Abstract. The study compares two groups of students who graduated
from high school in the Milwaukee Public Schools (MPS) during 1997-2001.
Students who had participated in MPS Montessori programs from preschool
through 5th grade were matched to a comparison group on the basis of
gender, SES, race/ethnicity, and high school attended. Data from the ACT
and WKCE, as well as overall and subject-specific high school grade
point averages, were used in exploratory and confirmatory factor
analyses. Once a model was established, the factors were regressed on
the students" demographic characteristics and type of elementary
education in a structural equation modeling framework. The Montessori
group had significantly higher scores on tests associated with the
math-science factor. There were no significant group differences for the
factors associated with English/social studies and grade point average.
A Montessori education is one of the more common alternatives to
traditional schooling. In the United States, more than 5,000 Montessori
schools are affiliated with national or international Montessori
organizations, and many others operate independently. Montessori schools
are typically characterized by multiage classrooms, unique didactic
materials, self-pacing, self-chosen activities, and a virtual absence of
homework, grades, and standardized tests.
In recent years, Montessori programs have expanded from private to
public settings, and from preschool into elementary school and beyond.
This growth of a system with decidedly different pedagogical practices,
coupled with the demand for assessment and scientifically supported
teaching methods, has raised questions of accountability. The purpose of
the current research, which assesses longitudinal outcomes for children
who experienced eight to nine years of education in Montessori public
schools, was to determine whether Montessori programs offer a viable
Outcomes of Montessori Education
Studies of Montessori schools span nearly a century and cover
diverse topics. Researchers have explored relationships between
Montessori education and various outcomes, ranging from private speech
(Krafft & Berk, 1998) and drawing ability (Cox & Rowlands,
2000), to positive emotions, energy, and intrinsic motivation (Rathunde
& Csikszentmihalyi, 2005). However, the majority of research on
Montessori outcomes has focused on students' cognitive
The results from these studies are often difficult to interpret and
generalize from because of methodological shortcomings, such as small
sample size, attrition, lack of random assignment, and poor or
unmeasured implementation of Montessori practices. In addition, such
confounding factors as parental choice (Hill & Craft, 2003; Shumow,
Vandell, & Kang, 1996) and the high-SES level of most Montessori
students (Duax, 1989) have not always been taken into account. Although
these problems render the results of such research inconclusive, the
general picture that emerges is that Montessori students might
outperform traditionally schooled peers.
In one of the more experimentally sound studies, Miller and Dyer
(1975) assessed four different Head Start programs in Louisville by
randomly assigning 214 children to one of 14 classes: 4 traditional, 4
Bereiter-Engelmann, 4 Darcee, and 2 Montessori. Because no qualified
Montessori teachers could be found, the researchers recruited college
graduates, who were then given eight weeks of summer Montessori
training. Children were assessed through 2nd grade, and then again from
6th to 10th grade. Different measures were employed at different ages,
but included Stanford Achievement tests, Stanford-Binet Intelligence
Scales, the WISC-R, Ravens Progressive Matrices, and tests of
self-esteem, creativity, aspirations, sex-role behavior, and
Over time, the performance of the children shifted, with initial
gains followed by losses. The effects of these Head Start programs
mirrored the "wash-out" seen in other early intervention
studies (e.g., Lee, Brooks-Gunn, Schnur, & Liaw, 1990). The males in
the Montessori program were an exception. They consistently outperformed
all other experimental subgroups on IQ, and were the only group that was
not relatively lower at the end of 10th grade than at the end of
preschool (Miller & Bizell, 1983, 1984).
Unfortunately, the design of the Louisville study was compromised
by attrition: at older ages, some groups had as few as six subjects.
Another problem was the quality of the Montessori implementation, which
consisted of a one-year exposure to teachers who were minimally trained
and experienced. In a typical Montessori school, a child spends three
years in one classroom, preferably with the same teacher, and with
classmates of three different ages. Ideally, the child begins the
program by age 3. By studying children for less than one year, in a
classroom that had only 4-year-olds, the experiment was evaluating a
much compromised version of Montessori. Montessori consultants also
confirmed these weaknesses.
Other researchers used a similar experimental design to assess
different preschool curricula, including Montessori. Their results
replicated some of the positive findings of Miller and colleagues (e.g.,
Montessori children were less likely to drop out of school or to repeat
a grade), but shared the same methodological issues of attrition and
implementation (Karnes, Schwedel, & Williams, 1983; Karnes, Teska,
& Hodgins, 1970).
More recently, Lillard and Else-Quest (2006) studied children from
a low-income population who, at ages 2-3, had won or lost a public
Montessori school lottery in a major U.S. city. The Montessori program
was recognized by AMI-USA, which required it to meet a high standard of
Montessori implementation. Children in the experimental group had won
the lottery and had been in Montessori continually since age 3; those
who lost the lottery were the control group. This unique design
accounted for differences in parental motivation, because all parents
had enrolled their children in the lottery. The children were tested at
ages 5 or 12 on a variety of social and academic outcomes. The control
children were at a variety of schools, mostly public, and in the same
neighborhood as the public Montessori.
There were several differences between the 5-year-old Montessori
students and their peers in the control group. The Montessori
5-year-olds performed better on standardized achievement tests
(Woodcock-Johnson Letter-Word identification, Word Attack, and Applied
Math sub-tests) and other cognitive measures (false belief task,
dimensional card sort). No differences were found on tests of Picture
Vocabulary, Understanding Directions, Spatial Reasoning, and Concept
Formation, or on a delay of gratification test. The researchers also
found differences in social outcomes: on a social problem-solving task,
the Montessori children were more likely to make references to justice
or fairness, and they were more likely to be involved in shared peer
play and less likely to engage in rough and tumble play at recess.
The Montessori 12-year-olds wrote essays that were rated higher for
creativity and more sophisticated sentence structures. In comparison to
the control group, Montessori 12-year-olds reported that they felt a
greater sense of community at school and they were more likely to choose
positive assertive responses to conflicts presented in a social
problem-solving questionnaire. The two groups performed equally well on
the Woodcock-Johnson tests at age 12. One problem with this study is
that, although the effect sizes were respectable for education research,
the samples were small (25-30 per group).
Not all researchers have found an advantage for Montessori
students. Lopata, Wallace, and Finn (2005) compared 4th- and 8th-graders
in three magnet schools--Montessori, "back to basics," and
"open classroom"--and in a traditional neighborhood school,
employing mathematics and language scales of standard achievement tests
(New York State Exams and the Terra Nova). The results were mixed and
varied by grade levels, with most tests showing no differences. Although
asserting that their study did not find support for Montessori
education, the authors note the limitations of their findings. Despite
the fact that a large number of children were studied (543 in total),
only one school of each type was tested and information on quality of
program implementation was not available. Furthermore, there were no
data concerning age of entry or length of enrollment in any of the
schools. Finally, children were not randomly assigned to programs, and
it is unclear how parental backgrounds might have varied across the
In sum, a limited number of studies have assessed the outcomes of
Montessori education. Most of these are compromised by undocumented or
poor Montessori quality, small sample sizes, or lack of random
assignment. In addition, few studies have assessed the impact of
Montessori education on high school achievement; those that have done so
also have been hampered by small samples and biased by attrition. In
this era of evidence-based education, there is a need for up-to-date,
carefully constructed studies of the outcomes of Montessori programs.
The current research addresses previous methodological concerns by
utilizing a retrospective longitudinal design to examine various high
school achievement outcomes.
Overview of Design
This study assessed high school outcomes of children who had
previously attended two different public Montessori programs from
preschool through the 5th grade. A valid control group is a substantial
issue in a study of this nature. Although admission to the Montessori
schools was by lottery, no records of lottery participants remained.
Consequently, the authors, in consultation with the Milwaukee Public
Schools (hereafter MPS), focused statistical control on the high school
years by establishing a comparison group of students who attended and
graduated from the same high schools as the Montessori students. The
purpose of this comparison group (the Peer Control group) was to
control, insofar as possible, for other life experiences, especially
educational experiences after 5th grade.
The research plan was as follows: 1) identify the students who had
completed the 5th grade at two public Milwaukee Montessori schools
(MacDowell and Greenfield) in the academic years 1990-1994; 2) ascertain
the high school destinations of these students; 3) establish a
comparison group of graduates at each high school that Montessori
students attended; and 4) compare Montessori and non-Montessori students
on academic outcomes that could be obtained from high school records and
Participants and Procedures
At the outset, MPS staff hand-searched archived files and
constructed a list of students who had completed 5th grade between 1990
and 1994 at the MacDowell and Greenfield schools. Of the initial list of
396 students, 75 represented duplicate names or students for whom no
further data could be found (most likely meaning that they had
unofficially left MPS for another school system); 69 others had formally
transferred out of the MPS system. Twenty-nine students were officially
classified as dropouts, 11 had received an alternative high school
diploma, and 11 were still in school. Thus, a net of 201 students who
had graduated after maintaining active status within MPS were eligible
for the study. The identities of the students were known only to
relevant MPS staff.
Of these 201 students, 144 (72 percent) had attended 7 different
MPS high schools (out of 18 possible in 1999-2000); each of these high
schools had at least 10 former Montessori students. The remaining 57
students graduated from a variety of other MPS high schools, with 9 or
fewer total Montessori graduates.
It should be noted that the four high schools with the highest
number of Montessori graduates (51.8 percent of the total) were quite
selective. One is the largest of four International Baccalaureate (IB)
programs in the state, and in 2000--based on the number of IB and AP
exams given--it was the top-ranked Wisconsin high school; another is a
city-wide arts specialty program, with admittance based upon audition;
the third, a technical school, emphasizes the integration of academic
disciplines with technology, based upon national, state, and industrial
norms; the fourth is a rigorous university preparatory program
(Milwaukee Public Schools, 2000).
One approach to construction of the peer control group would be to
sample randomly within each of the high schools attended by the
Montessori students. However, evaluation of the demographics of the
Montessori group and their high school peers revealed this approach to
be unsound. First, the percentage of Montessori students taking
advantage of the MPS free/reduced lunch program (a surrogate for SES)
was small (about 5 percent) compared to the MPS high school average (58
percent in 1999-2000), as well as to the average (48.25 percent in
1999-2000) at the four high schools (described above) that they were
most likely to attend. Second, the percentage of Montessori high school
students who were classified as minority (59.2 percent) was somewhat
lower than either the MPS average (82.4 percent in 1999-2000) or the
average for the four most frequently attended high schools (71 percent).
With these facts in mind, we constructed a modified peer control
group. Using the criteria of gender, race/ethnicity, and
free/reduced-price lunch status, a demographically identical peer group
was generated at each high school with 10 or more Montessori-origin
graduates. The schools with nine or fewer Montessori graduates were
treated as a single school and (correspondingly) a demographically
identical peer group was generated from their pooled populations.
The Montessori and Peer Controls were each composed of 54.7 percent
females and 45.3 percent males. In each group, 10 students (about 5
percent) had qualified for free or reduced-price lunch status. The
groups were identical in terms of overall race/ethnicity, with 59.2
percent of each group classified as non-white minority and 40.8 percent
classified as white. Variations emerged within the Montessori and Peer
Control groups in the specific percentages of race/ethnicity
classifications (see Table 1), but these were not significantly
different, [chi square] (4, N= 402) = 5.69, p > .20. The two groups
did not significantly differ in terms of the high schools they had
attended, [chi square] = (17, N = 398) = 6.46, p > .95).
All dependent variables used in this study were based upon data
from MPS records. Missing data were the result of incomplete or
illegible older records. Intercorrelations for the dependent measures
are available upon request from the first author.
The Wisconsin Knowledge and Concepts Examination (WKCE) is a
nationally standardized achievement test given to all MPS 10th-grade
students. (Published by CTB-McGraw-Hill, the test is known elsewhere as
the Terra Nova.) The WKCE consists of 5 scales: Reading, Language Arts,
Mathematics, Science, and Social Studies. Students' national
percentile scores from these scales were included as dependent measures.
The ACT is the standardized test generally taken by college-bound
MPS seniors. It provides achievement data in English, Mathematics,
Reading, and Science Reasoning, as well as a composite score. For the
1997 through 1999 graduates, ACT scores were found on the high school
transcripts. By 2000 and 2001, a change in MPS student privacy policies
meant that these scores were no longer included on transcripts.
The Cumulative Unweighted Grade Point Average (GPA) was the measure
of overall high school achievement; per MPS practice, the GPA gave no
extra weight to honors courses and failing grades were included. Almost
all GPAs were found on the high school transcripts; if not, they were
manually computed by summing the number of units attempted times grade
value and dividing by the number of units attempted. Unweighted grade
point averages also were manually computed for the specific subjects of
Social Studies, Mathematics, Science, Foreign Language, and English.
The independent variable was previous exposure to Montessori
education. The two Montessori elementary schools included in this study
were well-established and considered to have good Montessori
implementation. Teachers were rigorously trained in Montessori education
and classrooms were composed of multiage groupings of students. After
enrolling at either age 3 or 4, the children in this study received 8 to
9 years of Montessori education before graduating from these schools.
For an extended discussion of the Montessori implementation at the
schools, see the comprehensive history by Butz and Miller (1988).
Overview of Statistical Analyses
The differences between Montessori-educated high school students
and their matched controls were examined for several academic variables:
composite and subtest scores for the ACT and WKCE, as well as overall
and subject-specific high school grade point averages. Due to the large
number of dependent variables in our data set, factor analysis was used
to determine the number of underlying dimensions of the dependent
variables, and to identify the subset of variables that corresponded to
each of these dimensions. A series of confirmatory and exploratory
factor models were fit in order to determine the factor structure that
best represented the data. The effects of gender, race/ethnicity, SES,
and Montessori education were then modeled at the factor level.
Muthen and Muthen's Mplus program (www.statmodel.com), with
the missing data algorithm, was used. The factor models were fit in a
confirmatory set-up using all available data, but exploratory models
were based on the 53 participants with complete data.
Exploratory Factor Analysis
Exploratory factor models were fit to the 53 participants who had
complete data, with Promax Rotation. The exploratory models indicated
that three factors existed in the data. The first factor, GPA, had
substantial loadings on the six GPA variables. The second and third
factors represented general content areas of the ACT and WKCE. The
second factor, Math/Science, had high loadings by the seven math and
science tests and the composite score of the ACT. The third factor,
English/Social Studies, had high loadings by the nine English and social
studies tests, the two science tests, and the ACT composite.
Confirmatory Factor Analysis
Five factor models were compared using confirmatory factor
analysis. Two of the models were based on the results of the exploratory
factor analysis and we included three additional models based on a
priori hypothesis: 1) a one-factor achievement model in which all
observed variables loaded on a single factor; 2) a two-factor model
representing Math/Science and English/Social Studies; and 3) a
three-factor model in which the GPA scores loaded on a GPA factor, the
ACT scores loaded on an ACT factor, and the WKCE scores loaded on a WKCE
factor. The first model based on the exploratory factor analysis (EFA),
Exploratory A, has a relatively simple structure, as only the ACT
composite score has a dual loading on the Math/Science and the
English/Social Studies factors. The second factor model based on the
results of the EFA, Exploratory B, has a slightly more complex factor
structure as the two science tests, ACT Science Reasoning and
WKCE-Science, have dual loadings as well as the ACT composite score.
This second model more closely mirrors the results from the EFA. The
path diagram for this model is shown in Figure 1.
The fit statistics for the five confirmatory factor models are
contained in Table 2. The confirmatory model, Exploratory B, best fits
the data ([chi square] = 974, df = 224, RMSEA= 0.09). The dual loadings
of the science tests in Exploratory B were a significant improvement
over Exploratory A ([DELTA][chi square] = 99, Adf = 2), indicating that
the science tests measure both reading ability and mathematics/science
ability. The factor intercorrelations and standardized factor loadings
for the best fitting model are contained in Tables 3 and 4,
Structural Equation Modeling Analysis
Once the factor structure was established, the factors were
regressed on gender (-0.5 = female, 0.5 = male), ethnicity (-0.5 =
majority, 0.5 = minority), social economic status (-0.5 = not eligible
for free lunch, 0.5 = eligible for free lunch), and type of elementary
education (-0.5 = traditional, 0.5 = Montessori) of the subjects.
Because all of the variables were effect coded (-0.5, 0.5) and the
factor variances were set to unity, the effects are standardized and
represent the exact difference between groups. There were several
significant results (see Table 5). Attending a Montessori elementary
school had a significant positive effect on the Math/Science factor
(0.30). Children who received a Montessori education outperformed
children who attended traditional elementary schools on the Math/Science
factor by approximately one-third of a standard deviation.
[FIGURE 1 OMITTED]
Additionally, females had higher GPAs than males (0.46) and
non-minority students outperformed minority students on the GPA (0.88),
Math/Science (1.26), and English/Social Studies (1.21) factors. The
measure used for socioeconomic status, eligibility for the free lunch
program, also had a significant effect on GPA. Economically
disadvantaged students had a lower GPA factor than students who were not
eligible for the free lunch program by almost one standard deviation
In sum, the results of the structural equation analyses indicate
that children who attended Montessori elementary schools scored higher
on high school standardized math and science tests than their peers who
attended traditional schools. There were no significant differences
between Montessori and non-Montessori students on GPA and standardized
tests of English and Social studies.
Despite a very different educational experience through 5th grade,
students who had attended Montessori schools performed as well as their
matched high school peers on most measurements, and even better on the
Math/Science composite. The results suggest two related questions.
First, why were there significant differences in favor of Montessori
students on standardized tests of mathematics and science? Second, why
were there no significant group differences for the Montessori students
on standardized tests of English/Social Studies and on school grades?
Maria Montessori developed didactic materials and methods for all
major areas of academic growth (Montessori, 1912/1988). Perhaps best
known are Montessori's unique sensorial mathematics materials. They
are manufactured to a set standard, presented to the child in the same
sequence, and used in the same manner across all children at authentic
Montessori schools. A Montessori mathematics education tends to be
distinctive and highly consistent. From age 3 on, Montessori children
work with abstract mathematical concepts in a concrete form. (The
science materials, which take the form of stories called Great Lessons
and are initially less sensorial, become concrete in the elementary
levels as children work with laboratory experiments.) There are also
specially designed Montessori language arts materials--the foundations
for skills used in English and social studies--that follow the same
principles of learning embodied in the Montessori science and
mathematics curriculum. The pertinent issue is why differences appeared
in math and science, but not in English and social studies.
The pattern of significant and non-significant group differences on
standardized tests found in this study may reflect a number of factors.
One perspective on this issue might be inferred from the results of a
large-scale study of classroom instruction (Pianta, Belsky, Houts,
Morrison, & NICHD Early Child Care Research Network, 2007). This
study suggests that traditional schools spend much more time on language
arts than they do on mathematics and science. For example, in the 1st
and 3rd grades, more than 50 percent of instruction was in literacy and
less than 10 percent was in math. In Montessori schools, children are
expected to spend as much time working on mathematics and science as
they do on language arts. Thus, long-term differences between the
Montessori and Peer Control students may be influenced by differential
amounts of exposure to these learning domains.
Differential exposure also may be occurring at home. Families seem
to be generally better at facilitating the cognitive skills of language
arts (through books, conversation, and opportunities for enrichment)
than they are at stimulating the cognitive skills of mathematics and
science. For example, research suggests that parents are likely to
engage children in reading-related activities (Christenson, Rounds,
& Gorney, 1992). Furthermore, parents seem to have less information
and confidence about how to promote early math skills (Hill & Craft,
2003), and they have less sense of their children's actual
mathematical competence (Pezdek, Berry, & Renno, 2002).
Long-term differences on standardized tests may simply mean that
Montessori children may be receiving more exposure to mathematics and
science. This phenomenon may reflect not only absolute exposure, but
also timing: as noted, in Montessori schools, the use of mathematics
materials begins relatively early. The nature of the materials
themselves also may be important. Montessori mathematics materials
embody abstract ideas in a concrete form, incorporating movement,
concentration, and control of error (among other things). The impact of
these materials on cognitive development is a promising topic for
Grade Point Averages
The Montessori and Peer Control groups did not significantly differ
on the GPA factor, although in raw terms, both general and
subject-specific grade point averages favored the Montessori group. It
is important to consider that the Montessori and Peer Control students
evidenced strong school performance relative to their counterparts in
the MPS: their overall grade point averages were 2.72 and 2.59,
respectively, while the general MPS overall grade point average in
1999-2000, for example, was 1.69. For MPS students with 90 percent or
better attendance, the 1999-2000 GPA was 2.52 (Milwaukee Public Schools,
The interpretation of findings concerning grades is complex. Grades
are likely to reflect a variety of influences, some of which are
non-cognitive (Messick, 1979). These can include such variables as
family background characteristics and educational values, school
attendance, and class participation. Grade point average also can depend
upon the ease or difficulty of curricula, and on differences in grading
and teaching styles among instructors (Noble, Davenport, Schiel, &
Pommerick, 1999a, 1999b; Noble & McNabb, 1989). By matching on
demographic characteristics and, more importantly in this regard, on
high school of graduation, we hoped to reduce the impact of some
Many of the students in this sample--both Montessori and Peer
Control--attended the most rigorous of the MPS high schools, where
expectations and support for school achievement would have been high.
Their school attendance patterns, as found on the transcripts, were
virtually identical. It is also possible that the Montessori students
were taking higher level math and science courses (something suggested
by their higher standardized test scores), but because GPA was
unweighted, the impact of more challenging classes is not reflected in
the GPA variable.
One limitation of this research is lack of control for certain
parent variables. Despite the fact that selection for the Montessori
programs was made via lottery, children in this study were not randomly
assigned to Montessori or non-Montessori schools; their parents probably
chose these schools. One cannot determine how parental motivation
(Shumow et al., 1996), involvement in school (Hill & Craft, 2003),
or attitudes toward education (Glenn, 1993) might have systematically
influenced outcomes across the two groups.
These limits are mitigated in part by the study's design. The
construction of a comparison group based on equivalent high school
experience allows control for a substantial portion of subsequent
educational experience, as well as some of the factors that vary with it
(Noble, Davenport, Schiel, & Pommerick, 1999a, 1999b). Ideally, in
public school systems that use lotteries for admission to their
Montessori programs, those who were not admitted (the "lottery
losers") can be identified and used as a control group, as was done
in the study by Lillard and Else-Quest (2006).
Another limitation of this research lies in not knowing the prior
educational experiences of the Peer Control group. At the time the
children in this study were in elementary school, MPS had a wide variety
of school choices, including language immersion, creative arts, and
gifted and talented. Knowing the preschool and elementary school history
of children in the comparison group (in addition to the specific 6th-
through 8th-grade histories of both groups) might help us to better
understand the academic similarities and differences between Montessori
and Peer Control students.
As public school records become increasingly centralized and
systematized, future researchers--especially if they design prospective
studies--will be better able to document the nature and realities of
The results reported here are for students attending traditional
MPS high schools, assessed five to seven years after they had
participated in a preschool through elementary Montessori program. The
measures were not particular to Montessori, but rather to the standard
achievement tests and academic records of a public school system. The
peer control group established common high school experience for both
groups, and in demographic characteristics (such as gender, race, and
eligibility for free lunch), the two groups were nearly identical.
With the qualification that the experience is that of a single
school system, this study indicates that a program such as Montessori,
with a rigorous set of principles and practices, can be implemented by a
major urban school system with a high degree of fidelity to these
standards and can achieve equal or better outcomes than are achieved by
a conglomerate of other school programs. Many people have expressed
concern that Montessori programs ill-prepare students for the
competitive environments they face in high school. These results provide
compelling evidence that this is not the case. Despite having spent the
first five years of elementary school in a non-traditional school
environment, without tests, grades, homework, or standard lectures, the
Montessori students were doing as well or better than the control group
that presumably had those traditional features.
Another notable finding is the better performance on mathematics
and science standardized tests shown by the Montessori graduates. In an
era when we are particularly concerned with STEM (Science, Technology,
Education, Mathematics) education and with U.S. students lagging behind
in these disciplines, this result is key. The difference (1/3 of a
standard deviation) is not enormous, but the students had been enrolled
in the same math and science programs for the 5 to 7 years leading up to
the tests that constituted the dependent measures here. That early
exposure to a different mathematics/science program could have such a
difference after several subsequent years of exposure to the same
education is remarkable. This begs the question of whether Montessori
math/science education beyond 5th grade might further accentuate the
This study supports the hypothesis that Montessori education has a
positive long-term impact on student achievement. Additionally, it
provides strong evidence that students can successfully move from
Montessori programs to traditional schools.
We thank the Bader Foundation and the O'Shaughnessy Foundation
for their funding of this research, the Milwaukee Public Schools (MPS)
and the American branch office of the Association Montessori
Internationale (AMIUSA) for their cooperation, and Doreen Lange, Tim
McElhatton, Angeline Lillard, Naomi Wentworth, and Margaret Germann for
their assistance with various parts of the research. A portion of this
work was presented at the AMIUSA National Conference, Minneapolis, July
2002, at the National Meeting of the American Educational Research
Association, San Francisco, April 2006, and at the Biennial Meeting of
the Society for Research in Child Development, Boston, March 2007.
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Kathryn Rindskopf Dohrmann
Lake Forest College
Tracy K. Nishida
University of California, Berkeley
National Center for Educational Restructuring and Inclusion (NCERI)
The Graduate School and University Center, The City University of
Dorothy Kerzner Lipsky
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Kevin J. Grimm
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Table 1 Racial/Ethnic Classifications of the Participants
Montessori Group Peer Control Group
Frequency Percentage Frequency Percentage
Black 107 53.2 95 47.3
White 82 40.8 82 40.8
Hispanic 7 3.5 18 9.0
Islander 3 1.5 4 2.0
Native American 2 1.0 2 1.0
Fit Statistics for Confirmatory Factor Models
Model df [chi square] RMSEA
One Factor 230 2203 0.15
Two Subject Factors 227 2056 0.14
Three Area Factors 227 1232 0.11
Exploratory A 226 1073 0.10
Exploratory B 224 974 0.09
GPA Science Social Studies
Math/Science 0.73 1.00
English/Social Studies 0.71 0.86 1.00
Standardized Loadings for the Chosen Factor Model
GPA Science Social Studies
Overall GPA 0.97 -- --
Social Studies GPA 0.88 -- --
Math GPA 0.85 -- --
Science GPA 0.88 -- --
English GPA 0.89 -- --
Foreign Language GPA 0.79 -- --
ACT Composite -- 0.26 0.75
ACT English Total -- -- 0.95
ACT English Use/Mechanics -- -- 0.93
ACT Rhetoric -- -- 0.91
ACT Math Total -- 0.99 --
ACT Elementary/Algebra -- 0.94 --
ACT Algebra/Geometry -- 0.85 --
ACT Geometry/Trigonometry -- 0.91 --
ACT Reading -- -- 0.94
ACT Social Science -- -- 0.92
ACT Arts & Literature -- -- 0.87
ACT Science Reasoning -- 0.31 0.63
WKCE-Reading -- -- 0.85
WKCE-Language Arts -- -- 0.88
WKCE-Math -- 0.83 --
WKCE-Science -- 0.43 0.41
WKCE-Social Studies -- -- 0.57
Table 5 Regression Coefficients With Standard Errors
Predictor GPA Math/Science Soc. Studies
Montessori 0.19 (0.10) 0.30 (0.12) * -0.04 (0.11)
Gender -0.46 (0.11) * 0.21 (0.12) -0.13 (0.11)
Ethnicity -0.86 (0.11) * -1.26 (0.13) * -1.21 (0.12) *
Free Lunch -0.88 (0.24) * -0.29 (0.27) -0.33 (0.26)
Note. * indicates a significant parameter, p < 0.05