Texas Students’ College Expectations:
Does High School Racial Composition Matter?
Michelle Bellessa Frost
Princeton University
Office of Population Research
Preliminary Draft, not for citation
Revised August 17, 2004
This research was supported by the Hewlett Foundation and Ford Foundation. Institutional
support was provided by the Office of Population Research. Special thanks go to Marta
Tienda, Mario Small, Germán Rodriguez, and Meredith Kleykamp for helpful comments at
various stages in this research. A version of this paper was presented at the Notestein
Seminar Series at Princeton University in May 2004. Please direct comments to Michelle
Bellessa Frost, Office of Population Research, Princeton University, Princeton, NJ, 08544,
mbfrost@princeton.edu.
1
Introduction
Although 50 years have passed since the landmark Brown vs. Board of Education
case, public schools remain in large part segregated by race and ethnicity. Furthermore, the
recent removal of court mandates to desegregate schools and challenges to other race based
assignment policies have led to an increase in segregation. Across the nation, 66 percent of
blacks and 73 percent of Hispanics attend schools in which at least half the students are not
white (Orfield and Yun 1999). In Texas, a state with a large and rapidly growing minority
school age population, school segregation is widespread. For example, in 2002-03 twothirds of Hispanic and half of black students attended schools with at least 70 percent other
minority students (Texas Education Agency 2003)1. Yet, despite the prevalence of
segregation, few recent studies have examined how school racial composition influences
students’ educational outcomes.
Among these important educational outcomes, the goal to attend and complete
college is an essential first step toward an eventual university degree. Early work in the
status attainment tradition established the importance of educational expectations on
academic attainment and other school outcomes, both within and across racial groups
(Sewell, Haller et al. 1969; Sewell, Haller et al. 1970; Campbell 1983; Hanson 1994; Hao
and Bonstead-Bruns 1998; Buchmann and Dalton 2002). Expanding on studies that
investigated only the effects of individual level attributes on expectation formation, other
sociologists turned to contextual models to search for school influences on individual
students’ educational expectations, including an examination of how desegregation efforts
were impacting black students’ outcomes (Meyer 1970; Alexander and Eckland 1975; St.
John 1975; Hauser, Sewell et al. 1976; Alwin and Otto 1977). However, by the late
2
1970’s, this research was largely abandoned because of the lack of results showing any real
effects of schools, as well as a changing political climate. Combining the importance of
understanding the impacts of continued school segregation in a state with widely
heterogeneous schools with recent advances in multilevel statistical models and computing
ability with, I examine whether and how school racial composition influences Texas high
school students’ educational expectations.
Specifically, three possible scenarios linking school racial composition to
educational expectations are considered. First, school racial composition could act merely
as a proxy for individual characteristics that directly influence expectations to complete
college, such as family socioeconomic status. This suggests that no school effects on
expectations exist, and is the default position of most previous research. Or, it is possible
that school effects are indeed present, but that the distribution of students by race/ethnicity
within school reflects other school characteristics, such as academic climate, that are
related to the level of educational expectations within a school. Finally, the prospect exists
that something fundamental about racial composition in school directly influences the
educational goals held by students there. In order to analyze the relative explanatory power
of these three alternatives, I employ multilevel models to answer the following research
questions: Does the level of educational expectations vary between schools? What is the
relationship between school racial composition and educational expectations? Do student
characteristics and other school characteristics explain why school racial composition is
related to educational expectations? Which factors are most important in understanding
between school differences in students’ educational goals?
1
Data from the Texas Education Agency analyzed by author.
3
So as to investigate these questions, the paper proceeds as follows. Grounded in a
comprehensive literature review, I detail three hypotheses that explain how and why school
racial composition can influence students’ expectations to graduate from college.
Following a discussion of a unique survey suited to test these propositions and why Texas
is an apt location for the study of school effects, I outline an analysis plan. Results from
hierarchical logistic regression models suggest the counterintuitive finding that when
comparing similar schools, greater concentrations of minority students are associated with
an increased likelihood of students in those schools expecting to attain a 4-year college
degree. The final section discusses the implications of these findings.
Influences of School Racial/Ethnic Composition on Educational Expectations
A central hypothesis of this research is that school characteristics, and specifically a
school’s racial/ethnic composition, exert an independent impact on students’ educational
expectations. A simple way to conceptualize school effects is to envision a single student
attending a given school, and then alternatively attending a different school; here, a school
with a different racial composition. My analysis addresses how this hypothetical student’s
educational expectations would change by attending a substitute school in the absence of
other changes in the student’s personal and family circumstances. In this section, I
examine evidence to formulate three separate but interrelated hypotheses regarding how the
racial and ethnic makeup of a school could impact the school level of educational
expectation.
Relationship to Student Characteristics
4
First, the school racial composition could act, in part, as a proxy for the individual
characteristics of the enrolled students. Thus, differences in average educational
expectations across schools might reflect compositional differences in student bodies that
are associated with racial composition. For example, a high minority school often includes
larger shares of students from poor families and with prior educational deficiencies. On the
whole, these students have lower levels of expectation to attend college, but this is partly a
function of individual students’ characteristics that are associated with the school racial
composition and not because of any school characteristic in and of itself. In the strongest
version of this hypothesis, educational expectations for two statistically identical students
who attend vastly different schools would be similar. In other words, this hypothesis
suggests that apparent school effects are attributable in part to correlated individual student
characteristics. In order to locate and isolate true school effects, then, individual level
correlates of educational expectations must first be accounted for. Additionally, most
research examining correlates of educational expectations has focused on individual level
explanations. The next section, thus, briefly reviews literature focusing on student factors
that influence educational goals.
Starting with the Wisconsin status attainment model, Sewell and others elaborated
on Blau and Duncan’s (1967) basic stratification model that introduced social
psychological processes, including educational expectations, to explain educational and
occupational attainment (Sewell and Shah 1968; Sewell, Haller et al. 1969; Sewell, Haller
et al. 1970). Initially, they focused on how the encouragement and expectations of people
important to students, including parents, teachers, and friends explained variation in
5
students’ educational expectations and aspirations (Sewell and Hauser 1992).2
Additionally, Sewell et al.(1969) theorized of the influence of both academic performance
and social origins on students’ educational expectations.
In extensions of Sewell’s original model of educational expectations (Sewell and
Shah 1968; Sewell, Haller et al. 1969; Sewell, Haller et al. 1970), others have focused more
exclusively on how socioeconomic factors—including the direct and opportunity costs of
attaining higher education—shape educational ambitions (Jencks, Crouse et al. 1983;
Morgan 1998). For example, Morgan’s (1998) rational choice framework concentrates
attention on how family resource differences to pay for education and expected benefits of
educational credentials shape educational expectations.
Researchers interested in the influences of race and ethnicity on educational
ambitions find that minority students, especially blacks, have higher educational aspirations
and expectations than whites of comparable socioeconomic status and early educational
experiences (Kao and Tienda 1998; Qian and Blair 1999; Hirschman, Lee et al. 2003).
Goldsmith (2004) links higher minority educational goals to other ambitions as a
representation of a generalized pattern of optimism among minority youth. Examinations
of immigrant expectations further confirm that first and second generation immigrants are
highly optimistic about their children’s futures, often expressing college ambitions for their
offspring (Kao and Tienda 1995; Cheng and Starks 2002)
Thus, at the student level, prior studies in the Wisconsin status attainment tradition
identify three types of covariates that explain differentials in educational expectations:
significant others’ influence, student socioeconomic background, and academic ability and
2
Here, significant others’ expectations can by conveyed indirectly through modeling, as in the case of
admired peers or educated adults, or through specific encouragement of college attendance, often given by
6
experiences. Furthermore, other lines of research suggest that minority and immigrant
status are associated with college expectations. These student characteristics are not
randomly distributed across schools—students are often clustered in schools according to
these factors. Therefore, the impact of racial composition on college expectations partly
derives from differences in the student body composition of schools. Specifically, I
hypothesize that once relevant student characteristics are accounted for, between school
differences in educational expectations will shrink. Furthermore, an initial negative
relationship between the proportion of minority students and the average level of
educational expectations in a school will lessen, weakening the link between the two. I
label this the null hypothesis, since it suggests no independent effects of school racial
composition or other school characteristics. Table 1 describes the substantive and analytic
components of this and other hypotheses.
Relationship to Other School Characteristics
Second, racial composition can act as a proxy for other school characteristics that
impact student educational expectations. I examine three possibilities, including school
socioeconomic status, school average achievement level, and school academic
environment. First, schools with high proportions of minorities are also schools that are
likely to have a high concentration of economically disadvantaged children. Thus, with a
high correlation between race and socioeconomic status, average educational expectations
of high minority schools might derive from the school socioeconomic composition.
Research findings in the 1960’s and early 1970’s, emanating from a flurry of work focusing
on the effects of school context on educational expectations, showed that high school
students from high SES schools had higher aspirations than those who attended low SES
influential adults, including parents and teachers (Sewell, Haller, et al, 1969; Haller, 1982).
7
schools, even after controlling for their individual SES (Michael 1961; Turner 1964; Meyer
1970). Researchers theorized that the aspirations and attainment of a low SES, working
class student might be raised by informal contact with higher SES peers in middle class
schools because of exposure to middle class values, aspirations, and knowledge (Thrupp
1997). Presumably, the cultural norms found in a school with few poor students valued
educational attainment and identified college attendance as desirable and even inevitable
(Jencks and Mayer 1990). The normative role of peers, both providing and reinforcing
standards, is central to this perspective. According to the Coleman report, transmission of
middle class values from socioeconomically privileged White students to poor minority
children was an important benefit of desegregation (Coleman 1966).
This suggests that independent of a student’s own family socioeconomic status,
there are accrued benefits from attendance in a non-poor school: thus, the socioeconomic
composition of peers is an important school characteristic to consider in examination of
students’ educational goals. Additionally, this implies that average educational
expectations in schools with large shares of minorities are depressed because high minority
schools are also schools of lower socioeconomic status. By comparing schools of the same
poverty level, the overall relationship between school minority composition and the
average level of educational expectations will become less negative. In other words,
equalizing schools by school poverty and school socioeconomic status should increase the
adjusted level of educational expectations in high minority school should increase. (See
Table 1.)
A second school characteristic of likely importance also emerged from early
research. High minority schools are also more likely than predominately white schools to
8
have lower levels of overall achievement. Perhaps, then, school racial composition is
partly an indicator of scholastic attainment. In addition to considering the socioeconomic
composition of a school, Davis (1966) examined the role of achievement context on student
expectations. He suggested that peers supply a means of reference for self-examination,
with a high ability student body providing a more competitive scholastic environment. In
a challenging scholastic environment, with academic rewards distributed primarily within
schools, students suffer by comparison to more able students. Thus, a student of a given
ability level in a highly scholastic student body has a lower academic self-perception than a
student of comparable ability in a less talented school. Furthermore, students in high
ability schools stand out less in comparison to their bright counterparts and receive less
attention and encouragement to attend college from teachers and counselors (Meyer 1970).
Davis called this the frog-pond effect.
Other research examined the impact of desegregation on black students’ aspirations.
In a review article, St John (1975) reports that most studies find black students’ movement
to desegregated White schools to be associated with a corresponding drop in their
educational ambitions. This is consistent with Davis’s frog-pond model: as black students
entered desegregated schools with more skilled and competitive student bodies, not only
did their academic self perception drop, but so too did their expectations to attend college,
mainly because “realistic possibilities” were reconceptualized (Falk 1978).
The frog-pond view implies a negative relationship between average levels of
school achievement and educational expectations, and suggests that predominately
minority schools have higher average expectations due to the lower average achievement
levels of their student bodies. Thus, the theorized effects of school SES and school
9
achievement on educational expectations are in opposite directions. Equalizing schools by
achievement composition should decrease the adjusted average expectation level in high
minority schools, if Davis’s frog pond theory is correct. (See Table 1.)
A third school characteristic related to both minority composition and educational
expectations is the academic climate, the scholastic atmosphere of a school and the general
amount of educational engagement and interest on the part of the students. Because of
fewer resources, large student-counselor ratios, less rigorous curriculums, and lowered
teacher expectations, school with large shares of minority students are likely to have less
academic environments (Rumberger and Willms 1992; Caldas and Bankston 1998;
Ferguson 1998; Corwin, Venegas et al. 2004). Additionally, the school socioeconomic and
achievement composition are interrelated with a school’s overall academic climate, making
it difficult to completely separate these factors analytically. However, direct measures of
school climate suggest that schools with greater academic and collegiate foci are also
schools with higher average educational goals and lower shares of minority students. Thus,
predominately minority schools might have lower levels of expectations due to the
correlation with schools’ less academic atmospheres. By equalizing school on academic
environment, increasing proportions of minority students should be associated with more
positive levels of educational expectations. (See Table 1.)
My second hypothesis with its three variants suggests that the effect of school racial
composition on educational expectations can be explained in part by the relationship
between school racial composition and other school characteristics, including school
socioeconomic status, school achievement, and academic environment. I list the explicit
substantive and analytic hypotheses for each school mechanism in Table 1.
10
Racial Composition’s Independent Association
As an alternative to hypotheses one and two, including its three variants, there is the
ever present possibility that something fundamental about racial composition exists to
influence the school level of educational expectations. Supporters of affirmative action in
higher education have based recent legal arguments on this notion: the compelling need for
racial and ethnic diversity derives from important and socially desirable educational
outcomes (Gurin, Dey et al. 2002). This view presumes that there is some optimal racial
and ethnic composition of student bodies that enhances educational outcomes for students
of all racial and ethnic groups. Likewise, it is possible that high school racial composition
could independently influence high school students’ educational expectations, with similar
effects for students of all racial groups.
However, there are also theories that suggest a differential impact of racial
composition on minority students. John Ogbu theorized the development of an
oppositional culture when members of involuntary minority groups, defined as groups
historically forced to incorporate within the majority society by colonization, enslavement,
or conquest, are concentrated in geographical areas, such as schools (Fordham and Ogbu
1986; Ogbu 1991). Because of their shared experience of exclusion and discrimination,
involuntary minorities develop a group identity, whose main characteristic is direct
opposition to the majority culture. Presumably, black or Hispanic students who desire to
excel academically and pursue higher education are betraying their group identities by
“acting White” and hence are marginalized from their groups. Ogbu’s premise implies that
there is a statistical interaction between students’ ethnicity and the racial composition of
their school. Specifically, when black and Hispanic students attend schools with critical
11
masses of their own groups, the development of an oppositional culture leads to a
devaluation of academic goals and lowers educational ambitions. In concrete terms, higher
proportions of minority students should be associated with lower average expectations, but
only for these minority students.
Other studies find that minority self esteem and academic self perception is lower in
racially balanced schools than in high minority schools (Drury 1980; Gray-Little and
Carels 1997). Thus, if self esteem shapes educational expectations, in part, then minority
students who attend schools where their own race is more highly represented will have
higher expectations to attend and graduate from college. This is reminiscent of Davis’
(1966) earlier frog-pond hypothesis. Based on this proposition, black school administrators
in districts with large black populations have created schools solely for black children, with
an Afro-centric curriculum, because they believe it will be of greater educational benefit
than a mixed race school. This view contradicts Ogbu’s claims about oppositional culture:
Ogbu implies that high minority composition produces poor educational outcomes for
minority students, while the self esteem hypothesis suggests that minority students might
have more ambitious educational goals when they are clustered together.
Finally, a recent paper offers another possible explanation for an independent effect
of racial composition. Goldsmith (2004) found that black and Hispanic students have
higher educational expectations when attending schools with more minority students and
minority teachers, while white beliefs are largely independent of the amount of school
segregation by race. He suggests that this is because black and Hispanic students have
more positive beliefs about their future prospects and more pro-school attitudes, and that
their concentration in school improves the normative climate. He also claims that minority
12
teachers are better able to raise minority students’ beliefs than are white teachers. He
concludes that when clustering of minority students within schools occurs, although
disadvantageous in some regards, optimism and pro school attitudes increase among these
minority students.
Although I won’t directly test these three theories in this paper, I shed some light
on their validity by an examination of the empirical evidence of an independent influence
of racial composition on expectations, as well a differential impact of racial composition on
students of differing races. (See Table 1.)
DATA
Data for this study are primarily taken from the Texas Higher Education
Opportunity Project (THEOP), an ongoing project designed to understand the
consequences of Texas’ replacement of a race sensitive college admission regime with a
percent plan on minority students’ college enrollment3. The sampling design of this study
makes the study of school effects possible.
The survey was based on a stratified random
sample of 108 Texas public schools with a student body consisting of at least 10 enrolled
seniors, and which was further stratified on the basis of metropolitan area status and school
racial/ethnic composition. Of the eligible schools selected, 93% participated in the study.
Thus, 13,803 seniors are clustered in 96 high schools, and 19,969 sophomores are clustered
in 97 high schools. The sample is representative of students enrolled in Texas public high
schools during the spring of 2002.
3
Under the 1996 5th Circuit Court Hopwood v. University of Texas Law School decision, race sensitive
affirmative action for college admissions was banned. In its place, the Texas legislature passed HB 558,
popularly known as the top 10% Law, which allows the top 10% of students from any Texas high school to
attend any public university in Texas.
13
During the spring of 2002, baseline data were collected within sampled schools
from high school sophomores and seniors using a paper and pencil survey. A random
sample of the original senior cohort is being followed for a planned total of six years as
these students continue from high school on to college and other post high school activities.
The first follow up of the senior cohort took place during spring and summer of 2003.
Additionally, the sophomore cohort were reinterviewed during their senior year, in the
spring of 2004. For the purposes of this study, I use baseline data only from the senior
cohort.
The survey asked respondents about their grades and class rank, course taking,
extra-curricular activities, and knowledge and perceptions of college admissions, including
the top 10% law. Additionally, seniors were asked about their future plans, college
applications, and their university preferences. Essential for the purposes of our study,
students were asked how much education they would like to attain, a series of questions
about their educational experiences, and how much encouragement they received from
teachers, counselors, and parents regarding college attendance, as well as standard
background questions, including immigration status and language ability.
To assess contextual determinants of educational expectations, I merged data from
the US Department of Education and the Texas Education Agency (TEA) with the
individual level data files using a school identifier. The Common Core of Data, a program
of the United States Department of Education, is an annual collection of school and district
level information, and I use this data to obtain information on school racial composition,
the key independent variable, as well as on school poverty, measuring the proportion of
students eligible for free and reduced price lunches. The TEA provides school-level
14
information about a variety of outcomes, including high schools’ achievement and test
scores, AP course availability and enrollment, and school size. Finally, by aggregating
survey data by school, I generated additional contextual variables, including school
parental education level and the proportion of students within a school knowing that the top
ten percent of students from each school are automatically granted admission to any public
Texas university. Although I only use the senior survey data for statistical analyses, I
aggregate both senior and sophomore data together by school in order to obtain greater
precision in contextual measures.
I imposed two constraints on my study sample. First, I omit all cases that lack valid
responses in my main dependent variable, educational expectations. This excludes 7.6% of
the sample cases4. Second, because individual variable measuring racial status, I include
only those students identifying themselves as White, black, Hispanic, and Asian. Other
ethnic groups had small sample sizes, and thus I omit all students who report that they are
Native American, “other”, or multi-racial. Only a small proportion of the sample is
dropped for this reason, 1.7%. Thus, the final study sample is made up of 12,526 senior
students clustered in 96 schools.
To address the other individual level missing data in my study sample, I used a
form of hotdeck imputation. In order from the most missing to the least missing, I
regressed each variable with missing values on all the other individual level variables used
in the analysis, and then sorted the data based on predicted values for the variable of
4
In the survey, the question from which I draw my dependent variable of educational expectations,
“Realistically, how far do you think you will go in school?” immediately follows the question, “How far
would you like to go in school?” measuring academic aspirations. After examining the missing patterns in
the two questions, it seems highly likely that those who were missing on the second question (expectations)
but not the first (aspirations) assumed that the questions were identical and believed answering the second
was replicating their previous answer. Thus, for the small portion of students who were missing on
15
interest. I then divided my sample up into bins of 50 respondents each to locate donors for
missing values. Within each bin, I randomly selected a non-missing value to impute a
value for missing cases. I repeated this process for each of the variables with missing data
and flagged all instances where data were imputed.
Texas as a research context
Texas, like other immigrant receiving states, has witnessed rapid change in its racial
and ethnic diversity, especially among the school age population. This makes Texas a
propitious location to study school effects. Between 1980 and 2000, as the total school
age population increased, the white school age population declined as a proportion of the
total from 56% to 43%, while the Hispanic share of the total rose from 28% to 40%
(Murdock, Hoque et al. 1997). This trend is expected to continue. If the school age
population was distributed equally throughout the state of Texas by race, this demography
would not give reason to investigate the effects of school racial composition on educational
outcomes. However, this is not the case: the state is racially segregated by region, within
cities, and by school district.
Figure 1 shows how the racial distribution of students within schools varies by race
across the state of Texas. The bar furthest on the left shows the overall school racial
composition experienced by the average student in Texas in 2002. As a trait of individual
students, these differences indicate that the average Texas student attends school with about
50% white students, one-third Hispanic, 12% black, and 2% Asian. Then, each additional
bar to the right represents the school racial composition for the typical black, white,
Hispanic, and Asian student. Because of housing patterns, residential segregation, and
expectations, but not aspirations, I replaced their response for aspirations on the expectations question. This
included .72% of the sample.
16
geographic clustering, students of differing races attend school with very difference racial
compositions. Thus, Figure 1 shows that the average Hispanic student attends a school that
is more than 60% Hispanic, and 29% White, 8% black, and 2% Asian. Yet, the average
white students attends schools with two-thirds white students and only 20% Hispanics. All
in all, a clear pattern of racial clustering within schools emerges. Given this racial
separation of students in Texas, it is important to understand how school racial composition
impacts educational outcomes, and specifically, educational expectations.
Measures and Descriptive Results
Educational expectations was obtained from a closed-choice question that asked
high school students how much education they realistically expect to attain. Choices range
from high school graduation to Ph.D., M.D., or other professional degree. I convert these
responses into a dichotomous variable measuring whether survey respondents expect to
attain a 4-year college degree. Table 2 shows that on average, 67% of students expect to
attain a 4-year college degree. Overall expectations are high, given current statistics
suggesting that only 32% of recent high school graduates actually attained a four year
college degree5. However, because I focus on senior students, high school dropouts are
excluded from the sample, likely inflating somewhat the proportion of the senior cohort
that expect to complete college. At the same time, other studies have reported similar
levels of educational expectations among high school youth (Kao and Tienda 1998; Qian
and Blair 1999; Hirschman, Lee et al. 2003). Table 2 also shows differences in average
expectation by the racial composition of schools. Here, low and high minority schools are
defined to be schools in the first and last quartile, respectively, of the school proportion of
17
total non-Asian minority students. Thus, 60% of students in high minority schools,
compared to almost 70% of students in low minority schools, expect to attain a college
degree.
The key independent variables in my analysis are school racial/ethnic composition,
measured as the proportion of black and Hispanic students within each school6. The
average school in the sample contains slightly more than 50% white students, one-third
Hispanic students, and 12% black students, with the remaining 2% student population
consisting primarily of Asian students. In the schools with the lowest shares of minority
students, almost 90% of students, on average, are white, compared to only 8% in schools
with high proportions of minorities.
I measure two aspects of school composition by generating indices through factor
analysis to operationalize school socioeconomic status and school academic climate. My
third measure of school composition, school achievement, is based on only one variable.
All variables measuring school characteristics are described below. Table 3 shows factor
loadings and Cronbach’s alphas for variables included in the indices.
One measure of the school’s socioeconomic status is the school average of attained
parental education, which captures both parental income differences and values about
education. Presumably, a greater proportion of college educated parents within a school
will translate to strong school support for higher education. A critical mass of college
educated parents can impact the quality of instruction because they are more likely to be a
collective agent for high standards and an academic curriculum in a school. Because I am
5
Author’s tabulations from March 2002 CPS.
Although the composition of Asian students within schools suggests a unique and interesting impact on the
level of expectations to complete a 4-year college degree, the limited variance in this variable produced
unstable estimates. Thus, I focus here on only disadvantaged minority groups.
6
18
interested in student’s college expectations, I measure parental education at the school level
as the proportion of parents who have obtained at least a four year college degree. The
school average for the sample is one-third. However, this varies dramatically between
high- and low- minority schools. In low minority schools, 44% of parents have attained at
least a 4-year college degree, while the comparable proportion in high minority schools is
half as many parents, only 21%.
As an additional measures of school socioeconomic status, I use the proportion of
students qualifying for free and reduced price lunches. Only 23% of students in low
minority schools, compared with 61% in high minority schools, qualify, while the sample
average is 37%. Using factor analysis, I combine these two measures to generate an overall
measure of school socioeconomic status, with positive scores representing schools with
wealthier students. Comparison of high and low minority school shows that schools with
many minority students are, as expected, poorer.
I measure school achievement by using data from the Texas Education Agency
regarding the proportion of the schools’ 10th graders who met state standards in all required
state testing areas on the Texas Assessment of Knowledge and Skills (TAKS)7. Because of
state requirements, seniors are not tested, and data is only available for 10th graders.
Although my sample consists of 12th graders, this measure reflects the achievement
composition of the school they attended. Because lower ability students are more likely to
withdraw from school between 10th and 12th grade, measurement of academic achievement
in the 10th grade provides a better index of school achievement than a comparable measure
of senior students. On average, about 50% of sampled students passed Texas state tests in
all required testing areas. As expected, low minority schools have higher levels of
19
achievement than high minority schools, with 58% compared with 37%, respectively, of
students meeting state standards in all tested areas.
I use three measures of a school’s academic environment: feeder high school
status, AP courses taken per senior, and the proportion of students reporting knowledge of
the top 10% law. Feeder high schools are affluent schools with strong histories of sending
students to the two Texas flagship universities: University of Texas—Austin and Texas
A&M. Thus, for each university, the top 20 high schools, based on the numbers of students
admitted to UT-Austin and A&M, are designated as feeder schools. In total, only 4 schools
in our sample are feeder schools, but three of these have low minority shares, while there
are no feeder schools among the highest minority schools in our sample. By school, the
average number of AP courses taken per senior taken is slightly lower in high minority
schools: .145 vs. .211 in low minority school. In additional, only 30% of students within
schools, on average, report knowing about the top 10% law, a key feature of Texas higher
education, and this varies little between low and high minority schools. Using factor
analysis, I combine these three variables into one overall measure of school academic
climate, and as expected, high minority schools have less scholastic environments, on
average.
In order to isolate the impacts of school level characteristics on educational
expectations, I include several categories of individual covariates in the multilevel analysis
that are well established correlates of educational expectations, including students’
socioeconomic background, educational background and experience, significant others’
influence, and language and immigration8. All student characteristics are taken from the
7
8
Includes English language arts, math, science, and social studies.
Hispanic status, language, and immigration are not highly correlated.
20
THEOP 2000 wave 1 survey. Table 1 shows that approximately half of Texas high school
students are White, and one-third are Hispanic, which is consistent with state reports. The
remainder of the student population is divided between blacks, around 11%, and Asians,
4%. Thus, the school age population in Texas is about equally split between white and
minority students.
Table 1 also shows how the other independent variables vary according to the
school racial composition. Higher shares of parents of students who attend low minority
schools completed college. For the most part, students from higher minority schools are
disadvantaged with respect to their educational experiences and background, but there are a
couple of notable exceptions. Students in high minority schools are more likely to be
enrolled in a college preparatory curriculum, according to their self reports9. Additionally,
these students are more likely to report positive attitudes towards school and express
educational goals. As anticipated, higher proportions of students in high minority schools
are immigrants and speak languages other than English with friends, which suggests some
deficiency in English language ability.
Estimating School Effects on Educational Expectations
I use a multilevel modeling strategy to estimate how school racial composition and
other school characteristics impact educational expectations. In multilevel parlance, level-1
refers to the micro-level unit of analysis, here the individual student, and level-2 refers to
the contexts where level-1 units are clustered, in this instance the school (Raudenbush and
Bryk 2002). Multilevel regression has increasingly been used to estimate class, school, and
other context effects within multiple level data structures, especially when individuals
21
observations are clustered within these higher level units. Because students clustered
within schools are not statistically independent observations, traditional linear and binary
regression models produce downwardly biased standard errors, which can lead to incorrect
inferences about the statistical and substantive importance of school context variables (Guo
and Zhao 2000). However, multilevel models explicitly adjust for the nonindependence of
sample members who share a level-2 context, such as a school (Raudenbush and Bryk
2002).
Two general types of multilevel models are used to estimate school effects on a
specific student level outcome, namely random slope and random intercept models. With
random slope models, the effects of individual student attributes are allowed to vary across
schools. Thus, these models explicitly test for differences in slopes across schools.
Random-intercept models examine questions about differences in the level of a student
outcome across schools. When the outcome variable differs across schools, random
intercept models can be used to identify what school characteristics are responsible for
different outcomes. Because my research focuses on the extent to which school racial
composition and other explanatory variables explain variance in educational expectations
across schools, I fix all slopes and estimate random intercept models to answer the
following questions: Does the level of educational expectations vary across schools? Do
student and school characteristics explain the relationship between school racial
composition and educational expectations? Do student characteristics, school racial
composition, and other school level characteristics account for variation in educational
expectations between schools? Specifically, I use hierarchical logistic random intercept
9
However, I have no ability to control for the quality of the courses students have taken.
22
models estimated with sixth order approximation to the likelihood based on a Laplace
transform for Bernoulli models.
To begin, I first examine a simple histogram of the proportion of students by school
who expect to complete a four-year college degree. This is the school level distribution of
my dependent variable and provides a visual description of how much variation in
educational expectations exists between schools. Following up with this descriptive
analysis, I formally test whether there is significant between school variation in expectation
to complete a university education by estimating a simple unconditional model without any
predictors. This provides a baseline estimate of τ00, the between school variance, and its
standard error, information to analyze the underlying premise of this paper that educational
expectation do in fact vary between schools. The initial estimate of τ00 serves as a point of
comparison for subsequent models. Thus, I can examine how much τ00 is reduced—or how
much of the between school variance in educational expectations is explained—by the
inclusion of specific groups of variables.
Subsequently, I model the effect of school racial/ethnic composition on educational
expectations before any controls, providing an estimate of the observed relationship
between them. Because of the continuous measure of school racial composition,
coefficients represent the estimated change in log odds of expecting a 4-year college degree
that are associated with a unit change in the percent of Hispanic or black students in a
school.
Next, I introduce student characteristics into my models to examine how much of
the between school variance in educational expectations is due to school differences in
student composition, and how the association between school racial composition and
23
educational expectations changes with these additions, as discussed in the null hypothesis.
Table 1 provides analytic details for this and the other hypotheses I test. I also examine in
brief how students’ individual level characteristics impact educational expectations. In
these regressions, I centered the values of each student variable around the grand mean by
subtracting the state mean from each one. Although grand mean centering does not change
the estimated values of the regression slopes, it does shift the value of the intercept. With
this transformation, the intercept provides an estimate of a school’s mean college
expectation level with the statewide average on all included variables. Because grand
mean centering provides more stable estimates (Raudenbush and Bryk 2002), I use this
transformation throughout the analysis.
In the next step of analysis, I test hypothesis 1 by adding in the other school
characteristics, one group at a time, to a model that includes both student racial
composition and individual student characteristics. Because a school’s socioeconomic
status, achievement, and academic environment could be related to school racial
composition and students’ expectation to complete a university degree, I use these model to
examine how the estimates of the school racial composition variables change in the
presence of these additional school characteristics. (See Table 1.) Additionally, I can
observe if the other school variables exert an independent effect on educational
expectations. I include school size as a control variable.
In the final analytic portion designed to evaluate hypothesis 2, I look for evidence
of independent effects of the school minority composition on seniors’ college expectations
by analyzing a full model with all school level and student level characteristics. I
additionally include interaction effects between individual students’ race and their schools’
24
racial composition to ascertain whether the effect of racial composition on educational
expectations varies by student race. (See Table 1.)
Results
The central question of my analysis is how school racial composition impacts high
school students’ expectations to complete a 4-year college degree. Beginning my analysis,
I examine between school differences in educational expectations with a histogram shown
in Figure 2. This data is reported at the school level with a total sample size of 96, and so
the x-axis measures the school average of the proportion of students who expect to attain a
4-year college degree. For example, there are 23 schools in the sample where between
46% and 55% of the students in these schools expect to complete college, as shown by the
4th bar. For seniors, the school average proportion of students who expect to complete a 4year college degree ranges from 20% to 90%, with a clustering of schools falling between
50% and 80%. This figure demonstrates substantial heterogeneity of educational
expectations across Texas high schools. Substantively, a school where only 30% of
students expect to complete college is quite different from one where 80% of students
expect to complete college.
In order to formally test whether there is significant variation in the level of
educational expectations among schools, as suggested by Figure 2, I test an unconditional
model, which estimates only τ00, the between school variance component, and an intercept
describing the mean level of educational expectations, and these results are presented in
Model 1 of Table 3. Although hierarchical logistic models do not allow comparisons of the
between- and within-school variance components of expectations to complete college, the
25
initial estimate of the between school variance component, or τ00, provides a benchmark for
examining the sources of reduction in the between-school variance. Because the estimates
of τ00 and its standard error confirm that the level of expectation to complete a 4- year
college degree does vary significantly among schools10, I next turn to multivariate analysis
to examine the sources of this variation and analyze the role of school racial composition
on educational expectations.
Model 2 in Table 3 shows the effects of the percentage of black and Hispanic
students on plans to complete college before any other covariates are added. While the
distribution of black students is not related to educational expectations, the proportion of
Hispanic students in a school is negatively associated with the proportion of students in a
school who expect to complete a 4-year college degree. In substantive terms, a 10%
increase in the share of Hispanic students lowers the school odds of expecting a 4-year
college degree by 5% (1-exp(-.005*10)).
Model 3 in Table 3 shows results from a model testing the null hypothesis to
determine if racial composition acts as a proxy for the school composition of student
characteristics. By adjusting for individual socioeconomic status, educational experiences
and achievement, significant others’ influence, race, and immigration status, the negative
impact of the proportion of Hispanic students on educational expectations disappears,
suggesting that as schools increase the number of Hispanics enrolled, these students
average less of the resources and educational experiences associated with college
graduation expectations. Furthermore, the 26% reduction in τ00 from Model 2 and Model 3
suggests that the collection of student level characteristics related to educational
10
HLM does not provide significance tests of the Laplace transform approximations because of disagreement
over exactly how to estimate p-values, but using a rough rule of thumb, parameter estimates larger than 1.96
26
expectations at the school level is responsible for a substantial portion of the between
school variance in educational expectations. The weakened relationship between school
racial composition and educational goals lends some support to the null hypothesis
proposing that school racial composition acts as an indicator of individual student
characteristics that influence their educational expectations. (See Table 1.) However,
examination of τ00 and its standard error for Model 3 show that the between school
variance in educational expectations is still significant, not entirely accounted for by
differences in school composition.
For the most part, the student level results from Model 3 are consistent with
previous research and in the expected directions. Parental socioeconomic status,
educational background and ability, and significant others’ influences are strongly
associated with students’ educational expectations. Speaking a language other than English
with friends, suggesting limited English proficiency, is associated with lower expectations,
while individual immigration status is also associated with lower expectations, even when
adjusting for socioeconomic status and educational background. I find no racial/ethnic
differences in expectations to complete college once I also adjust for socioeconomic status
and educational background, in contrast to other research that finds that blacks, and
sometimes Hispanics, have significantly higher expectations than whites of comparable
socioeconomic status (Qian and Blair 1999; Hirschman, Lee et al. 2003; Goldsmith 2004).
To evaluate the second hypothesis that racial composition is a proxy for other
school characteristics that influence educational expectations, I examine models that add
the school characteristics one group at a time to Model 3 in Table 3, just reported. Table 4
reports the results from these models, showing only the coefficients of the school level
times their standard error are significant at the .05 level, and this estimate of τ00 clearly meets this criteria.
27
variables, even though all individual level variables are also included.11 The first model
includes the factored variable measuring the socioeconomic composition of the school and
shows that schools with more college educated parents and fewer students qualifying for
free/reduced price lunches are strongly associated with students’ college expectations.
Thus, when the socioeconomic composition of the school increases by one standard
deviation on the factored scale, the odds of expecting a college degree increase by 50%12.
Once school are equalized by their socioeconomic composition, the proportion of
both black and Hispanic students becomes positively and significantly related to college
expectations. Substantively, among schools of comparable socioeconomic status, a 10%
increase in Hispanic students raises the odds of expecting to complete a 4-year college
degree by 8%, while the comparable figure for a 10% increase in black students is 9%. As
predicted by hypothesis 1a, because higher educational expectations are associated with
both schools of higher socioeconomic status and lower proportions of minority students,
adjustment for the socioeconomic composition of schools results in a positive association
between higher proportions of minority students and higher overall levels of expectations.
(See Table 1.)
With the second group of measures, I include the achievement composition of the
school. The effect on college expectations of the school average pass rate on the state
standardized tests is positive and significant: a 10% increase in a school’s pass rate is
associated with a 12% increase in the odds of students expecting to graduate with a 4-year
11
In each of these models, estimates of individual level coefficients and standard errors do not change in any
substantial fashion from those reported in Model 3, Table 3. Full student level results are available upon
request.
12
A similar analysis using individual variables rather than a factor show similar results and suggests that the
proportion of college educated parents in a school is especially important in explaining between school
variation in educational expectations.
28
college degree. Unfortunately, comparable data is not available for individual student
achievement, and although I have adjusted for other student factors that are associated with
achievement, I can not eliminate the possibility that this school variable simply reflects
variation in individual achievement. At best, it is likely that the effect of school
achievement shown here is overstated. However, given these caveats, the positive effect of
achievement on expectations is the opposite from what the Davis frog pond model
suggested. In fact, as school average scholastic achievement increases, individual college
expectations increase as well.
Similar to the socioeconomic composition of schools, equalizing schools based on
their achievement composition results in an association of higher proportions of black
students with rising expectations. An increase of 10% in the black proportion of students
within a school yields a 9% increase in the school level odds of expecting a 4-year college
degree. Thus, greater educational expectations are associated with higher levels of school
achievement, but high minority schools are more likely to have low average levels of
scholastic achievement. Once adjustment is made for the achievement composition of
schools, higher proportions of minority students result in increased expectation levels,
contrary to the predictions of hypothesis 2b. (See Table 1.)
In the next model, I examine the influence of academic environment on both
educational expectations and the effect of racial composition on expectations. Results in
Table 4 show both that academic environment is unrelated to expectations and does not
mediate the impact of racial composition on expectations, contrary to the prediction of
hypothesis 1c. (See Table 1.)
29
I include all school variables in a complete full model, shown in Model 4 of Table
3. Results show, as suggested before, the positive effects of school socioeconomic
composition and achievement composition on educational expectations, although the effect
of school SES is reduced somewhat from the earlier model shown in Table 4. Additionally,
in this model, the proportions of black and Hispanic students are positively related to
educational expectations. Thus, equalizing school achievement and socioeconomic status,
an increase of 10% in the proportion of black or Hispanic students in a school is associated
on average with a 8-13% increase in the odds of expecting a 4-year college degree. This
finding suggests an independent effect of school racial composition, consistent with my
third hypothesis. (See Table 1.) The between school variance for the full model of .082
represents a 65% decrease in τ00 from the previous model that controlled only for
individual level characteristics and school racial composition.13 Thus, a substantial
proportion of the school level differences in educational expectations is accounted for with
the school variables included in my analysis. Other analysis shows that this reduction is
largely due to the addition of school parental education composition included in the school
socioeconomic status factor: thus, a primary reason for the between school heterogeneity of
educational expectations derives from school differences in average parental education
level. However, comparison of τ00 and its standard error in Model 4 still show that the
variation in educational expectations between schools remains statistically significant,
13
Because of the sequential ordering of my models, it is impossible to compare τ00 from a model with only
student characteristics to one with both student and school characteristics. Other analysis, not shown here,
estimates τ00 to be .242 when only level-1 characteristics are included, a 29% reduction from the
unconditional model. Adding level-2 characteristics to this results in a τ00 of .082, leading to the conclusion
that level-2 characteristics are responsible for a reduction of 66% in the between school variance not
accounted for by level-1 characteristics.
30
indicating that there are other undetermined factors that influence differences between
schools in students’ educational goals.
Finally, I consider if the effect of school racial proportion is the same for students
of differing racial and ethnic groups by including interaction terms between individual
student race and school racial distribution and these results are shown in Model 5 of Table
3. Both the main effects of the variables measuring the school proportion of black and
Hispanic students their statistical significance suggesting that for white students, attending
schools with black or Hispanic students is associated with higher educational expectations.
Additionally, black and Hispanic students’ expectations improve in schools with larger
shares of black students, contradicting Ogbu’s suggestion of a negative relationship
between the individual minority students and the proportion of minority students. This
finding could be related to the self esteem or optimism hypotheses presented earlier,
although it is unclear why only the proportion of black students and not Hispanic students
is significantly associated with higher college expectations for minority students.
Discussion
Unlike most studies that consider school effects on educational outcomes, this study
finds several school characteristics that are associated with higher educational expectations,
including greater proportions of minority students. The observed negative relationship
between the proportion of minority students and educational expectations is reversed by
comparing schools with similar kinds of students, socioeconomic levels, and scholastic
achievement. Moreover, the analysis suggests that although greater concentrations of
minority students positively influence students of all racial backgrounds, greater
31
concentrations of black students have an even larger influence on black and Hispanic
students.
How robust is the finding that students who attend school with large proportions of
minority students are more likely to expect to graduate from a 4-year university? I tested
various specifications of the variables measuring school racial composition to examine
whether the same results emerge from predominately white schools, mixed racial schools,
and predominately minority schools. These analyses (based on dichotomous measures to
represent segments of the school minority composition) reaffirmed my basic result: all
other things equal, college expectations are higher among student, who attend schools with
greater shares of minority students. I also considered whether there is an optimal mix of
students associated with higher educational expectation, and that any segregated school—
either highly white or highly minority—would not exhibit the same level of expectations by
including higher-order racial composition terms. These results further support the positive
monotonic influence of schools’ minority composition on educational expectations.
Whether higher proportions of minority students actually raise students’ goals to
complete a university degree or whether more segregated schools concentrate students with
more ambitious educational goals is unclear. Because of the cross-sectional nature of the
survey data used and the nonrandom assignment of students to schools, this question of
causality cannot be definitively answered. It is possible that students differ across schools
in ways that are related to their educational expectations, but were not accounted for in this
analysis. Nevertheless, this study showed that net of individual and school differences,
students attending more minority segregated schools, and black and Hispanic students
32
attending more black schools are more likely to have ambitious educational goals to
complete college.
What are possible reasons for the counterintuitive finding that in similar school
contexts, students in schools with greater shares of minority students are more likely to
expect to graduate from a 4-year college? The evidence from this analysis does not square
with either the oppositional culture or the self-esteem hypothesis. Ogbu’s oppositional
culture theory suggested that concentrated shares of minority students result in lowered
educational ambitions, but only for minority students. My findings refute this claim: I find
that increased proportions of minority students are associated with higher educational
expectations, for all students. My findings are closer to those proposed by the self-esteem
hypothesis, which suggests that segregated schools benefit minority students’academic self
image, leading to higher educational goals. Contrary to my findings, this effect is only
expected for minority students, but the additional importance of greater school
concentrations of blacks for black and Hispanic students’ educational goals provides some
support for this hypothesis. Perhaps, as suggested by the self-esteem hypothesis, the reason
that black and Hispanic students have higher educational expectations when attending
schools with more black students is because of the greater school academic self-esteem in
segregated schools due to a shielding from real levels of competition.
There are two
problems, though, with this explanation. There is no theoretical reason to assume that the
concentration of Hispanic students would not have an influence similar to black
concentration on educational expectations. But, I find no differential influence of the
proportion of Hispanic students on the educational goals of black and Hispanic students.
Additionally, the self-esteem hypothesis shares some similarities with Davis frog pond
33
theory: both suggest that students are shielded from a realistic and complete view of
academic competition by school segregation, although the mechanisms are different. I find
evidence in this analysis that school achievement levels are associated with higher
educational expectations, contrary to Davis’ frog pond theory. If achievement is positively
linked with self esteem, then it is not clear that self esteem will be higher in schools with
high concentrations of minority students. With direct self-esteem measures, a more
complete investigation of this theory would be possible. However, self-esteem in THEOP
is measured only at wave 2, available only for a sub-sample of the original 13,803 students.
Because the original school level sample is not used for wave 2 sampling, it is impossible
to link student self-esteem with school effects.
In a variation of this theme, Goldsmith (2004) reports that minority students
attending segregated minority schools with many minority teachers are more optimistic and
express more pro-school attitudes than similar minority students attending white schools.
He suggests that the racial composition of the teaching faculty is key to understanding this
effect, and that minority teachers are better able to encourage and influence minority
students. Despite differences in our data14, I attempted to replicated his results, but found
no evidence that schools’ teacher racial composition influenced students’ educational
expectations. Goldsmith’s study focused on very high educational goals (graduate or
professional school) of younger, 8th grade students, whose expectations are not fully
formed and who may have more unrealistic educational goals. Perhaps these younger
more impressionable students are more influenced by their teachers than older students
who are more seasoned by life’s reality checks. Whatever the reasons for this difference, I
14
Goldsmith uses NELS 1988 national data.
34
find no evidence that minority teachers in schools with large proportions of minority
students are associated with high educational expectations.
Goldsmith (2004) also claims that school concentration of black and Hispanic
students in schools improves their normative climate because they have more optimistic
and pro-school attitudes, which could lead, in turn, to more ambitious educational goals.
“Concentrating students with high beliefs generally will raise all students’ beliefs” (p. 141).
In subsequent analysis, I find that black and Hispanic students do have more pro-school
and positive attitudes than do white students, and this seems to be one likely explanation,
and would account for the reason why even for white students, schools with more minority
students are associated with higher educational expectations. My findings also square with
research by Ainsworth-Darnell and Downey (1998), who find that black students report
more pro-school attitudes than do whites, which enhances their academic success.
However, in further analyses, I find that the overall school attitudinal climate is unrelated
to educational expectations and does not mediate the association between school racial
composition and educational expectations. It is possible that these measures do not
completely capture optimism and pro-school attitudes within a school. More research is
needed to examine the association between school racial composition and school optimism.
Although school racial composition, the focus of this paper, is associated with
college expectations, it is noteworthy that other school factors, especially the school
parental education composition, are more important in explaining why schools differ in
their levels of student educational expectations. Thus, although student in high minority
schools do have the advantages of higher than expected educational goals, they are also in
school contexts disadvantaged by low socioeconomic status and low achievement, in
35
addition to greater levels of individual socioeconomic and educational disadvantage.
Furthermore, educational expectations are only one of many important academic outcomes
that accrue to students during the period of their high school enrollment and only one of the
first of many steps to an eventual university degree. Further work is needed to consider
how high schools influence other stages of the college preparation and attainment process,
including academic preparation, application, and initial and continued university
enrollment.
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41
Figure 1. School Racial Composition by Individual Student Race
100%
90%
80%
70%
60%
Asian
Black
50%
Hispanic
White
40%
30%
20%
10%
0%
All Students
White
Hispanic
Black
Asian
Student Race
42
Figure 2: Average expectation by school, Seniors.
43
Table 1. Hypotheses regarding the association between school racial composition and educational expectations
(SRC=School racial composition, EE=Educational Expectations)
Substantive Hypothesis
Null Between school differences
in EE and the impact of
SRC on EE derives in part
from individual differences
in the students attending
schools, rather than from
any independent school
effects.
H1
Analytical Hypothesis
Results
I hypothesize a negative baseline relationship between SRC and EE. By adjusting
for student characteristics, including family socioeconomic background, students’
educational experience and ability, significant others’ influence, and race and
immigration status, the between school variance in EE will be reduced
substantially and the effect of SRC on EE will become less negative.
Confirmed: 23% of the between
school variance is associated with
students’ individual characteristics,
and the observed negative relationship
between SRC and EE disappears,
leaving no net relationship. See Table
4, Model 3.
Effect of SRC on EE
SRC is correlated with other school characteristics that influence EE. But
derives from the
adjusting for these factors, the relationship between SRC and EE can be better
relationship of SRC to other
1a. School socioeconomic status: Because school SES is negatively related
school characteristics that
to the SRC and positively related to EE, by adjusting for school SES, the
are associated with student
effect of SRC on EE becomes more positive.
EE, including school SES,
1b. School achievement: Because school achievement is negatively related
school achievement, and
to both the SRC and EE (frog pond theory), by adjusting for school
school academic
achievement, the effect of SRC on EE becomes more negative.
environment.
1c. Academic environment: Because more academic school environments
are negatively related to the SRC and positively related to EE, by adjusting
for school academic environment, the effect of SRC on EE becomes more
positive.
H2
SRC independent
influences EE, and might
differentially influence
black and Hispanic
students. However, there is
no consensus on the
existence or direction of a
differential effect.
1a, Confirmed: See Table 5
1b, Refuted: See Table 5. School
achievement is positively related to
EE, and by adjusting for it, the effect
of SRT on EE becomes more positive
1c, Refuted: See Table 5. School
environment was not related to EE,
and did not mediate the effect between
EE and SRC.
2a. Independent effect of school racial composition : even after adjusting
for student and school characteristics associated with EE, a statistically
significant relationship between SRC and EE remains.
2a, Confirmed. See Table 4, Model 4.
2b. Interaction effect : I do not hypothesize a specific interaction effect
between individual student race and SRC, but examine empirical evidence
to see what it exists, and if so, what form it takes.
2b. The proportion of black students
is positively associated with higher EE
for both black and Hispanic students
than for similar white students.
44
Table 2. Descriptive Statistics by School Racial Composition*
(Standard deviations)
Dependent Variable
Expect to complete a 4 year college degree
School Level Variables
Racial/Ethnic Composition
Percentage Black students
Percentage Hispanic students
Percentage White students
Socioeconomic Status
Percentage qualifying for free/reduced
priced lunches
Percentage of parents with 4-year
college degree
School SES factor (two preceding variables
factored together)
Achievement
Percentage students meeting state
standards, all tests
Academic Environment
Feeder high school
Average
Low Minority
Schools
High Minority Source of
Schools
Data
0.666
0.685
0.597
[96]
[24]
[24]
12.4
(17.8)
32.0
(30.1)
53.1
(31.0)
2.9
(04.1)
7.9
(5.3)
86.9
(6.7)
18.6
(29.2)
72.2
(29.3)
8.0
(6.5)
36.6
(22.1)
34.3
(17.4)
0
(.852)
22.7
(15.3)
43.9
(19.6)
0.542
(.755)
61.0
(15.7)
21.4
(9.8)
-0.845
(.520)
51.7
(18.3)
58.2
(19.7)
37.0
(12.8)
0.042
0.0125
0
Survey
CCD
CCD
CCD
CCD
Survey
TEA
THEOP
project data
Number of AP courses taken per senior
0.191
(.199)
29.5
(14.5)
0
(.755)
1305
(1123)
0.211
(.271)
28.7
(20.8)
0.188
(1.30)
804
(1093)
0.145
(.115)
26.8
(7.8)
-0.205
(.214)
1818
(977)
[12526]
[2868]
[3019]
Black
0.104
0.041
0.146
Survey
Hispanic
0.338
0.109
0.788
Survey
White
0.518
0.801
0.056
Survey
0.396
0.518
0.196
Survey
0.834
0.876
0.787
Survey
Percentage seniors knowing about
Top Ten Percent Plan
Academic environment factor (three preceding
variables factored together)
School size
Student Level
Race/Ethnicity
Parental Socioeconomic Status
Parent college graduate
Parents own home
TEA
Survey
TEA
Table 2 continues on next page
45
Table 2 continued
Average
Low Minority
Schools
Educational Experiences and Background
Enrolled in college prep track
0.633
0.594
0.663
Survey
Had early expectations to attend college
0.556
0.614
0.451
Survey
GPA
3.17
(.017)
0.434
3.3
(.036)
0.466
3.01
(.034)
0.391
Survey
2.7
(.011)
1.07
(.054)
2.64
(.020)
1.16
(.124)
2.85
(.017)
1.08
(.085)
Survey
0.937
0.946
0.927
Survey
0.86
0.859
0.892
Survey
0.043
0.011
0.138
Survey
0.12
0.088
0.209
Survey
Know about Top 10% Law
Attitudes towards education
Number of AP courses
Significant Others' Influence
Parent encourage college attendance
Teacher encourage college attendance
Immigration and Language
Speak language other than English with friends
Foreign-born
High Minority Source of
Schools
Data
Survey
Survey
*Appropriate school variabls are measured as percentages to ease interpretation at the multivariate
stage of analysis and are labeled as such in this table. Other variables are measured as proportions.
Student level statistics are weighted
Low minority schools are schools in the first quartile of the distribution of combined black and hispanic students
High minority schools are schools in the last quartile of the distribution of combined black and hispanic students
46
Table 3: Factor loadings and Cronbach's Alpha
Description of Variable
School Socioeconomic Status
Proportion of parents with college degree
Proportion of students qualifying for free/reduced price
Factor
Loading
α
0.792
0.792
0.828
School Academic Climate
Feeder High School
Proportion of students knowing about Top Ten Percent Plan
Number of AP courses taken per senior student
0.680
0.567
0.555
0.669
47
Table 4. Hierarchical Logistic Regressions of College Expectations (Log Odds)
(Laplace Estimation)
Intercept
School Level
Percentage Black Students
Percentage Hispanic Students
1
0.637 ***
(0.071)
2
3
4
0.647 ***
0.778 ***
0.847 ***
(0.072)
(0.082)
(0.051)
5
0.771 ***
(0.065)
-0.005
(0.006)
-0.005 *
(0.002)
0.010
(0.004)
0.019
(0.004)
0.592
(0.137)
0.015
(0.005)
-0.155
(0.129)
0.012
(0.006)
0.003
(0.005)
0.000
(0.003)
0.012
(0.004)
0.008
(0.003)
0.295
(0.117)
0.009
(0.004)
-0.088
(0.110)
0.031
(0.006)
School socioeconomic status factor
Percentage students meeting state
standards, all tests
Academic climate factor
School size
**
*
*
*
***
Interaction Terms
Percentage Black*Black
Percentage Hispanic*Black
Percentage Hispanic*Hispanic
Hispanic
Asian
Parental Socioeconomic Status
Parent College
Home ownership
Educational Experiences and Background
Enrolled in college prep track
Had early expectations to attend college
GPA
Know about Top 10% Law
Attitudes towards education
Number of AP courses
Significant Others' Influence
Parent encourage college attendance
Teacher encourage college attendance
Immigration and Language
Speak language other than English
with friends
Foreign born
***
***
***
0.020 **
(0.006)
0.020 ***
(0.006)
0.005
(0.004)
-0.006
(0.004)
Percentage Black*Hispanic
Individual Level
Black
*
0.062
(0.068)
-0.137
(0.080)
-0.101
(0.119)
-0.011
(0.073)
-0.039
(0.086)
-0.412 ***
(0.122)
-0.083
(0.102)
-0.122
(0.096)
-0.020
(0.164)
0.644 ***
0.661 ***
(0.070)
(0.081)
0.258 **
0.274 ***
(0.091)
(0.082)
0.625 ***
(0.078)
0.320 **
(0.105)
0.596
(0.066)
0.860
(0.065)
0.508
(0.047)
0.751
(0.064)
0.421
(0.051)
0.175
(0.022)
0.553
(0.076)
0.821
(0.069)
0.531
(0.051)
0.680
(0.066)
0.498
(0.060)
0.189
(0.024)
***
***
***
***
***
***
0.608
(0.068)
0.903
(0.064)
0.557
(0.051)
0.657
(0.062)
0.459
(0.056)
0.187
(0.023)
***
***
***
***
***
***
***
***
***
***
***
***
0.831 ***
0.818 ***
(0.118)
(0.117)
0.318 ***
0.314 ***
(0.072)
(0.076)
0.854 ***
(0.121)
0.320 ***
(0.077)
-0.392 *** -0.556 **
(0.096)
(0.171)
-0.435 **
-0.431 ***
(0.145)
(0.097)
-0.656 **
(0.186)
-0.392 ***
(0.099)
τ00
0.341
0.304
0.233
0.083
0.067
0.064
0.059
(0.069)
(0.019)
(0.024)
SOURCE: 2002 Texas Higher Educational Opportunity Study, 12526 students clustered in 96 schools
*** p<.001; **p<.01; * p<.05
All variables are grand mean centered
48
Table 5. Hierarchical Logistic Regressions of College Expectations on
School Characteristics1 (Log Odds)
Intercept
Model 3,
Table 1
0.778 ***
(0.082)
+ School
+School
+Academic
SES
Achievement
Environment
0.828 ***
0.873 ***
0.849 ***
(0.050)
(0.054)
(0.053)
Racial Composition
Percentage Black Students
Percentage Hispanic Students
0.003
(0.005)
0.000
(0.003)
0.009 *
(0.004)
0.008 *
(0.003)
0.009 **
(0.003)
0.002
(0.002)
0.003
(0.006)
-0.002
(0.002)
Socioeconomic Status
School socioeconomic status factor
0.406 ***
(0.117)
Achievement
Percentage students meeting state
standards, all tests
Academic Environment
Academic climate factor
School Size
0.011 **
(0.004)
0.104
(0.091)
0.039 ***
(0.006)
0.120
(0.026)
0.028 ***
0.036 ***
(0.006)
(0.005)
τ00
0.233
0.106
0.114
(0.069)
(0.026)
(0.023)
1
Models here include all controls for students' individual characteristics included in Table 4.
*** p<.001; **p<.01; * p<.05
SOURCE: 2002 Texas Higher Educational Opportunity Study, 12526 students clustered in 96 schools
All variables are grand mean centered
49