ࡱ> tvs@ _xjbjbܡܡ EFrl$PBV $$$$$$  , ^ $$$$$ z$$zzz$$$ zN$ z&z  , k  czc z THE BEST SCHOOL DISTRICTS IN TEXAS FOR AFRICAN AMERICAN STUDENTS 1998-2001 A REPORT OF THE TEXAS EDUCATIONAL EXCELLENCE PROJECT Number 17 June 2002 Kenneth J. Meier Texas A&M University Robert D. Wrinkle J. L. Polinard University of Texas-Pan American For further information contact: http://teep.tamu.edu 979-458-0104 or in South Texas Robert D. Wrinkle, Department of Political Science, University of Texas, Pan American, 956-381-3341 rdwe116@panam1.panam.edu The Texas Educational Excellence Project (TEEP) is a joint program of the Departments of Political Science at Texas A&M University and the University of Texas-Pan American. TEEP seeks to apply scholarly research to educational policy issues in order to make recommendations for greater quality and equity in Texas school systems. The Best School Districts in Texas for African American Students 1998-2001 Texas minority students continue to make impressive gains on the statewide TAAS exam. The results of the 2001 TAAS exam indicate that scores for African American students continue to close the gap with Anglo students. In 1996, only 46.9 percent of African American Students passed the TAAS compared to 79.8 percent of Anglo students. In 2001 72 percent African American students passing all tests compared to 90.4 percent of Anglo students. However, while African American students have made impressive gains over the past five years, the gap still remains substantial. Statewide averages, however, mask some impressive performance by individual school districts. The Texas Educational Excellence Project believes the first step in improving black tests scores is to identify school districts that do a better job of educating black students. Programs and policies in these districts can then be used by other districts to improve performance. The Hooks Independent School District provides one such example. TAAS pass rates for black students in Hooks have improved from 57.6 percent in 1996 to 88.6 percent in 2001. This dramatic improvement has resulted from a variety of efforts by school district leaders and teachers to identify effective programs and ensure district-wide implementation. Programs include early intervention programs implemented at lower grade levels to ensure students acquire fundamental skills. Hooks makes use of innovative technology and laptop computers to ensure that no student fails to get an adequate educational opportunity. The Hooks district is a relatively small district, and their approach might not be directly transferable to large urban school districts. Many urban schools, however, also get dramatic improvements. The Galena Park school district had an African American pass rate of 54% in 1996 and 85.8 percent in 2001. The Galena Park district achieved this improvement by working in an aligned curriculum and intensive teacher training. The Texas Educational Excellence Project uses a technique of analysis known as multiple regression to identify school districts that do a better job of educating black students. This analytical tool makes it possible to develop generalizations about the overall performance of Texas school districts in how well they educate black students, while also providing information that can be used to make comparisons across individual school districts. Our model is based on what is generally know as an education production function where student performance (defined as black pass rates on the TAAS) is a function of inputs into the educational process, such as operating expenditures, student-teacher ratios, and various educational policies. Estimation of this production function results in predictions about how well districts are expected to do, given the level of inputs available to them. Based on the results of the production function model, we compare how well districts actually perform to how well the statistical model predicts they should perform based on their inputs. The difference, if any, between the actual results and the predictions indicates how well districts are doing in educating black students. An Education Production Function School districts are organizations; they receive inputs (resources and students) from their environment and produce outputs (educated students among others). A vast literature has designated a variety of education production functions whereby the outputs of school systems can be evaluated relative to their inputs (Burtless 1996; Smith 1995; Hanushek 1986; 1989; 1996). Our dependent variable is the school districts pass rate for black students on the TAAS exam. Texas requires all school districts to administer exams to students in several grades on an annual basis. We make no claim that results on TAAS exams account for all of the overall learning experience of black students. Student performance is a multi-dimensional concept that can be measured in variety of different ways. However, pass rates on TAAS exams do measure whether students are picking up basic academic skills from grade to grade. Our dependent variable, therefore, focuses primarily on how well districts perform in teaching black students basic skills, and should not be construed as an overall measure of black student learning. The independent variables fall into four general types--environmental constraints, financial resources, teacher qualifications, and district policies. Environmental constraints are factors that restrict agency performance; in the case of education the key constraint is how difficult/easy it is to educate students. In the context of education policy, poverty is a serious constraint on student performance. The measures of constraint are the percent of poor students (defined as those eligible for free school lunches) and the percentage of black families that live in poverty. We also measure the educational level of blacks in the school district using the percentage of blacks in the school district over age 25 with at least a high-school diploma. The education variable should be positively related to student performance and the other two measures should be negatively related to black pass rates. Financial resources are the basic raw materials of any organization's attempt to meet its goals. Three measures of financial resources are included--per student instructional funds, average teacher's salary, and percent of funds received via state aid. These represent total resources devoted to education, the attractiveness of teaching positions in a competitive marketplace, and state efforts to overcome the unequal distribution of local financial resources. The relationship between expenditures and educational outcomes is one of the most contested questions in all of educational policy. Hanushek (1986; 1989; 1996) contends that there is no consistent relationship between money and student outcomes. Although this finding has been challenged by others (Hedges and Greenwald 1996), it remains the conventional wisdom. In recent longitudinal studies, however, Murray (1995), Evans, Murray and Schwab (1997), and Murray, Evans and Schwab (1995) found that districts that increased expenditures had improved performance afterward. Bohte (1999) found that expenditures were correlated with higher test scores even when controlling for the previous year's test scores. We consider expenditures a critical variable for inclusion in the model. All relationships should be positive. The two teacher qualification measures (or lack thereof) are the percent of teachers who hold a temporary certification in a subject specialty (as opposed to a permanent certification) and the average number of years of teacher experience. The relationship for non-certification should be negative, while the expectation is that more experienced teachers will lead to higher student outcomes. Finally, the education production function contains three policy measures--the percentage of students taking gifted classes, class size, and student attendance (percent attending on an average day). Performance should be positively related to gifted classes and attendance and negatively related to class size. Texas has a large number of school districts; many are very small or deal with a homogeneous student body. In an effort to use a set of organizations relatively similar in the task that they perform, we have restricted our analysis to school districts with a least 1000 students and at least 10 percent black students. These restrictions resulted in a total of 159 districts in the study. The data analysis is a pooled time series with data from the years 1998 through 2001. In any pooled time series one needs to control for serial correlation resulting from any trend in the variables over time. A series of dummy variables are introduced to achieve this. The basic production function is shown in table 1. Several variables are powerful predictors of black student pass rate. These include background, and policy variables. The black student pass rate is strongly influenced by the percentage of black adults age 25 and older with at least a high school education. Attendance also is strongly and positively related to the black student pass rate. The greater the percentage of low-income students in the district, the lower the black student pass rate. No other variable achieved statistical significance. The results of this model allow us to compare school districts as to how well they do above (or below) expectations. As an illustration, the model predicted that the New Boston Independent School District would have an average black pass rate of 70.06% from 1997-2001. New Bostons actual pass rate of 83.75 represents a 13.09 percentage point improvement over this standard. Based on this method, the top ranked school district for black students in Texas was Linden-Kildare with a rating of +23.05% followed closely by Ferris with a +20.04 score and Hooks with a +20.02 score. The top forty districts are shown in table 2. The first column is the numerical score on which the districts are ranked. The second column is the average pass rate for black students from 1998 to 2001 and the third column is the ranking score for 2001 only. These forty districts represent a variety of different types of school districts located throughout the state. Table 3 reports the 25 best districts for black students in 2001 only. The Cuero Independent School Districts performance in 2001 is striking in magnitude, moving from a 1998-2001 average of 0.73 to 10.41 for 2001 only, a gain of almost 10 percentage points on our score ranking. Recent gains are likely the result of the benefits of policies adopted earlier so these are the districts that are likely to continue to be rated highly in future studies. Although our top 25 includes districts of all sizes, large districts often cannot change as rapidly as small districts simply because so many students are involved. Table 4 presents the top ten large districts (those with 15,000 or more students). Galena Park, Aldine, Lamar Consolidated and Goose Creek top this list of large districts. The table in the Appendix gives an alphabetical listing of all of the school districts examined in this study, along with their scores. Any person interested in a specific school district can examine the Appendix to locate that district and identify the score and rank. Conclusion This study has identified those school districts in Texas that performed better than expected on the pass rate for black students. These districts can serve as role models for other districts in Texas. The districts have a wide variety of programs for early diagnosis, coordination of curriculum, and parental involvement. Not all of the districts use the same approach, indicating that success can be attained in a multiplicity of ways. If effective programs and performances from these districts are identified, then they can be transferred to other districts with an overall benefit to black students. Although this study only examines exemplary districts, that should not detract from the relatively low over-all pass rate for black students in Texas. A great deal of additional improvement is needed in these districts as well as other districts to close the test gap between black and Anglo students. Substantial progress has been made in the last few years; a great distance remains to be covered. Improving educational opportunities for all Texas children requires a long-term commitment to education. Problems develop over a period of decades; solutions require both time and hard work. Table 1. The Education Production Function __________________________________________________________ Independent Variable Slope Standard Error Low Income Students -.0963 .0311 Gifted Students .0978 .1007 Attendance 2.7002 .5111 Teacher Salaries (k) .3232 .2746 Class Size -.2044 .3977 Noncertified Teachers -.0413 .1096 Teacher Experience .1921 .2492 State Aid -.0088 .0198 Instructional Funding (k) 1.5703 1.5470 Black Education Levels .2023 .0636 Black Poverty -3.5773 4.4034 ________________________________________________________________ R-Square .31 Adjusted R-Square .30 F 21.66 N of cases 688 Table 2. Forty Best Districts for Black Students 1998-2001 Rank District Score TAAS 2001 Score 1 Linden-Kildare 23.05 92.70 23.00 2 Ferris 20.04 83.35 17.78 3 Hooks 20.02 85.47 17.88 4 Pittsburgh 19.92 85.30 12.79 5 Atlanta 19.81 88.32 18.19 6 Angleton 15.99 87.93 14.91 7 Sweeny 13.98 86.07 15.50 8 Newton 13.31 75.32 11.53 9 New Boston 13.09 83.75 17.79 10 Del Valle 12.50 73.55 11.75 11 McGregor 12.09 82.13 9.77 12 El Campo 12.05 77.70 10.00 13 Galena Park 11.18 78.30 13.01 14 Aldine 10.29 75.85 8.43 15 Columbia-Brazoria 10.18 77.13 14.66 16 Tatum 10.01 76.13 8.37 17 Kountze 9.73 73.40 11.89 18 Hillsboro 9.70 71.95 7.51 19 Sulpher Springs 9.26 78.72 9.48 20 Denison 9.07 75.80 15.42 21 Bay City 7.70 70.15 7.34 22 Texas City 7.55 74.03 4.30 23 Whorton 7.30 70.65 7.15 24 Rice Consolidated 6.84 68.55 8.51 25 Terrell 6.68 72.13 4.01 26 Lamar Consolidated 6.67 72.22 3.71 27 Goose Creek 6.64 72.20 7.02 28 Longview 6.56 71.47 6.08 29 Liberty-Eylau 6.35 72.18 0.99 30 Waco 6.23 65.90 5.61 31 La Grange 6.13 72.35 8.06 32 Garland 5.65 75.15 4.28 33 Daingerfield-Lone St 5.53 73.07 4.53 34 La Marque 5.23 70.63 4.69 35 Connally 5.02 75.20 -5.26 36 Sabine 4.75 74.10 -5.95 37 Kirbyville 4.67 68.07 9.13 38 Houston 4.64 66.90 5.84 39 Abilene 4.49 72.65 10.12 40 Commerce 4.48 69.50 -3.27 Table 3. The Twenty-Five Best Districts for 2001 Rank District 2001 Score 1 Linden-Kildare 23.00 2 Atlanta 18.19 3 Hooks 17.88 4 New Boston 17.79 5 Ferris 17.78 6 Sweeny 15.50 7 Denison 15.42 8 Angleton 14.91 9 Columbia-Brazoria 14.66 10 Queen City 13.17 11 Galena Park 13.01 12 Pittsburgh 12.79 13 Kountze 11.89 14 Del Valle 11.75 15 Newton 11.53 16 Cureo 10.41 17 Abilene 10.12 18 El Campo 10.00 19 McGregor 9.77 20 Sulpher Springs 9.48 21 Kirbyville 9.13 22 Rice Consolidated 8.51 23 Aldine 8.43 24 Tatum 8.37 25 La Grange 8.06 Table 4. The Best Large Districts (15,000 Students) Rank District Score TAAS 2001 Score 1 Galena Park 11.18 78.30 13.01 2 Aldine 10.29 75.85 8.43 3 Lamar Consolidated 6.67 72.22 3.71 4 Goose Creek 6.64 72.20 7.02 5 Waco 6.23 65.90 5.61 6 Garland 5.65 75.15 4.28 7 Houston 4.64 66.90 5.84 8 Abilene 4.49 72.65 10.12 9 Grand Prairie 3.47 73.05 -1.36 10 Beaumont 3.36 68.15 0.95 References Bothe, John, 1999. "Class Size, Teacher Salaries and Student Performance." College Station, TX: Texas Educational Excellence Project. Burtless, Gary. 1996. Does Money Matter? The Effect of School Resources on Student Achievement and Adult Success. Washington, D.C.: Brookings Institution. Hanushek, Eric A. 1986. "The Economics of Schooling: Production and Efficiency in Public Schools." Journal of Economic Literature 24:1141-77. Hanushek, Eric A. 1989. "The Impact of Differential Expenditures on School Performance." Educational Researcher 23 (4): 45-65. Hanushek, Eric A. 1996. "School Resources and Student Performance." In Does Money Matter? The Effect of School Resources on Student Achievement and Adult Success, Gary Burtless, ed. Washington, D.C.: Brookings Institution. Hedges, Larry V. and Rob Greenwald. 1996. "Have Times Changed? The Relation between School Resources and Student Performance." In Does Money Matter? The Effect of School Resources on Student Achievement and Adult Success, ed. Gary Burtless. Washington: Brookings. Murray, Sheila E. 1995. "Two Essays on the Distribution of Education Resources and Outcomes." PhD. diss. Department of Economics, University of Maryland. Murray, Sheila E., William N. Evans and Robert M. Schwab. 1995. "Money Matters After All: Evidence From Panel Data on the Effects of School Resources." University of Kentucky and University of Maryland working paper: The Martin School. Smith, Kevin B. 1995. "Policy, Markets, and Bureaucracy: Reexamining School Choice." Journal of Politics 56 (May), 475-491. Appendix. Scores for All Districts Rank District Score TAAS 2001 Score 39 Abilene 4.49 72.65 10.12 14 Aldine 10.29 75.85 8.43 93 Alief -1.73 68.70 -4.41 57 Amarillo 2.53 65.68 2.56 59 Anahuac 2.22 67.78 -4.33 6 Angleton 15.99 87.93 14.91 119 Arlington -5.84 66.55 -3.22 151 Athens -11.48 55.08 -12.56 5 Atlanta 19.81 88.32 18.19 146 Austin -10.42 53.80 -8.14 48 Bastrop 3.39 66.68 1.07 21 Bay City 7.70 70.15 7.34 50 Beaumont 3.36 68.15 0.95 143 Bellville -8.87 57.83 -5.81 150 Brenham -11.38 53.88 -7.29 70 Bryan 0.75 63.50 3.53 108 Caldwell -4.18 62.08 -2.38 95 Cameron -1.86 63.03 -8.10 156 Carthage -13.67 54.20 -11.78 142 Cedar Hill -8.79 67.32 -6.74 68 Center 0.81 63.63 -1.90 53 Channelview 2.90 72.20 1.27 154 Chapel Hill -12.88 52.35 -12.14 133 Clarksville -7.28 57.90 2.38 145 Cleveland -10.14 49.15 -9.34 139 Cold Spring-Oakhurst -8.44 49.55 3.72 148 College Station -11.31 62.63 -7.32 15 Columbia-Brazoria 10.18 77.13 14.66 135 Columbus -7.96 62.30 -7.01 40 Commerce 4.48 69.50 -3.27 35 Connally 5.02 75.20 -5.26 136 Corrigan-Camden -8.15 53.90 -15.42 114 Corsicana -5.02 57.33 -2.64 153 Crockett -12.13 48.95 -12.09 85 Crosby -0.95 68.65 -0.32 43 Crowley 3.84 81.13 0.57 71 Cureo 0.73 66.28 10.41 33 Daingerfield-Lone St 5.53 73.07 4.53 124 Dallas -6.27 59.20 -6.83 10 Del Valle 12.50 73.55 11.75 20 Denison 9.07 75.80 15.42 94 Denton -1.82 66.03 -1.38 67 DeSoto 1.00 75.15 0.03 49 Diboll 3.39 65.15 1.19 122 Dickinson -6.15 56.35 -2.67 82 Duncanville -0.67 70.38 -1.05 74 East Central 0.02 69.60 -3.08 96 Edna -2.35 63.17 -11.34 12 El Campo 12.05 77.70 10.00 126 Elgin -6.36 56.65 -10.95 98 Ennis -2.96 64.03 0.18 52 Everman 3.07 70.93 5.20 132 Fairfield -7.26 62.20 -4.20 2 Ferris 20.04 83.35 17.78 80 Fort Bend -0.50 73.30 -1.56 100 Fort Worth -3.06 58.13 -2.49 88 Ft Sam Houston -1.18 80.72 -4.50 13 Galena Park 11.18 78.30 13.01 55 Galveston 2.85 62.35 2.88 32 Garland 5.65 75.15 4.28 117 Giddings -5.54 62.40 -2.60 106 Gilmer -3.78 61.80 1.28 118 Gladewater -5.64 60.65 -8.78 138 Gonzales -8.34 53.83 -3.46 27 Goose Creek 6.64 72.20 7.02 46 Grand Prairie 3.47 73.05 -1.36 144 Greenville -9.03 53.53 -2.22 63 Groesbeck 1.86 69.27 7.72 62 Hallettsville 1.90 71.75 4.75 79 Hardin-Jefferson -0.50 67.05 1.85 131 Hearne -7.17 52.88 -15.65 158 Hempstead -19.45 48.63 -11.56 125 Henderson -6.30 59.03 -7.33 18 Hillsboro 9.70 71.95 7.51 157 Hitchcock -14.14 51.33 -6.71 3 Hooks 20.02 85.47 17.88 38 Houston 4.64 66.90 5.84 99 Huntsville -2.98 63.63 0.52 61 Irving 2.02 74.25 0.30 129 Jacksonville -6.92 53.95 -13.67 72 Jasper 0.49 64.98 1.10 58 Jefferson 2.50 67.95 -2.17 75 Judson -0.09 71.43 -1.45 78 Kilgore -0.24 63.60 -2.74 76 Killeen -0.12 71.28 -3.45 37 Kirbyville 4.67 68.07 9.13 113 Klein -4.98 70.32 -5.72 17 Kountze 9.73 73.40 11.89 47 La Vega 3.45 67.45 2.43 34 La Marque 5.23 70.63 4.69 31 La Grange 6.13 72.35 8.06 26 Lamar Consolidated 6.67 72.22 3.71 128 Lancaster -6.68 60.75 -4.79 29 Liberty-Eylau 6.35 72.18 0.99 84 Liberty -0.77 67.10 -0.31 1 Linden-Kildare 23.05 92.70 23.00 104 Livingston -3.55 59.85 2.80 28 Longview 6.56 71.47 6.08 87 Lubbock -1.07 64.68 0.16 60 Lufkin 2.20 68.53 4.84 130 Madisonville -6.98 56.13 -0.15 92 Malakoff -1.56 63.33 2.48 120 Manor -5.85 58.63 -8.24 152 Marlin -11.96 50.33 -16.21 83 Marshall -0.75 64.63 4.38 11 McGregor 12.09 82.13 9.77 54 Mesquite 2.86 72.68 3.38 42 Mexia 3.98 69.88 2.25 121 Midland -5.99 58.63 -5.92 159 Mineola -23.44 46.53 -12.06 86 Mount Pleasant -1.05 64.28 2.23 103 Nacognoches -3.50 62.40 -5.33 102 Navasota -3.13 58.47 -3.67 9 New Boston 13.09 83.75 17.79 8 Newton 13.31 75.32 11.53 90 North Forest -1.37 60.03 -0.61 137 Palestine -8.28 57.42 -10.68 89 Paris -1.32 65.90 2.13 81 Pflugerville -0.53 73.60 -1.99 4 Pittsburgh 19.92 85.30 12.79 66 Port Arthur 1.39 59.33 4.46 41 Queen City 4.31 70.00 13.17 91 Randolph Field -1.51 82.65 -3.42 24 Rice Consolidated 6.84 68.55 8.51 141 Richardson -8.70 66.47 -6.88 45 Rockdale 3.50 71.52 -4.38 116 Royal -5.43 59.70 -4.20 115 Rusk -5.11 58.45 -6.21 36 Sabine 4.75 74.10 -5.95 147 San Antonio -10.76 52.60 -11.70 155 San Augustine -13.10 54.25 -13.93 110 Sealy -4.55 63.78 -3.45 105 Sheldon -3.65 67.28 -4.85 44 Shepherd 3.57 66.20 3.22 111 Sherman -4.76 62.72 -4.76 65 Silsbee 1.45 66.75 6.43 127 Smithville -6.61 58.42 -8.90 101 Spring -3.10 70.53 -4.21 51 Stafford MSD 3.27 77.90 -2.56 19 Sulpher Springs 9.26 78.72 9.48 7 Sweeny 13.98 86.07 15.50 16 Tatum 10.01 76.13 8.37 73 Taylor 0.30 65.85 -7.68 112 Teague -4.76 69.90 -9.54 123 Temple -6.24 61.17 -4.71 25 Terrell 6.68 72.13 4.01 109 Texarkana -4.52 60.05 0.35 22 Texas City 7.55 74.03 4.30 107 Tyler -3.82 64.93 1.43 30 Waco 6.23 65.90 5.61 149 Waller -11.33 57.35 -8.04 140 Waxahachie -8.49 60.88 -10.80 69 West Orange-Cove 0.78 63.88 7.61 56 West Oso 2.61 62.88 2.02 134 Westwood -7.72 60.75 -15.42 23 Whorton 7.30 70.65 7.15 64 Wichita Falls 1.47 69.43 1.63 77 Wilmer-Hutchins -0.23 55.65 -4.68 97 Yoakum -2.83 63.53 -2.63  PAGE 7 Q> 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