Do children attending private and parochial schools score higher
than their counterparts of similar background on tests that measure
cognitive skills? Numerous studies show that minority children in
public schools are not making substantial gains in achievement
levels on standardized tests. Clearly, the widely accepted
belief that nonpublic schools produce students with superior
cognitive skills --thus higher scores on
achievement tests--is partly fueling the movements in Milwaukee,
Cleveland, and Florida to offer school vouchers and greater
educational choices to parents in poor school districts. Should a
critical study comparing students in public and parochial schools
find no difference in achievement levels on standardized tests,
then the argument for vouchers and educational choice would be
weakened.
Background
Since the release of the well-known study
on high school achievement by James Coleman, Thomas Hoffer, and
Sally Kilgore (the Coleman report) in the early 1980s, both
academics and policy analysts have vigorously debated the inherent
differences in academic achievement attained by public and private
school students across America. While advocates of private
schooling argue that superior teaching yields superior students,
opponents of choice contend that the intrinsic differences occur
from self-selection. That is, parents of higher socioeconomic
status (SES) may be able to better afford private schooling and are
likely to be better educated themselves. One critic, former Wisconsin
state school superintendent Herbert Grover, describes this
sentiment succinctly: "Do private school children outperform
children in public schools? It's hard to imagine that they
wouldn't, given the initial advantages they enjoy from their
parents."
A
growing number of researchers have addressed this criticism by
integrating more SES and family background characteristics into
their models. The Heritage model
developed for this study is no exception. In the model described
below, we analyze those factors that might explain a student's
academic achievement. These include the stability within the home
as measured by whether or not the child changed schools and if the
child lives in an intact family. Also included is the amount of
reading materials in the home and whether the child's mother
attended college. Finally, the economic
status of the child's surrounding neighborhood is analyzed, noting
that achievement, on average, may be influenced by locational
effects.
The
following analysis is divided into three parts: 1) the rationale
for choosing the specific geographic pool and database, 2) the
methodology, and 3) the results of the statistical model.
Why Washington,
D.C.?
Three factors make D.C. an important
locale for this study. First, its public school system boasts one
of the highest per-pupil expenditures and lowest student-teacher
ratios in the nation. Second, its graduation rate
for public school students is near the bottom of the list, compared
with other states. Lastly, overall academic
achievement of its public school students has been significantly
low compared with other states. With all the educational
resources flowing into the District, it would follow that students
might do better than their counterparts in other parts of the
nation, but typically they do not.
A
second major reason that D.C. is an appropriate location for this
research is its demographic composition. The nation's capital has a
high percentage of non-white residents, offering unique insights
into a school system that primarily serves minorities.
Finally, and most important, Washington,
D.C., is the only U.S. city that may be analyzed in this fashion
using the available data. The NAEP database is rich with
information on both test scores and accompanying demographic and
family-background characteristics. These socioeconomic variables
are critical in exploring the issue of academic achievement. The
Department of Education National Center for Education Statistics
sharply restricts access to the NAEP data: Only licensed users who
agree not to publish any results that might identify individual
school districts are allowed access to the data. Thus, researchers are not
permitted to subdivide state data by cities, even though it would
be relatively easy to do so. But, because D.C. is considered on
equal footing with the states in the NAEP data collection
procedures, results are reported for Washington, D.C., and,
therefore, can be analyzed by socioeconomic characteristics.
Why Catholic
Schools?
Several factors make Catholic schools
appropriate for comparison with public schools. First, they
represent the single largest group of private schools in the
nation, with about 7,000 elementary and middle schools educating
some two million children. Second, Catholic schools
educate a sizable number of non-Catholics. In Washington, D.C., for
example, 52.1 percent of Catholic elementary school children are
not Catholic. In inner cities, Catholic
schools historically have helped underprivileged families through
tuition assistance programs and similar initiatives. As a
consequence, the proportion of minority students in these schools,
especially Hispanics and African-Americans, has increased over
time.
Currently, black enrollments in Washington
represent 79.5 percent of the total Catholic elementary school
population. This, coupled with the
demographic composition of Washington, signifies that Catholic
school students are increasingly indistinguishable from their
public school peers. This is an important factor
to underscore in the analysis below. The similar demographic makeup
of Catholic and public schools greatly facilitates the use of
parallel comparisons. Because this paper is interested only in the
differences between student achievement in Catholic and public
schools, data for other nonpublic, non-Catholic schools were
eliminated from the database.
Data Selection
Criteria
There was a conscious decision to limit
the model to African-American children for two reasons. The first
reason is statistical accuracy. The proportion of
non-African-American children living in Washington, D.C., is small.
The total number of children in fourth (age 9) and eighth (age 13)
grades in Washington, D.C. (the grade levels analyzed below) is
5,860 and 4,995, respectively. Of those children, less than one in
four are not African-American. Further, since this
analysis is interested in comparing Catholic with non- Catholic
school children, using other racial and ethnic groups might also
prove statistically problematic. Only about one out of every five
Catholic students is not African-American.
To
bring this into perspective, non-African-American Catholic students
barely represent 6 percent of the NAEP sample. However, there are some
2,300 African-American students in the fourth-grade NAEP District
of Columbia sample, and well over a hundred of these children are
in Catholic schools. Only 25 white Catholic school children in the
fourth grade were sampled. Similarly schooled Hispanic students
constitute only 20 of the children in the fourth-grade sample.
Although these 25 white and 20 Hispanic observations may yield
results, their statistical reliability would immediately be
questioned if those results were released.
The
second reason for limiting the sample is a data reporting
constraint. The license authorizing The Heritage Foundation to use
the NAEP data requires that we not release results from any
research that identifies any individual student or school. Because
the District is overwhelmingly African-American, the vast majority
of observations in the database are from these students (over 75
percent for the eighth-grade database). This is obviously not a
problem for the African-American sample, but it does raise serious
statistical issues for all the other racial and ethnic groups.
Unfortunately, this is particularly true for non-African-American
Catholic school students (as noted in the discussion above).
Reporting model output for whites, Hispanics, and Asians, puts
Heritage at risk of violating its license. We have therefore chosen
only to analyze African-American students.
Methodology
As
noted above, the model described in this study relies on data in
the National Assessment of Educational Progress District of
Columbia database. The NAEP tests are given to students in the
fourth, eighth, and twelfth grades biennially and alternately for
math and reading. That is, math and reading skills are assessed on
an alternate cycle: The math assessment was administered in 1992
and 1996; the reading assessment was administered in 1990, 1994,
and 1998 (at the completion of this study, the 1998 restricted-use
database had not been released). Test scores for D.C. public and
nonpublic school students in the twelfth grade were not used in
this study because data on twelfth graders are included in the
national survey, but are not available for individual states,
including the District of Columbia.
Since the early 1990s, NAEP's oversight
committee, the National Assessment Governing Board, has gathered
data on a state-by-state level to supplement the national test
administration that has been collected since the 1960s. This
information allows for improved analysis of differences in
achievement levels across participating jurisdictions, so
researchers can now make statistically valid inferences on a
statewide as well as nationwide level.
The
data used for this paper are from the 1996 Washington, D.C., NAEP
math survey. The database not only
contains information on test scores, but also includes
questionnaire responses on family status and other characteristics,
such as reading materials at home, time spent on homework, and
whether or not students have changed schools recently.
This
paper analyzes the differences in math test scores between Catholic
and public schools by examining the composite NAEP math score for
each sampled child. The following attributes of the child are held
constant: attendance at a Catholic school, education of child's
mother,
family status (one or two parents in the home), number of reading
materials in the home (such as newspapers, magazines, books, and
encyclopedias), median income within the school, and whether or not the
child has changed schools within the previous two years. Employing
these factors in the model addresses the concerns raised earlier in
this paper and allows for a fair and balanced comparison of
children across the District.