indiana

8,270

12,940

11,985

4,670

56.5%

-955

-7.4%

Iowa

7,755

2,910

4,150

-4,845

-62.5%

1,240

42.6%

Kansas

4,890

4,305

6,035

-585

-12.0%

1,730

40.2%

Kentucky

4,160

6,965

5,275

2,805

67.4%

-1,690

-24.3%

Louisiana

9,955

3,105

3,185

-6,850

-68.8%

80

2.6%

Maine

735

1,000

995

265

36.1%

-5

-0.5%

Maryland

18,895

18,755

26,765

-140

-0.7%

8,010

42.7%

Massachusetts

19,355

17,520

23,935

-1,835

-9.5%

6,415

36.6%

Michigan

27,330

18,330

20,640

-9,000

-32.9%

2,310

12.6%

Minnesota

12,340

7,180

14,420

-5,160

-41.8%

7,240

100.8%

Mississippi

1,350

1,035

2,695

-315

-23.3%

1,660

160.4%

Missouri

10,585

4,300

7,315

-6,285

-59.4%

3,015

70.1%

Montana

440

980

465

540

122.7%

-515

-52.6%

Nebraska

4,390

4,280

4,130

-110

-2.5%

-150

-3.5%

Nevada

10,410

9,690

9,445

-720

-6.9%

-245

-2.5%

New Hampshire

3,235

1,255

1,155

-1,980

-61.2%

-100

-8.0%

New Jersey

53,080

31,035

38,670

-22,045

-41.5%

7,635

24.6%

New Mexico

5,800

3,900

5,720

-1,900

-32.8%

1,820

46.7%

New York

75,560

87,320

83,310

11,760

15.6%

-4,010

-4.6%

North Carolina

20,495

25,145

27,890

4,650

22.7%

2,745

10.9%

North Dakota

695

770

415

75

10.8%

-355

-46.1%

Ohio

13,805

14,070

13,525

265

1.9%

-545

-3.9%

Oklahoma

10,450

9,740

5,935

-710

-6.8%

-3,805

-39.1%

Oregon

7,900

10,845

10,925

2,945

37.3%

80

0.7%

Pennsylvania

15,835

13,545

16,150

-2,290

-14.5%

2,605

19.2%

Rhode Island

2,570

3,420

4,610

850

33.1%

1,190

34.8%

South Carolina

6,195

4,080

11,865

-2,115

-34.1%

7,785

190.8%

South Dakota

380

790

1,835

410

107.9%

1,045

132.3%

Tennessee

13,740

10,160

9,800

-3,580

-26.1%

-360

-3.5%

Texas

106,445

126,650

130,990

20,205

19.0%

4,340

3.4%

Utah

5,695

8,155

7,410

2,460

43.2%

-745

-9.1%

Vermont

870

300

645

-570

-65.5%

345

115.0%

Virginia

25,800

24,835

25,835

-965

-3.7%

1,000

4.0%

Washington

14,835

21,350

24,375

6,515

43.9%

3,025

14.2%

West Virginia

2,845

235

200

-2,610

-91.7%

-35

-14.9%

Wisconsin

8,880

9,320

8,805

440

5.0%

-515

-5.5%

Wyoming

310

765

1,085

455

146.8%

320

41.8%

Total

1,016,365

1,012,755

1,082,260

-3,610

-0.4%

69,505

6.9%

Source: Table prepared by CRS, June 2007, based on data provided by the U.S. Department of Education (ED), Budget Service.

Note: The American Community Survey (ACS) is administered by the U.S. Census Bureau. The Census Bureau provides ED with specific data runs from the most recent ACS to enable ED to calculate Title III grants.

State-Reported LEP Student Counts

There are several potential sources of state-reported data and three types of state LEP student counts: (1) total number of LEP students, (2) number of LEP students receiving services (Title III or non-Title III), and (3) number of LEP students being served in Title III. The National Clearinghouse for English Language Acquisition and Language Instruction Educational Programs (NCELA) uses data provided by states to ED in their Consolidated State Performance Reports (CSPRs) to produce an annual state-by-state count of the number of LEP students enrolled.8 The CSPRs collect data on the total number of students identified as LEP. The most recent data available are for the 2004-2005 school year. Missing data and data discrepancies were resolved by NCELA through telephone calls to the relevant states.

The Common Core of Data (CCD) collects data on the total number of students receiving LEP services.9 This is not limited to Title III services only. Rather, it includes students served in appropriate programs of language assistance. This is somewhat different than the data available from NCELA, as the CCD count does not include students who are identified as LEP but are not receiving services.10 The most recent data available from the CCD are for the 2004-2005 school year.

A third source of data is the biennial report on Title III performance. The first report was published by ED in 2005 and covered 2002-2004. It included data on the number of LEP students served in Title III programs during the 2002-2003 and 2003-2004 school years. It did not, however, report on the total number of LEP students in the state or the total number of LEP students receiving Title III and non-Title III services. According to staff at NCELA, the second biennial report, expected later this year, will include counts of both the number of LEP students served in Title III programs and the total number of LEP students in the state. They also indicated that much of the data included in the forthcoming second biennial report has been drawn from the annual CSPRs.

LEP student counts from the NCELA data and CCD data are compared for the 2002-2003, 2003-2004, and 2004-2005 school years (Table 3). The NCELA data produced using the CSPRs are more complete than the data available from the CCD, as state data are missing for several states in the CCD data.11 As the NCELA LEP student count is, in theory, a more comprehensive count than the CCD LEP student count, it would be expected that the NCELA counts would be higher than the CCD counts but not substantially higher, as it is not expected that many parents would choose for their children not to receive services. The data on Table 3 do not consistently support these theories. For example, for the 2004-2005 school year, the NCELA count is actually lower than the CCD count in 18 states. For Indiana, Louisiana, Oklahoma, Vermont, and West Virginia, the NCELA count is at least 20% lower than the CCD count. Although it was expected that the NCELA count might be somewhat higher than the CCD count, in Florida, Mississippi, New Hampshire, North Dakota, Rhode Island, South Carolina, South Dakota, Vermont, and Wisconsin, the NCELA count is at least 20% higher than the CCD count. Similar issues exist with the data from the 2002-2003 and 2003-2004 school years. It is the exception, rather than the rule, that the NCELA data and the CCD data match or differ by a relatively small number of students. In addition, differences between the NCELA data and the CCD data change for some states from year to year with the NCELA count being higher in some years, the CCD count being higher in other years, and the magnitude of the differences between the counts changing from year to year. This raises questions about how states are conducting LEP student counts, whether these counts are being conducted consistently within a state and from year to year, and which students are actually being included in the counts.

Table 3. Estimated State LEP Student Counts Based on Data Available from the Common Core of Data and the NCELA: 2002-2003, 2003-2004, and 2004-2005

A

B

C

D

E

F

G

H

I

J

State

2002-2003 School Year

2003-2004 School Year

2004-2005 School Year

CCD
Data

NCELA Data

Difference (Col C-
Col B)

CCD
Data

NCELA Data

Difference (Col F -
Col E)

CCD
Data

NCELA
Data

Difference (Col I -
Col H)

Alabama

10,568

10,566

-2

10,825

13,312

2,487

14,801

15,295

494

Alaska

16,378

20,272

3,894

19,877

21,533

1,656

21,533

20,140

-1,393

Arizona

143,744

149,354

5,610

155,840

144,145

-11,695

194,171

155,789

-38,382

Arkansas

15,146

14,838

-308

17,174

15,581

-1,593

18,647

17,384

-1,263

California

1,599,542

1,599,542

0

1,598,366

1,598,535

169

1,585,647

1,591,525

5,878

Colorado

86,128

86,129

1

97,043

91,751

-5,292

90,372

90,391

19

Connecticut

22,651

22,547

-104

25,959

25,867

-92

27,931

27,580

-351

Delaware

3,449

3,523

74

3,956

4,246

290

4,858

5,094

236

District of Columbia

5,798

5,363

-435

5,727

5,201

-526

5,657

4,771

-886

Florida

203,712

292,077

88,365

196,037

282,066

86,029

214,562

299,346

84,784

Georgia

70,464

59,840

-10,624

65,876

59,126

-6,750

60,334

50,381

-9,953

Hawaii

12,853

12,853

0

12,850

12,850

0

17,017

18,376

1,359

Idaho

18,747

19,753

1,006

19,649

20,541

892

20,987

17,649

-3,338

Illinois

168,727

169,414

687

161,700

192,764

Indiana

42,629

22,584

-20,045

42,632

28,741

-13,891

51,212

31,956

-19,256

Iowa

13,961

13,961

0

15,238

15,238

0

14,606

14,421

-185

Kansas

17,942

25,006

7,064

22,399

25,504

3,105

26,041

23,512

-2,529

Kentucky

6,343

6,017

-326

8,446

8,446

0

10,471

11,181

710

Louisiana

11,108

6,854

-4,254

12,175

7,546

-4,629

12,979

7,990

-4,989

Maine

2,632

3,006

374

2,852

3,179

327

2,868

2,896

28

Maryland

27,311

27,422

111

27,695

27,849

154

21,709

24,811

3,102

Massachusetts

51,622

51,622

0

49,297

49,297

0

49,773

49,923

150

Michigan

60,479

62,025

62,265

240

62,778

64,345

1,567

Minnesota

51,275

52,244

969

53,507

54,878

1,371

56,976

56,829

-147

Mississippi

2,250

2,916

666

2,916

4,681

1,765

3,365

4,152

787

Missouri

13,121

13,121

0

14,855

14,855

0

15,403

Montana

6,642

7,043

401

6,668

6,948

280

6,716

6,911

195

Nebraska

13,803

13,803

0

15,586

15,586

0

16,124

16,124

0

Nevada

58,753

53,492

-5,261

69,896

58,753

-11,143

71,557

72,117

560

New Hampshire

3,270

3,270

0

2,755

2,755

0

2,569

3,235

666

New Jersey

57,548

57,245

-303

58,349

66,451

8,102

61,287

New Mexico

65,317

65,317

0

54,528

54,528

0

62,386

70,926

8,540

New York

178,909

302,961

124,052

191,992

203,583

North Carolina

59,849

60,149

300

60,967

70,937

9,970

68,381

70,288

1,907

North Dakota

883

6,176

5,293

1,638

6,500

4,862

2,033

4,749

2,716

Ohio

25,782

20,778

-5,004

23,368

23,302

-66

27,499

25,518

-1,981

Oklahoma

40,192

36,508

-3,684

40,042

33,266

-6,776

44,454

33,508

-10,946

Oregon

52,331

52,588

257

64,618

61,695

-2,923

64,676

59,908

-4,768

Pennsylvania

38,288

41,606

39,847

Rhode Island

10,087

11,600

1,513

9,723

9,645

-78

9,001

10,921

1,920

South Carolina

7,467

8,239

772

10,653

12,653

2,000

12,528

15,396

2,868

South Dakota

4,524

3,361

-1,163

4,477

3,433

-1,044

4,194

5,847

1,653

Tennessee

14,953

19,352

19,355

Texas

630,686

630,148

-538

661,052

660,707

-345

684,583

684,007

-576

Utah

43,299

46,342

3,043

49,556

46,521

-3,035

45,027

56,319

11,292

Vermont

1,057

1,052

-5

1,992

1,017

-975

1,990

1,393

-597

Virginia

49,845

49,840

-5

60,301

60,306

5

66,970

67,933

963

Washington

70,431

66,038

-4,393

58,523

69,323

10,800

75,103

75,678

575

West Virginia

1,281

2,103

822

1,477

1,594

117

1,774

1,236

-538

Wisconsin

25,764

34,203

8,439

26,424

35,770

9,346

26,616

35,871

9,255

Wyoming

3,519

3,206

-313

3,475

3,429

-46

3,593

3,742

149

Total

4,029,340

4,340,006

310,666

3,829,284

4,317,002

487,718

3,887,069

4,459,603

572,534

Source: Table prepared by CRS, June 2007. The "NCELA data" were provided by the National Clearinghouse on English Language Acquisition and Language Instruction Educational Programs based on an analysis of data reported by states on Consolidated State Performance Reports. The "CCD data" were collected through the Common Core of Data by the National Center for Education Statistics (NCES) at the U.S. Department of Education and reported in a series of annual reports (NCES 2005-314, NCES 2006-307, and NCES 2007-309).

Note: While a total is shown for the CCD data for the 2004-2005 school year, a total was not included in the NCES report, as data were missing for more than 15% of all schools or districts nationally.

−: Data were not available or data were missing from more than 20% of schools or districts within a state.

Although not shown in Table 3, data from the NCELA and CCD from 2003-2004 were compared with data reported in the biennial report for 2003-2004. As previously discussed, the NCELA data, in theory, provide the most comprehensive count of LEP students, including all identified LEP students. The CCD data, in theory, provide the second most comprehensive count of LEP students by including all students receiving LEP services. The biennial report data, in theory, are the least comprehensive of the three sources of data as they include only the number of LEP students receiving Title III services. A brief examination of data for Alabama, Alaska, Arizona, Arkansas, and California revealed that the biennial LEP student count was higher than the CCD count in Alabama and Arizona. It was also higher than the NCELA count in Arizona. This raises further questions about how LEP students are being counted at the state level and whether state counts are a reliable basis upon which to make state grant allocations.

State-Reported Immigrant Student Counts

Data sources for immigrant student counts are more limited than those available for LEP students. The primary source of this information is the Title III biennial report. States are required to report on the number of immigrant students enrolled and the number of immigrant students served in Title III programs. The most recent biennial report includes these counts for the 2002-2003 and 2003-2004 school years. Neither NCELA nor the CCD produces immigrant student counts. Table 4 provides the immigrant student counts from the biennial report for the 2002-2003 and 2003-2004 school years, the most recent years for which data are available.

Table 4. Immigrant Student Counts Based on State-Reported Data in Title III Biennial Reports: 2002-2003 and 2003-2004

A

B

C

D

E

State

Number of Immigrant
Children and Youth
During 2002-2003
School Year

Number of Immigrant
Children and Youth During
2003-2004
School Year

Difference in the Number
of Immigrant Children and
Youth (Col C - Col B)

Percent
Change

Alabama

5,355

4,166

-1,189

-22.2%

Alaska

1,818

1,163

-655

-36.0%

Arizona

40,721

34,074

-6,647

-16.3%

Arkansas

4,626

4,696

70

1.5%

California

254,450

269,939

15,489

6.1%

Colorado

10,486

15,642

5,156

49.2%

Connecticut

14,977

16,398

1,421

9.5%

Delaware

1,665

1,327

-338

-20.3%

District of Columbia

1,631

1,376

-255

-15.6%

Florida

169,819

158,168

-11,651

-6.9%

Georgia

38,919

40,150

1,231

3.2%

Hawaii

4,678

5,242

564

12.1%

Idaho

1,440

Illinois

61,139

65,629

4,490

7.3%

Indiana

10,686

11,130

444

4.2%

Iowa

3,925

3,284

-641

-16.3%

Kansas

9,184

7,924

-1,260

-13.7%

Kentucky

3,397

5,199

1,802

53.0%

Louisiana

3,848

3,683

-165

-4.3%

Maine

1,129

1,280

151

13.4%

Maryland

18,237

18,156

-81

-0.4%

Massachusetts

21,395

25,740

4,345

20.3%

Michigan

12,236

12,530

294

2.4%

Minnesota

15,414

16,236

822

5.3%

Mississippi

952

1,316

364

38.2%

Missouri

8,020

7,518

-502

-6.3%

Montana

273

348

75

27.5%

Nebraska

5,698

5,635

-63

-1.1%

Nevada

12,565

16,479

3,914

31.2%

New Hampshire

1,991

1,200

-791

-39.7%

New Jersey

54,185

45,814

-8,371

-15.4%

New Mexico

9,631

8,132

-1,499

-15.6%

New York

123,948

116,822

-7,126

-5.7%

North Carolina

31,183

29,232

-1,951

-6.3%

North Dakota

1,007

1,009

2

0.2%

Ohio

12,389

11,687

-702

-5.7%

Oklahoma

9,466

7,622

-1,844

-19.5%

Oregon

7,730

7,455

-275

-3.6%

Pennsylvania

15,519

16,138

619

4.0%

Rhode Island

3,322

2,900

-422

-12.7%

South Carolina

6,254

6,716

462

7.4%

South Dakota

909

1,020

111

12.2%

Tennessee

19,569

16,325

-3,244

-16.6%

Texas

121,064

116,818

-4,246

-3.5%

Utah

14,195

17,145

2,950

20.8%

Vermont

598

567

-31

-5.2%

Virginia

23,432

21,440

-1,992

-8.5%

Washington

21,196

24,997

3,801

17.9%

West Virginia

178

175

-3

-1.7%

Wisconsin

7,548

6,608

-940

-12.5%

Wyoming

191

191

0

0.0%

Total

1,222,748

1,215,881

-6,867

-0.6%

Source: Table prepared by CRS, June 2007, based on data provided by states in their Title III biennial reports (Biennial Evaluation Report to Congress on the Implementation of the State Formula Grant Program, 2002-2004).

Note:—= Data either not reported or not available.

ACS Data Compared with State-Reported Data

This section makes direct comparisons between the most recent ACS data and the most recent state data. It begins with a discussion of data limitations in making these comparisons. This discussion is followed by a detailed analysis of differences in LEP and immigrant student counts between the two types of data. The section concludes with an analysis of estimated FY2007 state grants using both data sources and how these grants would differ based on the underlying data used for the calculation.

Data Limitations

It should be noted that comparisons of student counts have been conducted with state data from two different school years. As the LEP student count accounts for 80% of a state's total grant amount, it was important to have the most recent data available and, if possible, to be using a school year comparable to the year in which the ACS data were collected. The LEP student counts produced by NCELA for the 2004-2005 school year met both these criteria. And, unlike the CCD data for the same school year, they presumably include a more nearly complete count of total LEP student enrollment, as the data were confirmed with state officials as needed. Although one of the primary purposes of this request was to compare the ACS data with state data, it should be noted that the NCELA and ACS data are collected from different respondents using different questions. Again, the NCELA data include the population of students identified as LEP, while the ACS is a sample survey conducted with native and non-native English speaking individuals.

As previously mentioned, data sources for immigrant student counts are more limited, so the latest available data were from the 2003-2004 school year. Thus, in addition to the aforementioned problems of collecting data from different respondents using different questions, the state-reported immigrant data were taken from a different year than the 2005 ACS data.

These caveats must be taken into account when examining student counts and estimated state grants based on these data. The estimated grant amounts discussed below are only rough estimates of what states might receive if state data were relied upon to make grants.

Student Count Data Comparisons

As shown in Tables 5 and 6, there are some substantial differences in LEP and immigrant student counts when the 2005 ACS data are compared with the 2004-2005 LEP student counts available from NCELA and the 2003-2004 immigrant student counts available from the biennial report. With respect to LEP student counts, for example, the state data indicate that there are almost 500,000 more LEP students in California than indicated by the ACS data. Arizona, Colorado, Florida, Nevada, New Mexico, Texas, and Utah each reported at least 25,000 more LEP students than accounted for by the 2005 ACS. At the same time, if state LEP student counts were used instead of ACS LEP student counts, Georgia, New Jersey, New York, and Pennsylvania would have their student counts reduced by 25,000 students or more. If the same data are examined based on the percentage change in student counts if state data were used instead of ACS data, Alaska would experience the largest percentage increase in LEP students (376.7%), followed by Montana (216.3%), North Dakota (179.4%), Utah (167.5%), and New Mexico (146.2%). Although California would experience the largest increase in the number of LEP students, this change would result in a 45.1% increase in LEP student enrollment.12 West Virginia would experience the largest percentage decrease in enrollment (62.0%), followed by Mississippi (47.2%), Ohio (46.8%), and Pennsylvania (46.3%).

If state data were used in lieu of ACS data for immigrant counts, Florida would experience the largest increase in the number of immigrant students, followed by New York, Illinois, and California (Table 6). Overall, increases in immigrant student counts would range from 16 students in Arkansas to 64,633 students in Florida. The largest decreases in the number of immigrant students would occur in Texas, followed by Maryland and Michigan. Overall, decreases in the number of immigrant students would range from 12 students in Pennsylvania to 14,100 students in Texas. In terms of percentage change in student counts, the largest increase in immigrant students would occur in North Dakota (143.1%), followed by Utah (131.4%) and Illinois (82.5%). The greatest decreases would be experienced by Wyoming (82.4%), followed by Idaho (71.3%) and Mississippi (51.2%).

Table 5. Comparison of Estimated Limited English Proficient Student Counts from the 2005 American Community Survey and 2004-2005 State-Reported Data

State

2005
ACS

2004-2005
State Data

Difference
(State - ACS)

Percent Difference

Alabama

18,745

15,295

-3,450

-18.4%

Alaska

4,225

20,140

15,915

376.7%

Arizona

121,895

155,789

33,894

27.8%

Arkansas

17,095

17,384

289

1.7%

California

1,097,205

1,591,525

494,320

45.1%

Colorado

61,675

90,391

28,716

46.6%

Connecticut

33,165

27,580

-5,585

-16.8%

Delaware

8,355

5,094

-3,261

-39.0%

District of Columbia

3,490

4,771

1,281

36.7%

Florida

234,505

299,346

64,841

27.7%

Georgia

85,275

50,381

-34,894

-40.9%

Hawaii

14,230

18,376

4,146

29.1%

Idaho

9,860

17,649

7,789

79.0%

Illinois

182,730

192,764

10,034

5.5%

Indiana

40,740

31,956

-8,784

-21.6%

Iowa

16,015

14,421

-1,594

-10.0%

Kansas

21,115

23,512

2,397

11.4%

Kentucky

17,160

11,181

-5,979

-34.8%

Louisiana

14,165

7,990

-6,175

-43.6%

Maine

3,535

2,896

-639

-18.1%

Maryland

47,550

24,811

-22,739

-47.8%

Massachusetts

64,815

49,923

-14,892

-23.0%

Michigan

62,675

64,345

1,670

2.7%

Minnesota

39,575

56,829

17,254

43.6%

Mississippi

7,870

4,152

-3,718

-47.2%

Missouri

21,765

15,403

-6,362

-29.2%

Montana

2,185

6,911

4,726

216.3%

Nebraska

14,935

16,124

1,189

8.0%

Nevada

38,540

72,117

33,577

87.1%

New Hampshire

5,000

3,235

-1,765

-35.3%

New Jersey

107,955

61,287

-46,668

-43.2%

New Mexico

28,805

70,926

42,121

146.2%

New York

275,230

203,583

-71,647

-26.0%

North Carolina

70,970

70,288

-682

-1.0%

North Dakota

1,700

4,749

3,049

179.4%

Ohio

48,005

25,518

-22,487

-46.8%

Oklahoma

21,085

33,508

12,423

58.9%

Oregon

49,910

59,908

9,998

20.0%

Pennsylvania

74,245

39,847

-34,398

-46.3%

Rhode Island

12,130

10,921

-1,209

-10.0%

South Carolina

22,940

15,396

-7,544

-32.9%

South Dakota

4,065

5,847

1,782

43.8%

Tennessee

28,635

19,355

-9,280

-32.4%

Texas

570,145

684,007

113,862

20.0%

Utah

21,050

56,319

35,269

167.5%

Vermont

1,900

1,393

-507

-26.7%

Virginia

57,440

67,933

10,493

18.3%

Washington

78,270

75,678

-2,592

-3.3%

West Virginia

3,250

1,236

-2,014

-62.0%

Wisconsin

38,855

35,871

-2,984

-7.7%

Wyoming

2,130

3,742

1,612

75.7%

Total

3,828,805

4,459,603

630,798

16.5%

Source: Table prepared by CRS, June 2007, based on data provided by the U.S. Department of Education (ED), Budget Service. The 2004-2005 student counts were provided by the National Clearinghouse for English Language Acquisition and Language Instruction Educational Programs (NCELA), based on an analysis of data reported by states on their Consolidated State Performance Reports.

Note: The American Community Survey (ACS) is administered by the U.S. Census Bureau. The Census Bureau provides ED with specific data runs from the most recent ACS to enable ED to calculate Title III grants.

Table 6. Comparison of Estimated Immigrant Student Counts from the 2005 American Community Survey and 2003-2004 State-Reported Data

State

2005
ACS

2003-2004
State Data

Difference
(State - ACS)

Percent
Difference

Alabama

7,710

4,166

-3,544

-46.0%

Alaska

965

1,163

198

20.5%

Arizona

35,660

34,074

-1,586

-4.4%

Arkansas

4,680

4,696

16

0.3%

California

251,275

269,939

18,664

7.4%

Colorado

16,835

15,642

-1,193

-7.1%

Connecticut

10,670

16,398

5,728

53.7%

Delaware

2,495

1,327

-1,168

-46.8%

District of Columbia

1,285

1,376

91

7.1%

Florida

93,535

158,168

64,633

69.1%

Georgia

36,945

40,150

3,205

8.7%

Hawaii

6,645

5,242

-1,403

-21.1%

Idaho

5,010

1,440

-3,570

-71.3%

Illinois

35,965

65,629

29,664

82.5%

Indiana

11,985

11,130

-855

-7.1%

Iowa

4,150

3,284

-866

-20.9%

Kansas

6,035

7,924

1,889

31.3%

Kentucky

5,275

5,199

-76

-1.4%

Louisiana

3,185

3,683

498

15.6%

Maine

995

1,280

285

28.6%

Maryland

26,765

18,156

-8,609

-32.2%

Massachusetts

23,935

25,740

1,805

7.5%

Michigan

20,640

12,530

-8,110

-39.3%

Minnesota

14,420

16,236

1,816

12.6%

Mississippi

2,695

1,316

-1,379

-51.2%

Missouri

7,315

7,518

203

2.8%

Montana

465

348

-117

-25.2%

Nebraska

4,130

5,635

1,505

36.4%

Nevada

9,445

16,479

7,034

74.5%

New Hampshire

1,155

1,200

45

3.9%

New Jersey

38,670

45,814

7,144

18.5%

New Mexico

5,720

8,132

2,412

42.2%

New York

83,310

116,822

33,512

40.2%

North Carolina

27,890

29,232

1,342

4.8%

North Dakota

415

1,009

594

143.1%

Ohio

13,525

11,687

-1,838

-13.6%

Oklahoma

5,935

7,622

1,687

28.4%

Oregon

10,925

7,455

-3,470

-31.8%

Pennsylvania

16,150

16,138

-12

-0.1%

Rhode Island

4,610

2,900

-1,710

-37.1%

South Carolina

11,865

6,716

-5,149

-43.4%

South Dakota

1,835

1,020

-815

-44.4%

Tennessee

9,800

16,325

6,525

66.6%

Texas

130,990

116,818

-14,172

-10.8%

Utah

7,410

17,145

9,735

131.4%

Vermont

645

567

-78

-12.1%

Virginia

25,835

21,440

-4,395

-17.0%

Washington

24,375

24,997

622

2.6%

West Virginia

200

175

-25

-12.5%

Wisconsin

8,805

6,608

-2,197

-25.0%

Wyoming

1,085

191

-894

-82.4%

Total

1,082,260

1,215,881

133,621

12.3%

Source: Table prepared by CRS, June 2007, based on data provided by the U.S. Department of Education (ED), Budget Service. The 2003-2004 immigrant student counts are based on data provided by states in their Title III biennial reports (Biennial Evaluation Report to Congress on the Implementation of the State Formula Grant Program, 2002-2004.)

Note: The American Community Survey (ACS) is administered by the U.S. Census Bureau. The Census Bureau provides ED with specific data runs from the most recent ACS to enable ED to calculate Title III grants.

Estimated FY2007 State Grants

An analysis of the differences in estimated FY2007 grant amounts if the aforementioned state data, rather than the 2005 ACS data, were used to determine grant amounts revealed that grant amounts would change in most states, in some cases increasing or decreasing by substantial amounts. For example, if state data, rather than ACS data, had been used to calculate the FY2007 grant amounts, California's grant amount would have increased by $34.2 million or 20.2% (Table 7). Other states that would have experienced substantial increases in their FY2007 grant amounts include Florida ($7.8 million or 19.2%), Utah ($4.4 million or 123.7%), and New Mexico ($4.3 million or 100.2%). One interesting trend to note is the general reduction in state grant amounts that would occur in Northeast states (e.g., Connecticut, Maine, Massachusetts, New Hampshire, New Jersey, New York, Pennsylvania, and Rhode Island), if state data were used to calculate grant amounts. Overall, increases would have ranged from $20,000 in South Dakota to $34.2 million in California. The largest loss of funds would have been experienced by New York ($10.9 million or 24.3%), followed by New Jersey ($7.0 million or 38.5%), Georgia ($5.7 million or 37.5%), and Pennsylvania ($5.4 million or 47.2%). Overall, the decreases would have ranged from $12,000 in Kansas to $10.9 million in New York. With respect to the percentage change in grant amount, Alaska would have received the largest increase (262.1%), and Mississippi would have experienced the largest decrease (55.2%).

Table 7. Estimated FY2007 State Grants Based on the 2005 American Community Survey and State-Reported Data

A

B

C

D

E

State

Estimated
FY2007 Grants
(2005 ACS)

Estimated
FY2007 Grants (State Data)

$ Difference Between FY2007 Grants Based on State Data Versus ACS Data
(Col C - Col B)

Percent
Difference

Alabama

3,277,000

2,103,000

-1,174,000

-35.8%

Alaska

651,000

2,356,000

1,705,000

261.9%

Arizona

19,664,000

20,623,000

959,000

4.9%

Arkansas

2,721,000

2,387,000

-334,000

-12.3%

California

169,058,000

203,216,000

34,158,000

20.2%

Colorado

9,812,000

11,571,000

1,759,000

17.9%

Connecticut

5,460,000

4,641,000

-819,000

-15.0%

Delaware

1,354,000

695,000

-659,000

-48.7%

District of Columbia

593,000

663,000

70,000

11.8%

Florida

40,669,000

48,478,000

7,809,000

19.2%

Georgia

15,123,000

9,451,000

-5,672,000

-37.5%

Hawaii

2,578,000

2,549,000

-29,000

-1.1%

Idaho

1,833,000

2,105,000

272,000

14.8%

Illinois

27,485,000

27,758,000

273,000

1.0%

Indiana

6,580,000

4,626,000

-1,954,000

-29.7%

Iowa

2,523,000

1,921,000

-602,000

-23.9%

Kansas

3,390,000

3,378,000

-12,000

-0.4%

Kentucky

2,797,000

1,743,000

-1,054,000

-37.7%

Louisiana

2,176,000

1,243,000

-933,000

-42.9%

Maine

566,000

500,000

-66,000

-11.7%

Maryland

9,135,000

4,500,000

-4,635,000

-50.7%

Massachusetts

11,022,000

8,024,000

-2,998,000

-27.2%

Michigan

10,373,000

8,370,000

-2,003,000

-19.3%

Minnesota

6,708,000

7,886,000

1,178,000

17.6%

Mississippi

1,314,000

589,000

-725,000

-55.2%

Missouri

3,619,000

2,435,000

-1,184,000

-32.7%

Montana

500,000

804,000

304,000

60.8%

Nebraska

2,382,000

2,336,000

-46,000

-1.9%

Nevada

6,009,000

9,614,000

3,605,000

60.0%

New Hampshire

772,000

500,000

-272,000

-35.2%

New Jersey

18,222,000

11,208,000

-7,014,000

-38.5%

New Mexico

4,338,000

8,684,000

4,346,000

100.2%

New York

44,717,000

33,853,000

-10,864,000

-24.3%

North Carolina

12,261,000

10,628,000

-1,633,000

-13.3%

North Dakota

500,000

626,000

126,000

25.2%

Ohio

7,685,000

3,961,000

-3,724,000

-48.5%

Oklahoma

3,375,000

4,464,000

1,089,000

32.3%

Oregon

7,633,000

7,391,000

-242,000

-3.2%

Pennsylvania

11,343,000

5,984,000

-5,359,000

-47.2%

Puerto Rico

3,086,000

3,086,000

0

0.0%

Rhode Island

2,078,000

1,495,000

-583,000

-28.1%

South Carolina

4,288,000

2,358,000

-1,930,000

-45.0%

South Dakota

729,000

749,000

20,000

2.7%

Tennessee

4,781,000

3,717,000

-1,064,000

-22.3%

Texas

87,896,000

87,415,000

-481,000

-0.5%

Utah

3,538,000

7,916,000

4,378,000

123.7%

Vermont

500,000

500,000

0

0.0%

Virginia

10,295,000

9,621,000

-674,000

-6.5%

Washington

12,795,000

10,824,000

-1,971,000

-15.4%

West Virginia

500,000

500,000

0

0.0%

Wisconsin

5,976,000

4,630,000

-1,346,000

-22.5%

Wyoming

500,000

500,000

0

0.0%

Total

617,177,000

617,177,000

0

0.0%

Source: Table prepared by CRS, June 2007. Estimated FY2007 state grants based on the American Community Survey (ACS) were calculated by the U.S. Department of Education (ED), Budget Service. Estimated FY2007 state grants based on state-reported data were calculated by CRS using 2004-2005 limited English proficient student (LEP) counts available from the National Clearinghouse for English Language Acquisition and Language Instruction Educational Programs, and 2003-2004 immigrant student count data available based on data provided by states in their Title III biennial reports (Biennial Evaluation Report to Congress on the Implementation of the State Formula Grant Program, 2002-2004.)

Note: All data sources used to make these calculations were the most recent data sources available. State-reported data were used from two different years because the LEP student counts account for 80% of a state's grant and more recent data were available for LEP student counts than for immigrant student counts. In addition, the use of the 2004-2005 LEP student count data was more comparable to the 2005 ACS data than the 2003-2004 LEP student count data would have been. Details may not add to totals due to rounding.

Notice: These are estimated grants only. In addition to other limitations, much of the data which would be needed to calculate final grants are not yet available. These estimates are provided solely to assist in comparisons of the relative impact of alternative formulas and funding levels in the legislative process. They are not intended to predict specific amounts states will receive.

Selecting Data on Which To Base the Distribution of Funds

The use of either the ACS or state data for calculating Title III state grants has drawbacks. This section examines the methodological issues associated with using either the ACS data or state data as the basis for distributing state grants. It also examines issues specific to counting LEP students and counting recent immigrant students. The section concludes with a brief discussion of the requirement that ED use the most accurate of these data sources to allocate state grants.

ACS Data

As previously discussed, the ACS data measure factors that are not necessarily related to student enrollment, and there may be data problems due to the subjective nature of the questions and the reliance on self-reported data. For example, respondents to the ACS may not want to report that they speak English less than "very well," as this may be perceived as a socially undesirable response. Although these problems are consistent across states, the Census Bureau found some inconsistency in responses to these questions during its reinterview process to examine data quality.13 In addition, there is no research available that demonstrates how accurately the ACS data represent the population of LEP students.14 If these data continue to be used as the basis for distributing state grants, developing a better understanding of this relationship may be critical.

The estimates of the number of students who are recent immigrants are also based on self-reported data. However, the question used to make this determination is more objective than the question used to determine whether a student is LEP, as it asks for factual information. Thus, responses to this question may be more consistent than the questions used to determine LEP.15

State-Reported Data

State-reported data also have several problems that could complicate their use as the basis for determining state grants. In responding to a GAO study examining the Title III formula, ED indicated that state data were missing or incomplete for several states.16 ED also noted that states did not necessarily assess all LEP students, which could result in the number of students identified as being LEP exceeding the number of students assessed annually for English language proficiency (as required by Title I of the ESEA).17 In addition, ED noted that states may have provided inconsistent data because the instructions to states for providing this information did not include definitions of the data to be included. GAO found that the aforementioned instructions were sufficiently vague as to allow multiple interpretations of the instructions, and reported that ED had indicated that it would clarify the instructions for the 2006-2007 Consolidated State Performance Report (due in December 2007). ED was also in the process of providing feedback to states on the data provided on the 2003-2004 and 2004-2005 CSPRs and expected that this would lead to improved state data for subsequent school years. Until these data are reported by states, however, it is not possible to know how complete these data will be and whether additional followup, such as the efforts conducted by NCELA regarding the 2004-2005 data, will be needed to produce final counts that could be used as the basis for determining state grants.

These issues are further complicated due to the different methodologies used to identify which students are LEP students, as there is no standard methodology by which students with limited English proficiency are identified. Screening instruments used to identify LEP students vary by state and even within states. Even among states using similar methods, the states may differ in their interpretation of the results. States may also differ in how they determine which students to screen for LEP. Although most states use home language surveys to determine what language is spoken at home, some states may also use strategies such as classroom observations to identify students for screening.

There are also problems with immigrant student counts reported by states. GAO found that state officials question the reliability of the data they collect, as schools and school districts may not be permitted to ask students directly whether they are immigrant students.18 Rather, some states and districts rely on information about a student's place of birth and date of entry into the school system to determine whether a student is a recent immigrant. These determinations may be further complicated if a student has no prior school documentation, so there is no way to determine based on student records whether the student previously attended another school in the United States and for how long.

It should be noted, however, that if grants are determined on the basis of state-reported data, possibly through the CSPRs, a perverse incentive may be created for states to over-report the number of LEP and immigrant students to gain additional federal funds. As the funds available for this program are limited to a specific appropriation amount, if some states inflate their number of eligible students, other states legitimately serving Title III eligible students may receive less funding than they should receive.

Data Accuracy

Although statutory language permits ED to choose the most accurate of the ACS or state data, ED told GAO that is has not yet established criteria or a methodology for determining which of these data sources is the most accurate.19 According to the GAO report, "Education officials state that as the state data improve and become complete, complex analysis will be needed to determine the relative accuracy of these data and the ACS data."20 Thus, until this analysis is completed by ED or another organization, it may be difficult to determine whether the use of ACS data or state data will result in a grant distribution that most accurately reflects the number of LEP and recent immigrant students by state.

Possible Alternatives

Given the drawbacks in using either the ACS or state-reported data as the basis for determining state grants, other alternatives could be considered. As previously mentioned, no research demonstrates that the ACS data accurately reflect the actual LEP student population. One option may be to require the National Academy of Sciences (NAS) to conduct a study to examine the methodology used to produce the ACS data on which Title III state grants are currently based, the availability of alternative indicators, and the reliability of the data. NAS was required to conduct a similar study of the Small Area Income and Poverty Estimates (SAIPE) data used for Title I purposes (Improving America's Schools Act, P.L. 103-382, Title I, Section 1124(c)(4)). In addition or alternatively, developing a formula based on both the ACS data and the state-reported data could be considered, possibly averaging the student counts from each. This strategy could be used on a long-term basis or as a means of transitioning from the use of ACS data to state data to determine state grants. Using both types of data simultaneously, however, would require state data and ACS data to be available from comparable years. A third alternative, specifically designed to reduce the volatility of the ACS data, would be to average the LEP student counts produced by the ACS for the last two or three available years, and do the same for the ACS immigrant student counts.

Footnotes

1.

Statutory language defines a limited English proficient student to be a student (1) who is between the ages of 3 and 21, (2) who is enrolled or is preparing to enroll in an elementary or secondary school, (3) who was not born in the United States or whose native language is a language other than English, who is a Native American or Alaska Native, who is a native of the outlying areas, who comes from an environment where a language other than English has had an impact on the student's level of English language proficiency, or is a migratory student whose native language is not English and who comes from an environment where English is not the dominant language, and (4) whose difficulties in speaking, reading, writing, or understanding English may prevent the student from reaching the proficient level on state assessments required under Title I, succeeding in classrooms where English is the language of instruction, or participating fully in society (Section 9101). Statutory language defines an immigrant student as an individual 3 to 21 years old who was not born in any state and has not been attending a school in the United States for more than three full academic years (Section 3301). These latter students are referred to as immigrant or recent immigrant students throughout this report.

2.

Through FY2005, a reservation was also made to provide continuation grants for competitive grants awarded prior to the enactment of the NCLBA.

3.

For the purposes of this report, the term "state" includes the District of Columbia and the Commonwealth of Puerto Rico.

4.

More specifically, Section 1111(b)(7) requires states to assess the English language skills of students with limited English proficiency on an annual basis.

5.

Testimony provided by Cornelia M. Ashby to the House of Representatives, Committee on Education and Labor, Subcommittee on Early Childhood, Elementary and Secondary Education. (March 23, 2007). Impact of NCLB on English Language Learners. (Hereafter referred to as Ashby testimony.)

6.

U.S. Government Accountability Office. (2006). No Child Left Behind Act: Education's Data Improvement Efforts Could Strengthen the Basis for Distributing Title III Funds (GAO-07-140). Available online at http://www.gao.gov. (Hereafter referred to as GAO, Basis for Distributing Title III Funds.)

7.

Ibid., p. 10.

8.

Information about how NCELA produces LEP student counts was provided by NCELA staff members, Dr. Judith Wilde and Suzanne Abdelrahim.

9.

The CCD uses the term English language learners (ELL) rather the LEP. The term LEP was used until the 2001-2002 school year. For consistency, the term LEP is used throughout this report.

10.

For example, students may not receive LEP services if their parents do not want them to participate.

11.

For several states, data are either not available, or data were missing for more than 20% of schools or districts in a state, so the data were not publicly reported.

12.

The percentage change in the number of students is calculated relative to the number of LEP students identified on the ACS. As California has the largest number of students based on the ACS counts, having the largest increase in the number of students based on the state data is not a large enough increase relative to California's initial LEP student count to result in the largest percentage increase among the states.

13.

Schneider, P. (2004). Census 2000 Testing, Experimentation, and Evaluation Program (Topic Report No. 12, TR-12). Washington, DC: U.S. Census Bureau. Available online at http://www.census.gov/pred/www/rpts/TR12.pdf.

14.

GAO, Basis for Distributing Title III Funds.

15.

Ibid.

16.

Ibid.

17.

As previously noted, ED must use the most accurate of either the ACS data or the number of children being assessed for English proficiency as required under Title I.

18.

Ibid.

19.

Ibid.

20.

Ibid., p. 13.