ࡱ>   Sbjbj<< -w^^cQ! ]]]=]IE-^.p.:..1"21 >1DH50155..<<<5eR..D6<5D<<BX"~D.V]J8v.D(DE0IEVD(I;^IP~DI~D$F1d2<033F1F1F1DD<dF1F1F1IE5555IF1F1F1F1F1F1F1F1F1 : July 2000 School of Urban and Public Affairs University of Texas at Arlington Center for the Study of Education Reform University of North Texas Center for Public Policy University of Houston Texas Center For Educational Research Austin Texas Open-Enrollment Charter Schools Third Year Evaluation Part Two Texas Open-Enrollment Charter School Evaluation Part Two Introduction to Part Two of the 1998-99 Evaluation 1 Section VI: Parental Participation and Satisfaction Levels 4 Introduction 4 How Did Parents Find Out About Charter Schools 7 Factors Affecting the Decision to Enroll in a Charter School 9 Parents' Expressed School Preferences 9 Behavioral Measures of Parent Preferences 10 Parent Satisfaction with Previous Schools 14 Parent Evaluation of Charter Schools 15 Parent Participation in the Schools 17 Additional Information Provided by the Survey 18 Summary 19 Section VII: Review of Demographics and Student Performance 21 Introduction 21 Definitions for Types of Schools 21 Classification of Charter Schools for this Analysis 21 Classification of Students for Analysis 22 Measure of Student Performance 23 Demographic Information 25 Data Sources and Analysis 25 Student Information 26 Staff Information 27 Revenue and Expenditures 27 Student Performance 31 School Level TAAS 31 Student Level TAAS 37 Student Engagement Measures 47 School Completion Measures 48 Summary 49 Section VIII: Charter School Revenues and Expenditures 51 Revenue Sources 53 Expenditures 54 Expenditures by Function 55 Expenditures by Object 59 Expenditures by Program 59 Summary 60 Section IX: Commentary and Policy Challenges 62 Data Disaggregation 62 Racial and Ethnic Diversity 63 Student Satisfaction 63 Parent Choices 64 Parent Satisfaction with Charter Schools 65 Effects on Public School Districts 65 Funding 65 Student Performance 66 Attendance and Dropout Rates 66 Appendix 67 Appendix A: Parents of Charter School ChildrenTelephone Survey Table of Tables Section VI VI.1 Charter Parent and Comparison Group Ethnicity 4 VI.2 Charter Parent and Comparison Group Educational Achievement 5 VI.3 Charter Parent and Comparison Group Income 5 VI.4 Weights for Race/Ethnicity 6 VI.5a How Did Charter Parents Find Out about Charter School? 7 VI.5b Do Parents of Traditional Public School Children Know about Charter Schools? How Do They Find Out about Them? 8 VI.6 What School Attributes Influence Parents' School Choices? 10 VI.7 Differences in Racial/Ethnic Compositions of Traditional and Charter Schools by Race 13 VI.8 Grades assigned by Charter Parents to Their Children's Previous Schools 14 VI.9 Charter Parent Satisfaction with Specific Characteristics of Previous Schools 15 VI.10 Grades assigned by Charter Parents to Charter Schools 16 VI.11 Charter Parent Satisfaction with Specific Characteristics of Charter Schools 17 VI.12 Charter Parent Participation at Previous School 18 VI.13 Charter Parent Participation at Charter School 18 VI.14 Placement Tests and Homework Contracts 19 VI.15 Charter School Provenance 19 Section VII VII.1 TEA Snapshot Data: Student Information, 1998-99 School Year 26 VII.2 TEA Snapshot Data: Staff Information, 1998-99 School Year 27 VII.3 TEA Snapshot Data: Revenue and Expenditures, 1998-99 School Year 28 VII.4 School Demographics and Characteristics by Group, 1998-99 School Year 29 VII.5 School Demographics and Characteristics: At-Risk and Non-at-Risk Charter Schools 30 VII.6 TEA Snapshot Data: 1999 TAAS Performance 32 VII.7 Charter Schools and TEA Peer Groups: Comparison of TAAS Performance 33 VII.8 Reporting and Comment Criteria Used in this Section. Student Level-Data 34 VII.9 Comparison of TAAS Performance Among At-Risk, Non-at-Risk Charter Schools and State Averages Over a Two Year Period 36 VII.10 Charter Schools Included in TAAS Calculations at Campus Level, Group 1 Subset 37 VII.11 Number of Charter School Students with TAAS Scores, by Type of School Attended the Test Year, 19971999 38 VII.12 TAAS Performance Change (TLI) for All Grade Levels 39 VII.13 TAAS Mastering All Objectives for All Grade Levels 41 VII.14 TAAS Performance Change 1997 (Grade 8) to 1999 (Grade 10) 42 VII.15 TAAS Percent Mastering All Objectives 1997 (Grade 8) to 1999 (Grade 10) 43 VII.16 Movement of Students Between TLI Categories, Grade 8 to Grade 10 44 VII.17 Change in TLI Over Three Years 45 VII.18 Student Performance Other Than TAAS 47 VII.19 Attendance by Charter School Type 48 VII.20 Student Performance Other Than TAAS 49 VII.21 Other Student Performance by Charter School Type 49 Graph Comparison of Student Reading Performance, by School Enrollment Type 46 Section VIII VIII.1 Charter Schools Classified as At-Risk and Non-at-Risk 52 VIII.2 Comparison of Revenue Sources for Traditional Public Schools and Charter Schools for 1998-99 53 VIII.3a Comparison of Per-Student State and Total Revenue for Traditional Public Schools and Charter Schools for 1998-99 54 VIII.3b Comparison of Charter School Per-Student Revenue for 1998-99 54 VIII.4 Charter School Expenditures by Function for 1997-98 55 VIII.5 Comparison of Charter School Expenditures by Function for 1996-97, 1997-98, and 1998-99 56 VIII.6 Charter School Budgeted Expenditures by Function for 1998-99 57 VIII.7 Operating Expenditures by Function, At-Risk and Non-at-Risk Schools, 1998-99 58 VIII.8 Objects of Expenditure by Percentage for Charter Schools for 1998-99 59 VIII.9 Percentage Comparison of Charter School Program Expenditures for 1997-98 and 1998-99 60 VIII.10 Percentage Comparison of Program Expenditures for Traditional Public Schools and Charter Schools for 1998-99 60 Introduction to Part Two of the Texas Open-Enrollment Charter Schools, Third Year Evaluation In 1995, the Texas Legislature provided for the creation of twenty open-enrollment charter schools (TEC 12.101-120). Open-enrollment charter schools are public schools that are substantially released from state education regulations and exist separate and apart from local independent school districts. They may be sponsored by an institution of higher education (public or private), a non-profit organization (501(c)(3)) as set out in the Internal Revenue Code, or a governmental entity. In 1997, the Texas Legislature provided for an additional 100 open-enrollment charter schools as well as an unlimited number of charter schools that would serve students at risk of failure or dropping out of school. To qualify as a school serving at-risk students, school enrollment must include at least 75 percent at-risk students. During the 1996-97 school year, 17 open-enrollment charter schools were operating in Texas. In 1997-98 the charter schools numbered 19. In 1998-99, 89 charter schools operated for the entire school year, 43 of which were schools designated to serve at-risk students. TEC 12.118 calls for the Texas State Board of Education to designate an impartial organization with experience in evaluating school choice programs to conduct an annual evaluation of open-enrollment charter schools. Three entities were designated jointly to evaluate open-enrollment charter schools by the State Board of Education. The first entity consists of researchers from the Center of Urban and Public Affairs at the University of Texas at Arlington; the second entity comprises researchers from the Texas Center for Educational Research partnered with the Center for the Study of Education Reform at the University of North Texas, and the third entity consists of researchers from the Center for Public Policy at the University of Houston. Together the researchers comprise the charter school evaluation team. The evaluation team gathered data from all schools reported to be in operation for the entire 1998-99 school year. Some analyses reported in the evaluation consider charter schools as a group, but in many cases an aggregate result fails to capture the wide variation among schools. In particular, charter schools that serve a predominantly at-risk population of students are often quite different from those that serve few at-risk students. For this reason, the evaluation team grouped schools to distinguish between those that serve primarily traditional students and those that exist to serve students who are at-risk of leaving the public school system. This distinction is used in many of the sections of the Part One and Part Two reports. At-risk and non-at-risk schools often have different missions, a difference that influences enrollment, curriculum, pedagogy and programs. To lump these two types of schools together may obscure important distinctions. Therefore, the 89 charter schools addressed in this report are usually divided into distinct groups for purposes of analysis. The evaluation team assigned schools to at-risk or non-at-risk groups based upon the percentage of their students who were classified as at-risk. Schools serving a majority of at-risk students with mission statements targeting at-risk students were classified as at-risk schools. Those not meeting these criteria were classified as non-at-risk schools. It is important to note that some schools that the evaluators classified as at-risk are open-enrollment charter schools that do not have at-risk charters. Forty-three schools are classified as at-risk schools, and 40 schools were classified as non-at-risk schools. Six schools did not have sufficient information to permit their classification. Because data for the 1998-99 school year become available at different times following the close of the school year, the evaluation team chose to prepare the third-year evaluation in three parts. The Part One report comprised the following chapters: a review of the characteristics of open-enrollment charter schools; a report on the perspectives of charter school directors relating to operation, enrollment, curriculum, attrition, discipline and safety; a report on charter school student satisfaction; and a report on effects of open-enrollment charter schools on public school districts. A separate publication, School Profiles, presented descriptions for most of the 89 charter schools operating during the 1998-99 school year. The final part of the third-year evaluation is this Part Two report. Part Two includes chapters on parent satisfaction and family choice behaviors, demographics and student performance, charter school finance, and commentary and policy considerations. Part Two of the year-three evaluation is organized as follows: Section VI presents findings from the survey of parents of charter school and public school students. Dr. Gregory Weiher of the Center for Public Policy at the University of Houston and Dr. Kent Tedin of the University of Houston prepared this section. Section VII presents demographic and student performance data for charter school students. The Texas Center for Educational Research and Academic Information Management, Inc. prepared this section. Section VIII presents finance information for charter schools. Dr. Carrie Ausbrooks of the Center for the Study of Education Reform at the University of North Texas prepared this section. Section IX presents the evaluation teams commentary on the findings. Appendix A includes a copy of the survey instrument used to collect information about parent satisfaction from charter school and comparison groups. The reader should be aware that the charter school evaluation set out in the Texas statute does not constitute a compliance review of charter schools. Evaluators do not examine whether charter schools fulfill their missions, comply with the terms of their charters, or follow federal and state laws. The role of the evaluation team is to prepare a report about Texas charter schools as a group. For this reason, the report provides limited information about individual charter schools. While there are difficulties associated with summarizing data from schools as diverse as Texas charter schools, the evaluation team has attempted to provide a meaningful overview of the evaluation topics. Section VI: Parental Participation and Satisfaction Levels Introduction To gain a better understanding of why parents choose to send their children to charter schools, the types of parents who send their children to charter schools, and the level of satisfaction with the newly established charter schools, the evaluation team developed a telephone survey of charter school parents. The survey was administered to a sample of 1,006 parents of charter school children by an independent survey research firm based in Austin, Texas. A similar survey was administered to a comparison group of 639 parents of children in traditional public schools. The comparison group sample was drawn from rosters of schools in the Houston Independent School District and the Spring Branch Independent School District. Comparison group schools were chosen because they were geographically close to charter schools and they served children in the same grade levels as the charter schools. Since one purpose of interviewing the comparison group was to compare the characteristics of choosing and non-choosing parents, it was important to include parents for whom choosing a charter school was a realistic option. Each comparison group household is close to a charter school that serves the same grade levels as the traditional public school attended by the children in that household. Each parent in the comparison group could have sent his/her child to a charter school as easily the parents in the charter school sample. The comparison group makes it possible to compare the characteristics, preferences, and satisfaction levels of charter school parents with parents who have chosen to leave their children in traditional public schools. Tables VI.1, VI.2, and VI.3 present data on the race/ethnicity, education levels, and incomes of the charter school parents and the comparison group parents. Table VI.1 Charter Parent and Comparison Group Ethnicity Racial/Ethnic GroupCharter Parent SampleComparison GroupState Charter AverageAnglo28.626.821.5African American29.120.934.2Hispanic39.048.442.5Other3.33.91.8Total978622 Though the percentages of Anglo parents in the two samples are quite similar, the charter sample has a substantially higher percentage of black parents, and the comparison group has a substantially higher percentage of Hispanic parents. Furthermore, both groups are somewhat dissimilar from the state charter average of racial distributions reported by the ˿Ƶ. These disparities are cause for concern because many of the educational outcomes by which schools are evaluated are mediated by race and ethnicity. Table VI.2 Charter Parent and Comparison Group Educational Achievement Achievement LevelCharter Parent SampleComparison Group8th grade or less8.619.49-11th grade9.613.9GED4.01.9High school graduate19.017.2Less than two years college13.53.8More than two years college13.511.2College degree22.316.6Graduate degree9.314.4Total1000628 Table VI.2 indicates that higher percentages of parents in the comparison group have low levels of educational achievement. However, similar percentages in each group are high school graduates. Furthermore, the percentage of charter parents who have a college or graduate degree (31.4 percent) is quite similar to the percentage of comparison group parents who have such degrees (31.2 percent). Table VI.3 Charter Parent and Comparison Group Income Income LevelCharter Parent SampleComparison GroupLess than $5,0004.57.0$5,000-9,9994.05.9$10,000-14,9996.88.5$15,000-19,9998.27.8$20,000-24,9999.39.5$25,000-34,99914.911.6$35,000-49,99915.69.9$50,000-74,99915.48.5more than $75,00011.714.9Total1006639 Table VI.3 indicates that comparison group parents are more heavily represented in lower income categories than are charter parents. In order to enhance the comparability of the two samples, the charter parent sample and the comparison group were weighted to reflect the overall distributions of racial and ethnic groups in Texas charter schools. This weighting procedure makes the two samples comparable with respect to race/ethnicity. The weights are presented in TableVI.4. Table VI.4 Weights for Race/Ethnicity Racial/Ethnic GroupCharter Parent SampleComparison GroupAnglo.77.82African American1.211.69Hispanic1.12.90Other.56.55 In this section, data concerning charter school parents are frequently divided into two categories those whose children attend at-risk schools and those whose children attend non-at-risk schools. About half of the open-enrollment charter schools in Texas serve primarily students who are at-risk of leaving the education system before graduating from high school (see Texas Open-Enrollment Charter Schools: Third Year Evaluation. Part One for a complete description of at-risk classification). Indeed, the state legislature has exempted charter schools that agree to enroll at least 75 percent at-risk students from restraints placed on the number of charters to be issued statewide. Because at-risk and non-at-risk schools differ greatly in terms of their missions, the objective characteristics of the students they enroll, and the educational aspirations of students and parents, it would muddy the waters greatly to lump them together. Unfortunately, it is not easy to draw comparison samples for the parents of children attending at-risk and non-at-risk charter schools separately. Separate comparison group samples were drawn for the purposes of the year one evaluation by identifying comparison schools for each of the open-enrollment charter schools. Only nineteen schools were in operation at the time of that report, and even though the number was relatively small, the evaluation team was not able to get rosters for each of the comparison schools within the reporting period. Since eighty-nine schools were in operation in year three, it was not practical to attempt to identify a matching school for each charter school. Attempting to create separate comparison groups is also complicated by the fact that the at-risk and non-at-risk categories pertain to schools, not individual students. We believe that the comparison group provides a reasonably good standard of reference for the charter parent sample as a whole, particularly when weighted to have the same racial distributions as the charter school sample. Many of the tables in this section break the charter sample down into at-risk and non-at-risk, but there is no attempt to do so with the comparison group. The discussion in this section addresses the following issues: How did parents learn about their charter school? What factors prompted parents to choose a charter school? How satisfied are parents with their charter schools in comparison to the schools that their children attended previously? How satisfied are they in comparison to parents of children in traditional public schools? How Did Parents Find Out about the Charter School? It is important to determine how parents learned about the charter schools they chose for their children. Is the public in general aware of charter schools? Do different kinds of parents find out about charter schools from different sources? Do the methods of publicizing charter schools lead to enrollments that are racially or socioeconomically distinctive? Parents were asked how they found out about the charter schools their children attend. Similarly, parents in the comparison group were asked if they knew of charter schools in their vicinity, and if so, how they became aware of them. The results are presented in Tables VI.5a and VI.5b. Table VI.5a How Did Charter Parents Find Out about Charter Schools? (percentages results reflect weighting for race and ethnicity) Information SourceNon-at-RiskAt-RiskNewspapers10.66.8Television or radio7.95.2Private schools2.41.0Public schools7.324.5Community center1.91.0Church5.21.0Friends/relatives61.449.5Teachers3.210.9Number of parents630192X2 = 71.504, df = 7, p < .000 Table VI.5a indicates that a majority of parents find out about the charter school their child attends from informal sources, principally friends and relatives but also through churches. This is noteworthy because of the well-established finding in sociology that such informal networks are highly segregated by race and class. When information about charter schools is transmitted via this channel, one would expect that it would mediate for charter schools that are racially and socioeconomically distinctive. This tendency is strongest for parents of students attending non-at-risk schools, though it is somewhat mitigated by the fact that these parents are also more likely to find their way to a charter school through information relayed by the news media (newspaper, radio, or television 18.5 percent to 14 percent). A second noteworthy finding is that parents of students attending at-risk schools are much more likely to learn of charter schools from public schools or from teachers (35.4 percent to 10.5 percent). In fact, for parents of students attending at-risk charter schools, the public schools and teachers categories combined rival friends and relatives as a source of information for parents of students attending at-risk schools, while no other information source comes close to the importance of friends and relatives (61.4 percent) for parents of students attending non-at-risk charter schools. Table VI.5b Do Parents of Traditional Public School Children Know about Charter Schools? How Do They Find Out about Them? (percentages results reflect weighting for race and ethnicity) Heard of Charter Schools?Know of a Charter School Nearby? How Did You Hear of Charter Schools?No54.7Yes26.5Newspapers14.4A little28.4No 73.5Radio/TV9.1Something9.5Private schools.9A lot7.5Public schools24.4Comm. ctr.1.3Church1.0Friends/Rel.29.7Teachers1.5Other17.8Total641641170 Table VI.5b reflects data from the survey of comparison group parents. These parents were asked if they had heard of the charter school program in Texas. The evaluation team believes that this particular sample is more likely to have heard about charter schools because they were drawn from the rosters of schools that are near to both charter schools and campus charter schools created by local school districts. The responses indicate that 54.7 percent of these parents had never heard of charter schools. Only about 17 percent indicate that they had heard something or a lot about charter schools. It is also interesting that the overwhelming majority of this group does not know that there are charter schools in close proximity to the public schools their children attend. It should be reemphasized that these parents were interviewed precisely because the schools their children attend are close to charter schools. When comparison group parents that are aware of the charter schools are asked how they learned about them, the pattern of responses is similar to that of charter school parents. More say they learned from friends or relatives than from any other source. The margin is not as large for comparison parents, however. Public schools and teachers (25.9 percent) and the media (23.5 percent) are cited by substantial percentages of comparison group respondents as their means of learning about charter schools. The evaluators believe that these results should be considered in combination with the results presented in Table VI.5a. The public, in general, is not aware of the charter school option. Those that do know about charter schools, both those who send their children to them and those who do not, have learned about them to a great extent from friend and neighbor networks that are likely to be segregated by race and class. This combination of factors may partly explain why charter schools are more racially distinctive than the public schools generally. Factors Affecting the Decision to Enroll in a Charter School In this section, data of three kinds are presented. First is data on the stated preferences of surveyed parents of charter school students. Second is data on the actual choices that parents made. Third is data on parent satisfaction with the schools their children attended prior to transferring to charter schools. Parents Expressed School Preferences Parents of charter school children were asked a battery of questions regarding factors important in their decision to enroll their child in a charter school. They were also asked their opinions of their childs previous school. In previous interviews, parents of charter school students were read a list of attributes of schools and were asked which of the attributes were important to them in choosing a charter school. They could choose any or all of the attributes without having to indicate which was the most important. For the third year evaluation, parents were provided with a list of six attributes, but they were asked to pick the one that was most important to them in making their particular choices. The six school attributes were high standardized test scores, discipline, location, a student body which was ethnically compatible with the child in question, the teaching of moral values, and safety. Parents were then read the list of five remaining attributes and asked to identify the most important from among them. Then the remaining four attributes were read, and parents were asked to identify which of them was most important. The six attributes, along with the percentages of parents citing each as most important, second-most important, or third-most important are presented in Table VI.6. Table VI.6 What School Attributes Influence Parents School Choices? (percentages results reflect weighting for race/ethnicity) School Attribute1st Choice2nd Choice3rd ChoiceAverageHigh test scores20.819.720.220.2Better discipline25.726.523.225.1Students mostly the same race1.22.53.82.5Location of charter school12.110.29.210.5Teaching moral values26.724.322.724.6Safety13.416.820.917.0Total787722675 If one concentrates on first choices of parents their most important reason for choosing a charter school more parents cite the teaching of moral values than any of the others. Next most important is better discipline, followed by high test scores, safety, and the location of the school. Another way to summarize these results is to add across columns and divide by three. The resulting scores are the percentages of parents that mentioned each attribute as being most important, second in importance, or third in importance. By this measure, discipline is slightly ahead of the teaching of moral values. The one attribute that conspicuously trails all the others, no matter how the importance of the various attributes is measured, is a student body in which the majority is of the same race/ethnicity as the child. Almost none of the interviewed parents cited this attribute as having any importance. Behavioral Measures of Parent Preferences These are only the stated preferences of charter school parents, however. Interview data such as these have been criticized in scholarly literature on the grounds that respondents know that they should not choose certain attributes, even if those are the ones that really had the greatest impact on their decisions. This criticism is most frequently made with respect to racial attributes. Parents know, the argument is made, that they are not supposed to take race into account in evaluating schools. Fortunately, we can use empirical measures to check on the validity of at least some of these expressed preferences. Parents were asked to name the schools that their children attended previously and, if they were public schools, to identify the school districts in which they were located. Knowing the schools that children previously attended permits the evaluation team to evaluate parent behavior in three areas test scores, race/ethnicity, and location. Where data were available, the differences in percentages of students passing all components of the Texas Assessment of Academic Skills (TAAS) test for the previous schools and the charter schools were computed. Similarly, differences in ethnic compositions of student bodies were measured. When addresses of both previous schools and charter schools were available, the distances between the two were measured. Test Scores. The Academic Excellence Information System (AEIS) data for Texas were used to determine for individual schools, both charter and traditional, what percentage of students passed all of the components of the TAAS test in 1998-99. For each respondent, where complete data were available, the passing percentage for the traditional public school that the child left was subtracted from the passing percentage of the charter school to which he/she transferred. This is not a perfect measure of high test scores. For that, the average score of the students would have been better, but such averages are not reported in the AEIS data. Collectively, if parents were interested in choosing schools with higher objective test scores, they should have considered enrolling them in the traditional public school system. The average parent whose child transferred from a traditional public school to a charter school went to a charter school where the percentage of students passing all components of the TAAS test was 18.1 points lower. For the cases where data were available, over 75 percent of the transfers to charter schools were to schools with lower passing percentages than the public schools from which students transferred When the focus is limited to those parents who cite high test scores as a first preference, the results improve slightly. Multivariate analysis indicates that such parents were more likely to improve the percentage of the student body passing the TAAS exam by transferring their children to a charter school. Still, the average transfer, even among this group, resulted in a decline in the percentage of the student body passing the TAAS exam of 13.2 points. Well over half of the parents who said that their chief interest was to pick a school with high TAAS scores transferred their children into charter schools that had a lower percentage of students passing the TAAS exam than the traditional public schools that their children left. Location. Previous studies of school choice have determined that location is one of the variables that parents take into account in choosing a school for their children. Table VI.6 indicates, however, that it is only fifth in importance of the six attributes offered to parents in the charter survey. Perhaps parents understand that they may appear petty if they allow location, and ultimately convenience, to supercede the importance of more lofty-sounding considerations such as test scores, safety, discipline, and moral values. In order to gain some empirical measure of the importance of location beyond the expressed preferences of parents, the evaluation team recorded the addresses of the traditional public schools that children transferred out of as well as the addresses of the charter schools that they transferred into. Using the map option of the Yahoo Internet search engine, it is possible to estimate the distances between these addresses. It is important to emphasize that these are the distances from the childrens previous schools to their charter schools, not from their homes to the charter schools. In spite of the fact that few of the parents interviewed placed high importance on school location, 75 percent of the 560 respondents for which distance and driving time could be measured chose a school that was 8.4 miles or less from the public school their child previously attended, with driving time between the two schools of 18 minutes or less. The evidence is that school location powerfully constrains the choices made by charter school parents, even though they may not say that it is an important factor in their choice decisions. Race/Ethnicity. Previous research indicates that survey responses concerning racial attitudes may be biased by respondents knowledge that it is often considered inappropriate for preferences and choices to be based on race. The percentages of charter parents who identify the race of students in prospective schools as an important factor in making their school choices are very small. But are charter parents more likely to act upon racial considerations, even though they may state that such considerations are not important? To address this issue, researchers recorded 1998-99 percentages of student bodies that were Anglo, African American, and Hispanic for all of the traditional public schools and charter schools identified by respondents. To measure the differences in racial concentrations between the traditional public schools previously attended by students and the charter schools they transferred into, the relevant percentages for the traditional schools were subtracted from charter school percentages. For instance, differences in concentrations of Hispanic students were measured by subtracting the percentages of students who were Hispanic in the traditional public schools previously attended by charter students from the percentage of Hispanic students in the charter schools. The resulting percentage point differences for Anglo, African American, and Hispanic students were used to determine if: Anglo students were likely to transfer into charter schools that were more Anglo than the public schools they transferred out of; African American students were likely to transfer into charter schools that were more black than the schools they transferred out of; and Hispanic students were likely to transfer into charter schools that were more Hispanic than the public schools they transferred out of. The results are presented in Table VI.7. Table VI.7 Differences in Racial/Ethnic Compositions of Traditional and Charter Schools by Race (percentage point differences no weighting for race/ethnicity) Racial/Ethnic GroupMean Percentage Point Difference in Group ConcentrationAnglo8.11African American14.77Hispanic3.70 Table VI.7 indicates that the average Anglo student who leaves a traditional public school for a charter school goes to a school that serves 8.11 percentage points more Anglo students. The average African American transferring from a traditional school to a charter goes to one that serves 14.77 percentage points more African American students. Finally, the average Hispanic transfer goes to a charter school that serves 3.7 percentage points more Hispanic students than the school he/she left. The evaluators performed a multivariate analysis to determine if the tendency for each group to choose charter schools with higher percentages of that group than the schools they left would survive a series of controls for other influences. These controls include: whether the student transfers to an at-risk or a non-at-risk charter school whether the parent indicates that the states definition of at-risk describes his/her child the number of years the student has attended a charter school the frequency with which the respondents attends church whether the respondent expects his/her child to attend college after leaving high school the highest level of education completed by the respondent the childs grade whether the respondent owns his/her home whether the respondent indicates that it is a problem to transport the child to the charter school whether the respondent indicates that the school previously attended by the child was safe the distance from the old school to the charter school In the presence of this battery of controls, the effect of race on school choice persists. A Anglo parent is still likely to send his/her child to a school that is more Anglo than the public school the child left after taking these considerations into account. Similarly, African American parents are likely to send their children to schools that are more African American, and Hispanic parents are likely to send their children to schools that are more Hispanic. This presents the apparent contradiction that almost no parents are willing to say that race is important in choosing a charter school, but race remains a good predictor of the schools that parents ultimately choose. Parent Satisfaction with Previous Schools Another issue examined by the research team was whether parents were unhappy at their previous schools and fleeing intolerable conditions. The answer to this question depends heavily upon whether the previous school was a public or a private school. As Table VI.8 indicates, when the previous school is private, parents give much higher grades than when it was public. These results can be put into context by comparing the outcomes with the results for the comparison group. Charter parents whose children previously attended public schools give those schools much lower marks than those given by the comparison group parents to the schools their children attend. Charter parents whose children previously attended private schools, on the other hand, give them much higher marks than those given by the comparison group parents. Table VI.8 Grades Assigned by Charter Parents to Their Childrens Previous Schools (percentages results reflect weighting for race/ethnicity) GradeCharter School ParentsComparison GroupPrevious Private SchoolPrevious Public SchoolAllA43.620.224.833.9B28.222.924.137.3C16.630.928.019.6D6.612.311.15.1F5.013.712.03.9Total181724904641Private-Public X2 = 57.77, df = 4, p < .000 This pattern persists in Table VI.9 in which charter parents are asked to rate specific characteristics of schools their children previously attended. Parents whose children previously attended private schools are much more likely to say they were very satisfied with these attributes. The satisfactions levels are much lower for charter parents whose children previously attended public schools. Table VI.9 Charter Parent Satisfaction with Specific Characteristics of Previous Schools (percentages results reflect weighting for race/ethnicity) CharacteristicVery SatisfiedSomewhat SatisfiedSomewhat DissatisfiedVery DissatisfiedPrivate Teachers Teaching moral values Location Discipline Parent-teacher relations Parent input into running school Background of students57.025.16.111.765.420.17.86.764.220.710.64.559.723.85.011.663.019.94.412.746.624.214.614.654.931.46.37.4Public Teachers Teaching moral values Location Discipline Parent-teacher relations Parent input into running school Background of students33.836.413.915.928.032.915.423.859.428.84.77.129.931.716.521.935.431.815.017.826.632.617.623.229.140.116.913.9Teachers: X2 = 34.144, df = 3, p < .000 Moral Values: X2 = 89.842, df = 3, p < .000 Location: X2 = 14.047 df = 3, p = .003 Discipline: X2 = 60.001, df = 3, p < .000 Parent-teacher: X2 = 48.742, df = 3, p < .000 Parent input: X2 = 27.464, df = 3, p < .000 Student Background: X2 = 44.885, df = 3, p < .000 In summary, charter school parents whose children previously attended private schools are highly approving of those schools. They appear to have chosen charter schools in the hope of finding something even better, or perhaps to save on private school tuition. It seems more accurate to characterize charter school parents whose children previously attended public schools, on the other hand, as leaving those schools because of low levels of approval and satisfaction. Parent Evaluation of Charter Schools The grades assigned to the charter schools by charter school parents are presented in Table VI.10. Overall, the grades assigned to the charter schools are higher than the grades they assign to the schools their children previously attended (Table VI.8). Parents of students attending at-risk charter schools are somewhat more likely to assign their charter schools high grades than parents of students attending non-at-risk charter schools. Table VI.10 Grades Assigned by Charter Parents to Charter Schools (percentages results reflect weighting for race/ethnicity) GradeCharter School ParentsComparison GroupNon-at-Risk SchoolsAt-Risk SchoolsAllA40.052.442.533.9B33.225.331.537.3C13.212.012.919.6D8.652.7.85.1F5.15.25.33.9Total7452331001641Private-Public X2 = 12.68, df = 4, p = .013 This tendency also emerges in Table VI.11 which presents parent satisfaction levels from very satisfied to very dissatisfied for specific characteristics of the charter schools. Here again, parents of students attending at-risk schools tend to be more satisfied with the specific characteristics of charter schools than parents of students attending non-at-risk charter schools. The differences are statistically significant for satisfaction with teachers, parent input into the running of the school, and parent-teacher relations, and nearly so for discipline. Overall, the evidence indicates that: charter parents like the charter schools better than the schools their children previously attended; charter parents give their schools higher marks than comparison group parents give to their schools; and parents of students attending at-risk charter schools are even more satisfied with the charter schools than are parents of students at non-at-risk charter schools. Table VI.11 Charter Parent Satisfaction with Specific Characteristics of Charter Schools (percentages results reflect weighting for race/ethnicity) CharacteristicVery SatisfiedSomewhat SatisfiedSomewhat DissatisfiedVery DissatisfiedNon-at-risk Teachers Teaching moral values Location Discipline Parent-teacher relations Parent input into running school Background of students55.429.17.68.060.526.16.96.652.333.19.05.657.026.17.39.661.225.75.18.048.731.19.111.147.036.89.17.1At-risk Teachers Teaching moral values Location Discipline Parent-teacher relations Parent input into running school Background of students63.326.27.03.560.927.76.45.059.128.37.45.261.927.94.45.870.220.63.95.356.730.05.57.854.132.48.25.3Teachers: X2 = 7.57, df = 3, p = .056 Moral Values: X2 = .926, df = 3, p = .819 Location: X2 = 3.39, df = 3, p = .336 Discipline: X2 = 5.96, df = 3, p = .113 Parent-teacher: X2 = 6.29, df = 3, p = .099 Parent input: X2 = 6.49, df = 3, p = .090 Student Background: X2 = 3.44, df = 3, p = .328 Parent Participation in the Schools Parents also described their participation in their childrens schools. Table VI.12 presents percentages of charter parents who indicated they had participated in various events or activities at their childrens previous schools. Percentages are presented for non-at-risk and at-risk charter parents, and for parents whose children previously attended private and public schools. Percentages of comparison group parents who say they participate in these events and activities are also presented. As might be expected, parents of students at non-at-risk charter schools and those who sent their children to private schools participated somewhat more than their at-risk and public school counterparts. Overall, participation levels for charter school parents in previous schools are comparable to levels for the comparison group parents. Table VI.12 Charter Parent Participation at Previous School(percentages of parents saying yes results reflect weighting for race/ethnicity) ActivityNon-at-RiskAt-RiskPrivatePublicComparison GroupPTO/other meeting*(80.566.789.074.182.9School board meeting(34.332.839.832.234.0Make decisions(25.524.935.023.128.3School play/concert*(76.258.984.068.569.3Athletic event53.953.158.652.2Fundraising*(68.443.984.056.866.2Parent-teacher conference89.986.492.388.385.2* Non-at-risk/at-risk difference statistically significant ( Private/public difference statistically significant Table VI.13 presents percentages of charter parents who said they had participated in some activity at the charter schools attended by their children. Parents of students attending non-at-risk charter schools participate substantially more than parents of students attending at-risk charter schools. As a group, the charter parents are not notably more participant than the comparison group parents. In most cases, comparison group parents participate more than parents of students attending at-risk charter schools but not as much as parents of students at non-at-risk charters. Table VI.13 Charter Parent Participation at Charter School (percentages of parents saying yes results reflect weighting for race/ethnicity) ActivityCharter Parent SampleNon-at-RiskAt-riskComparison GroupPTO/special meeting*79.286.260.882.9School board meeting*39.843.031.234.0Program or curriculum decisions36.037.432.328.3School play/concert*62.068.644.269.3Fundraising*63.172.236.866.2Parent-teacher conference*85.890.173.885.2*Differences are statistically significant Additional Information Provided by the Survey This section includes relevant information about charter parents and their households obtained through the charter parent survey. Parents were asked if their children were required to take placement exams in order to be admitted to their charter schools. As shown in Table VI.14, 42 percent of parents indicate that their children were required to take such exams. Parents were also asked if they signed a contract to help children with homework when their children transferred to charter schools. Over 54 percent said that they had signed such contracts. Table VI.14 Placement Tests and Homework Contracts YesPlacement examination42.0Homework contract54.1* percentages results reflect weighting for race/ethnicity It is of some interest to know what proportion of charter school students come from public schools and what proportion come from private schools. Information in Table VI.15 shows that slightly less than a fifth of this survey sample comes from private schools. Children attending non-at-risk charter schools are much more heavily represented among those who formerly went to private schools than children attending at-risk schools. Table VI.15 Charter School Provenance Type of SchoolNon-at-riskAt-riskCharterPrivate22.16.418.2Public68.981.672.3No previous school9.112.09.5* percentages results reflect weighting for race/ethnicity X2 = 26.36, df = 2, p < .000 Summary The public, in general, is not aware of the charter school option. Those who do know about charter schools primarily learn about them from friends and neighbors. This may, in part, explain why charter schools are more racially distinctive than public schools generally. If one examines the expressed first choices of parents, the teaching of moral values is the most important reason for charter school selection. Next most important is better discipline, and next most important is high test scores. An examination of parent actions with regard to enrolling their children in school shows that students are transferring to charter schools with lower TAAS passing percentages than the public schools from which students transferred. They also enroll their children in a charter school that more accurately mirrors their own ethnicity than did the previous public school. School location also appears to constrain the choices made by parents of charter school students, although parents do not mention this as a highly important consideration. Charter school parents like the charter schools better than the schools their children previously attended. They give the charter schools higher marks than comparison group parents give to the public schools their children attend. The parents of at-risk charter school students are even more satisfied with the charter schools than are parents of students in non-at-risk schools. As a group, parents of charter school students do not participate in school activities more than the parents in the comparison group. In most cases, comparison group parents participate more than parents of students in at-risk charter schools, but not as much as parents of students in non-at-risk charter schools. Forty-two percent of charter school parents surveyed indicate that their children were required to take placement exams to be admitted to the school, and over 45 percent said they had signed contracts to help their children with homework. Section VII: Review of Demographics and Student Performance Introduction This section describes Texas charter school student demographics and program participation for 1998-99. It also provides summary information about charter school professional staff members, revenue, and expenditures. The descriptive information provides a context for the presentation and analysis of charter school student performance on the Texas Assessment of Academic Skills (TAAS). TAAS performance on reading, writing, and mathematics tests in terms of passing rates, mastery rates, and Texas Learning Index (TLI) scores are reported. Definitions for Types of Schools Charter schools. Open-enrollment charter schools are public schools that are substantially released from state education regulations and exist separate and apart from local independent school districts. In 1998-99, 89 charter schools operated for the entire school year, 43 of which were schools either chartered to serve at-risk students or actually serving high percentages of at-risk students under an open-enrollment charter. Public schools. For this section, the term public school is used to distinguish public schools in independent school districts from charter schools, which are a special subset of all public schools. Classification of Charter Schools for this Analysis Presentation of information in this section classifies charter schools two ways: (1) by type of student served; and (2) by length of time in operation. These classifications, explained below, are used in this section, starting with Table VII.4. Classification of schools by type of students served. The first classification system separates charter schools into at-risk and non-at-risk categories based on characteristics of students served. During the first two application cycles, all charters granted were designated open-enrollment, regardless of their mission or the type of student they would serve. Beginning with the third cycle, however, applicants have the choice of applying for a general open-enrollment charter or a 75 Percent Rule charter. The law requires that applicants awarded 75 Percent Rule charters maintain an enrollment of 75 percent or more students at risk of failure or dropping out. General open-enrollment charter schools may also serve 75 percent or more at-risk students, but they are not required to do so. Because some general open-enrollment charter schools serve a preponderance of at-risk students, the charter school evaluation team has adopted a broader definition of at-risk schools than the distinction made in law. To group schools in a fair and consistent mannerparticularly those that opened before the 75 Percent Rule provision was institutedteam members have examined each schools mission, special programs, and population served to classify it as at-risk or non-at-risk. Therefore, in addition to 75 Percent Rule charter schools, general open-enrollment charter schools with a stated mission to serve students at risk and enrolling a majority of at-risk students are classified as at-risk schools for this analysis. Conversely, general open-enrollment charter schools with missions unrelated to at-risk students and enrolling primarily non-at-risk students are classified as non-at-risk schools. The evaluation team classified 43 schools as at-risk. Duration of operation. The second classification system establishes three groups of schools corresponding to the number of years of available data on the TAAS. Group 1 schools were in operation in spring 1997 but several do not have TAAS data. In most cases, because of the many challenges associated with a start-up year, data from a charter schools first year of operation are not considered for campus-level analyses. On the other hand, student-level data are consideredregardless of a schools years of operationbecause failing part or all of TAAS can have immediate consequences for students, both in terms of instructional program and graduation status. Classification of Students for Analysis In this section, performance and change in performance for charter school students and public school students are compared and contrasted. Where appropriate, performance and performance change information for subgroups of public school students, selected on the basis of risk factors and racial/ethnic identification, are used to ensure fair comparisons. Public schools may designate students as at-risk according to a wide range of circumstances including failing TAAS, coming from single parent homes, or other reasons defined by districts. Because the ˿Ƶ (TEA) does not customarily report student performance information according to at-risk categories, a surrogate was selected for use in comparisons with at-risk charter schools. Because many students who are classified as at-risk are also classified as economically disadvantaged and score similarly on TAAS, TAAS scores of economically disadvantaged students are used when comparisons are made between state averages and at-risk charter schools. However, because TEA does not distinguish between at-risk and non-at-risk charter schools in its Snapshot report, all charter schools are included in one category for tables based on Snapshot data. Measures of Student Performance This section examines three aspects of student performance: student performance as evidenced by TAAS test scores, student attendance and engagement in school, and dropout rates. Although test scores are a necessary component of an evaluation required in law for most educational programs and the major determiner of accountability ratings in Texas, student engagement may be considered a precursor to performance measured by a test. TAAS. TAAS is the statewide criterion-referenced test used to rate campuses and districts in the Texas accountability system. In addition, it is used for individual student-level instructional decisions. TAAS currently includes three primary subtests: reading, writing, and mathematics. To receive a diploma, students must pass all three sections at the exit level (grade 10), in addition to meeting other course work requirements. Reading is comprised of six objectives, whereas mathematics has 13 objectives. Writing consists of a composition and multiple-choice items covering language usage. Science and social studies subtestscurrently given at grade 8 onlyare scheduled to become part of the accountability system at a later time. Students in grades 3 through 8 currently take TAAS reading and mathematics subtests every year; writing is administered at grades 4, 8, and 10. Grade 9 TAAS testing is scheduled to begin in 2003. At that time, an exit-level version of TAAS currently given in grade 10 will move to grade 11. The new version will include science and social studies subtests. Grade 10 will take TAAS mathematics and TAAS reading tests. Thus, the TAAS system continues to expand through grade levels and subjects. This evaluation will be enhanced when student test scores can be examined over a longer period of time and over more subjects. TEA currently evaluates performance for each of five student groupsAfrican American, Hispanic, Anglo, economically disadvantaged, and all studentsfor all TAAS subtests. A campus is rated low-performing if any student group on any subtest falls below a 45 percent passing rate (for tests taken in 1999). Passing a TAAS subtest generally means scoring correctly on 70 percent of items. The passing rate standard has been raised every year for the last five years. Student engagement. Student engagement in school may be understood partly in terms of attendance and mobility. This process variable may reflect students perception of their schools value and of how well their schools meet their needs. For most students, being present in the classroom is critical to academic success. Attendance may be particularly important for students with prior low performance levels on academic measures. Attendance may be viewed as an indirect measure of the degree to which a student believes that school is providing what he or she perceives as important. Although there are many circumstances that affect student attendance, it still may serve as a reflection of the appropriateness of instruction. Mobility may also be considered an indirect measure of student engagement. Students who move frequently may miss the sequence of instruction needed to master the Texas learning standards. According to TEAs definition, students are considered to be mobile when they have attended a particular school for less than 83 percent of the school year, that is, if they have missed six or more weeks at the school. Mobility is calculated by dividing the number of mobile students during a year by the number of students who were in membership at the school any time during that year. Completion rates. Measures of successful public school completion are important outcomes (and may be the most important measure for students served by at-risk charter schools). Three types of completion measures have unique definitions, according to Texas Academic Excellence Indicator System (AEIS) reports. The first two measures of completion to be considered here are the annual and longitudinal dropout rates. The 1999 TEA Accountability Manual defines the annual dropout rate as the number of students in grades 7 through 12 who dropped out during a school year divided by the number of students in those grades who were in membership at any time during that school year. Because a cumulative count of students is used in the denominator as well as in the numerator, this method for calculating the dropout rate was designed to neutralize the effects of mobility. Actual longitudinal dropout rates are determined by following a cohort of students who began grade 7 in a particular school year through the expected graduation date. This rate is based on six years of data collected via the Public Education Information Management System (PEIMS) at the individual student level. The actual longitudinal dropout rate is calculated by counting all students in the cohort whose final status, according to PEIMS, is dropout and dividing that number by the final number of students in the cohort after six years. Students who transfer out of the original cohort are subtracted from the denominator and those who transfer in are added to it. TEA also defines a completion rate for use in the AEIS as a measure of district performance. The completion rate is based on the cohort of students who began grade 9 four years previously and follows them through the current school year. Students are considered to have completed school if they graduated (early or on time), received a General Educational Development (GED) certificate, or are still enrolled in school. Students transferring from one district to another during this time may be counted by the last district in which they enroll. Students no longer reported in PEIMS are treated as transfers out of the Texas public education system, not as dropouts. The completion rate is calculated by dividing all completersthe sum of on-time graduates, early graduates, GED recipients, and continuing studentsby the number of students in the original grade 9 cohort, plus students transferring in, minus students transferring out. Graduation rate, in this context, pertains to students completing all requirements for a diplomaaccumulating sufficient credits and passing the exit-level TAAS. In addition, special education students may receive a diploma under requirements established by their admissions, review, and dismissal (ARD) committees. Demographic Information Numerous studies have reinforced the linkage between student and campus demographics and performance levels. The presentation of demographic data in this section will serve as an important contextual backdrop for the examination of student performance presented later. Data Sources and Analysis Sources. The demographic data examined in this section are derived from three sources: (1) 1999 Snapshot data from the TEA web site; (2) 1998-99 AEIS reports from TEA; and (3) individual student data provided by the TEA PEIMS office. With the exception of TAAS information, the majority of data are self-reported by school districts and charter schools through the PEIMS system to TEA. Computations. Data are reported from sources that use differing techniques for calculating overall averages; thus values are expected to differ by a small percentage. For example, TEA and the evaluation team differ slightly in how they compute a TAAS average. TEA compiles information from the individual student level (student is the unit of analysis) for TAAS performance in the AEIS and TEA Snapshot reports. By contrast, when constructing averages for charter schools separated into risk categories, the evaluation team considers the campus as the unit of analysis. Averages produced by TEA are weighted by student, whereas averages produced by the evaluation team are weighted by campus. In most cases, the resulting computational differences are small. Variations in numbers. An additional consideration concerns masking of TAAS data by TEA. When there are fewer than five students in a particular category, the data are masked to protect confidentiality. Masking is done not only by student group, but also by subject area. In addition, variations in numbers of students taking reading, writing, and mathematics subtests complicate year-to-year comparisons; numbers of campuses (or students) with listed data from one year to the next may not match. For the analyses in this section, results are included only for campuses (or students) with data in bothor, at times, all threeyears in a particular subject area. Until more charter schools have consecutive-year TAAS data, this will continue to be a problem, and number-of-campus (or number-of-student) notations are included in this section as appropriate. Charter campus versus public school district. TEA uses county-district and county-district-campus (CDC) numbers to identify and track individual districts and campuses. Because TEA recognizes most charter schools both as campuses and districts, and because new charter schools are constantly being created, some overlap and inconsistency exists in describing and reporting on charter schools. In this section, for example, the evaluation team uses campus numbers to get data such as mobility rates and TEA peer group comparisons but uses district numbers for access to other data, such as completion rates. Use of both data sourcescharter campuses and charter districtsleads to instances where the number of charter schools appears to differ. This apparent discrepancy does not affect the accuracy of the overall data. Analysis tools. Two commercial products were used for portions of the analysis: Excel 97 (Microsoft, Inc.) and Statistica (StatSoft, Inc.). The bulk of the analyses were performed using the Academic Information Management data analysis library. Programs within the library were developed using Microsoft Visual Basic 6.0. The programs are especially designed for processing student level data extracted from PEIMS data sets. Whenever possible, cross-validation of data was used to ensure accuracy. In addition, bounds checks were used within the analysis to eliminate statistically improbable data. Student Information Demographic information is useful in examining student performance. It forms a context for understanding student performance. Table VII.1 contains demographic information on 61 charter schools (in this case, classified as districts). It is immediately obvious when viewing the information in Table VII.1 that differences in percentages of students in racial/ethnic group categories exist between charter schools and the state average. Table VII.1 TEA Snapshot Data: Student Information, 1998-99 School Year Student Group Charter Schools (N=61)State Average (N=1042)% African American33%14%% Hispanic43%39%% Anglo22%44%% Other2%3%% Economically disadvantaged52.6%48.5%% Special education6%12%% Bilingual/ESL3%12%% Career and technology19%18%% Gifted/talented4%8%Source: 1999 Snapshot data: www.tea.state.tx.us Student is the unit of analysis. Within Texas public school districts, 14 percent of the students are African American students, whereas this group comprises one-third of Texas charter schools student population overall. The percentage of Hispanic students in charter schools is roughly the same as the state average; and the percentage of Anglo students is less than the state average. The percentage of economically disadvantaged students in charter schools is similar to the state average. (In Table VII.5, demographic data for students in at-risk and non-at-risk charter schools are presented separately. An examination of those data reveals a difference in student demographics between these two types of schools.) The percentage of students reported by charter schools as receiving either special education (six percent) or bilingual/ESL instruction (three percent) is considerably lower than the overall state average receiving such services (12 percent for each). Staff Information Staffing data are presented in Table VII.2. Charter schools list three percent of their staff members as central administrators, whereas one percent statewide are classified as central administrators. Because charter schools function both as districts and campuses and are generally smaller than most districts, the percent listed as central administration seems reasonable, given the economy of scale associated with operating small charter schools. Table VII.2 TEA Snapshot Data: Staff Information, 1998-99 School Year Type of Staff InformationCharter Schools (N=61)State Average (N=1042)% Central administration3%1%% Campus administration4%3%Average central administrator salary$47,234$64,779Average campus administrator salary$41,779$53,477Average teacher salary$27,107$34,357% Minority staff members57%36%Students per total staff8.57.8Students per teacher16.715.2% Teachers with one or more permits0.1%4.8%% Teachers w/ five or fewer years experience72.8%34.2%Teacher average years of experience4.911.8% Teachers with advanced degrees21.2%25.1%Teacher turnover rate55.3%15.4%Source: 1999 Snapshot data: www.tea.state.tx.us Salaries, regardless of whether earned by administrators or teachers, are lower in charter schools than state average salaries. Part of the difference in teacher salaries may be accounted for by the relative inexperience of charter school teachers. The percentage of charter school teachers with fewer than five years experience is about twice the state average72.8 percent and 34.2 percent, respectively. Moreover, the turnover rate for teachers in charter schools55 percentis much higher than the state average of 15 percent. Taken together, charter schools high turnover rate coupled with teacher inexperience may account for some differences in compensation. Revenue and Expenditures Information regarding revenue and expenditures in 1998-99 is presented in Table VII.3. Per-pupil state aid in charter schools exceeds the state average by roughly $2,000. Charter schools have no taxing authority and rely almost exclusively on state funds (supplemented to some extent by contributions and federal aid). In fact, total operating expenditures per pupil for charter schools are somewhat less than the state average for public schools. The small margins of fund balance (three percent) maintained by charter schools indicate that little money is available for unexpected expenses. The percent of charter school expenditures for regular education is greater than the state average for all districts, whereas the percentage of expenditures for special education is less. This is expected, given the small percentage of students in charter schools receiving special education services. Table VII.3 TEA Snapshot Data: Revenue and Expenditures, 1998-99 School Year Type of Revenue or ExpenditureCharter Schools (N=61)State Average (N=1042)State aid per pupil$4,225$2,275Total revenue per pupil$4,709$5,658Total operating expenditure per pupil$4,663$5,219Ratio operating/revenue99%92%% Fund balance3%21%% Expenditure regular education86%71%% Expenditure special education4%12%Source: 1999 Snapshot data: www.tea.state.tx.us In Table VII.4, demographic information for charter schools is broken down by duration-of-operation: Group 1 has (or could have) three years of TAAS data, Group 2, two years. Compare the state average information in Table VII.1 with the state average information in Table VII.4. This is the first instance of calculations by the evaluation team differing slightly from averages calculated by TEA. The difference reflects the unit of analysis used; the evaluation team uses schools as the unit of analysis because schools are classified into at-risk and non-at-risk categories. The general patterns, however, remain the same. For example, a much higher percentage of African American students attend charter schools than state schools overall. Table VII.4 School Demographics and Characteristics by Group, 1998-99 School Year DemographicGroup 1Group 2Both GroupsState AveragePercent African American24.4%35.0%30.8%14.4%Percent Hispanic48.6%36.4%41.2%38.6%Percent Anglo23.9%26.6%25.6%44.1%Percent Asian 2.9% 1.6% 2.1% 2.5%Percent eco-disadvantage37.8%57.2%49.5%48.5%Percent special education 4.4%13.3% 9.8%12.1%Percent mobile*54.0%----22.0%Percent LEP 5.0% 1.7% 3.0%13.5%Percent beginning teacher21.1%34.1%28.9% 7.7%Percent 1-5 year teachers42.7%36.5%39.0%26.7%Avg. teacher experience6.05.25.511.8Percent minority teachers50.5%49.7%50.0%25.4%Avg. dollars for instruct**$2,140$4,212$3,399$3,071% Dollars for instruct **65.8%68.9%67.6%57.5%Number of schools/districts2335581,042Source: PEIMS Charter school database and 1998-99 TEA AEIS reports * Mobility rate available only for Group 1 Schools. **PEIMS function code: Instruction 11 and 95 only Charter schools in Group 2 (the ones that have opened more recently) enroll more African American students and low-income students. They also serve a greater percentage of special education students. The proportion of beginning teachers in Group 2 is higher, meaning that schoolwide average teacher experience is lower. The mobility rate for Group 1 charter schools is 54 percent, more than twice the statewide rate of approximately 22 percent. Depending on context, this finding can be interpreted in two ways. It may relate to the ability of the school to provide instruction. When there is a constant turnover of students, sustaining high-quality instruction is quite difficult. On the other hand, the finding may relate to the perceived match between the students needs and the services (instructional and otherwise) provided by the school. In other words, students may be less likely to remain in a school that they perceive does not meet their needs. Some schools may have programs that serve students who need only short-term services. In these schools, mobility would likely be higher. Table VII.5 School Demographics and Characteristics: At-Risk and Non-at-Risk Charter Schools DemographicAt-Risk Charter SchoolsNon-at-Risk Charter SchoolsGroup 1Group 2Group 1Group 2Percent African American25.1%25.1%24.0%41.6%Percent Hispanic67.4%49.6%38.6%27.6%Percent Anglo 6.9%24.2%33.0%28.2%Percent Asian 0.3% 0.9% 4.2% 2.1%Percent eco-disadvantage58.6%73.5%26.7%46.4%Percent special education 5.5%23.1% 3.8% 6.7%Percent mobile*70.1%--43.8%--Percent LEP13.3% 0.3% 0.5% 2.6%Percent beginning teacher21.9%24.9%20.6%40.2%Percent 1-5 year teachers51.4%47.9%38.2%28.9%Avg. teacher experience4.74.66.75.5Percent minority teacher62.9%49.0%43.9%50.1%Avg. dollars for instruction**$2,130$6,127$2,146$2,828Percentage of dollars for instruction **71.4%71.5%62.0%67.0%Number of schools/districts8141515Source: PEIMS Charter school database and 1998-99 TEA AEIS reports * Mobility available only for Group 1 schools. **PEIMS function code: Instruction 11 and 95 only Table VII.5 presents demographics and other characteristics also depicted in Table VII.4, but in Table VII.5, the comparison is between at-risk and non-at-risk charter schools separated by duration-of-operation. An examination of data contained in Table VII.5 reveals that substantial differences exist between student populations in several categories, depending upon at-risk or non-at-risk status. At-risk schools have higher percentages of minority students, more economically disadvantaged students, more students identified for special education services, higher mobility rates, more limited English proficient students, less experienced teachers, and a higher percentage of dollars allocated for instruction. A comparison of Tables VII.4 and VII.5 reveals that some differences between the two types of charter schoolsat-risk and non-at-riskexceed differences between charter schools and the statewide average. For example, the average population of Hispanic students statewide is about 39 percent, whereas the average for charter schools is about 41 percent. Thus the percentages of Hispanic students in charter schools and public schools are similar when viewed in the aggregate. When percentages of Hispanic students in at-risk and non-at-risk charter schools are compared, however, substantial differences become apparent. Within Group 1 at-risk schools, there are about 29 percent more Hispanic students than the state average and 22 percent more than within Group 2. For Group 1, non-at-risk charter schools have more Anglo students (by 26 percentage points). Noteworthy differences appear between at-risk and non-at-risk charter school student populations for several other categories as well. To illustrate, percentages of economically disadvantaged students for charter schools and the state are within one percent of each other (see Table VII.4). However, an examination of the data in Table VII.4 and Table VII.5 reveals that there are many more economically disadvantaged students in at-risk than non-at-risk charter schools: 32 percent more in Group 1 at-risk schools than Group 1 non-at-risk schools. About 27 percent more students in Group 2 at-risk schools are low-income than in Group 2 non-at-risk schools. Other categories for which differences may be found are percentage of special education students and limited-English-proficient (LEP) students (Group 2 only) and percentage of teachers with fewer than five years experience. Student Performance School Level TAAS In the previous section, demographic data were presented to help the reader interpret patterns and establish a context for information about student performance. TAASa key measure of student performanceis central to the state accountability system. The applicability of TAAS as a measurement tool for students in charter schools may vary from school to school (a school serving primarily students with a history of success on TAAS compared with a dropout recovery school). However, TAAS must have a role in the analysis of charter schools for there to be public acceptance of ratings, given the significance of TAAS performance for most other schools in Texas. The reader is urged to consider context when judging changes in TAAS performance. For example, the percentage of Texas students passing TAAS has increased annually. If the performance of students in a school increases by 10 points, it may be considered an outstanding gain if the state average increases by 1 point, but not if the state average increases by 20 points. In this section, the evaluation team has attempted to provide context within which the reader may more appropriately interpret student performance change. Table VII.6 compares charter school and statewide TAAS performance data. The data in Table VII.6 are identical to those published on the TEA web site and include 1999 testing results. Prior-year data appear later in this section. It should be noted that percentages under the charters column combine information from both at-risk and non-at-risk charter schools in Group 1 and Group 2 categories. Also to aid the readers interpretation, Table VII.6 contains a relative difference column, which compares values for charter schools to the state average. The relative difference value is defined as state percent passing minus charter school percent passing divided by the state percent passing. This value is used to help account for differences in initial values. For example, a raw difference of 10 percentage points between a starting value of 10 points and a final value of 20 points represents an increase of 100 percent, whereas a change from 80 to 90 points is an increase of only about 13 percent. Both relative and absolute differences should be considered when examining TAAS performance differences between groups or between years of administration. Basically the relative difference measure highlights movement (or a comparison) from a lower level to a higher level. Table VII.6 TEA Snapshot Data: 1999 TAAS Performance Percent of All Students* Passing TAASCharter Schools (N=61)State Average (N=1042)Relative % Difference**Absolute % DifferenceAll tests taken59.1%78.4%24.619.3Reading76.1%86.6%12.110.5Writing71.3%88.2%19.216.9Mathematics67.2%85.7%21.618.5Percent of Students by Groups Passing All Tests TakenAfrican American42.6%64.1%33.521.5Hispanic59.5%70.1%27.510.6Anglo72.2%87.9%17.915.7Other81.8%89.1%8.27.3Economically disadvantaged54.2%67.9%20.213.7Source: 1999 Snapshot data:  HYPERLINK http://www.tea.state.tx.us www.tea.state.tx.us. The school is the unit of analysis. *"All students refers to students tested in grade levels at which TAAS is administered. **"Relative difference is defined as ((state passing charter passing)/state passing)*100. Neither relative nor absolute differences are included in Snapshot 1999. It is apparent from an examination of the data presented in Table VII.6 that performance in charter schools is lower in all areas, particularly in mathematics and writing. TAAS performance by subgroup also shows charter school performance to be lower than the state subgroup averages. The fact that there are far fewer experienced teachers in charter schools may account for some of the differences, particularly in mathematics performance. Texas schools generally are having difficulty attracting qualified mathematics teachersespecially at higher grade levels, where qualified math teachers may expect higher salaries than some charter schools offer. It is also apparent that the lower performance rate observed in charter schools is consistent across all student groups. Of particular concern is the finding that African American students performance in charter schools is lower than performance of students in other racial/ethnic groups and lower than performance for African American students statewide. African American students comprise a much greater proportion of students in charter schools than in the school population statewide. Because minority students are also frequently classified as economically disadvantaged, the evaluation team distinguishes between students in economically disadvantaged categoriesas well as between at-risk and non-at-risk charter school categoriesin analyses of student performance and progress, beginning with Table VII.9. Table VII.7 presents information that compares charter schools with their public school peer groups as determined by TEA. TEA provides a comparison group or peer group for each Texas campus. Peer groups are not constructed for districts. The peer groups consist of 40 similar schools, based on demographic characteristics such as percentage of minority and economically disadvantaged students and mobility. The purpose of identifying comparison groups or peer groups is to compare campus performance to very similar schools. Table VII.7 contains performance data for the five charter schools for which TEA identified a peer group in 1998-99. For other charter schools, the information needed for this analysis either was not available or was masked because five or fewer students within the school had TAAS scores. Table VII.7 Charter Schools and TEA Peer Groups: Comparison of TAAS Performance Charter School ID and NameCharter SchoolTEA Peer GroupAll Tests TakenReadingMathematicsAll Tests TakenReadingMathematics UH School of Tech81.8%100%81.8%83.6%90.4%91.2% George I. Sanchez 26.5%71.0%35.5%60.6%79.3%68.2% Girls & Boys Prep52.6%74.2%61.7%80.7%88.9%90.0% Medical Center40.9%86.4%40.9%67.1%82.3%72.2% Renaissance 58.8%80.8%67.2%82.2%89.3%90.4%Source: TEA AEIS reports, 1998-99. www.tea.state.tx.us/AEIS/ All charter schools included in Table VII.7 are classified as non-at-risk. Two charter schools outperformed their peer groups in reading on the 1999 TAAS. In the three other cases, charter schools performance was lowerin some cases considerably lowerthan their TEA peer groups performance. TEA peer groups are based on demographics, not on prior TAAS performance. For future peer group comparisons, it should also be noted that students in at-risk charter schools tend to have very low performance levels upon entry into the charter school. Comparisons based on these data are reported because they are in the public record. Still, the viability of the selected comparison may seem inappropriate in some instances. Peer group comparisons cannot be ignored, however, because they are used for the Texas Successful Schools Awards System. Thus, two points should be emphasized. First, whether or not peer groups are equitable, performance differences between charter schools and the peer group averages are quite large in some cases. Second, mathematics performance for charter schools (as noted in Table VII.6) compares less favorably to the state average than does reading performance, regardless of comparison made. The evaluation team acknowledges the difficulty of making appropriate analyses of student performance in relatively new entities such as charter schools. Every effort has been made to identify the appropriate categories within which to make comparisons and to build the most useful comparisons. Within this context, several relevant pointssuch as the small number of campuses and students, difficulties in matching campuses, and so forthare discussed throughout the remainder of this section. The reader is urged to bear these points in mind when forming judgments about the data presented in this section. Limited number of campuses. For this section, only charter schools with at least three years of TAAS data are examined for campus-level analyses of TAAS gain (Tables VII.9 through VII.17). Although this practice reduces the number of campuses that can be examined, the restriction should yield more representative data. In future years, the number of charter schools with a viable history of TAAS (and other performance measures) will increase. This will help stabilize the data at the campus level, especially when schools are separated into at-risk categories. Limited number of students. Within eligible schools, analysis of performance data is further limited by the relatively small number of students in some categories. TEA masks data when fewer than five students are in a category and uses a minimum number of 30 students in a group before counting their performance for computation of accountability ratings. In response to this limitation, the evaluation team has adopted the criteria shown in Table VII.8 for reporting and commenting on TAAS data. Table VII.8 Reporting and Comment Criteria Used in This Section. Student-Level Data When the number of students is TAAS data are Fewer than 30Not reported30 to 50Reported as a relevant findingMore than 50Reported as a finding that may be meaningful In most cases, students from several charter schools may be grouped into a single category. This is necessary because there are relatively few students in some schools or categories. Thus, statistical tests are not appropriate. As the number of students who have attended charter schools increases over the next few years, appropriate statistical analyses will be performed. As will be noted in Table VII.11, the number of students in charter schools with reading scores has increased from 576 in 1997 to 2,816 in 1999. This number is expected to increase again with the 2000 TAAS administration. Non-matched students. When TAAS passing rates are compared over time at the campus level, scores pertain to different sets of students from one year to the next. For this analysis, scores are generally reported as the percent passing for all grade levels combined. (Matched scores for individual students are presented in the next section which reports TLI scores.) Data for each year. Because few students took the TAAS in some schools, data are reported only when there are scores for each of three years. This problem should abate in coming years as enrollments increase. Consideration of all students versus economically disadvantaged students. As explained in the introduction, state-level data for economically disadvantaged students are used as a state-level surrogate for at-risk to make the most reasonable comparisons between at-risk charter schools and state averages. For non-at-risk charter schools, state scores for all students are used for comparison. This seems appropriate, given the relatively small percentage of economically disadvantaged students reported at non-at-risk schools. Starting point and ease of increasing scores. A familiar phenomenon associated with many criterion-referenced tests such as TAAS is a ceiling effect. That is, many students already score at the very upper ranges of measurement. Gains at that point become difficult to achieve. On the other hand, very low scores are frequently associated with significant gains. Progress is often easier to attain when the starting point is very low. Subject areas selected. The analyses presented in this section are restricted to all tests taken, reading, and mathematics. Although writing, science, and social studies are given at selected grades, change over contiguous grade levels cannot be measured. Moreover, writing is highly correlated to the other measures. The reader should note that the all tests taken category relates directly to both reading and mathematics passing rates, and, for certain grade levels, writing. Table VII.9 shows a comparison of student performance on TAAS in charter schools and public schools. These data are based on six at-risk and 10 non-at-risk charter schools that have data for more than five students in both 1998 and 1999 for reading, mathematics, and all tests taken. In most cases these are different students in one year versus the other, as is the case in the presentations in the AEIS reports. The number of schools is less than the total number of charter schools in Group 1 because some schools lack TAAS scores or are subject to masking when there are fewer than five student scores to report. The total number of TAAS answer documents (a measure of the number of students tested) is 262 for at-risk charters, with a range from 27 to 78 at the individual schools. The number for non-at-risk schools is 1,038, with a range from 10 to 308. Generally, the actual number tested and included in the accountability subset is somewhat lessabout 85 percent of students are included in the accountability subset at the state level. More detailed analysis of student level data is included later. The data included in Table VII.9 indicate that students in at-risk charter schools have made a large gain in relationship to economically disadvantaged students at the state level. Table VII.9 Comparison of TAAS Performance Among At-Risk, Non-at-Risk Charter Schools and State Averages Over a Two-Year Period All Tests TakenReadingMathematics19981999Change19981999Change19981999ChangeAt-Risk Charter15.0%30.9%+15.945.5%59.5%+14.020.5%39.6%+19.1State Average Eco-Dis61.2%67.9% +6.773.7%78.2% +4.571.5%78.7% +7.2Non-at-Risk Charter64.0%64.0% 0.081.1%85.7% +4.668.9%71.5% +2.6State Average All Students73.1%78.3% +5.283.3%86.5% +3.280.4%85.7% +5.3Source: Analysis of 1998 and 1999 AEIS data and charter school data extracted from PEIMS Economically disadvantaged students were chosen as the most appropriate comparison group for at-risk charters given the high percentage of economically disadvantaged students in these schools. TEA generally does not publish performance for at-risk students in AEIS reports or consider their performance in determining accountability ratings because district-specific definitions of at-risk may be applied in addition to state-mandated definitions. Given the fact that students in at-risk schools performed at a very low level (on average) in 1998 (e.g., 15 percent passed all tests taken and 21 percent passed the mathematics portion of TAAS), even significant gains in 1999 leave student performance far below the state average for all students as well as the statewide average for economically disadvantaged students. If students in at-risk charter schools maintain their current rate of progress, they will require several years to reach the state average. For example, it would take at-risk schools at least two more years before the passing rate for charter schools equals the state average for economically disadvantaged students, assuming no additional gain in the state average for these students and that charter schools can sustain this strong rate of increase. In addition, the variability among these relatively few schools is remarkable. Gains for at-risk schools for all tests taken ranged from a 44 point gain to a loss of 8 points. For non-at-risk schools, the range included a gain of 14 points versus a loss of 13 points. A more definitive statement regarding the progress of at-risk charter schools in TAAS performance must await the availability of TAAS scores from the 2000 administration. While non-at-risk charter schools, on average, are about equal to the state in reading performance, mathematics and all-tests-taken, passing percentages lag behind the state average. This result is in spite of the fact that the non-at-risk charter schools have a lower percentage of economically disadvantaged students than the state as a whole. The reader is cautioned to remember, however, that with only two years of data, no meaningful trend analysis is possible. Still, the lower performance levels for non-at-risk charter schools in mathematics, coupled with a lower rate of gain than the state average, is an area of concern. The charter schools included in the TAAS calculations and their status as either at-risk or non-at-risk are included in Table VII.10. Table VII.10 Charter Schools Included in TAAS Calculations at Campus Level, Group 1 Subset At-Risk Charter SchoolNon-at-Risk Charter SchoolWaco Charter SchoolTexas Academy of ExcellenceSer-Ninos CharterSeashore Learning Center Building Alternatives CharterWest Houston Charter SchoolAcademy of Transitional StudiesNorth Hills SchoolDallas Can! AcademyPegasus Charter SchoolBlessed Sacrament AcademyGeorge I. Sanchez CharterMedical Center Charter SchoolUniversity of Houston Charter School--TechnologyGirls & Boys Prep AcademyRenaissance Charter School Student Level TAAS Evaluators requested individual student-level dataincluding TAAS information, when availablefor more than 15,000 students enrolled in charter schools during 1997, 1998, or 1999. Because TAAS is currently administered only in grades 3 through 8 and 10, not all students who attended charter schools during those years have TAAS scores for each year. Still, a total of 7,031 students have a TAAS score in one or more of these years, and the resulting database is large enough to allow selected comparisons. Not every student of the 7,031 for whom TAAS scores are available attended a charter school from 1997 through 1999. Although some attended charter schools for three consecutive years, others started out in public schools in 1997 and later transferred to charter schools. Still other students attended charter schools in 1997 and later transferred to public schools. Thus the evaluation team has tracked TAAS scores for these students by location; that is, by the type of school students attended when they took TAAS. The figures in Table VII.11 represent the maximum number of students with TAAS scores in each of the three years as well as their location during that year. When students are matched across years with TAAS scores or separated into various categories, the number per category can be much smaller, as will be noted in Tables VII.12 through VII.17. The number of scores may also differ between reading and mathematics. Table VII.11 Number of Charter School Students with TAAS Scores, by Type of School Attended During the Test Year, 1997 1999 Type of School Student Attended During Test YearStudents with TAAS Reading ScoresStudents with TAAS Mathematics Scores199719981999199719981999Charter school5769002,8166601,0312,856Public school3,1822,7092,1473,3243,8572,255 Data collected for each student include three sets of values related to TAAS performance: (1) an indication of whether the student passed reading and mathematics TAAS subtests (that is, whether the student met minimum expectationsgenerally 70 percent correct); (2) an indication of whether the student mastered all TAAS objectives; and (3) the students Texas Learning Index or TLI score. The TLI is a score that describes how far a students performance is above or below the TAAS passing standard. TLI is provided for both TAAS reading and mathematics tests. TLI can also be used to measure a students progress from one year to the next. If the score this year is the same as last years, the student demonstrated one year of progress. If the TLI score rises (for example, a student with TLI 72 in math in 1997 has a TLI of 80 in math in 1998) the student has made more than one years learning progress. A TLI of 70 represents the passing standard. Comparisons based on TLI are used in Tables VII.12, VII.14, VII.16, and VII.17. Table VII.12 contains data based on individual students TLI scores and on changes in their scores, or TLI Average Gains (TAG). Data for students in at-risk charter schools appear on the left side of the table; non-at-risk, on the right. These data are for matched students; that is, the same student must have a meaningful TLI score both in 1998 and 1999 to be included. Thus, results presented in Table VII.12 are restricted to students who were in grades 3 through 7 in 1998 and grades 4 through 8 in 1999. State averages are derived from simple averages across grade levels. For at-risk charter schools, state-level comparison information for economically disadvantaged students is included in the lower left corner of Table VII.12. Note also that the data are presented according to the type of school in which students enrolled (public or charter) in 1998 and 1999. Table VII.12 TAAS Performance Change (TLI) for All Grade Levels SubjectAt-Risk Charter SchoolsNon-at-Risk Charter SchoolsCharterPublicChangeN StudentCharterPublicChangeN Student1998 TLI1999 TLITAG1998 TLI1999 TLITAGRead******1880.583.9+3.4126Math******2374.777.9+3.2128PublicCharterChangeN StudentPublicCharterChangeN Student1998 TLI1999 TLITAG1998 TLI1999 TLITAGRead80.983.7+2.650580.780.0 -0.71,108Math77.279.4+2.255776.274.5-1.671,137CharterCharterChangeN StudentCharterCharterChangeN Student1998 TLI1999 TLITAG1998 TLI1999 TLITAGRead******1883.585.0+1.5288Math58.166.1+8.03676.878.4+1.6299State Economically DisadvantagedState All Students1998 TLI1999 TLIChange TAGN Student1998 TLI1999 TLIChange TAGN StudentRead77.579.4+1.9756,46582.383.9+1.21,811,186Math74.577.0+2.5765,51678.280.2+1.61,823,345Source: TEA student assessment, analysis of individual student data ** Fewer than 30 students Because so few were tested, TLI data for students attending at-risk charter schools in 1998 and public schools in 1999 are not tabled, in keeping with the evaluation teams reporting criteria (see Table VII.8). Likewise, data for reading for students in at-risk charter schools in 1998 and 1999 are masked. Only for students transferring from a public school to an at-risk charter school are there sufficient numbers of students to examine in a meaningful manner. At-risk charter school students made a 2.6 point TLI gain for reading and a 2.2 point gain for mathematics. Their gains are slightly greater for reading than the state average gain for economically disadvantaged students (to whom at-risk charter school students are compared in this section). The gains for mathematics are not quite as large as the comparison group. These charter school students start out slightly higher than the state average for economically disadvantaged students (about 30 percent of students who attend at-risk schools are not economically disadvantaged). Overall, economically disadvantaged students score about 10 points lower than students who are not economically disadvantaged. This mix of student demographic background in at-risk charter school may account for the initial differences in scores between state averages and at-risk charter school students. A different pattern is noted for non-at-risk charter schools. Students transferring from non-at-risk charter schools to public schools show gains of about 3 points, about twice the average gain for all students in the state. However, students transferring from public schools to non-at-risk charter schools show small losses. For students attending non-at-risk charter schools during both test years, the average gain is about equal to the state average gain for all students. As was noted when campus-level information was examined (see Tables VII.9 through VII.11), gains achieved by students in non-at-risk charter schools are not as great as student gains in at-risk charter schools. In fact, for the majority of studentsmore than 1,000the average change is a loss (in terms of TLI score) when transferring from public to non-at-risk charter schools. On the other hand, when students transfer from charter to public schools, the gain is about twice the state average. It must be emphasized that attributing causality of this change will always be difficult. The issue of whether these changes in performance should be attributed to the relative instructional strength of the school cannot be answered from these data alone. Tables VII.13 and VII.15 contain information about percentages of students mastering all objectives for TAAS reading and mathematics subtests. Mastering all TAAS objectives is much more difficult than passing TAAS. There are six reading objectives and 13 mathematics objectives. Generally, three out of the four items must be answered correctly within objectives before a students score is considered to be at the mastery level. By contrast, as was explained in the introduction, students can generally pass TAAS by answering 70 percent of items correctly. Table VII.13 is similar to Table VII.12 because it allows the reader to compare the performance of students attending public schools and charter schools and during 1998 and 1999. Like Table VII.12, Table VII.13 distinguishes between at-risk and non-at-risk charter schools when presenting performance data. However, because data are not published for the state for economically disadvantaged students mastering all objectives, comparisons between this group and at-risk charter school students cannot be made. Table VII.13 TAAS Mastering All Objectives for All Grade Levels SubjectAt-Risk Charter SchoolsNon-at-Risk Charter SchoolsCharterPublicN StudentCharterPublicN Student19981999Change19981999ChangeRead******1833.3%41.3%+8.0126Math******2314.1%19.5%+5.4128PublicCharterN StudentPublicCharterN Student19981999Change19981999ChangeRead31.3%43.4%+12.150533.0%35.8%+2.81,108Math26.2%29.4% +3.255720.7%13.8%-6.91,137CharterCharterN StudentCharterCharterN Student19981998Change19981999ChangeRead******1849.3%53.8%+4.5288Math3%3%0.03626.4%25.8%-0.6299State All Students19981999ChangeN StudentRead44.9%50.9%+6.01,756,814Math31.0%33.1%+2.11,770,792Source: TEA student assessment, analysis of individual student data An examination of the TAAS mastery data presented in Table VII.13 reveals patterns that are similar to those noted in Table VII.12 for TAAS passing rates. These data, whether for at-risk or non-at-risk charter schools or for the state average, reflect lower performanceand less positive change in performancefor mathematics than for reading. Because TAAS data are available for so few students attending at-risk charter schools in 1998, the evaluation team offers no commentary about their scores. However, the change in mastery level for students transferring from public schools to at-risk charter schools compares favorably to the state average. For students attending non-at-risk charter schools in both 1998 and 1999, the percentage mastering all reading objectives started out higher than the state average; however, the rate of improvement is slightly less than the state average gain. Like passing, the mastery gains for students moving from a charter to a public school exceed those moving from a public school to a charter school. Similar to Table VII.12, Table VII.14 contains information about changes in performance on TAAS as measured by TLI average gains by students in public and charter schools. Table VII.14 presents information on students in grade 10. Because TAAS is currently not administered in grade 9, it is necessary to use data from the 1997 TAAS (rather than the 1998 TAAS) for students who took the 1999 TAAS as 10th graders when making comparisons of performance growth. During the intervening year (1998), about 60 percent of these students attended public schools. Table VII.14 TAAS Performance Change 1997 (Grade 8) to 1999 (Grade 10) SubjectAt-Risk Charter Schools*Non-at-Risk Charter SchoolsCharterPublicChangeN StudentCharterPublicChangeN Student1997 TLI1999 TLITAG1997 TLI1999 TLITAGRead--------85.789.7+4.073Math--------77.782.1+4.473PublicCharterChangeN StudentPublicCharterChangeN Student1997 TLI1999 TLITAG1997 TLI1999 TLITAGRead79.282.8+3.64980.179.8-0.387Math72.675.5+2.95469.869.9+0.187State Economically DisadvantagedState Non-Economically Disadvantaged1997 TLI1999 TLIChangeN Student1997 TLI1999 TLIChangeN StudentRead75.279.2+4.070,13784.786.3+1.6155,588Math72.674.9+2.370,70679.980.3+0.4156,388Source: TEA student assessment, analysis of individual student data *Because there were no at-risk charter schools with an 8th grade during 1997, that cell of Table VII.15 is blank. According to data shown in Table VII.14, there was a TLI gain for students transferring from public schools to at-risk charter schools. That gain is very similar to that shown for economically disadvantaged students in the state overall, as shown in Table VII.12. Similar to the pattern found when performance at lower grade levels was examined in Table VII.12, Table VII.14 reveals TLI gains above the state average for non-at-risk charter students who transferred to public schools and smaller TLI gainsor lossesfor those transferring from public to non-at-risk charter schools. Although data are available only for approximately 50 students in the at-risk schools shown in Table VII.14, their patterns of gain are strikingly similar to those found for the 500-plus elementary and middle school students included in Table VII.12. The pattern of very small gains or losses reported in Table VII.14 for students transferring from public to non-at-risk charter schools resembles the pattern observed in Table VII.13 for lower grade levels. Too few data were available for students attending charter schools in 1997 as 8th graders and in 1999 as 10th graders for an analysis. It is anticipated that more data will become available for this category when TAAS 2000 scores are examined. Table VII.15 is similar to Table VII.13, in that it presents information about percentages of students mastering TAAS reading or mathematics subtests. As was the case with Table VII.14, however, Table VII.15 reports only on students who were in grade 10 in 1999. Table VII.15 TAAS Percent Mastering All Objectives 1997 (Grade 8) to 1999 (Grade 10) SubjectAt-Risk Charter Schools*Non-at-Risk Charter SchoolsCharterPublicN StudentCharterPublicN Student19971999Change19971999ChangeRead--------49.3%62.4%+13.173Math--------28.8%42.5%+13.773PublicCharterN StudentPublicCharterN Student19971999Change19971999ChangeRead26.5%55.1%+28.64921.8%48.3%+26.587Math22.2%37.0%+14.85420.7%23.0%+2.387State All Students19971999ChangeN StudentRead37.0%61.0%+24.0200,000**Math27.0%31.0%+4.0200,000**Source: TEA student assessment, analysis of individual student data **Because there were no at-risk charter middle schools with an 8th grade during 1997, that cell of Table VII.17 is blank. ** Varies by grade level, in excess of 200,000 students, not matched. A contrast may be noted when comparing Table VII.14 and Table VII.15. Although TAG values increase only slightlyor in some cases even declinethe percentage of charter school students mastering all objectives increases. This was the case for non-at-risk schools both in reading and mathematics, and for the state average in reading. Table VII.16 is provided to help make sense of this seeming contradiction. Table VII.16 examines changes in students TLI scores over two years for all school types in greater detail than previous analyses. It must be noted, however, that additional data would be required to make definitive statements about the comparisons shown in Table VII.16. Therefore, the evaluation team considers this information on Table VII.16 as relevant, but because of small numbers, not likely to yield meaningful information for policy guidance. Because the current average state TLI for reading is approximately 85, TLI scores of 80 and above are designated as high and scores below that point are designated as low. Table VII.16 Movement of Students Between TLI Categories, Grade 8 to Grade 10 TLI CategoryAt-Risk Charter Schools*Non-at-Risk Charter SchoolsPublic 1997Charter 1999Public 1997Charter 1999Charter 1997Public 1999High TLI**273156565970Low TLI**2218313114 3Total Number494987877373Source: TEA student assessment, analysis of individual student data * There were no at-risk middle charter schools with an 8th grade during 1997. **High TLI is defined as 80 or greater; low TLI is defined as less than 80. For the 49 eighth graders who took TAAS in public schools in 1997 and transferred to at-risk charter schools by 1999, there was an increase in the number of students with scores in the high category and a corresponding decline in the number of students with low scores. A total of 87 students had transferred from the public school they attended in 1997 as 8th graders to non-at-risk charter schools by 1999. In this case, the number of students in high and low TLI categories did not change from 1997 and 1999. On the other hand, all but three of the 73 students moving from non-at-risk charter schools to public schools scored in the upper TLI range in 1999. A closer examination of the data indicate that the number of very low performing students in the at-risk charter schools remains about the same from 1997 to 1999. On the other hand, for the non-at-risk charter schools, the number of the very lowest performing students actually increases. For example, there were 15 students who had a TLI of 70 or less in 1997. For the same group of 87 total students in 1999, there were 17 students with a TLI below 70, and these students TLI performance had declined by about five points. On the other hand, those students moving from a charter to a regular public school showed an increase in the number of students in the high TLI range and a large drop in those below a TLI of 80. Thus the overall passing rate and/or TLI can increase or remain the same for a group of schools with some students moving lower in the score range. Yet at the same time, the performance of other students in the same group may improve to the extent that they master all objectives. Conclusions and judgments about performance based on averages mask performance gains and declines in all types of schools, public and charter. Information used for general reporting and institutional accountability should be supplemented with student-level information to plan appropriate instructional programs. Table VII.17 contains a detailed examination of student performance over three years as measured by TLI changes. Because this analysis requires three consecutive years of TAAS scores, the number of students in the data set is quite small, and grade 10 is omitted. To have enough students per group, percentages for at-risk and non-at-risk charter schools are combined, and two categories still contain fewer than 30 students. On the other hand, one category contains more than 1,000 students. This method of examination will be more effective over the next several years as scores for greater numbers of students become available. In addition, greater numbers will allow analyses that differentiate between students in at-risk and non-at-risk schools. Rows in Table VII.17 are ordered by declining numbers of students within categories; thus row order is related to the relative stability and meaning of the numbers. For ease in reference, rows are numbered as well as labeled. Table VII.17 Change in TLI Over Three Years 1: State averagesState 1997State 1998State 1999N StudentsReading80.682.383.91,756,814Mathematics76.878.280.21,770,7922: Pub/pub/chartPublic 1997Public 1998Charter 1999N StudentsReading79.482.382.31,107Mathematics76.078.478.11,1303: Pub/chart/chartPublic 1997Charter 1998Charter 1999N StudentsReading85.284.986.1156Mathematics79.779.080.21594: Pub/chart/pubPublic 1997Charter 1998Public 1999N StudentsReading83.581.084.373Mathematics79.777.480.2735: Chart/chart/chartCharter 1997Charter 1998Charter 1999N StudentsReading73.979.880.530Mathematics67.671.577.6336: Chart/pub/pubCharter 1997Public 1998Public 1999N StudentsReading******27Mathematics******287: Chart/chart/pubCharter 1997Charter 1998Public 1999N StudentsReading******25Mathematics******25Source: Analysis of 1998-99 AEIS data and charter school data extracted from PEIMS Row 1 of Table VII.17 contains average TLI changes for reading and mathematics statewide. From 1997 to 1998, the change for reading is a gain of 1.7 TLI points; from 1998 to 1999, a 1.6 point gain. Students whose scores are represented in row 2 also attended public schools during 1997 and 1998. Their reading TLI scores increased by 2.9 TLI points during that time. Because their scores were slightly below the state average in 1997, this gain brought their performance to almost equal to the state average in 1998. However, there was no additional gain from 1998 to 1999 when they moved from public to charter schools. Moreover, their mathematics performance declined slightly after they entered charter schools. Graph VII.1 displays this information in a different way. Individual lines correspond to enrollment patterns that are tracked in Table VII.17. For comparison, the performance of students who were enrolled in public school districts for the three years under consideration is depicted. Students attending a charter school for three years were initially at a lower level than students in the other groups. They had a six point TLI average gain after one year and a one point gain in the second year. The gap between this group of charter school students and students in public schools narrowed considerably. Graph VII.1. Comparison of Student Reading Performance, by School Enrollment Type  SSS State Average 1997, 1998, 1999 PPC Public 1997, Public 1998, Charter 1999 PCC Public 1997, Charter 1998, Charter 1999 PCP Public 1997, Charter 1998, Public 1999 CCC Charter 1997, Charter 1998, Charter 1999 TLI score changes for students attending public schools in 1997, transferring to charter schools in 1998, and staying through 1999 are shown in row 3 of Table VII.17. These students started out considerably above the state average (SSS) in 1997 (nearly five points in reading). After moving to charter schools in 1998, their performance declined slightly, then increased in 1999 to a point about equal to their 1997 level. Their net TLI gains over two years are 0.9 for reading and 0.5 for mathematics. Finally, row 4 contains information on students attending public schools in 1997, transferring to charter schools in 1998, and then returning to public schools in 1999. For 1998, their TLI scores both in reading and mathematics declinedby 2.5 and 2.3 respectively. However, in 1999 their TLI scores increased. Their reading TLI increased by 3.3, resulting in a net gain of 0.8, whereas their mathematics TLI increased by 2.8, for a net gain of 0.5. Performance of students represented in rows 6 and 7 of Table VII.17 are not discussed following the earlier evaluation team guideline regarding numbers of students in a category. Student Engagement Measures Some educators argue that TAAS is not an appropriate performance measure for some charter schools, particularly for schools serving at-risk students at the secondary level. For this reason, the evaluation team examined other measures of student performance to complement the report on TAAS. Tables VII.18 through VII.21 contain non-TAAS student performance information from AEIS. When listed, the number of charter schools appears as 61; the number of districts in the state as 1,042. However, the actual number of schools and districts varies according to indicators used in tables. For example, attendance information is available for all schools and districts, whereas dropout information is available only for schools and districts with grade 7 and higher. Similarly, college admission testing rates and school completion data are restricted to schools with graduating seniors. Table VII.18 Student Performance Other Than TAAS Performance MeasureCharter Schools (N=61)State Average (N=1042)Attendance rate (1997-98 school year)88.8%95.3%Percent tested (College admission) 199832.5%61.7%Percent above criterion (College) 1998 0.0%27.2%SAT I mean total (College) 1998756992ACT mean composite (College) 199815.820.3Source: 1999 Snapshot data: www.tea.state.tx.us As is apparent from Table VII.18, the average attendance rate for charter schools is lower than the attendance rate for the state. As shown in Table VII.19, a large difference in attendance rates exists between at-risk and non-at-risk charter schools. Attendance rates for at-risk charter schools are quite low, averaging 84 percent, while non-at-risk charter schools average 92.6. Thus average attendance rates for both types of charter schools fall below the state average of 95.3 percent and below the state requirement of 94 percent for acceptable performance. Another indirect measure of student engagement is the rate at which students take college admission exams. Students interested in pursuing higher levels of education are more likely to attempt either the SAT or ACT. Table VII.18 contains information about rates at which schools with upper-grade students take college admission exams. A comparison of rates reveals a large difference in the percent tested: well over half of students statewide take college admission tests, whereas not quite one-third of charter school students do so. The data do not help us learn why this discrepancy exists. It may be because many charter school students are at-risk and have lower expectations for future education. It may be due to economic status and the cost of the tests. Additionally, low-income students may see four-year college study as a financial impossibility and plan to attend a community college where the SAT and ACT are not required. Level of school performance, parent expectations or other factors AEIS does not report could also be factors. For charter school students taking ACT or SAT, the percent scoring above the criterion marks (1110 for SAT and 24 for ACT) is reported as zero. This is reflected in the much lower average scores for both tests. Although universities typically consider student qualifications other than test scores, scores in the 1,100 range are generally considered to be minimally acceptable at many major state universities that do not accept all applicants. Table VII.19 Attendance by Charter School Type Performance MeasureStudents Attending At-Risk Charter SchoolsStudents Attending Non-at-Risk Charter SchoolsAttendance (1997-98 school year)84.0%92.6%Source: Analysis of student-level data School Completion Measures Data presented in Tables VII.20 and VII.21 allow comparison of annual dropout rates in charter schools to the state average. The 1997-98 dropout rates are the most current available to the evaluation team at the time of the report. Although dropout rates for at-risk and non-at-risk charter schools vary considerably, rates for both types of schools exceed the six percent annual rate set by the state to designate schools as low-performing. Charter school completion rates reported by TEA are, as might be expected from the dropout rate, far below the state average. Table VII.20 Student Performance Other Than TAAS Performance MeasureCharter Schools (N=61)State Average (N=1042)Annual dropout rate (1997-98)15.6% 1.5%Completion rate (class of 1998)64.4%91.5%Source: 1999 Snapshot data: www.tea.state.tx.us Table VII.21 Other Student Performance by Charter School Type Performance MeasureStudents Attending At-Risk Charter SchoolsStudents Attending Non-at-Risk Charter SchoolsAnnual dropout rate 1997-9820.0% 8.4%Source: Analysis of student-level data Summary Texas charter schools serve a student population that has a higher percentage of low-income and minority students. Within Texas public school districts, 14 percent of the students are African American, whereas this group comprises 33 percent of Texas charter school student population. The percentage of Hispanic students in charter schools is roughly the same as the state average, and the percentage of Anglo students is less than the state average. Overall, charter schools report six percent of students in special education and three percent in bilingual education, lower than the overall state percentages receiving such services. Schools serving at-risk students have higher percentages of minority students, more economically disadvantaged students, more students identified for special education services, higher mobility rates, less experienced teachers, and a higher percentage of revenue allocated for instruction. The teacher turnover rate in charter schools is 55 percent, considerably higher than the 15 percent turnover reported for public schools Salaries for administrators and teachers are lower in charter schools than state average salaries. Lower relative experience of charter school educators accounts for part of the difference. Total operating expenditures per pupil for charter schools are less than the state average for public schools. Part of the difference is accounted for because charter schools serve lower proportions of special-needs students than do public schools. Persons interested in the performance of charter schools and charter school students should bear in mind the enrollment, staffing, and finance context when making judgments about performance. Performance on TAAS is lower in charter schools as a group than the state average for all public schools. TAAS performance by subgroups also shows charter school performance to be lower than the state average for corresponding subgroups. (There are individual instances of very high charter school performance that do not get highlighted when averages are reported.) Students in charter schools for at-risk students performed at low levels in 1998, but made strong gains in 1999. However, these gains leave performance for these students far below the state average for all students as well as the statewide average for economically disadvantaged students. The performance of at-risk charter schools is highly variable, with one school posting a 44-point gain and another an 8-point loss. In general, if students in at-risk charter schools maintain their current rate of progress, they will require more time to reach the state average, assuming no additional gains in the state average. A more definitive statement regarding performance progress of at-risk students must await the availability of one or more years of TAAS data. Students attending non-at-risk charter schools during 1998 and 1999 have a performance gain that is about equal to the state average gain for all students. Gains achieved by students in non-at-risk charter schools are not as great as student gains in at-risk charter schools, and the data reported here show some losses (in terms of TLI score) for students transferring from a public school to a non-at-risk charter school. For all types of students considered together, students attending a charter school for three years started with a lower performance level. They had a six-point TLI gain in the first year and a one-point TLI gain in the second year. The gap between students in charter schools for all three years and students who had different attendance patterns narrowed considerably during three years. The average attendance rate for charter school students is lower than the statewide attendance rate, and the difference between schools serving at-risk students and schools serving non-at-risk students is large. Dropout rates for both types of charter schools exceed the six percent annual rate set by the state to designate schools as low performing. Charter school completion rates are also well below the state average. Section VIII: Charter School Revenues and Expenditures Charter schools are funded almost entirely from state aid. They receive foundation program tier one and tier two funding for each student in average daily attendance (ADA). Tier one funding is based on what the students foundation program allotments would have been in the public school district where they live. For tier two, charter schools receive per-student funding based on the county average tier-two tax effort. This approach avoids the disparities that would occur because of different property tax rates in individual school districts. Foundation program allotments per student are higher if a student is eligible for career and technology education, bilingual education, compensatory education, gifted and talented education, or special education. If students are served by a compensatory education program, the charter school must offer free or reduced price lunches. Like public schools, charter schools are subject to state information reporting requirements of the Public Education Information Management System (PEIMS). In October of each year, charter schools and public schools report revenue and expenditure estimates from their adopted budgets. At the end of the fiscal year, charter schools and public school districts report actual revenue and expenditures. This section describes revenues and expenditures of Texas charter schools based upon an analysis of data reported by the ˿Ƶ (TEA). Data for public schools and charter schools for 1997-98 were obtained from PEIMS budget data reported by TEA. Data for charter schools for 1998-99 were obtained from the TEA Financial Data Mart Reports of PEIMS actual financial data. Program expenditure data come from TEA Snapshot 99 data. Finance data for traditional public schools for 1998-99 come from the TEA Ad Hoc Reports web site. Included in this report is 1997-98 school expenditure information for 19 (the first-generation) charter schools that were approved by the State Board of Education before August 1998, as well as 1998-99 expenditure information for 42 additional charter schools that were granted charters by the State Board of Education and were in operation by the fall of the 1998-99 school year. As with other sections of the full report, schools are grouped into two categories: at-risk and non-at-risk, with at-risk being defined as charter schools with a stated mission to serve at-risk students and with enrollments comprising a majority of at-risk students, as well as schools defined as 75% Rule charter schools as shown in Table VIII.1. Table VIII.1 Charter Schools Classified as At-Risk and Non-at-Risk At-RiskNon-at-RiskAcademy of Accelerated LearningAcademy of HoustonAcademy of Skills and KnowledgeAlief Montessori Community SchoolAcademy of Transitional StudiesAmerican Institute for LearningBlessed Sacrament AcademyBright Ideas CharterBuilding Alternatives CharterBurnham Wood Charter SchoolCedar Ridge Charter SchoolEagle Advantage Charter SchoolCoastal Bend Youth CityEd White School of Educational EnhancementDallas Can! Academy CharterEden Park AcademyE.L. Harrison Charter SchoolEncino SchoolGabriel Tafolla Charter SchoolGeorge I. Sanchez Charter High SchoolGulf Coast Trades Center/Raven SchoolGirls and Boys Prep AcademyHarris County Juvenile Justice CharterHiggs, Carter, King Gifted and Talented Charter AcademyHouston Can! Academy Charter SchoolMainland Preparatory AcademyImpact CharterMedical Center Charter SchoolJohn H. Wood Charter SchoolNancy Ney Charter SchoolKipp Inc. Charter New Frontiers Charter SchoolLa Escuela de las AmericasNorth Hills SchoolLife Charter School of Oak CliffNova School (West Oak Cliff)One-Stop Multiservice Charter NYOS Charter SchoolSER-Nios Charter SchoolPegasus Charter SchoolSouthwest Preparatory AcademyRapoport AcademyTechnology Education Charter High SchoolRaul Yzaguirre School for SuccessTexas Empowerment AcademyRenaissance Charter SchoolUniversity Charter SchoolSchool of Excellence in EducationWaco Charter SchoolSeashore Learning CenterStar Charter SchoolTexas Academy of ExcellenceTransformative Charter AcademyTwo Dimensions Preparatory AcademyUniversity of Houston School of TechnologyUniversal AcademyVarnette Charter SchoolWest Houston Charter SchoolTotal At-Risk: 25Total Non-at-Risk: 33 Sixty-one charter schools will be discussed in this section. Twenty-six additional charter schools that were open in 1998-99 are not included because data for them were not available. Of the 61 charter schools, 58 have information about mission and students served: 25 are at-risk schools, and 33 are non-at-risk schools. Where practical, comparisons are made between at-risk and non-at-risk charter schools, as well as between traditional public schools and charter schools. Revenue Sources Funding for public education in Texas comes from three primary sources: local, state, and federal. Local funding is derived from taxes on district property value. State funding is based on a finance system defined in state statute. Federal funds are appropriated by Congress, usually for specific programs or populations of students and must be expended for designated purposes. Table VIII.2 compares the sources of revenue for traditional public schools with charter schools for 1997-98 and 1998-99. Table VIII.2 Comparison of Revenue Sources for Traditional Public Schools and Charter Schools for 1998-99 Revenue SourcePublic Schools (Percentages)Charter Schools* (Percentages)Local (property tax)520State4486Federal35Other19Source: TEA Snapshot 99, pages 350 and 368. * For 1997-98, N=19; for 1998-99, N= 57. For 1998-99, revenue data were not available for the following schools: E.L. Harrison Charter School, George I. Sanchez, Rameses School, and New Frontiers Charter School. Charter schools do not have the authority to impose taxes; therefore, their primary source of funding is state revenue. In 1998-99, charter schools received five percent of their revenue from federal sources and nine percent from other sources, compared with three percent and one percent received by traditional public schools from these sources. When comparisons are made on a per-student basis (Table VIII.3a), charter schools received less per student in state revenue ($4,709) than the combined local and state revenue of traditional public schools ($5,659). Table VIII.3a Comparison of Per-Student State and Total Revenue for Traditional Public Schools and Charter Schools for 1998-99 Revenue SourcePublic Schools*Charter Schools* (N=57)State$2,275$4,225Total Revenue$5,658$4,709Source: TEA Snapshot 99, pages 350 and 368. * Public school enrollment: 3,945,089; charter school enrollment: 11,127. No reports were available for E. L. Harrison, George I. Sanchez, Rameses, or New Frontiers. ** Amounts are rounded to the nearest dollar. In the 1998-99 school year, the total revenue for charter schools ranged from receiving no revenue to revenue totaling $4,244,056, with an average total revenue per school of about $858,000. Total revenue for all charter schools was $57,569,461, with a total revenue per pupil of $4,709. The reported averages include anomalies such as schools failing to report revenue in some categories. It is anticipated that, with experience, charter schools will improve the quality of their data reporting. A comparison of the per-student revenue of at-risk and non-at-risk charter schools (Table VIII.3b) indicates that at-risk charter schools receive more state funding ($4,625) than non-at-risk charter schools ($3,655). Table VIII.3b Comparison of Charter School Per-Student Revenue for 1998-99 (N=57) Revenue SourceAt-Risk Schools* Charter (n=24)Non-at-Risk Schools** Charter (n=33)Local (taxes)$0$0State$4,625$3,655Source: ˿Ƶ, PAI Data Central: Financial DM Reports, http://penick.tea.state.tx.us/datacentral/Home/fdmreports.htm. * At-risk charter school enrollment: 4,523 ** Non-at-risk charter school enrollment: 6,604 Expenditures Texas schools report expenditures by function, object, and, in some cases, by program. Functions describe the broad purpose of expenditures, such as instruction or administration; objects describe the service or item purchased, such as salaries or supplies; and program classifications are used to identify instructional areas or arrangements, such as regular, special, and bilingual education programs. Expenditures by Function Table VIII.4 shows expenditures by function for 1997-98 for the first-19 charter schools. In the 1997-98 school year, half of charter school expenditures were for instruction and instruction-related services. It was also in these two areas that the greatest per-student expenditure occurred. Table VIII.4 Charter School Expenditures by Function for 1997-98 (N=19) ExpenditureTotal Expenditures Percent of Total ExpendituresPer-Student ExpendituresInstruction and instruction-related services$8,911,32050.03$2,580Instructional leadership$6,9080.03$2School leadership$1,502,4908.44$435Student support services$1,298,7047.29$376Student transportation$335,0381.88$97Food services$262,5041.47$76Extra-curricular and co-curricular activities$79,4420.45$23Central administration$1,968,78011.05$570Plant maintenance and operation$2,963,53216.64$858Security and monitoring$169,2460.95$49Data processing$231,4181.29$67Community services$82,8960.47$24Total$17,812,278$5,157Source: ˿Ƶ, PEIMS 1997-98, final budget data. Charter schools still spend more than traditional Texas public schools on central and general administration. Most charter schools are smaller than public schools and school districts; therefore, their greater administrative costs may be due to a lack of central infrastructure and an inability to take advantage of economies of scale. The lowest per-student expenditures were in the areas of instructional leadership, extra-curricular and co-curricular activities, community services, and security and monitoring. Table VIII.5 presents charter school expenditures over a three-year period. Table VIII.5 Comparison of Charter School Expenditures by Function for 1996-97, 1997-98, and 1998-99 ExpendituresPercent of Total Expenditures for 1996-97 (N=17)Percent of Total Expenditures for 1997-98 (N=19)Percent of Total Expenditures for 1998-99 (N=58)Instruction and instruction related46.750.055.8Instructional leadership0.50.11.0School leadership7.58.410.4Student transportation1.11.90.5Food services2.81.51.5Extra- and co-curricular0.80.40.4Plant maintenance and operation19.716.611.5Security and monitoring1.20.90.6Data processing1.81.31.2Community services0.70.50.1Other functions17.218.417.2Source for 1996-97: Texas Open-Enrollment Charter Schools Second Year Evaluation, p. 20 Source for 1997-98: ˿Ƶ, PEIMS 1997-98, final budget data. Source for 1998-99: ˿Ƶ, PAI Data Central: Financial DM Reports,  HYPERLINK http://penick.tea.state.tx.us/datacentral/Home/fdmreports.htm http://penick.tea.state.tx.us/datacentral/Home/fdmreports.htm. Expenditure data were not available for E.L. Harrison Charter School, George I. Sanchez, and Rameses School In the 1998-99 school year, instruction accounted for more than 60 percent of expenditures in traditional public schools and about 56 percent of expenditures in charter schools. Table VIII.6 shows charter school current operating expenditures by function for 1998-99. More than half of total expenditures were for instruction and instruction-related functions. Table VIII.6 Charter School Budgeted Expenditures for 1998-99 (N=58) ExpenditureTotal ExpendituresPercent of Total ExpendituresInstructional$29,454,85652School leadership 4,531,5168Central administration 8,496,59415Plant maintenance and operation 7,363,71413Other operating 5,664,39510Non-operating1,132,8792Total$56,643,954Source: TEA Snapshot 99, page 369. Instructional expenditures comprise 52 percent of budgeted expenditures, central administration makes up 15 percent of charter school expenditures, and transportation (not shown) makes up less than one percent of the other operating expenditures. Traditional public school budgeted expenditures for instruction are about 51 percent, central administration is about six percent, and transportation makes up about three percent of budgeted expenditures. The per-student total operating expenditure for charter schools is $4,633 per pupil compared with $5,219 for public schools. Table VIII.7 presents a comparison of operating expenditures for selected at-risk charter schools and non-at-risk charter schools for 1998-99. Table VIII.7 Operating Expenditures by Function, At-risk and Non-at-Risk Schools, 1998-99 Expenditure FunctionAt-Risk Charter Schools (n=25)Non-at-Risk Charter Schools (n=33)PercentPer StudentPercentPer StudentInstruction53.3$3,65254.3$2,330Instruction-related services0.9$590.6$27Curriculum/ staff devel.1.8$1252.0$85Instructional leadership0.7$501.2$53School leadership12.8$8737.3$312Guidance/ counseling2.8$1951.5$64Health services0.2$160.6$24Student transportation0.4$270.6$27Food services*0.7$492.3$97Co-/extra-curricular0.4$260.4$17General administration14.8$1,01313.6$584Plant maintenance & operation9.4$64313.4$574Security/ monitoring0.5$360.7$32Data processing1.2$801.3$54Community services >0.1$20.3$12Total$6,846$4,292Source: ˿Ƶ, PAI Data Central: Financial DM Reports, http://penick.tea.state.tx.us/datacentral/Home/fdmreports.htm. * Food services expenditures are comparable only when aggregated across all funds. At-risk total enrollment: 4,523; non-at-risk total enrollment: 6.951. Notice that the percent for instruction is greater than that reported for all charter schools in Tables 5 and 6. This subset of 58 schools has some schools with much higher overall expenditures than the average of all charter schools. Data reporting for charter schools presents anomalies and outliers that affect averages and percentages. The reader is cautioned to look only for general trends within these data, and the general trend shows that at-risk charter schools spend proportionally than their non-at-risk counterparts. As Table VIII.7 shows, at-risk and non-at-risk charter schools spent a similar percentage of total expenditures for instruction, but revenue available to non-at-risk schools is less. At-risk charter schools spent proportionally more on school leadership and non-at-risk schools spend proportionally more on general administration. Expenditures by Object Objects of expenditure include payroll, professional and contracted services, and supplies and materials. Table VIII.8 displays charter school expenditures by selected object categories in 1998-99. Table VIII.8 Objects of Expenditure by Percentage for Charter Schools for 1998-99 Expenditure ObjectCharter Schools * (N=59)At-Risk Charter Schools (N=24)Non-at-Risk Charter Schools (N=35)Payroll (6100)62.2%59.4%65.2%Professional/ contracted svcs. (6200)26.528.823.9Supplies/materials (6300)5.75.85.6Other operating expenses (6400)4.705.334.0Debt services (6500)1.00.71.3Capital outlay (6600)0.00.00.0Source: ˿Ƶ, PAI Data Central: Financial DM Reports,  HYPERLINK http://penick.tea.state.tx.us/datacentral/Home/fdmreports.htm http://penick.tea.state.tx.us/datacentral/Home/fdmreports.htm. * Total charter school student membership: 11,961 (at-risk = 4,523; non-at-risk = 7,438). Data were not available for E.L. Harrison Charter School and Rameses School. Payroll expenditures are the largest category for charter schools (and for traditional public schools). Professional and contracted services comprised slightly more than one-fourth (26.5 percent) of charter school object expenditures. This category of expenditures is for services rendered to school districts by firms, individuals, and other organizational entities. Expenditures by Program Instructional expenditures are a sub-set of operating expenditures and are categorized by program. Table VIII.9 shows a comparison of program expenditures for 1997-98 and 1998-99. In 1998-99, charter schools offered more special programs in the previous year and this is reflected in changes in expenditure percentages. Table VIII.9 Percentage Comparison of Charter School Program Expenditures for 1997-98 and 1998-99 ProgramPercent of Expenditures*1997-98 (N=19)1998-99 (N=61)Regular program9086Gifted & Talented0<1Career & Technology13Special education<14Compensatory education75Bilingual education22Sources: ˿Ƶ, PEIMS 1997-98, final budget data for 1997-98. The source for 1998-99 is Office of Policy Planning and Research, Division of Performance Reporting, ˿Ƶ, Snapshot 99: 1998-99 School District Profiles,  HYPERLINK http://www.tea.state.tx.us/perfreport/snapshot/99/state.html. http://www.tea.state.tx.us/perfreport/snapshot/99/state.html. *Budgeted expenditures. Table VIII.10 shows a comparison of program expenditures for traditional public schools with those for charter schools for the 1998-99 school year. Charter schools budgeted a greater percentage for regular education than traditional public schools, and traditional public schools spent a greater percentage in all other areas listed. Table VIII.10 Percentage Comparison of Program Expenditures for Traditional Public Schools and Charter Schools for 1998-99 ProgramPercent of ExpendituresTexas Public SchoolsCharter Schools* (N=61)Regular education7186Gifted & Talented2<1Career & Technology43Special education124Compensatory education75Bilingual education32Source: Office of Policy Planning and Research, Division of Performance Reporting, ˿Ƶ, Snapshot 99: 1998-99 School District Profiles,  HYPERLINK http://www.tea.state.tx.us/perfreport/snapshot/99/state.html. http://www.tea.state.tx.us/perfreport/snapshot/99/state.html. * Budgeted expenditures. Summary Texas open-enrollment charter schools derive the majority of their funding from state revenue and receive very little revenue from federal and other resources. There are some exceptions to this generalizations for schools with aggressive fund-raising programs. And Since they are not authorized to impose local taxes, charter schools receive no local tax funding. A little over half of charter school expenditures are for instruction and instruction-related services. Charter schools spend more than Texas public schools for general administration, which may be attributed to their smaller size and diminished ability to take advantage of economies of scale. At-risk charter schools spent a greater percentage of total expenditures for school leadership, and general administration, while non-at-risk charter schools spent a greater percentage of total expenditures for general administration and plant maintenance and operation. As with traditional public schools, the majority of budgeted program expenditures for charter schools was for regular education, with charter schools spending a greater percentage of their total expenditures in this area when compared with traditional public schools. From 1997-98 to 1998-99, charter school spending increased for special programs. Section IX: Commentary and Policy Challenges The 1998-99 school year marked Texas third year of experience with open-enrollment charter schools. With the expansion of charter schools in the state, more information becomes available for examination and critique. In the third year of evaluating open-enrollment charter schools, the evaluation team explored the experiences and opinions of charter school students and their families, public school administrators perceptions of charter schools, the performance of charter school students, and the operations of charter schools. While charter schools serve a relatively small proportion of Texas students, these schools continue to increase in number and in student enrollment. In 1998-99, 89 charter schools operated for the entirety of the school year, serving about 17,600 students. As of July 2000, the Texas State Board of Education (SBOE) has approved 178 charters over four charter school generations. Of the charters awarded, 169 are active. Over 140 charter schools operated in the 1999-00 school year. Much of the evaluation data, by nature, is self-reported or charter-collected, and thus the team relies, in part, upon charter school administrators to ensure compliance with evaluation team requests for data. As the number of charter schools increases, it becomes increasingly important to impress upon charter school directors, leaders, and principals, the need to comply with information requests associated with the Texas charter school evaluation. Data Disaggregation Charter schools in Texas are diverse and varied in terms of enrollment, ethnicity, grade levels, instructional methods, board composition, and teacher preparation and experience. Thus, when averages and other statistical measures are computed for the purpose of the evaluation, extreme caution is encouraged. By aggregating results, the diversity of charter schools may be neglected. While at-risk and non-at-risk grouping for evaluation purposes may alleviate some of these concerns, because of the diverse nature of charter schools, some examination must occur beyond the aggregated level. With the increasing number of charter schools, disaggregation along grade levels becomes more meaningful. At the campus level, examining the experiences of outliers should be considered, as this may influence the removal of these schools for certain analyses in order to gain a more clear understanding of general trends in Texas charter schools. It is difficult to make generalizations about charter schools because there is so much variation within the group of 89 schools operating in 1998-99. Efforts to group and analyze schools that are similar to one another produce problems with very small sample sizes. The evaluation team anticipates that as more charter schools open, more data will be available that will permit further refinements in classification and grouping. The growth in charter schools (and enrollment in them) will also provide more powerful information for study in 1999-00 and beyond. Racial and Ethnic Diversity Evidence grows that Texas open-enrollment charter schools are more racially distinctive than the states traditional public schools. Third-year evaluation results indicate that charter schools are racially distinctive when compared to the student populations of the school districts in which they are located. Analyses of charter parent survey data offer an explanation of why this is so. Parents and students have a tendency to choose charter schools that have higher concentrations of their particular ethnic groups. Anglos pick schools with higher percentages of Anglo students than the schools they leave, African Americans pick schools with higher percentages of African American students than the schools they leave, and Hispanics pick schools with higher percentages of Hispanics than the schools they leave. An additional explanation of the racial distinctiveness of charter schools may be the way that most choosers hear about them from family and relatives. Such networks are usually segregated by race and class, and this segregation is replicated in schools when students are recruited by word of mouth. The impact of this method of publicizing charter schools is magnified by the absence of any standardized, racially neutral method for informing the public generally about the existence and location of charter schools. Even parents who live in relative proximity to charter schools often are not aware of them. Another concern is the ability of charter schools to define their attendance zones. These zones are often dominated by a single racial/ethnic group, further contributing to the potential for the creation of racially distinctive charter schools. The evaluation team makes no comment about the desirability of racial distinctiveness of charter schools. It also makes no claim to understand the motives of households that choose the charter school option. The overriding concern is that racial distinctiveness in charter schools gives an opportunity to their critics and may contribute to controversy that overshadows the educational opportunities that such schools may offer. One policy change to address this would be to require some means of informing the public in general about the existence of charter schools. Such a step would alleviate the current dominance of friend and relative communication. A second step would be to prohibit charter schools from defining attendance zones or eliminate the requirement in law that boundaries be identified. Student Satisfaction Students continue to say they choose to attend charter schools because of the classes offered. This is especially the case for at-risk students, who seem to prefer attending a school that caters to their unique academic needs. The students feel that they get more personalized attention from the teachers, they like the smaller class sizes, and they enjoy having classes that target their interests. Furthermore, very few students attending schools for at-risk students report being dissatisfied with the school, and they give their charter school a much higher grade than they give to schools they have attended in the past. This same high level of satisfaction with charter schools is not seen among students attending charter schools not intended to serve at-risk students. Students in non-at-risk charter schools tend to be no more satisfied with the charter school than with their previous school, and they do not give the charter school a higher grade than their previous school. Thus, charter schools seem to be particularly adept at capturing and serving students who might otherwise drop out of school. For those students who are not at-risk but are looking for an alternative to regular public schools, however, charter schools as a whole do not seem to be fulfilling expectations. The level of overall satisfaction of students attending non-at-risk schools is lower than that of students attending at-risk schools, but it has changed very little over the past three years. In fact, though the percentage of students giving their non-at-risk charter school a failing grade has increased by 50 percent, the percentage of students giving their school an excellent grade has also increased by 33 percent. Despite the overall positive evaluations that at-risk students give to their charter school, the level of satisfaction has been declining over the past three years. The number of students very satisfied with their school has decreased since 1996-97, and the number of students dissatisfied has increased. As further evidence, the percentage of at-risk students giving their charter school a failing grade has quadrupled since 1996-97 and tripled since 1997-98. Evaluators do not have an explanation for this decline in satisfaction, but it is cause for concern. If charter schools wish to maintain a steady stream of applicants, they should strive to maintain high levels of student satisfaction. Parent Choices If one examines the expressed first choices of parents, the teaching of moral values is the most important reason expressed for charter school selection. Next most important is better discipline, and then high test scores. An examination of parent actions with regard to enrolling their children in school shows that students are transferring to charter schools with lower TAAS passing percentages than the public schools from which students transferred. They also enroll their children in a charter school that more accurately mirrors their own ethnicity than did the previous public school. School location also appears to constrain the choices made by parents of charter school students, although parents do not mention this as a highly important consideration. Parent Satisfaction with Charter Schools Charter school parents like the charter schools better than the schools their children previously attended. They give the charter schools higher marks than comparison group parents give to the public schools their children attend. The parents of at-risk charter school students are even more satisfied with the charter schools than are parents of students in non-at-risk schools. Charter schools are clearly fulfilling a need that some parents have for an alternative when they are dissatisfied with the public school. Effects on Public School Districts Superintendents from public school districts near charter schools are aware that students are leaving the districts to attend charter schools, but districts often do not have accurate data about who is leaving and who is returning. For this reason, it is difficult to determine precisely whether charter schools are somehow growing at the expense of public schools or whether they truly represent a complementary system. Some superintendents were concerned that charter schools were skimming good students (and their involved parents) away from public schools, while others reported that the charter school benefited the district by providing an alternative for difficult to educate, disaffected, or disruptive students. Areas of particular concern for superintendents include a belief that some charter schools do a poor job educating students and concern that charter schools are not being held accountable for students academic progress. A few superintendents believe that some directors running charter schools lack requisite managerial and financial experience and have concerns that some charter schools are not really open-enrollment. Some superintendents are also concerned that charter schools will affect the financial base for traditional public schools. Funding Like their public school counterparts, charter school leaders frequently report having inadequate financial resources. Fiscal data show charter school resources per student to be less than public school resources, in part because charter schools do not have access to property tax funding for facilities. Lower per-student funding is also related to the fact that charter schools serve smaller proportions of special-needs students. Charter school fund balances are extremely low (some schools have no fund balance), and this is a source of concern. School directors may need some assistance in public funds management and accounting to gain skill in building fund balances. Fund-raising from foundations, businesses, and individuals takes a significant amount of time for many charter school administrators, and schools also ask parents to participate in this activity. As charter schools become more skilled in business operations, directors may be able to improve the adequacy of their overall funding. For example, charter school directors may be able to increase attendance rates (or improve attendance reporting) and thereby improve their overall revenue outlook. Student Performance Student academic performance as a factor for evaluating charter schools reveals some interesting results. Charter school students in schools for at-risk students show performance gains but not enough to catch up (within a year or two) with the state average for all students or the state average for low-income students. Student performance in non-at-risk charter schools presents a complex picture. Some students perform well in a charter school setting, as well or better than peers in public schools. Others do not perform as well. Clearly, there is wide variance among charter schools in terms of student learning measured by TAAS. At a few schools, students perform at exemplary levels, and at a few others the results are well below the state performance standard. Three years of data (the first two of which include fewer than 20 schools) provide a starting point. Meaningful results on performance of students in charter schools await analyses conducted in 2000 and beyond. Attendance and Dropout Rates Charter school student attendance is below the state attendance standard. Attendance at at-risk schools is more than ten percentage points below that standard. These findings are a concern for two reasons. First and foremost, students need to be present at school (or at a school-sanctioned activity outside the campus) to learn from their teachers and peers. Second, lower attendance will result in lower funding, a topic of high concern for charter school administrators. Charter schools may want to seek ideas from public school districts about ways to improve attendance or work together among themselves to resolve this issue. Dropout rate calculations and statistics are at issue in Texas schools today. For this reason, judgment about dropout rates in charter schools should be tempered by the same concern and thoughtfulness as dropout rates across all types of schools. However, assuming the data and calculations for charter schools are no worse than they are for public school districts, there exists a very large gap in the performance of public and charter schools in terms of dropout and completion rates. Efforts should be made to narrow this gap, even if it cannot be expected (in the case of at-risk charter schools) to close within a few years. Appendix A Parents of Charter School Children Telephone Survey Parents of Charter School ChildrenTelephone Survey Year 3 ___________ ID: 1-4 Parents Name__________________________________________________________ Phone Number: Area Code________ Number_____________________ C5-7 C8-14 Charter School Name____________________________________________________________ C15-16  Hello, my name is ___________ and Im calling from __________________________ for the ˿Ƶ. The ˿Ƶ is required by state law to evaluate the Charter School program. May I speak to the parent or guardian of (STUDENTS NAME). (ONCE CORRECT RESPONDENT IS ON THE PHONE). For parents of children in Charter Schools, the ˿Ƶ would like to get information about your experience with your childs Charter School. If you have a few minutes, I would like to ask you some questions about the Charter School your child attended last year. (ONCE AGREEABLE CONTINUE) If you have more than one child in a charter school, the question will be about your OLDEST child who attended a Charter School last year. C17. Respondent Gender: Male___1 Female___2 1. What is the gender of your oldest child who attended a Charter School last year? (RECORD) C18. Male___1 Female___2 2. In what year was that child born? C19-20. 19___________ 3. How many years has that child attended a Charter School? C21. One year or less___1 Two years___2 Three or more___3 UNSURE___4 4. What was your childs grade or school year last year? (RECORD 1 through 12, if K code 0) C22-23______ 5. How did you learn about the Charter School? (RECORD) C24. Newspapers___1 C25. Television or radio___1 C26. Private Schools___1 C27. Public Schools___1 C28. Community Center___1 C29. Church___1 C30. Friends/Relatives___1 C31. Teachers___1 C32. Other______________________________________________________________________________ Write in Reason 6. Since your child has been in Charter School, how big a problem has it been to transport your children to school? Has it been a substantial problem, somewhat of a problem, just a small problem, or no problem at all? C33. Major problem___1 Somewhat___2 Small problem___3 No problem at all___4 7. For your child to be admitted to the Charter School, did he or she have to take a placement exam? C34. Yes___1 UNSURE___2 No___3 8. Did you have to sign a school-parent contract which requires you to supervise the homework for your child in the Charter School? C35. Yes___1 UNSURE___2 No___3 9. Did you or your spouse have to agree to do volunteer work at the school? C36. Yes___1 UNSURE___2 No___3 10. Did your child attend a private or public school prior to enrolling in the Charter School? C37. Private___1 Public___2 11. [IF PUBLIC SCHOOL ASK] What is the name of the school your child attended before he or she went to a Charter School? C38-39________________________________________________________________ 12. What is the name of the school district in which that school is located? C40-41__________________________________________________________________ 13. Different parents have different reasons for sending their children to Charter Schools. I will read you a list of some of the things parents think are important about a school. Which of the following characteristics of the Charter School your child attended last year was the single most important reason for moving your child to that Charter School. The reasons are: C42. Randomly Rotate Order High math or reading scores___1 Better Discipline___2 Students that are mostly the same race as your child___3 The location of the Charter School___4 Teaching moral values in school___5 Safety_____6 NONE/CANT CHOOSE/DONT KNOW___7 14. Is there some other reason that is more important than [REASON MENTIONED] for sending your child to a Charter School? C43-44___________________________________________________________________ 15. Next I will read you the five remaining characteristics from our initial list. Which of the remaining five was the most important reason for moving your child to a Charter School? C45. Randomly Rotate Order High math or reading scores___1 Better discipline___2 Students that are mostly the same race as your child___3 The location of the Charter School___4 Teaching moral values in school___5 Safety___6 NONE/CANT CHOOSE/DONT KNOW___7 16. Finally, I will read you the last four characteristics. Which of the last four was the most important reason for moving your child to a Charter School? C46. Randomly Rotate Order High math or reading scores___1 Better discipline code___2 Students that are mostly the same race as your child___3 The location of the Charter School___4 Teaching moral values in school___5 Safety___6 NONE/CANT CHOOSE/DONT KNOW___7 17. If you could afford it, would you send your child to a private school or not? (RECORD) C47. Yes___1 No___2 18. What do you think your child will do once he or she graduates from high school (READ OPTIONS) C48. Go to work___1 Join the military___2 Go to technical or vocational school___3 Go to community college___4 Go to a four year college___5 Other___6 19. At the school your child attended before he or she went to a Charter School, in general were you very satisfied, somewhat satisfied, somewhat dissatisfied or very dissatisfied with . . . Very Somewhat Somewhat Very [Randomly Rotate Order] Satisfied Satisfied Dissatisfied Dissatisfied UNSURE C49. The teachers 4 3 2 1 5 C50. Teaching moral values 4 3 2 1 5 C51. The location 4 3 2 1` 5 C52. The discipline 4 3 2 1 5 C53. Parent/Teacher relations 4 3 2 1 5 C54. Parents having an adequate 4 3 2 1 5 say on how the school was run 4 3 2 1 5 C55. The background of the students 4 3 2 1 5 20 At the Charter school your child attended last year, in general were you very satisfied, somewhat satisfied, somewhat dissatisfied or very dissatisfied with . . . Very Somewhat Somewhat Very [Randomly Rotate Order] Satisfied Satisfied Dissatisfied Dissatisfied UNSURE C56. The teachers 4 3 2 1 5 C57. Teaching moral values 4 3 2 1 5 C58. The location 4 3 2 1` 5 C59. The discipline 4 3 2 1 5 C60. Parent/Teacher relations 4 3 2 1 5 C61. Parents having an adequate 4 3 2 1 5 say on how the school was run 4 3 2 1 5 C62. The background of the students 4 3 2 1 5 21. If you were to grade the school your child attended before going to a charter school from A to F, what grade would you give it? (RECORD) C63. A___1 B____2 C____3 D___4 F___5 UNSURE___6 22. If you were to grade the Charter School your child attended last year, what grade would you give it? C64. A___1 B____2 C____3 D___4 F___5 UNSURE___6 23. At the Charter school your child attended last year, did you or your spouse ever (READ OPTIONS) YES NO UNSURE C65. Attend a PTO meeting or other special school meeting 1 2 3 C66. Attend a school board meeting 1 2 3 C67. Help make program or curriculum decisions 1 2 3 C68. Attend a school play or concert 1 2 3 C69. Help with fundraising 1 2 3 C70. Attend parent/teacher conferences 1 2 3 24. In your view, was the school your child attended before going to a charter school safe, somewhat unsafe or very unsafe? C71. Safe___1 Somewhat unsafe___2 Very unsafe___3 UNSURE___4 25 Where would your child have gone to school last year if the Charter School option had not been available? (READ OPTIONS) C72. Neighborhood public school___1 Magnet public school___2 Private religious school____3 Private non-religious school___4 Home school____5 Would have dropped out___6 DK___7 26. Did you or your spouse ever visit the school that your child attended before going to charter school? C73. Yes___1 No___2 27. [IF YES] About how many times a year did you visit? One, two, three, four or more? C74. One visit___1 Two visits___2 Three visits___3 Four or more___4 UNSURE___5 28. At the school your child attended before going to the Charter School, did you or your spouse ever (READ OPTIONS) YES NO UNSURE C75. Attend a PTO meeting or other special school meeting 1 2 3 C76. Attend a school board meeting 1 2 3 C77. Help make program or curriculum decisions 1 2 3 C78. Attend a school play or concert 1 2 3 C79. Attend a school athletic event 1 2 3 C80. Help with fundraising 1 2 3 C81. Attend parent/teacher conferences 1 2 3 29. Have any of your children dropped out of school before receiving a high school degree? C82. Yes___1 No___2 30. In summary, how satisfied were you with the Charter School your child attended last yearvery satisfied, somewhat satisfied, somewhat dissatisfied or very dissatisfied? C83. Very satisfied___1 Somewhat satisfied____2 Somewhat dissatisfied___3 Very dissatifeid____4 UNSURE 5 31. It is important for us to know if your child falls into the at risk category. The state defines a student as being at risk if he or she has failed any section of the most recent TAAS exam, or has failed two or more courses in the previous year. Does your oldest child who attended a Charter School last year fall into this at risk category? C84. Yes___1 UNSURE___2 No___3 RF___0 Finally, Id like to finish by asking you a few brief background questions. 32. What is the highest level of education you completed? (RECORD) C85-86. 8th grade or less___1 9-11th grade___2 GED___3 High School Grad____4 Less than two years college___5 More than two years of college, but no degree___6 College degree___7 Graduate degree___8 RF___0 33. Are you currently employed full time, part time, looking for work, disabled, in school, a homemaker, or retired? C87. Full time___1 Part time___2 Looking___3 Disabled___4 In school____5 Homemaker___6 Retired___7 34. [IF PART TIME] How many hours a week do you work? C88-89.______________________ 35. Are you married and living with your spouse, not married but living in a marriage like relationship, separated or divorced, never married, or widowed? C90. Married w/spouse____1 Marriage like relationship___2 Separated or divorced____3 Never Married____4 Widowed___5 RF___0 36. [IF MARRIED/LIVING WITH PARTNER] Is your spouse/partner employed full-time, part-time, or not working? C91. Full time___1 Part time___2 Not working____3 37. How often do you attend churchmore than once a week, once a week, several times a month, a few times a year, or never? C92. More than once a week___1 Once a week___2 Several times a month___3 A few times a year___4 Never___5 UNSURE___6 38. Do you, yourself, happen to be involved in any charity or social service activities, such as helping the poor, the sick or the elderly? C93. Yes___1 UNSURE___2 No___3 39. Other than for your childs school, in the past 12 months have you gotten together informally with or worked with others in your community or neighborhood to try to deal with some community issue or problem? C94. Yes___1 No___2 40. Do you own or rent your home? (RECORD) C95. Own____1 Rent___2 OTHER___3 41. How many years have you lived at your current residence? C96-97__________ 42. Have you ever received public assistance, such as AFDC or SSI? (RECORD) C98. Yes___1 UNSURE___2 NO___3 43. [IF YES} Are you currently receiving public assistance? C99. Yes___1 No___2 RF___0 44. Which of the following best describes your race or ethnicity? (READ OPTIONS) C100. White or Anglo___1 Black or African-American___2 Hispanic or Mexican-American___3 Asian or Asian-American___4 Native-American___5 OTHER___6 45. Which languages are spoken in your home? (RECORD) C101. English___1 C102. Spanish___1 C103. Chinese___1 C104. Vietnamese__1 C105. Other___1 46. What is your zip code? C106-107______ 47. Last year, in which category did your total family income fall? (READ OPTIONS) C108. Less than $5000___1 $5000-$9,999___2 $10,000-$14,999___3 $15,000-$19,999___4 $20,000-$24,999___5 $25,000-$34,999___6 $35,000-$49,999___7 $50,000-$74,999____8 more than $75,000____9 RF___0 48. One final question. Were you born in the United States? C109. Yes___1 No___2 RF___0 Thank you for your time. Texas Education Code 12.101(a)(1) - 12.101(a)(4).  The state limits the number of open-enrollment charter schools to 120 and allows for an unlimited number of charters for schools serving at least 75 percent of the student population classified as at-risk. Some schools with open-enrollment charters do, however, serve a student population of more than 75 percent at-risk students.  At the time of the analysis, the at-risk information could not be obtained from H.O.P.E., P.O.W.E.R., Paso del Norte, Positive Solutions Charter School, Rameses School, and Treetops School International; however, information obtained from TEA after the analysis reveals that H.O.P.E. and P.O.W.E.R. are at-risk schools H.O.P.E., P.O.W.E.R., and Rameses School no longer serve as charter schools.  School of Urban and Public Affairs, University of Texas at Arlington, et al., Texas Open-Enrollment Charter Schools: Third-Year Evaluation. Part One (Austin, TX: Texas Center for Educational Research, March 2000), pp. 10-11.  Analyses of parent preferences controlling for the at-risk/non-at-risk distinction and for race/ethnicity were carried out. The results for the at-risk/non-at-risk analysis are not presented here because a X2 indicated that the differences between the two groups are not different from zero at conventionally accepted levels of statistical significance i.e., the differences can be accounted for by random variation alone. Crosstabulations of parent preferences and race did indicate that Anglos, African Americans, and Hispanics differ with respect to the things they feel are important in a school. Subsequent multivariate analysis, however, indicated that these racial and ethnic differences rarely survive controls for other variables such as education, church attendance, the number of years at the charter school, and the parents expectations for the children once they leave high school. Furthermore, the rare cases in which race/ethnicity persist in the presence of these controls disappear when interactive terms are introduced. Hence, it is not African American respondents who are most likely to say that the teaching of moral values is most important, but African American respondents with lower levels of educational achievement; and it is not Hispanic parents who say that discipline is most important, but Hispanic parents with children in lower grades. In short, these data do not support the proposition that the attributes that parents say are important in schools differ by the race or ethnicity of the parent.  These percentages were computed after weights were applied for race/ethnicity.  Data on racial/ethnic distributions for some charter schools in operation in 1998-99 were not available from the ˿Ƶ website. Self-reported data from the charter schools were substituted for missing AEIS data where available.  Data are not presented for the parent groups for non-at-risk and at-risk charter schools separately because there are no statistically significant differences between the two in terms of the grades they would assign to their childrens previous schools.  Parent satisfaction data are not presented separately for parents of the non-at-risk and at-risk school groups because the differences between them were statistically significant only for the parent input attribute. Differences on all other attributes failed a X2 test of statistical significance.  Interestingly, however, the overall grades are not as high as the grades that parents who previously sent their children to private schools assigned to those schools. Differences in grades assigned to charter schools between parents who previously sent their children to private schools and those who previously sent their children to public schools are not presented because they did not pass a X2 test of statistical significance i.e., they can be explained solely by random variation.  The evaluation team shares authorship of Section VII with Academic Information Management, Inc.  Texas Open-Enrollment Charter Schools, Third-Year Evaluation. Part One, identifies the classification of 83 of 89 schools that operated in 1998-99. Six schools did not provide enough information to the evaluation team to permit their classification. See Part One, page 11, Table II.2.  Texas Education Code 29.081 (d).  Throughout this report, TEA Snapshot Data refers to information currently accessible to the public via the TEA web site ( HYPERLINK http://www.tea.state.tx.us) www.tea.state.tx.us). This information is also in the publication TEA Snapshot 99, published by TEA in April 2000.  The passing standard for acceptable performance of a subgroup for 2000 is 50 percent.  The rate is referred to as actual to distinguish it from the estimated rate previously reported in TEAs annual Report on Public School Dropouts.  Academic Information Management, Inc. is an educational consulting company in Austin, Texas.  Average charter school total operating expenditures are similar to the average operating expenditures of small school districts in Texas.  TAAS reporting is for the evaluation. Texas Education Code 12.118(b)(1).  www.tea.state.tx.us  Procedures for identifying peer groups may be found on the ˿Ƶ web site in the AEIS section. Look for comparable improvement reports.  HYPERLINK http://www.tea.state.tx.us/perfreport/ci/99/index.html www.tea.state.tx.us/perfreport/ci/99/index.html  The calculation for this projection is as follows: 30.9 percent plus (15.9 percent times two) equals 62.7 percent passing, compared to the state average in 1999, which was 67.9 percent.  The majority of students with experience at a charter school during 1997, 1998, or 1999 years also had public school experience during one or more of those years. The table shows the reading and mathematics data for the three years. In 1997, for example, analysts found 3,758 students (576 + 3,182) who had reading scores and who had attended a charter school in at least one of the three school years.  No attempt to separate schools according to duration-of-operation group has been made in Tables VII.11 through VII.17.  For this report, the evaluation team considers TLI scores of 30 or greater to be meaningful. TLI scores of less than 30 are excluded. TLI scores above 84 are included.  Overall, economically disadvantaged students score about 10 points lower than students who are not economically disadvantaged. Performance in this intervening year is presented in Table VII.17. Although data for additional students are available, their TLI scores are not high enough to be considered meaningful. Refer to Table VII.8 for criteria for reporting. It should not be assumed, however, that only four students changed categories and that all their scores improved. It is possible that some students with high TLI scores in 1997 scored in the low TLI range in 1999. This presentation is simply the counts of students in the various categories.  Refer to Table VII.8 for criteria for reporting.  Basic allotment adjustments for cost of education index and enrollment size are based on county averages.  http://penick.tea.state.tx.us/datacentral/Home/fdmreports/htm  http:// HYPERLINK http://www.tea.state.tx.us/adhocrpt/ www.tea.state.tx.us/adhocrpt/  Table VIII.1 contains the names of 58 charter schools. At-risk classification data were not available for Positive Solutions Charter School, Rameses School, and Treetops Schools International.  These schools are the following: Benjis Special Education Academy Charter School, Children First Academy of Dallas, Children First Academy of Houston, Faith Family Academy of Oak Cliff, Freedom School, Gateway, Guardian Angel Performance Academy, Heights Academy, Heritage Academy, H.O.P.E. Charter School, Jesse Jackson Academy, Northwest Mathematics, Science, and Language Academy, L.O.V.E., La Amistad Love and Learning Academy, Mid-Valley Academy, Radiance Academy of Learning, Ranch Academy, Rylie Faith Family Academy, Richard Milburn Alternative High School (Corpus Christi), Richard Milburn Alternative High School (Killeen), Sentry Technology Prep School, South Plains Academy, Texas Serenity Academy, Theresa B. Lee Academy, Valley High Charter School, and Waxahachie Faith Family Academy.  Texas Education Code, Chapter 42, Subchapter E.  Texas Education Code 12.102(4).  ˿Ƶ, Snapshot 99 (Austin, TX: TEA, April 2000), pp. 351 and 369.     1998-99 Charter School Evaluation, Part Two, Pg.  PAGE 1 1998-99 Charter School Evaluation, Part Two, Pg.  PAGE 20 1998-99 Charter School Evaluation, Part Two, Pg.  PAGE 50 1998-99 Charter School Evaluation, Part Two, Pg.  PAGE 61 1998-99 Charter School Evaluation, Part Two, Pg.  PAGE 66 1998-99 Charter School Evaluation, Part Two, Pg.  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