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4 State Procedures for Identifying and Classifying English Language Learners Although the Elementary and Secondary Education Act (ESEA) provides an official definition of a limited English proficiency (LEP) student, or English language learner (ELL) student, the act leaves it to states to operationalize the definition and to determine procedures for identifying students in need of Title III services. Figure 4-1 provides an overview of the classification and reclassification procedures. Every state has an initial identification process whereby it identifies the pool of linguistic minority students, assesses their level of English language proficiency (ELP) using either a brief ELP assessment (usually called a “screener” or a “placement test”) or a full-scale proficiency assessment, and determines which linguistic minority students are English language learners and therefore in need of Title III services. All states also have a process by which they annually assess ELL students’ progress in learning English, determine when they no longer need these services, and procedures for reclassifying students as former English language learners. Each state has developed its own approach, so the criteria for classification into and exit from ELL status, and the specialized services associated with it, vary across states. In addition, some states permit local control with respect to ELL classification and reclassification: the state sets forth general guidelines for ELL classification and exit criteria but allows local school districts to determine some or all of the criteria and performance standards for ELL classification and Title III services. Thus, in these states, the criteria can also vary from district to district. The criteria that states use for identifying students as ELL and as in need of Title III services ultimately determine the numbers that they report to the U.S. Department of Education (DoEd). Some states have relatively stringent entry criteria and relatively lenient exit criteria, which means they are providing Title III services only for students most in need. Other states have more lenient entry criteria and more
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FIGURE 4-1 ELL classification and reclassification procedures. aSome states use multiple exit criteria (e.g., a proficiency test, an academic achievement test, teacher’s judgment, local assessments, parental input, language team review, etc.). They may be administered or monitored simultaneously or meeting one criterion may be required to sequentially “trigger ” administration or review of others. bStudents who exit ESL must be followed for 2 years per federal law. On rare occasions, reclassified fluent English proficient students are judged to have been exited prematurely and are returned to ELL status to receive needed linguistic and academic services.
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stringent exit criteria, which means they are providing services to many students with English language difficulties and retaining them in the classification until they are ready to function without specialized language and instructional support services. If Title III funding is going to be based on the counts provided by the states, it is important to understand the policies, processes, and practices that lead to these counts and the ways that the policies, processes, and practices differ across the states. In this chapter, we compare the processes used by the states to classify students as ELL and therefore eligible for Title III services. After first commenting on the panel’s approach to obtaining the information, we discuss states’ procedures for initially classifying a student as an ELL. We then discuss states’ procedures for reclassifying students as “formerly English language learners” and exiting them from the ELL category and its attendant specialized services. In the final section of the chapter we discuss the reporting mechanisms under which the data on ELL students are gathered, assembled, forwarded, and maintained and the effects of those mechanisms. The committee relied on existing sources for information about state policies, practices, and criteria. The sources included several recent large-scale efforts to gather information on states’ procedures for identifying ELL students: extensive information by Bailey and Kelly (2010) on home language surveys; data from Wolf et al. (2008) on state (including the District of Columbia) policies, procedures, and criteria for the 2006-2007 school year; an in-depth study by Ragan and Lesaux (2006) of the procedures in place during the 2004-2005 school year in 10 states and 10 school districts with high enrollments of ELL students;1 and a study by Porta and Vega (2007) about states’ procedures and their ELP tests. These studies provided a snapshot of policies and practices prior to 2008-2009. For information about policies, procedures, and criteria in place in 2008-2009, the panel held focused reviews and discussions with officials in seven states: California, Colorado, New York, North Carolina, South Carolina, Texas, and Washington, all of which have high ELL student enrollments. In addition, we conducted a survey of state Title III administrators to update the information about the assessments their states use. 1 The states of California, Texas, Florida, New York, Arizona, Illinois, Colorado, New Mexico, Georgia, and New Jersey (listed in order by size of ELL student enrollment) and the districts of Los Angeles, New York City, Dade County, Chicago, Houston, Santa Ana, San Diego, Long Beach (CA), Clark County (NV), and Broward County (FL).
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INITIAL CLASSIFICATION OF STUDENTS Home Language Surveys The first step toward students’ initial classification as an ELL student, as shown on the left-hand side of Figure 4-1, is administration of a brief questionnaire referred to as the home language survey (HLS). Use of an HLS to identify linguistic minority students originated with the remedies implemented in 1975 after the Supreme Court decision in the Lau v. Nichols discrimination case.2 Although school systems are not required to use an HLS under federal law, Title III does require states to identify students in need of language support services, defining such individuals in terms of coming from “an environment where a language other than English has had a significant impact on the individual’s level of English language proficiency” (Bailey and Kelly, 2010, p. 1). In the absence of federal guidance, all states have recommended, and most have required, the use of an HLS as the first step in identifying students that are potentially in need of language support services. States and local school districts vary with regard to administering the HLS, beginning with when the questionnaire is administered. In some states, it is routinely administered to all students at the time of enrollment. Typically, the school official that handles new school enrollments asks the questions of the parent(s) or other adult guardian enrolling the child. In other states, the questionnaire is administered only to students who are referred for ELL services: referrals are typically made by parents and teachers. The questionnaires also differ with respect to the phrasing and content of the questions asked and with respect to the state regulations for implementation and interpretation of responses for further screening and assessment (Bailey and Kelly, 2010, p. 4). Further, some states are “local control states” and allow the school district to have final say over the questions used on the HLS. We asked officials in the seven states that we studied about the questions asked on their HLS and received the information below California: California is a local control state. The HLS includes, but is not limited to, the questions listed below. The local school district may add questions. Which language did your child learn when he/she first began to talk? Which language does your child most frequently speak at home? Which language do you (the parents or guardians) most frequently use when speaking with your child? Which language is most often spoken by adults in the home? (parents, guardians, grandparents, or any other adults) 2 See http://scholar.google.com/scholar_case?case=749115807849752427&q=lau+v.+nichols&hl=en&as_sdt=80000000000002&as_vis=1; http://www.pbs.org/beyondbrown/brownpdfs/launichols.pdf [November 2010].
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Colorado: Is a language other than English used in the home? Was the student’s first language other than English? Does the student speak a language other than English? New York: What language does the child understand? What language does the child speak most often? What language does the child read best? What language does the child write best? North Carolina: What is the first language the student learned to speak? What language does the student speak most often? What language is spoken in the home? South Carolina: What is the language that your child first learned? What language does the student speak most often? What language is most often spoken in the home? Texas: What language is spoken in the home most of the time? What language does the child speak most of the time? Washington: Is a language other than English spoken in the home? Did your child first speak a language other than English? What language did your child first speak? These examples illustrate the variety of questions used to initially identify students for ELL services in just a few states. (For a more comprehensive listing of state questions, see Bailey and Kelly, 2010.) In their analysis of the questions, Bailey and Kelly (2010) classify the differences along several dimensions. Some questions focus on the first or native language of the child; other questions focus on where the other language is spoken or what languages other than English are spoken; still others focus on the frequency with which the student speaks English, equating language dominance with proficiency. State practices for implementing an HLS also vary. In some states, the questions are standardized through a stateside mandated form. In states with local control, each school district determines the questions, often through use of sample question forms provided by the state that local school districts are encouraged to adopt. For
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instance, in Colorado and California, which have local control, the questions are recommended, but each district determines the exact questions to ask. States also differ with respect to follow-up to the HLS. When any response to an HLS suggests that the student may not be a native English speaker, some follow-up action is taken, generally within a prescribed time period of 30 days (Title III law, Part C-General Provisions, SEC. 3302(a)). Typically, the next step is to administer an initial assessment to evaluate the student’s level of English proficiency, although in some states, a parent or student interview may be conducted before deciding whether or not to administer a proficiency assessment. The validity of classifications based on the HLS has been questioned. For instance, Abedi (2008) noted that parents may not respond accurately because they misunderstand the questions, are worried about providing information that could lead to questions about their citizenship status, or are concerned that the ELL classification will lead to restricted educational opportunities for their child. These factors are likely to be more of an issue with recent immigrants or undocumented immigrants and in states with high populations of either group. In summary, most states use an HLS as the first step in the ELL classification process—the initial identification of students as linguistic minority and therefore potentially English language learners. However, the number and content of the questions, the administration procedures, and decision rules about the results vary from state to state and, in some states, from district to district. Initial English Language Proficiency Assessments The initial assessment of a student’s English language proficiency usually involves administering a test. States use a variety of tests for this purpose, which tends to affect the comparability of the state data. Some administer the full state ELP test that is used for federal annual accountability reporting. Other states use a brief proficiency assessment, often called a “placement test,” or a “screener.” The objective of these tests is to further determine the student’s level of proficiency in four language domains (speaking, listening, reading, and writing) after the initial HLS inquiry of language environment, preference, and use (typically in speaking) has signaled linguistic minority status. Table 4-1 shows the tests that each state uses for initial classification of students in need of Title III services. A majority, 27 states, use a screener test. Of these 27, 18 use one of the screener tests developed by the World-Class Instructional Design and Assessment (WID Consortium (the W-APT or the MODEL), 3 use the LAS Links Placement test, 4 use their own screener, 1 uses the LAB-R, and 1 uses the Woodcock Munoz Language Survey.3 Four states use their ELP test for the initial proficiency assessment (Alaska, Arizona, California, and Florida), while two states (Connecticut and Nevada) allow 3 For the full names of the tests, see Table 4-1.
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Allocating Federal Funds for State Programs for English Language Learners TABLE 4-1 Tests Used by the States for Initial Classification of English Language Learners for the 2009-2010 School Year State Test Used Type of Test Alabama W-APT WIDA Screener/placement test Alaska New IDEA Proficiency Test ELP test Arizona AZELLA ELP test (customized form of the SELP) Arkansas District chosen (LAS II or MAC II) Combination California CELDT ELP test Colorado CELA Placement test Screener/placement test Connecticut LAS Links Placement Test, LAS, or any ELP test any Screener/placement test or ELP test Delaware W-APT or MODEL WIDA Screener/placement test DC W-APT WIDA Screener/placement test Florida CELLA screener, LAS, or other test chosen by the district Combination Georgia W-APT WIDA Screener/placement test Hawaii LAS Links Placement Test Screener/placement test Idaho Idaho English Language Assessment (IELA) Screener/placement test Illinois W-APT, MODEL WIDA Screener/placement test Indiana LAS Links Placement Test Screener/placement test Iowa LAS, IPT (district chosen) Kansas KELPA, KEOPA-P, IPT, LAS, LAS Links, or LPTS (district chosen) Combination Kentucky W-APT WIDA Screener/placement test Louisiana District chosen Combination Maine W-APT or MODEL WIDA Screener/placement test Maryland LAS Links Placement Test Screener/placement test Massachusetts District chosen Combination Michigan ELPA Initial Screening Screener/placement test Minnesota District chosen Mississippi W-APT WIDA Screener/placement test Missouri W-APT WIDA Screener/placement test Montana District chosen Combination Nebraska District chosen Combination Nevada Pre-LAS or LAS Links Pre-LAS is a screener test; LAS Links is an ELP test New Hampshire W-APT WIDA Screener/placement test New Jersey District chosen Combination New Mexico W-APT WIDA Screener/placement test New York Language Assessment Battery-Revised (LAB-R) Screener/placement test N. Carolina W-APT or MODEL WIDA Screener/placement test N. Dakota W-APT WIDA Screener/placement test Ohio District chosen Combination Oklahoma W-APT WIDA Screener/placement test
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State Test Used Type of Test Oregon District chosen Pennsylvania W-APT WIDA Screener/placement test Rhode Island W-APT WIDA Screener/placement test S. Carolina District chosen (Woodcock Munoz Language Survey, LAS, IPT) Combination S. Dakota W-APT WIDA Screener/placement test Tennessee State developed test designed to be aligned with the ELDA Screener/placement test Texas District chosen Combination Utah District chosen Combination Vermont W-APT WIDA Screener/placement test Virginia W-APT, or district chosen WIDA Screener/placement test Washington WLPT-II Placement WLPT Screener/placement test (customized version of the SELP) W. Virginia Woodcock Munoz Language Survey Screener/placement test Wisconsin W-APT WIDA Screener/placement test Wyoming District chosen (but all used W-APT) WIDA Screener/placement test SOURCE: http://www.ncela.org; data confirmed by state Title III director. districts to choose between the state ELP test or the screener. In addition, 17 states allow districts to select the language proficiency assessment used for initial classification, though they generally provide a list of tests from which the district can select. Examples of Initial Classification Procedures Our discussions with Title III officials of the seven states we studied helped to clarify the steps and decisions involved in the initial classification process. The information is summarized below. California Students who are identified as having a primary language other than English based on the HLS, must be assessed on the California English Language Development Test (CELDT). The CELDT is the designated state test of English language proficiency. Therefore, pupils must achieve the English proficiency level on the CELDT to be classified as Initially Fluent English Proficient. To achieve the English proficient level on the CELDT, pupils at grades 2 through 12 must have an overall score of Early Advanced or above and all four domains (listening, speaking, reading, and writing) at Intermediate or above. Pupils in Kindergarten and grade 1 (K-1) must have an overall score of Early Advanced or above and listening and speaking domains at Intermediate or above. Students who do not score at this level are classified as ELL students.
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Colorado Students who are initially identified through the HLS are given a screener test, called the Colorado English Language Assessment (CELA) placement test. The screener assesses all four modalities (reading, writing, speaking, listening). A score of “Approaching Proficiency” or below indicates that ELL services are needed. New York A response other than English to any of the questions on the HLS triggers an informal interview conducted in the native language and in English. If the student speaks little or no English, the student is assessed with the Language Assessment Battery-Revised (LAB-R), the state’s screener test. Those who score below the proficient level are classified as ELL students. North Carolina Staff of the state’s English as a Second Language Program review the responses on the HLS, interview the parent or guardian as necessary, or observe the student to determine the home language. If it is determined that a student’s home language is other than English, the state’s screener test, the WIDA-ACCESS Placement Test (W-APT) is administered. For grades 1-12, those who score a composite of less than 5.0 or less than 5.0 on any of the four domains are identified as LEP students. For the first semester kindergarten W-APT, those who score less than 27 on listening and speaking are identified as LEP students. For the second semester kindergarten W-APT, those who score less than 27 on listening and speaking, less than 14 on reading, or less than 17 on writing are identified as LEP students. South Carolina If the response to any of the questions on the HLS is a language other than English, the student is further assessed. The state currently allows districts to choose from among the LAS, IPT, or Woodcock-Muñoz assessments. The state plans to adopt the ELDA placement test as an additional screener when the test becomes available. Texas A response other than English to either of the questions on the HLS triggers additional assessment. The local district is allowed to determine the assessment used for initial identification, provided it is one of the tests approved by the state education agency.4 For pre-K through 1st grade, districts are to use a test of oral language proficiency. For grades 2 and higher, students are given a norm-referenced achievement test in reading and language arts (such as the Iowa Test of Basic Skills). If the student scores below the 40th percentile, the case is sent to a review committee. Washington A response of “yes” to the second question on the HLS (“Did your child first speak a language other than English?) triggers additional evaluation with the state screener test, which is based on the SELP and called the WLPT-II (Washington Language Proficiency Test-II). Scoring at a level of 3 or below indicates 4 For a list of agency-approved tests for the 2010-2011 school year, see http://ritter.tea.state.tx.us/curriculum/biling/ListofApprovedTests2010_2011.pdf [December 2010].
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that the student is in need of ELL services. When responses to the HLS reveal that a language other than English is spoken in the home (first question) but the child speaks only English (second question), districts are required to follow up with the parent or guardian to ensure that the questions were clearly understood. ELL students are generally identified through the HLS, but teachers can also make referrals on the basis of their classroom observations. In summary, states use either the ELP test or a screener or placement test as the second step in the ELL classification process to determine which linguistic minority students are English language learners. However, the assessments and criteria used for initially classifying students as English language learners vary from state to state. In addition in some states, a variety of other criteria may be considered in the initial classification decisions. And in states that permit local control, the assessments and the criteria used for initially classifying students as English language learners may vary from district to district. CONCLUSION 4-1 Because of the differing state policies, practices, and criteria for initially identifying students as linguistic minority and for classifying them as an English language learner (ELL), individuals who are classified as ELL students in one state may not be classified as ELL students in another. In states that permit local control, students classified as ELL in one district may not be classified as ELL in another district in that state. RECLASSIFICATION OF ELL STUDENTS Criteria Considered Each year, all ELL students must be reassessed to evaluate their progress in learning English. Typically, students are given an ELP test, and those who score at the level that the state has defined as “English proficient” may be considered eligible for reclassification as a “former ELL” student. The proficiency level that is the threshold for reclassification is determined by the state. This step of the process is shown on the right-hand side of Figure 4-1 (above). In addition to scoring at the “English proficient” level on the ELP test, states consider a variety of other criteria in the reclassification process, such as performance on content area tests; input from school personnel; input from the parents or guardians; and other such measures as student grades, portfolios of the student’s work, student interviews, and evaluations of classroom performance. In local-control states, these criteria may differ by district within a given state. States use different combinations of these criteria, some using only the ELP test and some using as many as six different types of criteria. According to the information gathered by Wolf and colleagues (2008) for the 2006-2007 school year, 12 states consider only the ELP test score in reclassification
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FIGURE 4-2 Number of criteria used by states for ELL reclassification. NOTES: (a) Proficiency test scores, (b) content scores, (c) district-established criteria, (d) school personnel input, (e) parent or guardian input, (f) other. SOURCE: Wolf et al. (2008). Figure from Issues in Assessing English Language Learners: English Language Proficiency Measures and Accommodation Uses—Practice Review. National Center for Research on Evaluation, Standards, and Student Testing, University of California, Los Angeles. Copyright ©2008. The Regents of the University of California and supported under the Institute of Education Sciences, U.S. Department of Education. Available: http://www.cse.ucla.edu/products/reports/R732.pdf. Reprinted with permission. decisions, and 11 consider the ELP test and a second type of criterion—content-area achievement scores (7 states), district-level criteria (3 states), and other criteria (1 state): see Figure 4-2. Of the remaining states, 26 indicated that they use the ELP test and two other kinds of criteria, and 2 indicated that the criteria are established by districts and thus
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We obtained data on all four types of counts described above, but we focused our analyses on two of the counts, which we selected for conceptual reasons. The first is the unduplicated count of all students in the state who meet the ESEA definition of LEP (1 above). We judged that this count represented the most all-inclusive ELL estimate available from the states and is defined by law. However, as discussed earlier in this chapter, the law leaves it to states to operationalize this definition, and states’ policies, practices, and criteria affect their counts of students. And in local-control states, these policies, practices, and criteria may not be consistent across the state. We therefore decided to analyze a second count that we judged would provide a relatively objective measure across the states and would be relatively less susceptible to intrastate differences in local-control states: the number of students who were determined to be not proficient in English on a state’s ELP test (derived from 3 and 4 above). We refer to this count as “tested, not proficient.” As explained in Chapter 3, all states are required to determine a level of performance on the ELP test that defines when a student is “English proficient.” All districts within a state use the same test for this purpose, and the “English proficient” level is consistent throughout that state. When students meet this criterion, they are eligible for consideration for reclassification, although other criteria may come into play, which may differ both within a state and from state to state. So an ELL count based on those scoring proficient on the ELP test provides an estimate that is based on a criterion that is common across the state.8 For the most part, all of these data were available through the EDEN system and were provided to us by the DoEd. For the data that were not yet incorporated into the EDEN system, we obtained them through the Consolidated State Performance Reports (CSPRs), either from staff at the Department or from reports available online. The sources of the data used are indicated in the discussions below. Counts of all ELL Students Table 4-2 shows the numbers of ELL students in each state for the 2006-2007, 2007-2008, and 2008-2009 school years, listed in order by the average of these counts across the three school years. It also shows each state’s share of the total U.S. population of ELL students. Comparison of the data in Table 4-2 shows considerable year-to-year fluctuations in the absolute numbers of ELL students in some states. In Nevada, for example, which had the largest fluctuation, there was a decrease of about 23,000 ELL students, or about one-third, between 2006-2007 and 2007-2008 and a similar-sized increase between 2007-2008 and 2008-2009. Rhode Island also exhibited a fairly and the formats of those reports have changed considerably over the years and have been the same for many reports only since the 2006-2007 school year. Thus, we obtained data from the U.S. Department of Education beginning with the 2006-2007 school year. 8 We note, however, that reclassification policies, practices, and criteria define the population of students who take the proficiency test each year.
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TABLE 4-2 Numbers and Shares of All ELL Students by State: School Years 2006-2007, 2007-2008, and 2008-2009 State 2006-2007 2007-2008 2008-2009 3-Year Average Number Share* Number Share* Number Share* California 1,559,146.0* 36.4 1,553,091.0* 34.3 1,515,082.0 33.7 1,542,439.7 Texas 501,333.0 11.7 693,031.0 15.3 718,388.0 16.0 637,584.0 Florida 234,614.0 5.5 231,403.0 5.1 226,122.0 5.0 230,713.0 New York 196,153.0 4.6 210,359.0 4.6 183,952.0 4.1 196,821.3 Illinois 172,950.0 4.0 189,926.0 4.2 204,737.0 4.6 189,204.3 Arizona 152,753.0 3.6 149,721.0 3.3 125,636.0 2.8 142,703.3 North Carolina 87,745.0 2.0 127,449.0 2.8 113,823.0 2.5 109,672.3 Colorado 89,881.0* 2.1 85,323.0 1.9 88,907.0 2.0 88,037.0 Virginia 86,392.0 2.0 84,345.0 1.9 87,026.0 1.9 85,921.0 Washington 84,761.0 2.0 80,694.0 1.8 82,711.0 1.8 82,722.0 Georgia 74,132.0 1.7 79,987.0 1.8 80,890.0 1.8 78,336.3 Nevada 70,548.0 1.6 47,049.0 1.0 75,952.0 1.7 64,516.3 Oregon 61,914.0 1.4 62,111.0 1.4 63,011.0 1.4 62,345.3 Minnesota 63,858.0 1.5 61,229.0 1.4 61,486.0 1.4 62,191.0 Michigan 69,705.0 1.6 51,465.0 1.1 60,945.0 1.4 60,705.0 New Mexico 60,711.0 1.4 61,207.0 1.4 53,970.0 1.2 58,629.3 New Jersey 54,433.0* 1.3 54,503.0* 1.2 54,154.0 1.2 54,363.3 Massachusetts 54,071.0 1.3 55,730.0 1.2 49,073.0 1.1 52,958.0 Utah 48,399.0 1.1 46,770.0 1.0 44,470.0 1.0 46,546.3 Pennsylvania 45,431.0 1.1 46,357.0 1.0 47,672.0 1.1 46,486.7 Indiana 42,536.0 1.0 46,304.0 1.0 45,760.0 1.0 44,866.7 Wisconsin 41,312.0 1.0 43,790.0 1.0 47,866.0 1.1 44,322.7 Maryland 34,332.0* 0.8 40,421.0 0.9 40,051.0 0.9 38,268.0 Oklahoma 38,109.0 0.9 37,744.0 0.8 38,092.0 0.8 37,981.7 Ohio 29,240.0 0.7 35,038.0 0.8 36,376.0 0.8 33,551.3 Kansas 28,915.0 0.7 31,760.0 0.7 34,096.0 0.8 31,590.3 South Carolina 30,163.0 0.7 28,366.0 0.6 31,450.0 0.7 29,993.0 Connecticut 26,357.0 0.6 30,033.0 0.7 29,751.0 0.7 28,713.7 Arkansas 23,651.0 0.6 25,905.0 0.6 27,634.0 0.6 25,730.0 Tennessee 23,009.0 0.5 25,670.0 0.6 27,428.0 0.6 25,369.0 Alabama 18,358.0 0.4 20,943.0 0.5 19,523.0 0.4 19,608.0 Iowa 18,124.0 0.4 19,442.0 0.4 20,334.0 0.5 19,300.0 Missouri 22,365.0 0.5 19,053.0 0.4 16,338.0 0.4 19,252.0 Nebraska 18,190.0 0.4 19,128.0 0.4 18,394.0 0.4 18,570.7 Hawaii 15,660.0 0.4 18,681.0 0.4 18,564.0 0.4 17,635.0 Idaho 16,698.0 0.4 16,671.0 0.4 17,669.0 0.4 17,012.7 Alaska 20,761.0 0.5 16,823.0 0.4 12,030.0 0.3 16,538.0 Kentucky 10,816.0 0.3 12,896.0 0.3 14,589.0 0.3 12,767.0 Louisiana 8,629.0 0.2 11,474.0 0.3 12,497.0 0.3 10,866.7 Rhode Island 10,034.0 0.2 7,149.0 0.2 9,397.0* 0.2 8,860.0
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State 2006-2007 2007-2008 2008-2009 3-Year Average Number Share* Number Share* Number Share* Delaware 6,648.0 0.2 7,260.0 0.2 7,184.0 0.2 7,030.7 Montana 6,983.0 0.2 6,722.0 0.1 4,550.0 0.1 6,085.0 Mississippi 4,982.0 0.1 5,451.0 0.1 6,543.0 0.1 5,658.7 District of Columbia 4,717.0* 0.1 5,126.0 0.1 5,854.0 0.1 5,232.3 Maine 3,691.0 0.1 4,036.0 0.1 4,215.0 0.1 3,980.7 North Dakota 2,399.0 0.1 4,648.0 0.1 4,068.0 0.1 3,705.0 South Dakota 3,291.0 0.1 4,217.0 0.1 3,594.0 0.1 3,700.7 New Hampshire 3,149.0 0.1 3,201.0 0.1 4,076.0 0.1 3,475.3 Wyoming 3,006.0 0.1 2,395.0 0.1 2,277.0 0.1 2,559.3 West Virginia 2,248.0 0.1 2,336.0 0.1 1,618.0 0.0 2,067.3 Vermont 1,743.0 0.0 1,459.0 0.0 1,495.0 0.0 1,565.7 U.S. 4,289,046 100.0 4,525,892 100.0 4,499,072 100.0 4,438,033.3 NOTES: States are listed in order by the 3-year average of their reported numbers of ELL students. *The shares represent each state’s share of the total number of ELL students in the country. SOURCE: Data from the U.S. Department of Education, Education Data Exchange Network, except counts noted with an asterisk, which were obtained from the Consolidated State Performance Reports. large proportional swing, declining by about one-third, from about 10,000 to 7,100 students, between 2006-2007 and 2007-2008. Yet although the absolute numbers appear to fluctuate, the states tend to rank order quite similarly across the years in terms of their percentage share of the total ELL population in the country. For instance, the 11 states with the highest percentage shares of ELL students are the same across all 3 years. Approximately 75 percent of the nation’s ELL students in the country reside in these 11 states. Another way to think about the numbers of students served by each state is in relation to the total population of school-age children in the state. In effect, this percentage reflects the burden placed on the state: the percentage of its school-age population that needs Title III services. Table 4-3 shows each state’s count of all ELL students as the percentage of the total number of K-12 students enrolled in the state’s public schools,9 which we refer to as the state ELL rate. Comparison of these percentages across the 3 years shows that they tend to be 9 Data on the total number of K-12 students enrolled in the state’s public schools are from the Common Core of Data for the 2006-2007, 2007-2008, and 2008-2009 school years: see http://nces.ed.gov/ccd [November 2010].
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TABLE 4-3 Rates of All ELL Students by State: School Years 2006-2007, 2007-2008, and 2008-2009 2006-2007 2007-2008 2008-2009 Alabama 2.5 2.8 2.6 Alaska 15.7 12.8 9.2 Arizona 14.3 13.8 11.6 Arkansas 5.0 5.4 5.8 California 24.3 24.5 23.9 Colorado 11.3 10.6 11.1 Connecticut 4.6 5.3 5.2 Delaware 5.4 5.9 5.9 District of Columbia 6.5 6.5 7.5 Florida 8.8 8.7 8.5 Georgia 4.6 4.8 4.9 Hawaii 8.7 10.4 10.3 Idaho 6.2 6.1 6.5 Illinois 8.2 9.0 9.7 Indiana 4.1 4.4 4.4 Iowa 3.8 4.0 4.2 Kansas 6.2 6.8 7.3 Kentucky 1.6 1.9 2.2 Louisiana 1.3 1.7 1.8 Maine 1.9 2.1 2.1 Maryland 4.0 4.8 4.7 Massachusetts 5.6 5.8 5.1 Michigan 4.0 3.0 3.6 Minnesota 7.6 7.3 7.3 Mississippi 1.0 1.1 1.3 Missouri 2.4 2.1 1.8 Montana 4.8 4.7 3.2 Nebraska 6.3 6.6 6.3 Nevada 16.6 11.0 17.7 New Hampshire 1.5 1.6 2.0 New Jersey 3.9 3.9 3.9 New Mexico 18.5 18.6 16.4 New York 7.0 7.6 6.7 North Carolina 6.1 8.6 7.6 North Dakota 2.5 4.9 4.3 Ohio 1.6 1.9 2.0 Oklahoma 6.0 5.9 5.9 Oregon 11.0 11.0 11.1 Pennsylvania 2.4 2.6 2.6 Rhode Island 6.6 4.8 6.5 South Carolina 4.3 4.0 4.4 South Dakota 2.7 3.5 3.0 Tennessee 2.4 2.7 2.8 Texas 10.9 14.8 15.4 Utah 9.2 8.1 7.7 Vermont 1.8 1.6 1.6 Virginia 7.1 6.9 7.1 Washington 8.3 7.8 8.0 West Virginia 0.8 0.8 0.6 Wisconsin 4.7 5.0 5.5 Wyoming 3.5 2.8 2.6 NOTE: State rates of ELL students are calculated as the number of ELL students in the state divided by the number of K-12 students enrolled in public schools in the state. SOURCE: Data from the U.S. Department of Education, Education Data Exchange Network except counts noted with an asterisk, which were obtained from the Consolidated State Performance Reports.
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quite stable. However, there are still some fairly substantial changes. For example, Texas experienced an increase of about 5 percentage points in its rate of ELL students over the 3 school years, increasing from 10.9 percent in 2006-2007 to 15.4 percent in 2008-2009. In contract, over the same period, Alaska experienced a decrease of roughly 6 percentage points. The fluctuation in the absolute numbers of ELL students in Nevada also showed up in the data for the state rate, which was 16.6 percent in 2006-2007, 11.0 percent in 2007-2008, and 17.7 percent in 2008-2009. Counts of Tested, Not Proficient Students As noted above, states annually report the number of students who take their ELP test and the number of students who scored at the “English proficient” level.10 Because these counts were not available through the EDEN system, staff at the DoEd provided us with the counts for two school years, 2007-2008 and 2008-2009:11 see Table 4-4. The table lists the states in order by the average of the counts across the 2 school years. The table also shows each state’s share of the total population of ELL students in the country who were tested and determined to be not proficient in English. As with the counts of total ELL students (shown in Table 4-2 above), there were some fairly large differences in the absolute numbers across the 2 years. The largest increase was for Wisconsin, where the numbers more than tripled (from 12,865 students in 2007-2008 to 44,729 in 2008-2009). Colorado, Minnesota, and Virginia also saw fairly large increases, with their 2008-2009 counts roughly 50 percent higher than those for 2007-2008. In contrast, some states experienced decreases, the largest of which was Michigan, with a 31 percent decrease in absolute numbers from 2007-2008 to 2008-2009 (from 56,919 to 38,389). Despite the fluctuations in absolute numbers, the states tended to rank order quite similarly across the 2 years with regard to their shares of students. Rank orderings of the seven states with the highest shares remained nearly identical across the 2 school years. Comparison of state shares across the two types of counts (total ELL students and “tested, not proficient” students) also shows considerable similarity in the rank orderings. For instance, as can be seen by comparing Tables 4-2 and 4-4, the 16 states with the highest percentage shares are the same across the two counts; and the rank orderings of these states change only slightly across the two tables. For example, in Table 4-4, New York is ranked third and Florida is ranked fourth, and in Table 4-2, 10 We determined the number of students who scored below the proficient level by finding the difference between these two numbers. 11 These counts were not available for previous years because of differences in reporting and formatting. For the years of our analysis, counts were for all states except California for the 2008-2009 school year. In order to be able to include California in our analyses, we substituted the counts for the 2007-2008 school year for the missing data.
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TABLE 4-4 Numbers and Shares of ELL Students Reported Tested, Not Proficient for 2007-2008 and 2008-2009 School Years State 2007-2008 2008-2009 2-Year Average Number Sharea Number Sharea California 896,521 29.37% 896,521b 28.63% 896,521.0 Texas 460,680 15.09% 477,611 15.25% 469,145.5 New York 170,710 5.59% 166,212 5.31% 168,461.0 Florida 165,325 5.42% 161,734 5.16% 163,529.5 Arizona 126,675 4.15% 89,555 2.86% 108,115.0 Illinois 108,836 3.56% 101,507 3.24% 105,171.5 North Carolina 101,645 3.33% 93,150 2.97% 97,397.5 Colorado 53,340 1.75% 84,660 2.70% 69,000.0 Washington 67,425 2.21% 69,631 2.22% 68,528.0 Virginia 52,910 1.73% 83,538 2.67% 68,224.0 Nevada 63,642 2.08% 66,330 2.12% 64,986.0 Georgia 62,576 2.05% 62,999 2.01% 62,787.5 Oregon 55,390 1.81% 55,301 1.77% 55,345.5 Michigan 56,919 1.86% 38,389 1.23% 47,654.0 New Mexico 44,874 1.47% 43,824 1.40% 44,349.0 Minnesota 35,871 1.17% 52,452 1.67% 44,161.5 Indiana 38,334 1.26% 41,569 1.33% 39,951.5 New Jersey 38,953 1.28% 40,571 1.30% 39,762.0 Pennsylvania 36,007 1.18% 31,886 1.02% 33,946.5 Massachusetts 26,212 0.86% 36,354 1.16% 31,283.0 Ohio 29,584 0.97% 31,267 1.00% 30,425.5 Oklahoma 29,484 0.97% 28,477 0.91% 28,980.5 Wisconsin 12,865 0.42% 44,729 1.43% 28,797.0 Kansas 28,455 0.93% 27,003 0.86% 27,729.0 Utah 27,733 0.91% 27,666 0.88% 27,699.5 South Carolina 26,147 0.86% 27,937 0.89% 27,042.0 Maryland 19,718 0.65% 33,518 1.07% 26,618.0 Arkansas 23,612 0.77% 25,104 0.80% 24,358.0 Tennessee 19,376 0.63% 18,588 0.59% 18,982.0 Connecticut 18,535 0.61% 16,881 0.54% 17,708.0 Hawaii 15,085 0.49% 15,649 0.50% 15,367.0 Alabama 16,099 0.53% 12,490 0.40% 14,294.5 Missouri 12,185 0.40% 16,313 0.52% 14,249.0 Iowa 14,203 0.47% 14,197 0.45% 14,200.0 Alaska 14,183 0.46% 13,861 0.44% 14,022.0 Idaho 14,157 0.46% 10,530 0.34% 12,343.5 Nebraska 12,244 0.40% 12,044 0.38% 12,144.0 Kentucky 11,493 0.38% 12,771 0.41% 12,132.0 Louisiana 11,456 0.38% 10,206 0.33% 10,831.0 Rhode Island 5,741 0.19% 6,505 0.21% 6,123.0 District of Columbia 4,656 0.15% 4,664 0.15% 4,660.0 Delaware 3,089 0.10% 4,999 0.16% 4,044.0
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State 2007-2008 2008-2009 2-Year Average Number Sharea Number Sharea Maine 3,134 0.10% 3,789 0.12% 3,461.5 Mississippi 1,159 0.04% 5,645 0.18% 3,402.0 New Hampshire 2,840 0.09% 3,348 0.11% 3,094.0 North Dakota 4,257 0.14% 1,923 0.06% 3,090.0 South Dakota 2,846 0.09% 2,818 0.09% 2,832.0 Wyoming 1,872 0.06% 1,856 0.06% 1,864.0 Montana 1,572 0.05% 1,052 0.03% 1,312.0 Vermont 1,210 0.04% 1,208 0.04% 1,209.0 West Virginia 1,148 0.04% 853 0.03% 1,000.5 United States 43,052,983 3,131,685 NOTES: The numbers of tested, not proficient students were computed for each state by subtracting the number of all LEP (ELL) students proficient or above on a state’s proficiency test from the number of all LEP (ELL) students tested on the state annual ELP assessment. States are listed in order by the 2-year average of their numbers of ELL students determined to be tested, not proficient. aPercentages represent each state’s share of the tested, not proficient students in the country. bData not available; 2007-2008 count used so that state shares could be estimated. SOURCE: Data from the Consolidated State Performance Reports (CSPR) provided by the U.S. Department of Education. Florida is third and New York is fourth. Similarly, in Table 4-4, Arizona is fifth and Illinois is sixth, and in Table 4-2, Illinois is fifth and Arizona is sixth. These small differences in shares indicate that allocations based on the counts of all ELL students and allocations based on the counts of tested, not proficient students would be quite similar. The overall correlations between the shares for the two counts were 0.99 for both 2007-2008 and 2008-2009. Table 4-5 shows the state rates for the counts of tested, not proficient students. The rates in Table 4-5 show the count of tested, not proficient students as a percentage of the total population of school-age children in the state. For the most part, the state rates are similar across the 2 school years, with fluctuations generally in the range of 2-3 percentage points. The largest difference was in Wisconsin, where the increase in absolute numbers across the 2 school years resulted in an increase of the rate from 1.47 percent to 5.12 percent. Comparison of state rates across the two types of counts (Tables 4-3 and 4-5) reveals some differences: the overall correlations between the rates for the two counts were 0.92 for 2007-2008 and 0.95 for 2008-2009. Effect of Data Reporting Systems on Data Quality Although we have documented some anomalies in the state-provided counts of ELL students, they seem to be less prevalent in data for the most recent school
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TABLE 4-5 Rates of Tested, Not Proficient Students by State, 2007-2008 and 2008-2009 School Years (in percentage*) State 2007-2008 2008-2009 Alabama 2.16 1.68 Alaska 10.82 10.61 Arizona 11.65 8.23 Arkansas 4.93 5.24 California 14.13 N/A Colorado 6.65 10.34 Connecticut 3.25 2.98 Delaware 2.52 3.99 District of Columbia 5.94 6.79 Florida 6.20 6.15 Georgia 3.79 3.80 Hawaii 8.39 8.72 Idaho 5.20 3.83 Illinois 5.15 4.79 Indiana 3.66 3.97 Iowa 2.93 2.91 Kansas 6.08 5.73 Kentucky 1.73 1.91 Louisiana 1.68 1.49 Maine 1.60 1.97 Maryland 2.33 3.97 Massachusetts 2.72 3.79 Michigan 3.36 2.31 Minnesota 4.28 6.27 Mississippi 0.23 1.15 Missouri 1.33 1.78 Montana 1.10 0.74 Nebraska 4.20 4.12 Nevada 14.82 15.31 New Hampshire 1.41 1.69 New Jersey 2.82 2.94 New Mexico 13.64 13.27 New York 6.17 6.06 North Carolina 6.82 6.26 North Dakota 4.48 2.03 Ohio 1.62 1.72 Oklahoma 4.59 4.41 Oregon 9.79 9.82 Pennsylvania 2.00 1.80 Rhode Island 3.89 4.48 South Carolina 3.67 3.89 South Dakota 2.34 2.23 Tennessee 2.01 1.91
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State 2007-2008 2008-2009 Texas 9.85 10.05 Utah 4.81 4.94 Vermont 1.29 1.31 Virginia 4.30 6.76 Washington 6.54 6.71 West Virginia 0.41 0.30 Wisconsin 1.47 5.12 Wyoming 2.17 2.13 *Percentages are calculated as the number of test not proficient students in the state divided by the number of K-12 students enrolled in public schools in the state. SOURCES: Data are from the Consolidated State Performance Reports (CSPR) provided by the U.S. Department of Education. The numbers of tested, not proficient students were computed for each state by subtracting the number of all LEP students proficient or above on the state annual ELP assessment from the number of all LEP students tested on the state annual ELP assessment. year than in prior years. For instance, counts of total ELL students were missing for five states for the 2006-2007 school year but for only one state for the 2008-2009 school year. And for the 2 years we examined, only one state had missing data for the count of tested, not proficient students. The DoEd staff told us that they have worked on refining the instructions and formatting of the CSPRs and on ensuring that the EDEN data are accurate. The department has worked to remediate some of the earlier problems and developed a format for data elements that has been consistent for several years now. We also note that, in education, as in many other fields, there have been vast improvements in data availability and access in recent years. The local and state education agencies and the DoEd have been particularly driven to improve data to address new accountability provisions of the NCLB. Other factors have also influenced the recent advances in data availability, access, and quality. Standardization has been enhanced over the years by efforts such as the National Center for Education Statistics initiative to support the National Forum on Education Statistics, which brings together data system specialists from state agencies to focus on common data issues. The attention that has been paid to documenting the EDEN system and clarifying its specifications has also paid dividends. New initiatives—such as efforts to create quality longitudinal databases represented in the work of the Data Quality Campaign and recently augmented by $250 million in American Recovery and Reinvestment Act funding—have also begun to pay dividends in standardization of data elements and the development of sophisticated data systems to capture, analyze, and promulgate student data. Thus, while we find some issues with the quality and availability of data on ELL students, we recognize the significant improvements that have been made
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throughout the system, and are encouraged by new initiatives that continue to focus attention on further improvements. CONCLUSION 4-4 There are concerns about the accuracy of the compilation and reporting of state data to the Department of Education. However, there have been significant improvements in the collection and reporting of these data over the past several years, and systems show promise for further improvements in the coming years.
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