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1 2014 Impacts of Career and Technical Schools on Postsecondary Outcomes: A Case Study of a Large Urban School District Ruth Curran Neild Vaughan Byrnes Center for Social Organization of Schools Everyone Graduates Center Johns Hopkins University October 2014

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3 Impacts of Career and Technical Schools on Postsecondary Outcomes: A Case Study of a Large Urban School District Ruth Curran Neild Vaughan Byrnes Center for Social Organization of Schools School of Education Johns Hopkins University October

4 Table of Contents EXECUTIVE SUMMARY... 5 SECTION I: INTRODUCTION The Philadelphia Context Data Methods SECTION II: ENROLLMENT IN POSTSECONDARY EDUCATION Descriptive Comparisons of Enrollment in Postsecondary Education Estimates of Impact on College Enrollment SECTION III: PERSISTENCE IN POSTSECONDARY EDUCATION Descriptive Comparisons of Enrollment in Postsecondary Education Estimates of Impact on Persistence SECTION IV: POSTSECONDARY DEGREE ATTAINMENT Descriptive Comparisons of Postsecondary Degree Attainment Estimates of Impact on Postsecondary Degree Attainment SECTION V: RECEIPT OF PELL GRANTS APPENDIX REFERENCES

5 EXECUTIVE SUMMARY Within the past decade, public investments and private donors have sought to remake the high school in various ways: by organizing them around unifying themes, creating improved curricula for students who enter high school underprepared, developing standards and end-ofcourse exams, breaking larger schools into smaller units, and creating small autonomous schools. Despite this flurry of activity, there has been relatively little discussion about the role of Career and Technical Education (CTE) schools in preparing students to enter higher education and the workforce, although career and technical l high schools have been part of the American educational landscape since at least the 1930s. For many years, these schools were called vocational schools, but have acquired the more general career and technical designation in an effort to re-brand them as providing preparation for postsecondary education and the world of work. A result of the lack of research on CTE schools is that there has been no gathering of evidence on their effects on a variety of student outcomes, including academic achievement, labor market outcomes, and postsecondary enrollment. This report addresses that gap by presenting evidence on the impact of CTE schools in one city Philadelphia, Pa., on postsecondary enrollment, persistence, and degree attainment. These analyses follow up on a previous report on CTE schools and high school attainment and achievement outcomes. The research questions for this report are: What is the effect of CTE schools on enrollment in two-year or four-year degreegranting institutions of higher education? What is the effect of CTE schools on persistence in two-year or four-year degreegranting institutions of higher education? What is the effect of CTE schools on two-year or four-year degree attainment? This report presents findings from a case study of five CTE schools in the School District of Philadelphia. Three cohorts of students the Classes of 2003, 2004, and 2005 are the focus. Students in these cohorts were admitted to the CTE schools through a lottery that admitted students through random selection, taking into account student race/ethnicity to achieve courtordered racial balance in the schools. This study takes advantage of this so-called natural experiment by comparing outcomes for applicants who were admitted with those for students who did not receive an acceptance. Three types of estimates are created for each outcome: 1) an Intent-to-Treat (ITT) estimate, which compares outcomes for students who were accepted to CTE schools to outcomes for students who were not accepted; 2) a Local Average Treatment Effect (LATE) estimate, which takes into account the actual take up of the offer of admission by students; and 2) a Dosage estimate, which compares students who attended a CTE school to students who did not attend. 5

6 Key findings include: CTE schools had a positive impact on postsecondary enrollment, although the effects were not consistent across cohorts. For the Class of 2003, there were positive ITT, LATE, and Dosage impacts of CTE schools on enrollment in two-year colleges. For the Classes of 2004 and 2005, there were positive impacts on enrollment in four-year colleges. For the Classes of 2003 and 2004, there were positive impacts of enrolling in either a two-year or a four-year college. We conclude that there appear to be positive CTE impacts on postsecondary enrollment, although they are not as consistent across cohorts as we might want to see. The positive effects of CTE schools on postsecondary enrollment were not driven by a single school or a single cohort. CTE impacts on postsecondary enrollment were mediated by high school graduation. When postsecondary outcomes are examined for high school graduates only, there is no significant CTE impact. A descriptive analysis of mean outcomes by cohort and CTE school indicates that while the magnitude of the differences between treatment and control students varies from school to school, the impacts are not being driven by a single CTE school or subset of schools. 6

7 The Context of Career and Technical Education in Philadelphia During the school years that are the focus of this study ( through ), the School District of Philadelphia had four high schools where the primary focus was on providing career and technical training for students who hoped either to pursue postsecondary education or enter the workforce immediately after high school. A fifth high school was given CTE status for the Class of These high schools served students from across the district. There were many more applicants in each cohort than the CTE schools could serve, and they admitted students using a lottery that took into account only student race/ethnicity (to achieve racial balance) and how highly each student had prioritized the school on his application form. For the Class of 2003, CTE schools entered all applicants into their lotteries, regardless of their prior achievement, attendance, or behavior. For the Classes of 2004 and 2005, each of the CTE schools screened applicants for school-related performance. After removing students with weaker records from the applicant pool, the schools conducted their lotteries. As a result of this screening, the CTE Classes of 2004 and 2005 entered high school with stronger academic performance than the Class of Career and technical courses were offered at most of the approximately 40 public high schools in Philadelphia. Some of the larger neighborhood high schools had a variety of CTE courses of study that rivaled those of the CTE schools. But in general, the greatest variety of occupationally focused courses was to be found at the career and technical high schools. Across both CTE and neighborhood high schools, saw a gradual decrease in the variety of CTE schools, including a decline in the number of single-class courses of study (e.g. child care). At the same time, the number of students across the district who enrolled in any CTE course during high school rose slightly. During the administration of Superintendent Paul Vallas ( ), and under pressure from Perkins III requirements, the district began to emphasize courses of CTE study that allowed students to earn certificates, corresponded to areas of job growth and opportunity in the local labor market, and enabled partnerships with local companies and city government (e.g. firefighting). During the time that the Classes of 2003 through 2005 were attending high school, however, this focusing and aligning programs of study with local industry was just beginning. It is important to be clear that, in general, the CTE programs that Philadelphia s students experienced did not garner any award or notice for being exemplary, nor were they cutting edge models of excellence (Philadelphia Workforce Innovation Board, 2008; Philadelphia Youth Network. 2009). It is also noteworthy, however, that the career and technical high schools operated within a district that supported high school choice and that encouraged all high schools to offer college preparatory courses in mathematics, science, and foreign language. How were CTE impacts measured? This study relies entirely on student record data kept by the School District of Philadelphia. These data include enrollment and graduation status, transcript information (including course grades), test scores, attendance, special education status, English language 7

8 learner status, and school(s) attended, from eighth grade forward, in addition to applications to high schools and high school admissions decisions. Two strategies are used to model Intent-to-Treat estimates. The first strategy, which uses a multilevel model, allows students to be represented in the data set multiple times, with the frequency equivalent to the number of CTE schools applied to. Students are nested within a specific lottery/cohort combination. In this model, the treatment and control groups resulting from each school s lottery for each cohort are compared. By comparing students within the same lottery, we eliminate any bias that might have resulted from different CTE schools using different criteria to screen applicants into their lottery; this is of concern for the Classes of 2004 and A disadvantage of this model is that it potentially underestimates the impact of CTE schools as a whole because some students who are considered treatment students at one CTE school are considered controls at another CTE school. Our second modeling technique uses fixed effects, with controls for the school(s) to which the student applied and their cohort. Students are represented once in the data set. The advantage of this modeling strategy is that it will not produce an underestimate of CTE effects as serious as the multilevel strategy described above; its disadvantage is that it does not directly compare students who were accepted and not accepted to particular CTE schools. The statistical significance of the estimates and direction of the effects produced by these two Intent-to-Treat strategies are consistent across most outcomes. The Dosage estimate uses the multilevel modeling strategy described above but introduces a control for the proportion of the time a student attended a CTE school while enrolled in a Philadelphia public high school. All models controlled for student race/ethnicity as empirical analysis demonstrated that the probability of acceptance at particular CTE schools in particular cohorts varied according to racial/ethnic background. Implications This research is a case study of the effects of CTE schools in a particular large city school district during a particular time period that spanned Perkins III and Perkins IV. As with any case study, a full interpretation of the results must take into account how the city s social and educational context affects how the community and district staff perceive CTE schools. While this report does not present an exhaustive analysis of how parents and students view Philadelphia s CTE schools, the empirical data demonstrate that in Philadelphia, these schools were highly sought after. Large percentages of eighth-graders applied to at least one CTE school for high school. Further, while the CTE schools in Philadelphia were rather ordinary in terms of their occupational focus and curriculum, they were subject to school district efforts to increase college-preparatory course taking in all high schools. Thus, there were many opportunities for 8

9 students at Philadelphia s CTE schools to take college-preparatory mathematics, science, and foreign language. The high percentages of CTE students who earned credits in these courses supports the argument that, in this context, CTE schools did not behave as a dead end school or a school of last resort. One of the clear messages of this report, then, is that it is not always or necessarily the case that CTE schools are associated with weaker academic outcomes for students. In some situations Philadelphia being one of them academic outcomes for CTE schools may equal or exceed those of other schools in the district. That these impacts were observed in a research study that used randomized design strengthens the validity of this assertion. It is beyond the scope of this study to establish the mechanisms by which CTE schools come to have the impacts we observe. Several differing, but not mutually exclusive, mechanisms could be hypothesized. Perhaps there is something powerful about CTE education, including the possibility that it helps students to see more clearly the connections between school and workplace success. Or, there may be nothing intrinsically important about CTE as a school focus; instead, the important factor may just be that the school had a focus, in contrast to neighborhood high schools, which try to be all things to all students. There may be peer effects associated with bringing together students who have the personal advantages and prior achievement, demonstrated by participating in school choice and being screened into the lottery (for the Classes of 2004 and 2005). Students may perceive CTE schools as special and work to maintain their grades and behavior so as not to be returned to their neighborhood high schools for inadequate performance. It would be a mistake to conclude - purely from this empirical analysis - that an approach to high school curriculum that emphasizes career and technical education is superior to other curricular focuses. On the other hand, it would be equally mistaken to dismiss career and technical education schools as necessarily, in all educational contexts, reducing the probability that students will graduate from high school and earn credits in courses needed for admission to and success in postsecondary education. 9

10 SECTION I: INTRODUCTION This report describes the results of an analysis of postsecondary education outcomes for Philadelphia public school students who applied to attend at least one of the city s career and technical (CTE) high schools. Specifically, we examine patterns of enrollment and persistence in, and graduation from, two-year or four-year degree-granting institutions. As an exploratory analysis, we report on students use of Pell grants to support education at private postsecondary trade and technical schools that do not offer Associates or Bachelors degrees. This report focuses on members of Philadelphia s high school cohorts whose on-time (four-year) high school graduation dates were June 2003, June 2004, or June For each of these cohorts, the city s public CTE high schools were substantially oversubscribed, and applicants to these schools were selected for admission by random lottery. As a result, a strong argument can be made that the treatment and comparison groups differ at the mean only on whether they were selected by chance process to attend a CTE school. Lottery selection means that the comparability of treatment and control groups extends to both observable and unobservable characteristics, which should be distributed randomly across both treatment and control groups. A previous report compared high school achievement and attainment outcomes for CTE students and other students in these cohorts (Neild, Boccanfuso, & Byrnes, 2013). Using student record data from the School District of Philadelphia, accepted and non-accepted applicants to CTE schools were compared on on-time graduation rates, five- and six-year graduation rates, achievement growth in mathematics and literacy, completion of two or more sequenced CTE courses, and completion of college preparatory coursework in mathematics, science, and foreign language. Two types of comparisons were made: 1) accepted applicants versus non-accepted (the Intent to Treat comparison), and 2) students who actually attended a CTE school versus those who did not (the Dosage comparison). In sum, our previous report on high school education outcomes found that there were substantial positive impacts of CTE on high school graduation; mixed effects on college preparatory course-taking, with some advantages for CTE students and some advantages for comparison group students; and no impact on achievement growth in mathematics and literacy. The key impact of CTE schools appeared to be on the acquisition of high school diplomas. This report extends the previous set of analyses by examining postsecondary educational outcomes for CTE students. Specifically, we track the percentage of students who enroll in a two-year or four-year degree-granting institution; their persistence in postsecondary education once enrolled; and acquisition of a two-year or four-year degree. For this analysis, we use data from the National Student Clearinghouse, obtained from the School District of Philadelphia and merged with student record data from the district. As an exploratory analysis, we use data on receipt of Pell Grants to examine the extent to which CTE students chose postsecondary trade or technical training over two-year or four-year degree-granting institutions.

11 The Philadelphia Context The district context for this study was described in greater detail in a previous report (Neild, Boccanfuso, & Byrnes, 2013). Here we provide a summary of this context to orient the reader to the general, relevant features of the city and school district that are the focus of this study. The School District of Philadelphia serves a population of mostly minority students from low-income families. During (one of the focal years for this study), 86 percent of the students in Philadelphia s schools were members of minority groups, and 69 percent were eligible for free or reduced-price lunch (Garofano & Sable, 2008). Approximately 65 percent of the students were African American, 15 percent were Latino, 5 percent were Asian, and 15 percent were White (Balfanz, Herzog, & MacIver, 2007). High School Choice At the high school level, school choice is a notable feature of the School District of Philadelphia. Each fall, the high school choice process begins for Philadelphia eighth-graders who plan to attend public high schools or who are considering the public schools as an option. The high percentage of eighth-graders who apply to one or more high schools indicates that school choice has become a normal part of the transition to high school in Philadelphia. Among students who were eighth-graders in the Philadelphia public schools during (potential members of the Class of 2003), 70 percent applied to at least one high school outside of their attendance zone. For eighth-graders in (the Class of 2004) and (the Class of 2005), the percentages were 69 percent and 62 percent, respectively. Research on subsequent cohorts of Philadelphia s incoming ninth-grade students indicated that this downward trend was an aberration, as rates of students applying to schools outside of their attendance zones have increased, reaching 65 percent for the class of 2007, and 73 percent for the class of 2010 (Gold et al, 2009). A notable feature of the high school choice program is that students were permitted to apply to multiple schools or programs. The number of schools to which students were permitted to apply varied from cohort to cohort. For the Classes of 2004 and 2005, we observe in our data that some students applied to as many as 10 high schools. For the Class of 2003, some students applied to as many as 16 choices. This large number of applications for the Class of 2003 was due in part to a feature of the application process that year that permitted students to apply to multiple lottery-based programs within the same school. Students who chose to apply to multiple high schools were asked to rank their choices by preference. All else being equal, a student who indicated that a particular school was his first choice had a better chance of being admitted than a student who indicated that the school was a lower-ranked choice on his list of preferred schools. When the Classes of were applying to high school, there were three primary types of public high schools in Philadelphia: 11

12 Neighborhood high schools served students living in particular geographical areas. Each student had a default neighborhood high school based on residence. Students who did not gain admission to another school via the high school choice process were assigned to their default high school. Students from outside the catchment area of a particular neighborhood high school could apply to attend a program at that school, and if there were excess seats the school, the student could be admitted. About 75 percent of the students in the Classes of attended a neighborhood high school. Special admissions high schools served students from across the school district and were permitted to select students based on their seventh- and eighth-grade course marks, attendance, disciplinary records, and test scores, as well as an interview or audition. When the cohorts that are the focus of this report were applying to high schools, special admissions schools included competitive exam schools that were founded in the mid-19 th century (Central and Girls High School); schools that were established more recently and offered themes such as engineering, international study, or the arts; and schools without a specific theme that offered college-preparatory curricula. The minimum achievement levels and other criteria required for admission varied from school to school. About 13 percent of the students in the Classes of attended one of these special admissions schools. Career and Technical (CTE) high schools provided career-related training in addition to the traditional academic subjects. These schools had no residential catchment areas but served students from across the city. For the Classes of 2003 and 2004, students could apply to one or more of four CTE schools: Bok, Dobbins, Mastbaum, and Saul. The Class of 2005 could apply to one or more of these four schools, plus an additional school (Swenson) that had become an independent entity and accepted students from throughout the city. For the Class of 2003, all CTE applicants were entered into the CTE lottery regardless of their prior achievement, attendance, or disciplinary records. For the Classes of 2004 and 2005, the CTE schools were permitted to shape their entering freshman classes by first screening applicants for previous achievement and attendance, and then conducting the lottery. About 12 percent of the students in the Classes of attended one of these CTE schools. Among eighth-graders during the school year (and who, therefore, were potential members of the Class of 2003), 43 percent (6,647 students) applied to at least one CTE high school; among those who applied to any school (including special admit schools and neighborhood high schools), 61 percent applied to a CTE school. The percentages were similar for the Classes of 2004 and 2005: 42 percent (8,825 students) and 43 percent (5,371 students) of all eighth-graders, respectively, applied to at least one CTE school. 12

13 The High Schools Admissions Decisions After student high school application forms were submitted, individual schools and the district began the process of determining which students would receive offers of admission. Students were admitted to high schools through several processes. The way in which an admissions decision was reached depended on the categories of schools to which students applied. Special admissions schools made their own admissions decisions based on student achievement and behavior; lottery-based programs such as the CTE schools that are the focus of this study - made admissions decisions randomly from their pool of applicants. Special admissions schools. Although admissions materials state that these schools screened applicants on the basis of previous academic achievement, attendance, and school behavior, and sometimes an interview and/or audition, almost nothing is known publicly about how school or district personnel weighed this information to come to an admissions decision. What we do know is that students who applied to multiple special admissions schools could receive more than one offer of admission. For example, if an academically top-notch student applied to four special admissions schools, she could have received four offers of admission. Lottery admissions schools. For the Class of 2003, all students who applied to a lotterybased school were entered into the lottery, regardless of prior academic achievement, attendance, or behavior; there was no screening to make sure that applicants in the lottery pool met any particular criteria. The lottery was conducted using a computer algorithm that took into account student racial/ethnic background in order to promote racial balance (see below). A lottery for each school was first conducted for students who ranked that school as their first choice. Students who were admitted to their first-choice school or program were taken out of the lottery for any subsequent choices they listed; students could receive only one offer of admission to a lottery-based school or program. After this first round of the lottery was conducted, any student who did not receive admission at their first-choice school and who had indicated a second-choice school was entered into a second round of the lottery. If a student was not a winner in the second round, then the lottery tried to place students in their third-choice school. This process was repeated for as many choices as students had made, up to the maximum number allowed (in years when a maximum was stipulated). For the Classes of 2004 and 2005, the admissions process for at least some lottery schools had two stages. The CTE schools that are the focus of this paper used this two-stage process. The first stage was the crafting of the lottery pool. Applicants were screened by the individual schools for requisite academic, attendance, and behavioral characteristics and, sometimes, based on their interest in the career fields offered and/or performance in an interview. In the second stage, the lottery was conducted for students who had been screened in to the lottery. The lottery for each school was conducted first for students who had indicated that the school was their first choice, then for students who had indicated that the school was their second choice, and so on. The number of acceptances that students received depended in part on whether they applied only to lottery admissions schools. These students could be accepted only to one program; in the end, their choice about which school to attend was between their neighborhood 13

14 high school and the one other school to which they had been accepted. Students who applied to multiple special admissions schools, or to at least one special admissions school and at least one lottery-based school, however, had the possibility of being accepted to more than one school. In the previous report on CTE educational outcomes, we presented evidence to show that the CTE lotteries for each school and each class appear to have been random lotteries with some consideration given to racial balance. Variables for student race/ethnicity were the only ones on which accepted and non-accepted students consistently differed statistically. As a result, to improve the specificity of our models, we control for student race/ethnicity. Students Choices Students who received an acceptance to one high school could decide to attend that school or to remain at their neighborhood high school. Students with two or more acceptances needed to decide which of their three or more choices (including their neighborhood high school) they most preferred. In other words, being accepted to a school was not the same thing as being assigned to that school. As a result, there were some students who were accepted to a CTE school who chose not to attend that school. It is for this reason that we conducted both Intent-to- Treat analyses (which compare those who were accepted to a CTE school and those who were not) and Dosage analyses (which compare those who attended a CTE school and those who did not). Data This study relies entirely on 1) student record data from the School District of Philadelphia, 2) data on postsecondary enrollments and graduation from the National Student Clearinghouse (NSC), and 3) data on receipt of Pell grants. The school district and NSC data sets were merged by the NSC, using student names, birthdates, and (in some cases) social security numbers provided by the School District of Philadelphia. Pell grant data were merged with student record data using student names and birthdates. Student Record Data Student record data sets from the School District of Philadelphia provide individual information about students: their courses, course grades, progress toward high school graduation, attendance, test scores, schools attended, and high school choice participation and outcomes. These data sets cover the school year through the school year (the on-time graduation date of the Class of 2005). The files contain a unique identifier for each student so that their data can be combined into a longitudinal data set. Comparisons of the data observed in the administrative data sets to publicly available data sources for overlapping measures provided confidence that the data were accurately recorded and reported. The types of student record data sets and the associated variables for each are as follows: 14

15 Courses taken, course grades, and credits earned. For each school year, the course-taking file provides a list of courses in which each student was enrolled; the final grade (A-F) for each course; the number of credits that the student earned for the course; and the academic area in which the student earned that credit. Academic areas include core subjects required for graduation (mathematics, English, social studies, and science) and elective credits. Enrollment, graduation, and withdrawal from school. For each school year, these files contain two key variables that indicate whether the student s last known status for that school year was enrolled, withdrawn, or unclear. Students who were no longer listed on the district s enrollment rolls for any reason were listed as withdrawn. A second variable provides detail on the reason for a student s withdrawal from the school district. For example, a student could have been removed from the school rolls because he or she graduated, dropped out, died, or transferred to another school district, among other reasons. Attendance. For each school year, the number of days present at school and the number of days enrolled in school are available. These two variables permit a calculation of the attendance rate. High school choice variables. This file identifies each high school to which the student applied; whether each school was the student s first choice, second choice, and so on; the outcome of that student s application (accepted or not accepted to each school); and if the student was not accepted, the reason why (for example, GPA or attendance was too low to meet the school s standards for admission). Miscellaneous student data. These files include demographic data, including race/ethnicity, gender, and birth date; coding for exceptionalities, including receiving special education and/or English-Language-Learner services; and the last school attended for that school year. School data. These data include percentage of students who are low income at the school and whether the school is a CTE school, neighborhood high school, or special admissions school. National Student Clearinghouse Data The National Student Clearinghouse (NSC) is a non-profit organization that collects and organizes student-level postsecondary enrollment and degree completion information. It reports that 3,300 institutions of higher learning provide data on student enrollment and graduation to the NSC, and that these institutions enroll 92 percent of all higher education students in the United States. School districts can use the NSC data to track the progress of their graduates through postsecondary education, employers can use the data to verify degrees, and colleges and universities can use the data to examine patterns of transfer into and out of their institution. 15

16 All institutions offering two-year and four-year degrees, as well as postsecondary trade or training schools (also called private licensed schools) offering certifications, are eligible to report their data to the NSC. Postsecondary trade schools are authorized by their states to offer certifications in areas such as bartending, truck driving, cosmetology, or medical assistance. Further, for an additional fee, the NSC will provide data on whether the student has earned an industry certification, primarily in areas such as computer software. However, our review of the NSC files for Philadelphia students indicated that the files contained information only on students at schools offering two-year or four-year degrees. We did not request additional data on industry certifications. Therefore, the NSC data should be understood as providing information only on enrollment in, and graduation from, two-year and four-year institutions. The NSC data on postsecondary enrollment and graduation that we used for this analysis were obtained by the School District of Philadelphia, which pays for the option of receiving these postsecondary data for its graduates. The data merge is conducted by the NSC, using names, birthdates, and, in some cases, social security numbers of district graduates. The NSC data files extended from the fall 2003 semester through the spring 2010 semester. NSC data on enrollment and graduation are provided by semester, including summer. If a student does not appear in the database for a given semester, the inference is that he/she was not enrolled at one of the participating institutions. Students who are enrolled at two or more participating institutions in a single semester will be represented in the data set multiple times for that semester. It is important to note that not all students in the NSC data set are seeking a degree. Some may be taking a course here or there to obtain a certification or to try out college. In the NSC data set, however, we have no way to distinguish those who are seeking a degree from those who intend only to take a course or two. Further, the NSC data do not provide information on students course enrollments, grades, or placement into developmental or remedial courses. Variables available for each semester from NSC data are: The characteristics of the institution at which the student is enrolled. These include the name of the institution; the city and state in which it is located; and whether it is a twoyear or four-year degree-offering institution. Full-time, half-time, or part-time status. For each institution, whether the student is enrolled full-time or has some other type of enrollment is indicated. Graduation and major. If a student has graduated with a two-year or four-year degree, the institution from which he/she earned a degree is indicated, as well as the semester during which the degree was awarded. In most cases, a major is indicated. Data on subdegree certifications are not provided in the NSC data. 16

17 Pell Grant Data Because the NSC data did not include information on enrollment in private license schools, we added data on receipt of a Pell Grant, obtained from the U.S. Department of Education. These data are available for calendar years 2004 through Pell Grants for postsecondary education are federal grants available to individuals of all ages who demonstrate high financial need and would not otherwise be able to enroll in higher education. Most importantly for this analysis, Pell Grants can be used not only at two-year and four-year colleges but also at accredited private license schools as long as the individual is working toward a professional licensure, such as a beautician/barber license (Bennett, n.d.). Thus, the Pell Grant data set is one of the best options for learning more about the extent to which CTE students pursue additional education at private license schools rather than at institutions that offer a twoyear or four-year degree. There are notable limitations to the conclusions that can be drawn from the Pell Grant data set. First, as all students attending private license schools do not qualify for Pell Grants, any analysis that uses Pell Grant receipt to estimate the percentage of students attending private license schools almost certainly produces an undercount. Second, the Pell Grant data set does not include information on whether students received the professional license toward which they had been working. Finally, for students attending schools that offer varied types of licenses, we cannot identify the particular license toward which they were working. It is important to note that this is an exploratory analysis and allows us only to produce aggregate estimates of the percentage of CTE applicants who received a Pell Grant, the types of institutions at which their Pell Grant was spent, and the semester(s) during which each student used a Pell Grant at these institution(s). Variables available for each semester from the Pell Grant data set are: The name of the institution at which the Pell Grant was spent; and The city and state in which the institution was located. From these variables, we created a variable indicating whether the student had ever used a Pell Grant at a private license school. To do this, we screened out cases where the student had clearly attended a two-year or four-year school. For the remaining schools, we coded them as private license schools if their names clearly indicated that their key purpose was to provide training for licensure in a particular occupation not requiring a college degree (for example, cosmetology/barbering schools, truck driving schools, LPN nursing schools). For any schools where the name did not make clear what credentials were offered, we searched the Internet for information that would allow us to categorize them. Any school that offered a two-year degree in addition to professional licenses was not coded as a private license school. We did not use the Pell data to create the variable for whether students enrolled in a twoyear or four-year institution. That determination was made from the NSC data. 17

18 Methods Types of analysis This analysis of postsecondary outcomes includes three broad types of estimates: 1) an Intent-to-Treat effect of CTE schools; 2) a Local Average Treatment Effect (or LATE), which adjusts effect estimates for the percentage of students assigned to a condition who actually experienced the condition; and 3) a Dosage analysis, which adjusts for the number of years students attended a CTE school. While related, these analyses ask slightly different questions, which can be summed up as asking about the effect of assignment to the intervention versus the effect of experiencing the intervention. The Intent-to-Treat (ITT) analysis asks, What is the effect of program assignment on the outcome? In this case, the ITT question is, What is the effect of being accepted to a CTE school on postsecondary outcomes? The Local Average Treatment Effect (LATE) analysis asks, What is the average effect of the treatment per person induced to receive it? The Dosage analysis asks, What is the effect of experiencing more of the treatment - in this case, attending a CTE school for a longer period of time? (For a discussion of various effect estimates, see Bloom, 2005.) Establishing the treatment and control groups for ITT, LATE, and Dosage analyses Students who are included in this analysis had three things in common. First, they attended Philadelphia public schools (not including charter schools) for eighth grade and enrolled in a Philadelphia public high school for ninth grade during the next school year. Second, they entered high school as members of the Class of 2003, 2004, or Third, when they were in eighth grade, they applied to attend one or more CTE high schools. Once the universe of students who applied to CTE schools had been established based on their high school application records, we created treatment and control groups. For the ITT analysis, treatment and control groups are defined in two ways and, as we show below in the Estimation Methods section, we use two different methods to estimate the ITT impacts of CTE schools. The first way that we define ITT treatment and control groups is by school; that is, for each CTE school, the applicants are divided into those who were accepted and those who were not. Students who applied to more than one CTE school and were accepted to one but not to another could be coded as part of the treatment group for one CTE school and part of the control group for another school. A reason for creating treatment and control groups by school is that there were observable differences between schools in the 18

19 characteristics of their applicants, suggesting that impacts should be estimated by school and then averaged for an overall effect. The second way that ITT treatment and control groups are defined is a simple binary variable, with 1 equal to having been accepted to a CTE school and 0 for not having been accepted. For the Dosage analysis, the treatment group consisted of students who had attended a CTE high school for any length of time, regardless of whether there was a record of the student actually being accepted to a CTE high school. The control group is comprised of students who did not attend a CTE school. Some students in the control group were not accepted to a CTE school, while some were accepted but did not attend. Estimation methods For Intent-to-Treat estimates, we used two modeling strategies. The first strategy is a mixed model that allows students to be represented in the data set multiple times. The number of times that students appear in the data set is equal to the number of CTE schools to which he or she applied. We used a two-level model (Raudenbush & Bryk, 2002), with students nested within lotteries. Because students who were entered into the lottery at more than one CTE school are represented in the data set more than once, we use robust standard errors to correct for the non-independence of some observations (White, 1982). Separate models were estimated for the three different cohorts. In essence, this estimation strategy allows us to find the CTE effect for each lottery and create an average across all CTE lotteries for a given cohort. While this modeling strategy deals with the bias inherent in comparing outcomes for students who participated in different lotteries (where participation is non-random), it produces conservative estimates of the overall impact of CTE schools. This is because a student who applied to multiple CTE schools and attended one of them will be included as a treatment student once for the lottery to which he or she was accepted and as a control one or more times for other lotteries to which the student applied but was not accepted. The potential of this modeling strategy to underestimate any positive effects of CTE is particularly acute for the Class of 2005, for which between approximately one-quarter and one-third of the rejected applicants enrolled at other CTE schools. Given the potential of this modeling strategy to underestimate the overall effects of CTE schools, we produced a set of fixed-effects estimates in which students are represented only once in the data set. The dependent variable is a dummy variable for whether the student was accepted to any CTE school. Instead of nesting students within lotteries, we included a set of four dummy variables (five variables for the Class of 2005, which had five CTE school options) indicating whether the student was included in a lottery for a specific school. This modeling strategy has the disadvantage of not being able to control for the ranking that a student gave a specific school on his/her application (which we know had an impact on a student s probability of being accepted, and potentially indicated more or less serious interest in CTE education), nor does it 19

20 compare students to others who were not accepted to a particular school. It has the advantage, however, of not including in the treatment groups any students who attended CTE schools. To achieve racial balance in the schools, the lottery took into account student race or ethnicity. Further, students who identified a particular school as a top choice had a higher probability of being admitted to the school than students who gave it a low ranking. Therefore, we control for race/ethnicity in both types of models; we control for the ranking given to each school in the first model. The equation we use for the Intent-to-Treat mixed model is as follows. This equation is for continuous variables such as scores on standardized tests; for binary dependent variables, we use a multilevel logit model. Level One Y ij = β 0j + β 1j (Accepted to Lottery l in year y) ij + β 2j(African American) ij + β 3j (Asian) ij + β 4j(Latino) ij + β 5j (Other ethnicity) ij + β 6j (Ranking given to school) ij + r ij Level Two β 0j = β 1j = β 2j = β 3j = β 4j = β 5j = 00j + u 0k 01j 02j 03j 04j 05j The equation for the Intent-to-Treat fixed-effects estimates of predictors of continuous dependent variables is as follows. Binary dependent variables were modeled with a logit model. Y = β 0 + β 1 (Accepted) + β 2 (White) + β 3 (Asian) + β 4 (Latino) + β 5 (In School A Lottery) + β 6 (In School B Lottery) + β 7 (In School C Lottery) + β 8 (In School D Lottery)+ r For estimates of Dosage effects, we used a mixed-model approach, with each student potentially represented multiple times in the data set. This model introduces a control for the proportion of the first four years of high school that a student actually attended a CTE school, as well as controls for race/ethnicity, gender, the number of CTE schools applied to, receipt of special education in eighth grade, receipt of English Language Learner services in eighth grade, 20

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