Content uploaded by Angeline Lillard
Author content
All content in this area was uploaded by Angeline Lillard on Jan 31, 2018
Content may be subject to copyright.
This article appeared in a journal published by Elsevier. The attached
copy is furnished to the author for internal non-commercial research
and education use, including for instruction at the authors institution
and sharing with colleagues.
Other uses, including reproduction and distribution, or selling or
licensing copies, or posting to personal, institutional or third party
websites are prohibited.
In most cases authors are permitted to post their version of the
article (e.g. in Word or Tex form) to their personal website or
institutional repository. Authors requiring further information
regarding Elsevier’s archiving and manuscript policies are
encouraged to visit:
http://www.elsevier.com/copyright
Author's personal copy
Preschool children's development in classic Montessori,
supplemented Montessori, and conventional programs☆
Angeline S. Lillard
Department of Psychology, University of Virginia, Charlottesville VA 22904-4400, USA
article info abstract
Article history:
Received 21 December 2010
Received in revised form 9 January 2012
Accepted 12 January 2012
Action Editor: Robin Hojnoski
Research on the outcomes of Montessori education is scarce and re-
sults are inconsistent. One possible reason for the inconsistency is
variations in Montessori implementation fidelity. To test whether
outcomes vary according to implementation fidelity, we examined
preschool children enrolled in high fidelity classic Montessori pro-
grams, lower fidelity Montessori programs that supplemented the
program with conventional school activities, and, for comparison,
conventional programs. Children were tested at the start and end of
the school year on a range of social and academic skills. Although
they performed no better in the fall, children in Classic Montessori
programs, as compared with children in Supplemented Montessori
and Conventional programs, showed significantly greater school-
year gains on outcome measures of executive function, reading,
math, vocabulary, and social problem-solving, suggesting that high fi-
delity Montessori implementation is associated with better outcomes
than lower fidelity Montessori programs or conventional programs.
© 2012 Society for the Study of School Psychology. Published by
Elsevier Ltd. All rights reserved.
Keywords:
Early childhood education
Fidelity of implementation
Academic achievement
Social development
School readiness
1. Introduction
Montessori education has been in existence for over 100 years, and today is used in over 4000 schools
in the United States alone (Cossentino, 2005), including about 400 public and charter schools (Shapiro,
2007). However, studies of Montessori education's impact on development are rare (Walsh & Petty,
2007). The few studies that exist present a mixed picture, with some showing better outcomes than
other programs (Besancon & Lubart, 2008; Dohrmann, Nishida, Gartner, Lipsky, & Grimm, 2007; Lillard
& Else-Quest, 2006; Miller & Bizzell, 1984; Rodriguez, Irby, Brown, Lara-Alecio, & Galloway, 2005), and
Journal of School Psychology 50 (2012) 379–401
☆This research was supported by grants from the Brady Education Foundation and the National Science Foundation. I thank Alyssa
Hart, Nicole Godine, Linda Kim, Matt Lerner, Jeff Spies, and Morgan Woodyard for their help with running the study and statistical
analyses, and the parents, children, and schools who participated.
E-mail address: lillard@virginia.edu.
0022-4405/$ –see front matter © 2012 Society for the Study of School Psychology. Published by Elsevier Ltd. All rights reserved.
doi:10.1016/j.jsp.2012.01.001
Contents lists available at SciVerse ScienceDirect
Journal of School Psychology
journal homepage: www.elsevier.com/locate/
jschpsyc
Author's personal copy
others showing similar or even worse outcomes (Cox & Rowlands, 2000; Krafft & Berk, 1998; Lopata,
Wallace, & Finn, 2005). This article examines whether different outcomes are associated with different
implementations of Montessori, consistent with other domains in which fidelity of implementation has
been related to different program outcomes (Blakely et al., 1987; O'Donnell, 2008).
1.1. Montessori education and its outcomes
Montessori education began in a slum in Rome in 1907 when Maria Montessori, one of the first woman
physicians in Italy (Kramer, 1976; Povell, 2009), extended her sensorimotor work with children with
mental disabilities to children who were typically developing and from low-income backgrounds. A dis-
tinctive feature of Montessori education is dozens of specific materials
1
(Lillard, 2011a) and activities
that confer learning through action (Piaget, 1970, pp. 147–8). These materials were developed by Dr. Mon-
tessori and her collaborators over 45 years (with some limited modifications thereafter) and are integral
to the program that also involves placing children in 3-year groupings, lessons that are almost exclusively
in small groups or one-on-one (Hojnoski et al., 2008), a highly organized physical space, and free choice
among constructive learning activities (Humphryes, 1998). The materials used in these activities provide
corrective feedback, and are grouped into curricular areas of Sensorial, Language, Mathematics and Geom-
etry, Geography, Culture, Music, and Art, as well as Practical Life (Montessori, 1967, 1989a, 1989b). Theo-
retically, Montessori education embodies many features known to enhance learning and development
(Glenberg, Jaworski, Rischal, & Levin, 2007; Lillard, 2005, 2011b), but only some studies of Montessori ed-
ucation show that it confers better developmental outcomes.
Three published studies of Montessori education have used some form of random assignment to min-
imize possible selection effects. The most recent of these found better outcomes for low-income children
in a public Montessori school than those in business-as-usual control schools on a variety of measures,
both at ages 5 and 12 (Lillard & Else-Quest, 2006). However, the other two randomized controlled studies,
both involving Head Start, found that immediate outcomes for Montessori programs were similar to those
of other types of preschool programs (Karnes, Shewedel, & Williams, 1983; Miller & Dyer, 1975), although
effects did appear later (“sleeper effects”). In one study (Karnes et al., 1983) delayed social and cognitive
benefits appeared by high school for all children who had previously attended Montessori programs, and
in the other (Miller & Bizzell, 1984) later benefits emerged only for boys.
Other studies have examined outcomes of Montessori education using samples that were matched at
either the individual or school level. One recent study using four demographically-matched traditional
public and magnet city schools found equal math and worse language arts outcomes for 8th graders en-
rolled in public Montessori schools as compared to children in the matched schools; 4th graders in Mon-
tessori and other types of programs performed equally (Lopata et al., 2005). These findings contrast with a
different study finding that children who had attended public Montessori programs from ages 3 to 11 per-
formed better at ages 15 to 18 in math and science than demographically-matched classmates who had
been in other programs through the 5th grade (Dohrmann et al., 2007). Other studies have shown better
socio-emotional outcomes for children attending Montessori middle schools than controls in
demographically-matched conventional middle schools (Rathunde & Csikszentmihalyi, 2005a, 2005b),
whereas another study documented less private speech—a developmentally-important activity—by chil-
dren attending a Montessori school than by controls attending a conventional preschool who were
matched by family socioeconomic status (Krafft & Berk, 1998). In sum, the existing research presents a
mixed picture regarding Montessori education outcomes. One possible explanation for this mixed picture
concerns implementation of the Montessori program in the different studies.
1.2. Implementation fidelity
Fidelity of implementation refers to how well a program is implemented relative to the original or the
ideal. The concept has long been of concern in the health literature, but its importance in education liter-
ature is only recently being recognized (O'Donnell, 2008). Higher implementation fidelity is generally
1
Hereafter, Montessori materials refers both to Montessori materials (e.g., the Pink Tower) and activities (e.g., Table Washing and
the Silence.)
380 A.S. Lillard / Journal of School Psychology 50 (2012) 379–401
Author's personal copy
associated with better program outcomes, and lower fidelity, in which programs are altered from the orig-
inal, is often associated with poorer outcomes (Carroll et al., 2007; Durlak & DuPre, 2008; Odom, 2009;
O'Donnell, 2008). However, there is a flip side to implementation fidelity: longevity. Programs last to
the extent that they “reinvent”(O'Donnell, 2008, p. 44) themselves by adapting to the cultures and cir-
cumstances into which they disperse (Goodman & Steckler, 1989). By compromising fidelity in the adap-
tation process, programs can lose some of their effectiveness, but they can gain in endurance. Indeed,
research on scaling interventions up frequently shows that positive effects diminish with dissemination
(Durlak & DuPre, 2008), which common sense would suggest entails adaptation. A purpose of this re-
search is to examine whether Montessori education might also reflect this tradeoff between high fidelity
and endurance.
1.3. Types of Montessori implementation
The existing literature rarely discriminates Montessori program implementations, but two basic styles
can be observed in the United States: a classic approach that adheres tightly to Dr. Montessori's original
program as outlined in her books (Montessori, 1967, 1989a, 1989b) and a supplemented one in which
conventional school activities and materials are added to the core program.
2
The classic implementation
is strict and traditional, and often identified with the Association Montessori Internationale (AMI), the or-
ganization Dr. Montessori founded to carry on her work. It includes 3-hour work periods in the morning
and, for children over age 4, in the afternoon as well; a 3-year age grouping; a single trained teacher;
and a specific set of Montessori materials. However, few Montessori programs in the United States have
a strict and traditional program. Indeed, as Povell (2009) discussed at length, adaptation to the local cul-
ture was an important aim of Dr. Nancy Rambusch, the founder of the American Montessori Society
(AMS), America's largest Montessori society that is credited with reviving Montessori education in
1960s America (O'Donnell, 2007). As stated on the AMS website, “From the beginning, Dr. Rambusch
and AMS advanced a modified version of Montessori education, more attuned than the original to mid-
20th century American culture”(American Montessori Society, 2011). Adapting Montessori education to
the local culture was integral to its re-rooting in America in the 1960s (it had been popular in the 1910s
but diminished thereafter). Although this American adaptation had several aspects, such as making a col-
lege degree a prerequisite for teacher training, one aspect—the focus here—was adding to the standard set
of Montessori materials. Rambusch is said to have added “easel painting, clay modeling, and educational
toys”(O'Donnell, 2007, p. 87), and today, the AMS School Accreditation standards state that, “Classroom
environments in quality Montessori schools are equipped with a full range of Montessori and curriculum
support materials”(emphasis added; American Montessori Society, 2009, p. 6, Standard 3.71). Regardless
of organizational affiliation, many Montessori classrooms worldwide adapt the basic program. Besides
supplementary materials, other common Montessori adaptations are shorter work periods, special classes
and additional teachers for extracurriculars, grades, and homework. Without such flexible adaptation,
Montessori might not have taken root and thrived in America as it has since 1960. At issue is whether ad-
aptation might be associated with different levels of effectiveness.
The studies reviewed earlier showing more positive outcomes all involved high fidelity or “classic”
implementations of Montessori. Lillard and Else-Quest (2006), which showed that at 5 and 12 years of
age children who attended Montessori programs scored higher on several social and cognitive outcome
measures, and Dohrmann et al. (2007), which showed that in high school children who had previously
attended Montessori programs excelled in science and math, both involved Montessori programs that
would likely be considered classic implementations because the schools were associated with AMI. Four
of the five schools used in the Rathunde and Csikszentmihalyi (2005a,b) studies examining social-
emotional outcomes were associated with AMI; even the one that was not officially recognized by AMI, be-
cause it had not sought the status, was hand-picked for its classic implementation (Rathunde, personal com-
munication, July, 10, 2009). In contrast, the Head Start studies (Karnes et al., 1983; Miller & Dyer, 1975)
showing weaker and distal effects had low fidelity implementations. Both programs included only children
of one age (4-year-olds) rather than the 3-year age grouping Dr. Montessori's books (e.g., 1967, p. 35,
2
Supplemented programs might differ in other ways as well; in this study use of Montessori materials is the index of fidelity of
implementation.
381A.S. Lillard / Journal of School Psychology 50 (2012) 379–401
Author's personal copy
p. 302; 1989c, p. 68) describe. In one program, only one-half hour per day—not three hours—was spent
working with the Montessori materials (Karnes et al., 1983). Schedules were not provided for the other
Head Start study, but its Montessori programs' mean implementation score was 6.5 on a scale of 0 (not
at all)to10(best possible), suggesting adaptation or a shift from the classic approach (Miller & Dyer,
1975). Krafft and Berk's (1998) article showing less private speech describes limited Montessori work
time, supplementary materials, and “workstations”set up by the teachers at the Montessori school where
they tested. In contrast, materials in classic Montessori classrooms are typically made available for children
to choose from open low shelves (Montessori, 1966, p. 121). The Montessori elementary school used in the
Lopata et al. (2005) study, which found worse language arts scores for children in 8th grade, issued evalu-
ative grades to children and also had “specials”(both alterations to a classic Montessori program; see
Montessori, 1967, pp. 59–60). Taken together, these reports leave open the possibility that fidelity of imple-
mentation might explain variations in outcomes, with higher fidelity programs possibly being associated
with better outcomes.
Differences in implementation are multifarious, and there are no established measures of Montessori
program fidelity. One difference that is simply and objectively measurable is the percentage of children
in a classroom using classic Montessori materials at any given moment. This is essentially “a measure of
the basic extent of use of the curricular materials,”which is one of six accepted ways of measuring pro-
gram fidelity (O'Donnell, 2008, p. 39). This unidimensional measure might index other more complex as-
pects of fidelity (see Carroll et al., 2007, for discussion of complexity), like organization of the environment
or navigation of the curriculum. Children must virtually always use Montessori materials in classrooms
that provide only those materials, and teachers who provide only the classic Montessori materials are like-
ly to also be strict about how they implement other aspects of the program. The set of materials that are
required for a true Montessori program is well-agreed upon by Montessori teacher trainers (Lillard,
2011a), and Dr. Montessori (1989c) advised against expanding on this set:
The material of our schools today is based on the selection that the children have voluntary made
themselves from the mass of things that was placed at their disposal …This selection brought us
to the conception that there must be just that amount and no more. . . . The fundamental fact in
the preparation of the environment is to have only one set of each type of material. (p. 64)
This selection of materials was considered complete: “The didactic materials, for instance, established
through experimentation, is [sic] given complete to the teacher”(Montessori, 1997, p. 31). As O'Donnell
(2007) noted regarding adding to this set of materials, “Modern embellishments to the curriculum did
not please the . . . purists”(p. 87).
In supplemented Montessori programs, however, at any given moment, children might be engaged
with activities beyond the classic Montessori set of materials, such as crafts projects, commercial puzzles,
games, and blocks, and worksheets. Working with such materials instead of the classic Montessori ones
could in theory be beneficial, harmful, or neutral. This exploratory study sought preliminary empirical ev-
idence on this issue.
Children's development across the school year was examined in two types of Montessori preschool
programs: ones that use only classic materials and ones that supplement the classic materials with
commercial ones. Development in conventional preschool programs that had no Montessori materials
was also examined for comparison. The conventional programs were in highly regarded schools and
were aligned with the basic principles of the National Association for the Education of Young Children
and recognized by the state's Independent Schools association; in addition, parents of children in the
Montessori programs most often chose them as the alternative private school their child would attend
were a Montessori program not available. Each sample was composed of families that as a group were
statistically the same in terms of income, education, and ethnicity. Importantly, with one exception
the children's scores on the tasks at the beginning of the school year did not differ between the pro-
grams, mitigating the concern that unobserved family or child characteristics associated with school
selection were the main drivers of results, since selection effects should have been observed in the
fall as well. The exception (vocabulary score) favored the conventional programs, and this was used
as a covariate in statistical analyses. The outcomes measured in this study fit under the overarching
concept of “school readiness.”
382 A.S. Lillard / Journal of School Psychology 50 (2012) 379–401
Author's personal copy
1.4. School readiness
Young children's school readiness, or preparedness to thrive in school settings, is of great concern
(Graue, 2006; Pianta, Cox, & Snow, 2007). Children who arrive in first grade lacking some number and let-
ter knowledge, age-appropriate language skills, and sufficient social skills and self-regulation disadvan-
tage themselves and also their classmates (Blair et al., 2007; Raver, Garner, & Smith-Donald, 2007).
School readiness is therefore a major goal of early childhood programs (Pianta et al., 2007). Here we tested
for a multifaceted set of skills that help children thrive in early school settings: executive function, theory
of mind, social problem solving, early reading, vocabulary, and early math (Blair & Diamond, 2008; Blair &
Razza, 2007; Howes et al., 2008; Kendeou, van den Broek, White, & Lynch, 2009; Welsh, Parke, Widaman,
& O'Neil, 2001). The value of reading, vocabulary, and math for school success is clear; the others are dis-
cussed in the sections that follow.
1.4.1. Executive function
Executive function (EF) is an umbrella term covering several component skills, such as working mem-
ory, inhibitory control, attention, planning, and flexibility (Bull, Espy, & Wiebe, 2008; Garon, Bryson, &
Smith, 2008; Huizinga, Dolan, & van der Molen, 2006; Miyake, Friedman, Emerson, Witzki, & Howerter,
2000). It is sometimes viewed as redundant with self-regulation (Blair & Diamond, 2008; Bronson,
2001). Executive function skills are significantly related to children's success in school (Blair & Razza,
2007; Bull et al., 2008; Espy et al., 2004; McClelland, Acock, & Morrison, 2006; McClelland et al., 2007;
Mischel, Shoda, & Rodriguez, 1989; Passolunghi, Vercelloni, & Schadee, 2007) as well as social skills
(Hughes, 1998; Mischel et al., 1989; Riggs, Jahromi, Razza, Dillworth-Bart, & Mueller, 2006). Executive
function is trainable (Diamond & Lee, 2011; Dowsett & Livesey, 2000; Rueda, Rothbart, McCandliss,
Saccomanno, & Posner, 2005; Thorell, Lindqvist, Nutley, Bohlin, & Klingberg, 2009), diminished by some
experiences (Lillard & Peterson, 2011), and helped by certain preschool programs (Diamond, Barnett,
Thomas, & Munro, 2007; Lillard & Else-Quest, 2006).
1.4.2. Theory of mind
Theory of mind is a set of interrelated concepts through which we explain and predict others' ac-
tions (Wellman, 1990). Performance on theory of mind tasks has been shown to predict social com-
petence in children (Baron-Cohen, 2000; Capage & Watson, 2001; Dunn & Hughes, 2001; Razza, 2005;
Tager-Flusberg, 2003; Watson, Nixon, Wilson, & Capage, 1999), which in turn is related to success in
school (Welsh et al., 2001) and life (Salovey & Mayer, 1990). Preschool performance on the central
theory of mind task, the false belief task, also predicts math and reading performance in kindergarten
(Blair & Razza, 2007).
1.4.3. Social problem solving
Children with better social problem solving skills are both more socially competent (Pettit, Dodge, &
Brown, 1988) and better-liked by their peers (Erwin, 1993; Rubin & Daniels-Beirness, 1983). Children
with more social competence also do better in school (Ladd, Birch, & Buhs, 1999; Malecki & Elliott,
2002; Welsh et al., 2001). These three abilities and three academic abilities were examined in this study.
1.5. Study overview and hypotheses
The research conducted here was designed to address two main questions. First, do preschool chil-
dren's school readiness skills change from fall to spring as a function of program type (Classic Montessori,
Supplemented Montessori, or Conventional)? Second, within Montessori programs, does the percentage
of children using Montessori materials in a classroom predict children's school readiness skills in the
spring, after controlling for fall skill levels? We hypothesized that the gains of children in Classic Montes-
sori programs would exceed those of children in Conventional programs for the outcomes tested, mainly
because of an earlier study (Lillard & Else-Quest, 2006). In that study, low-income children in a public
school implementing a classic Montessori program were compared with children who had lost the lottery
for that Montessori program and were instead enrolled in other programs ranging from typical Nth Street
Elementary to high caliber conventional language immersion schools (Lillard & Else-Quest, 2006).
383A.S. Lillard / Journal of School Psychology 50 (2012) 379–401
Author's personal copy
Significant differences were seen for all but one of the outcomes measured here (i.e., vocabulary), al-
though different tasks were used to measure some constructs. The Lillard and Else-Quest (2006) study
was able to use randomization to control for possible selection effects, but it concerned a different popu-
lation. Also, based on the existing research, we expected children in Classic Montessori programs would
outperform children in Supplemented Montessori programs, although we know of no direct comparisons
of children in these different types of Montessori program. In addition, because of past research, we hy-
pothesized that Supplemented Montessori programs would not be associated with better performance
than Conventional programs.
2. Method
2.1. Participants
One hundred seventy-two children ranging in age from 33 to 76 months at the fall test date partici-
pated. Table 1 shows demographic information by program type. According to the heads of schools, vir-
tually all of the children attending Montessori programs entered their present classroom at age 3, and
those attending the conventional programs entered the program at age 3 but changed classrooms in
the fall after they turned 4 because the conventional programs divided classrooms by 3- to 4-year-olds
and 4- to 6-year-olds.
Maternal education, reported for 98% of the sample, ranged from 4.45 to 4.73, with “4”indicating com-
pleting a 4-year college degree, and “5”indicating some graduate education. Over 90% of children were
White, reflecting the composition of the communities in which the schools were located; 5% were African
American, 3% were Asian, 1% were Hispanic, and 1% were of other races and ethnicities. All children were
fluent in English.
2.2. Settings and teachers
2.2.1. Program type
Classrooms associated with three program types were targeted in this study. All three types of pro-
grams offered 3-hour sessions for 3- and 4-year-olds and 6- to 7-hour sessions for 5-year-olds. Classic
and Supplemented Montessori classrooms shared many features that are discussed first, followed by the
ways in which they diverged.
2.2.1.1. Montessori (including Classic Montessori). All 12 Montessori classrooms adhered to Montessori phi-
losophy in important ways: they all employed a 3-year age grouping which aligned Dr. Montessori's devel-
opmental stages (ages 3 to 6), none used extrinsic reward programs (like gold stars), and the teachers
gave mainly small group and individual lessons. All of the Montessori classrooms had four to five group
tables seating four to six children, four to five tables that seated only one child, and a circle taped on
Table 1
Demographic features of children and programs.
Variable Program type
Classic Montessori Supplemented Montessori Conventional
Number of classrooms 3 9 6 (3 at each age)
N(girls) 36 (22) 95 (47) 41 (26)
Average age of children in months (SDs) 55.6 (10.27) 54.01 (10.84) 59.17 (8.43)
Number of children at ages 3, 4, and 5+ 9, 15, 12 28, 40, 27 2, 21, 18
Maternal education 4.58 (0.55) 4.61 (0.66) 4.73 (0.51)
Percent White 85 92 95
Average years teacher has taught 2.0 (range 1–3) 8.3 (range 1–30) 7.7 (range 5–12)
Average proportion (and SD) of children engaged
in Montessori work across snapshots
.98 (.03) .48 (.17) NA
384 A.S. Lillard / Journal of School Psychology 50 (2012) 379–401
Author's personal copy
the floor for circle time. Low shelves were placed around the room and had materials organized into the
Montessori curriculum areas. The Montessori classrooms all had 2 to 3 hours of dedicated work time in
the mornings, during which children freely chose work off the shelves, and some outdoor time midday.
Snacks in all the Montessori classrooms were available to children to take individually when they wanted.
In all the Montessori classrooms, there was some whole class circle time, during which teachers read, con-
versed with students, and gave whole-class lessons in Grace and Courtesy (a part of the Montessori cur-
riculum). Older children in all the Montessori classrooms stayed for lunch and another 2- to 3-hour
work period in the afternoon. Classic Montessori classrooms as well as Supplemented Montessori class-
rooms shared these features.
2.2.1.2. Supplemented Montessori implementations. Classrooms targeted as implementing Supplemented
Montessori differed from those targeted as implementing Classic Montessori in three key ways. First, in
addition to offering many of the classic Montessori materials, they also offered conventional preschool
materials, like craft projects, beads, puzzles, workbooks, commercial games like Memory, and commercial
materials like LEGOs, on classroom shelves. Second, once or twice a week, the morning work period was
interrupted for specials, such as 30-minute music or Spanish lessons. Third, a second adult was involved
with the children as the main teacher. In contrast, in the Classic Montessori classrooms, a second adult ob-
served the children but rarely interacted with them.
2.2.1.3. Conventional. In the conventional classrooms, there were areas set up for pretend play (e.g., sup-
plying dress-ups and a toy kitchens) and reading (supplying books and pillows), and shelves of typical
preschool materials, like blocks, LEGOs, beads, and puzzles. Each classroom had five or six tables seating
4 to 6 children and a circle on the floor for circle time. Art supplies were also present, including paints,
crayons, markers, and playdough. Children in both programs also had workbooks for math and language.
In both conventional schools the day was organized in a mix of lessons, specials, outside time, circle
time, snack and lunch time, and free play time in the classroom, reflecting the array of activities typically
seen in American preschools (Hamre & Pianta, 2007). In lessons, which took a total of about 60 minutes
each morning, children sat with the teacher (sometimes as a whole class and other times in small
groups) while they discussed, for example, days of the week and different letters and their sounds and
practiced counting and elementary math. The daily schedule of lessons was structured in one school pro-
gram (e.g., 30 minutes of reading daily, 20 minutes of math daily, and 20 minutes of Science on Wednes-
days and History on Thursday) and more variable in the other. Specials involved children going out of
the class for art, music, and Spanish. Outside time was usually free play outside, but occasionally teachers
organized games like tag. Snack time involved children sitting at group tables and being served a snack.
During free playtime in the classroom, about 90 minutes in the morning at each school, children were
able to choose their own activities. Like most conventional preschools (Mashburn et al., 2008), these
two did not subscribe to any particular named curriculum, like High/Scope (Epstein, 2006), but had
put together their own. None of the Conventional classrooms had any Montessori materials. In both con-
ventional programs, ages were stratified, with 3- to 4-year-olds in one classroom and 4- to 6-year-olds in
another.
2.2.2. Teachers
All of the teachers were White women. Teachers at the Classic Montessori school were in their 1st to
3rd years of teaching, teachers at the Supplemented Montessori schools were in their 1st to 30th years,
and those at the Conventional schools were in their 5th to 12th years. Prior research has shown that
teacher experience has no effects or at most modest effects on student outcomes (Greenwald, Hedges,
& Laine, 1996; McDonald Connor, Son, Hindman, & Morrison, 2005; NECCRN, 2002), so teacher experi-
ence was not expected to be important, but analyses were conducted to verify this in the current
study. All the Montessori teachers had been certified by a Montessori organization and had college de-
grees; all but one of the conventional teachers had a college degree. Teachers at the Classic Montessori
had all completed AMI training courses; 6 of the teachers at the Supplemented Montessori had AMS
training and 3 had AMI training. Every teacher had an assistant. Teacher education as indicated by col-
lege degrees has not been associated with child outcomes (Early et al., 2007), and thus, was not included
in analyses for this study.
385A.S. Lillard / Journal of School Psychology 50 (2012) 379–401
Author's personal copy
2.3. Measures
2.3.1. Executive function (EF): The Head-Toes-Knees-Shoulders task
The Head-Toes-Knees-Shoulders (HTKS) task (Ponitz et al., 2008) asks that children carry out an op-
posing response, for example touching their toes when asked to touch their head. It is thought to involve
several components of executive function: working memory to keep rules in mind, attention to tester in-
structions, planning to execute the action, and inhibitory control to avoid the prepotent response. The
HTKS task predicts kindergarten achievement and is significantly related to parent and teacher reports
of inhibitory control and behavior regulation in preschool populations (McClelland et al., 2007; Ponitz,
McClelland, Matthews, & Morrison, 2009; Ponitz et al., 2008). Six-month test–retest correlation coeffi-
cients are over .55 for kindergarteners (Ponitz et al., 2008). Scoring reliability for this measure has been
demonstrated in prior studies (Ponitz et al., 2009, as cited in Ponitz et al., 2008).
To conduct this task, the experimenter taught the child a rule: “If I say to touch your head, I want you to
touch your toes, and if I say to touch your toes, I want you to touch your head.”After training, the child was
given 10 such commands in a fixed order with no command repeated more than twice in succession. Chil-
dren were scored 2 if they immediately followed the opposite instruction, and 1 if they did so after a quick
touch of the wrong location. If children scored at least 10 (of a possible 20) on the first 10 commands, a
second rule was added: “When I say to touch your knees, you touch your shoulders, and when I say to
touch your shoulders, you touch your knees.”After training on this command, children were given 10 ad-
ditional trials involving all four commands, for a final score of 0 to 40.
In addition to HTKS, the choice modification of the classic delay of gratification task, in which children
chose whether to have one desirable item (i.e., stickers and wind-up toys) immediately or have three later,
was also used to assess inhibitory control (Mischel et al., 1989). Subsequent literature review of this task
revealed that even when nine such trials are used, it is unrelated to other tests of inhibitory control
(Hongwanishikul, Happeny, Lee, & Zelazo, 2005), so it is not discussed further (see also Schwarz,
Schrager, & Lyons, 1983; Toner, Holstein, & Hetherington, 1977).
2.3.2. Theory of mind
Theory of mind was assessed in this study using the Theory of Mind Scale (Wellman & Liu, 2004), a set
of tasks that 90% of American children come to pass in a particular order as indicated by Guttman scaling
and Rasch analysis (Wellman, Fang, & Peterson, 2011), and which has been widely adopted and validated
in a range of populations, including Chinese children (Wellman, Fang, Liu, Zhu, & Liu, 2006), German chil-
dren (Aschersleben, Hofer, & Jovanovic, 2008), deaf children (Peterson & Wellman, 2009), and children
with specific language impairment (Farrant, Fletcher, & Maybery, 2006). Because of the ages of children
in this study, we used the 3 most difficult items on the 5-item scale: Perceptual Access (which data
from 280 American and Australian children suggest is passed at age 4.45), False Belief (which the average
American child passes at age 4.77), and Hidden Emotion (which the average American child passes at age
5.15; ages taken from Wellman et al., 2011). Others have presented these tasks in a variety of orders, al-
though Hidden Emotion is typically last. In this study, to minimize testing time, the False Belief task was
always presented first, Hidden Emotion was presented only if a child passed False Belief, and Perceptual
Access was presented only if a child failed False Belief. Although data is not available for all three of
these tasks across the ages studied here, the 4-week test–retest correlation coefficient for 5-year-olds
on a set of similar false belief tasks was r= .77 (Hughes et al., 2000). Materials for this task were 4 dolls
3 to 4 inches high, a doll-sized side table with a drawer containing a small shell, a BandAid box containing
a pencil, a small super-ball, and a placard showing a sad, neutral, and happy face.
First, children were given the False Belief task, in which they were shown the BandAid box and asked if
they knew what was inside. Children almost always guessed the typical contents; if not, they were
prompted (“What's usually in this box?”) and then guessed correctly. The box was opened, revealing
the content, and the experimenter commented, “Ha! Look at that! There's actually a pencil in there!”
The box was closed, and a doll was brought out. The experimenter added, “Peter has never seen inside
this BandAid box. Now here comes Peter. So, what does Peter think is in the box? BandAids or a pencil?
[Target question]. Did Peter see inside this box? [Memory question]”Children who answered both ques-
tions correctly were given two points and moved up to the Hidden Emotion task. Children who answered
either question incorrectly received 0 points and moved down to the Perceptual Access task.
386 A.S. Lillard / Journal of School Psychology 50 (2012) 379–401
Author's personal copy
For the Perceptual Access task, a nondescript wooden chest with a closed drawer containing a small
shell was brought out, and children were asked, “What do you think is inside the drawer?”Regardless
of what children guessed, the experimenter said, “Let's see,”and opened the drawer. “There's really a
shell inside!”She closed the drawer and asked, “Okay, what is in the drawer?”as a memory check, and
then produced a doll. “This is Polly. Polly has never seen inside this drawer. Now here comes Polly. Does
Polly know what is in the drawer? Did Polly see inside the drawer?”Children who answered “no”to
both questions were scored 1; otherwise the score was 0.
Children who passed the False Belief task, and thus were very likely to understand the Perceptual Ac-
cess task, went on to the Hidden Emotion task after False Belief. For Hidden Emotion, first children were
shown the sheet with happy, neutral, and sad faces on it, and were asked to point to the sad and happy
faces. Then they were shown the first doll, and the experimenter said, “This is Joey. Today is Joey's birth-
day. He really wants a bicycle for his birthday, and he thinks his uncle is going to give him a bicycle.”Then
the second doll was produced. “This is Joey's uncle. His uncle is coming to give him his birthday present.
Look, his uncle is giving him a ball for his birthday.”The sheet of faces was presented again, and children
were asked, “Which picture shows how Joey really feels when he gets the ball?”and then, “Which picture
shows what Joey's face will look like when he gets the ball?”A correct response was to point to the sad face
for how Joey really feels, and the happy one for what his face looks like. A point for being correct on this
task was added to the 2 points acquired for being correct on False Belief (because it was assumed that such
a child would also be correct on Perceptual Access), and so a child who passed Hidden Emotion received a
total of 3 points for the Theory of Mind scale.
2.3.3. Social problem solving
An object acquisition story from the Social Problem Solving Task (Rubin, 1988), one of the tasks used to
assess social competence in the NICHD's seminal study of early child care (see also Spivak & Shure, 1974),
was also used here. Children's performance on this task in kindergarten has been related to sociometric
status in first grade (Rubin & Daniels-Beirness, 1983) and to teacher ratings of social skills (Rubin &
Clark, 1983). A prior study had found that children responded similarly on each of three stories, so only
one story was used here (Lillard & Else-Quest, 2006). For this task, children were shown a picture of
two children of their same race and gender and told the children were their same age. One of the children
in the picture was reading and the other looking on. Children were told, “(Reader) has been looking at this
book for a long time and (Onlooker) really wants to look at the book. What could (Onlooker) do or say so
he/she could have a look at the book?”Children's responses were recorded by hand, and then children
were asked, “What else could he/she do or say?”and finally, “What if it was you? What could you do or
say so you could have a look at the book?”
We did not use the standard method for scoring children's responses. Instead, based on prior research,
we coded the number of references to sharing or fairness (for example, references to how they might trade
items or how the reader had had 10 minutes with the book and now could the other person have 10 mi-
nutes). Three undergraduate coders were trained to recognize such responses by rating at least 60 re-
sponses collected in other studies until their level of agreement with coding of the author was over
90%; then they went on to code the responses collected in this study, with two coders and the author cod-
ing every response. Inter-rater reliability, both between the two undergraduate coders and for each coder
with the author, was very high (r> or=.95 on 100% of children's responses), and differences were re-
solved by discussion. The number of sharing and fairness or justice strategies children used among their
three responses was summed for a score ranging from 0 to 3.
2.3.4. Reading, vocabulary, and math
Reading, vocabulary, and math were assessed with Form A of the Woodcock-Johnson III (Woodcock,
McGrew, & Mather, 2001; hereafter WJ III). All three WJ III tasks were administered and scored according
to the manual with one exception. Because at some of the Montessori schools children first learned cursive
letters rather than print, at those schools the initial WJ III testing book pages (the letter identification
items) were overlaid with cursive letters. This adaptation has been used in other research (Lillard &
Else-Quest, 2006). Scores from all tasks were raw scores.
Reading was assessed with the Letter-Word Identification task in which one has to identify letters and
increasingly difficult words. The manual reports a one-year test–retest reliability coefficient of .92 for
387A.S. Lillard / Journal of School Psychology 50 (2012) 379–401
Author's personal copy
children ages 4–7; split-half reliability coefficients are .97, .98, and .99 for 3-, 4-, and 5-year-olds, respec-
tively. Vocabulary was assessed with the Picture Vocabulary task (McGrew & Woodcock, 2001), which has
children identify pictures. The manual does not report test-retest reliabilities for this task, but split-half re-
liability coefficients are .84, .81, and .76 for 3-, 4-, and 5-year-olds. Math achievement was examined via
the Applied Problems subtest. This task involves simple counting, addition, and subtraction, reading
clock faces, and reporting and calculating coin values. The manual reports a one-year test–retest reliability
coefficient of .92 for children ages 4–7, and split-half reliability coefficients of .92, .94, and .92 for 3-, 4-,
and 5-year-olds.
2.4. Procedure
Recruitment and other study procedures were approved by the university's internal review board.
2.4.1. Recruitment
Children were recruited from seven different schools, five Montessori and two Conventional. The Mon-
tessori schools were selected initially, and for convenience: their geographical locations made them easily
accessible for testing. All schools that were invited to participate (via a letter of invitation) elected to do so.
Letters were sent home to parents in all the classrooms serving 3- to 6-year-old children. The letter was
accompanied by informed consent and basic demographic information forms. Included on the latter
form for Montessori parents was the question, “If Montessori were not available, what school would
your child attend?”The two most commonly selected private schools were then approached for participa-
tion as Conventional programs, and both agreed to participate. About half of all recruited parents from all
schools consented.
2.4.2. Testing
Children were tested individually in a quiet area at their school. Five research assistants (3 undergrad-
uate and 2 postgraduate) were trained to test children. Task procedures were practised with at least three
children in the laboratory during piloting until the author was satisfied that the assistant was competent
to run the procedures in the schools.
Test sessions took 15–25 minutes. The experimenter engaged each child in a few minutes of casual con-
versation until the child seemed comfortable, then administered the tasks in a set order: Sticker Delay, The-
ory of Mind Scale, Reading, Wind-Up Delay, Math, HTKS, Social Problem-Solving, and Vocabulary.
2.4.3. Classification of the Montessori classrooms into programs
Although programs were chosen by a subjective judgment of implementation type (Classic or Supple-
mented), an objective measure was used for confirmation. To objectively classify the Montessori class-
rooms, four trained observers (two undergraduate and two post-graduate) conducted 5-minute
snapshot observations of material use in the classrooms. These observations were typically completed be-
tween 9:30 and 11 a.m., with the only stipulation being that it was not completed when children were en-
gaged in a whole class group activity. Three observers were trained to recognize classic Montessori
materials by studying the classic Montessori materials in catalogs; the fourth observer had AMI Primary
training so knew the materials. Observers entered the classroom during the morning work time twice dur-
ing the fall and twice during the spring and noted what every child in a classroom was doing by marking a
prepared list of common Montessori materials and some common supplemental activities. Observations
were conducted by starting on one side of the classroom and marking down each child's activity, then
moving towards the center and marking the activity of each child there, and then moving to the other
side. Sometimes children moved; each child was counted only once, at their first activity during the obser-
vation. Observers checked with the author after conducting an observation when they had seen a material
they did not recognize and its categorization was determined through discussion; the author consulted
with trained Montessori teachers on rare occasions when needed. Four snapshot observations were
made in each Montessori classroom, spread across the year.
Percentages of children present who were engaged in classic Montessori work were averaged across
snapshots for each classroom. Interrater reliability was obtained for 20% of observations by a second ob-
server, and agreement on the numbers of children engaged in broad categories of activities (i.e.,
388 A.S. Lillard / Journal of School Psychology 50 (2012) 379–401
Author's personal copy
Montessori, Supplemented, can't tell, and off-task) was highly reliable, kappa=.93. Note that in specifying
that a child was using a Montessori material, there was no allowance for whether a child was using the
material correctly. Incorrect use of the material could of course produce noise in the data, but training
all observers on correct usage of each piece of material was beyond the scope of this study.
3. Results
First, Montessori classrooms were classified according to the measure of fidelity (the proportion of
children using Montessori materials, averaged across the classroom observations). This step was followed
by unconditional Hierarchical Linear Modeling (HLM) to examine whether nesting by classroom was nec-
essary. Because it was not, ANOVAs determined whether programs differed on relevant demographic fac-
tors. Next, differences in fall scores were examined for the outcome variables of interest.
With these preliminary analyses in hand, the main research questions were addressed with analyses of
gains across the school year. Most of these analyses were done with ANOVAs (using SPSS Version 19),
which are appropriate for interval-scaled data. Two of the variables were less aligned with an interval
scale: Applied Problems and Theory of Mind. Applied Problems goes from simple addition to clock and
coin problems to word problems; there is no sense in which the amount of gain in ability required to
pass any two successive problems is the same in scale as the amount of gain required to pass some
other two problems. This applies to the Theory of Mind Scale as well: although children pass the tasks
in a consistent order, the developmental difference underlying a 0 to 1 gain on the scale might not be
equal in magnitude to the difference underlying a gain from 2 to 3. Because of this, for these two tasks
nonparametric analyses were also used (Siegel & Castellan, 1988). Finally, regression analyses were con-
ducted to determine whether within the set of all Montessori classrooms, the fidelity measure predicted
children's gains.
3.1. Preliminary analyses
3.1.1. A priori classroom differences
The unconditional HLM revealed intraclass correlations of less than .11 for all variables of interest, well
below the standard cut-off of .25 that would suggest nested modeling was needed (Guo, 2005).
3
Further,
classrooms were demographically matched with respect to key parent variables: ANOVAs indicated no
significant differences across the 18 classrooms either in parent education, F(17,167) =1.29, p=.20, or
family income, F(16,1240)=1.21, p=.27. Parent education is a particularly important predictor of child
outcomes (NECCRN, 2003) and its equivalence across samples is important.
3.1.2. Classroom classification
In three Montessori classrooms, the percentage of children using Montessori materials ranged from
95%–100%, and in the other nine Montessori classrooms, the range was 38–56%. A one-way ANOVA
showed that there were significant differences in the proportion of children using Montessori materials
across classrooms, F(11, 52)=9.57, pb.001, and follow-up Tukey's tests showed that all three classrooms
at one school differed significantly from every classroom at the other four schools (all psb.05), and none of
the classrooms at the other four schools differed significantly from each other (ps>.9). The percentage of
children using Montessori materials thus appeared to be a suitable objective measure by which to classify
Montessori programs as Classic or Supplemented.
3.1.3. Potentially confounding classroom variables
Preliminary analyses showed no correlation between years of teaching experience and children's gains
across the school year on any of the measures: more experienced teachers were not associated with chil-
dren showing more or less gain. In addition, within the Supplemented Montessori sample, t-tests showed
no significant relations between teacher training (AMI vs. AMS) and student outcomes. Thus, teacher
training alone was not a significant predictor variable.
3
Intraclass correlations for the classroom level were as follows: Letter-Word Identification, .05; Picture Vocabulary, b.001; Ap-
plied Problems, b.001; Social Problem Solving, b.001 Theory of Mind, .08; and Head Toes Knees Shoulders, .03.
389A.S. Lillard / Journal of School Psychology 50 (2012) 379–401
Author's personal copy
Table 2
Means (and SDs) in fall and spring and mean gains across program types.
Measures Program type
Classic Montessori Supplemented Montessori Conventional
Fall Spring Gain Fall Spring Gain Fall Spring Gain
Letter-Word Identification** 14.08 (8.28) 25.36 (13.38) 11.28 (7.97) 12.07 (10.39) 17.81 (12.83) 5.61 (5.09) 16.45 (9.07) 22.35 (12.10) 5.90 (5.07)
Picture Vocab** 16.50 (3.43) 19.00 (3.05) 2.92 (2.03) 17.18 (3.29) 18.19 (3.09) 0.95 (1.95) 19.00 (3.05) 20.13 (3.29) 1.08 (2.22)
Applied Problems
t
15.78 (4.49) 20.36 (4.36) 4.58 (3.12) 15.71 (4.92) 18.88 (5.48) 3.06 (2.97) 18.00 (3.7) 21.53 (4.79) 3.54 (2.39)
Head-Toes-Knees-Shoulders** 22.06 (14.34) 35.78 (4.70) 13.72 (11.42) 17.30 (13.86) 24.47 (12.27) 7.22 (10.99) 24.93 (11.78) 32.60 (8.21) 7.67 (7.95)
Social Problem Solving* .22 (.54) .56 (.94) .33 (1.01) .42 (.74) .43 (.75) .01 (.97) .35 (.86) .30 (.61) −.05 (.68)
Theory of Mind 1.50 (0.78) 1.89 (0.92) 0.39 (0.84) 1.25 (0.79) 1.47 (0.89) 0.22 (0.81) 1.63 (0.93) 1.75 (0.95) 0.13 (1.27)
Note. Differences in gains favoring Classic Montessori over one or both other types of program: *p=.05; **pb.02;
t
pb.05 by Kruskal–Wallis rank test.
390 A.S. Lillard / Journal of School Psychology 50 (2012) 379–401
Author's personal copy
An ANOVA revealed a significant difference in the ages of children across program types, F(2, 169) =
3.67, p=.03. Children in the Conventional programs were significantly older on average (59.2 months
at fall test) than children in the Supplemented Montessori programs (54.0 months), Tukey's HSD =5.16,
p=.02, so age was used as a covariate in linear analyses. There were no age differences between the Clas-
sic Montessori programs (55.6 months) and either of the other two types: Tukey's HSD was not significant
between Classic and Supplemented (p=.71) and between Classic and Conventional (p=.28). As shown in
Table 1, gender was distributed similarly across the three types of programs, χ
2
(2)=2.87, p=.24.
3.1.4. Fall scores
Only one variable was different across programs at the start of the study (see Table 2): Children attend-
ing Conventional programs had higher fall vocabulary scores: M=19.00, SD=3.05; the Supplemented
Montessori had the next highest, M=17.18, SD=3.29, and the Classic Montessori had the lowest,
M=16.50, SD=3.43, F(2, 169) = 4.50, p=.01, partial η
2
=.05. Simple Planned Contrasts (Rosenthal &
Rosnow, 1985) showed a significant difference of 1.8 (pb.01) between the Conventional and Classic Mon-
tessori programs. Because vocabulary score is highly correlated with intelligence scores (McGrew &
Woodcock, 2001), subsequent analyses included fall Picture Vocabulary scores as a covariate. The Sidak
procedure was used to control for Type I error in this and all Planned Contrasts reported here.
3.2. School-year gains
Analyses of covariance (controlling for fall age, fall score on that outcome, test interval, and fall Picture
Vocabulary score) revealed differences in school year gains by program type for four of the six outcome
variables. One-tailed significance levels were applied for tasks on which differences were found in a
prior study: Letter-Word, Applied Problems, and Social-Problem Solving (Lillard & Else-Quest, 2006).
3.2.1. Letter-Word Identification
Children in Classic Montessori programs gained an average of 11.28 points (SD =7.97), whereas chil-
dren in Supplemented Montessori programs gained an average of 5.61 points (SD = 5.09) and children
in Conventional programs gained an average of 5.90 points (SD=5.07) across the school year. These
gain scores were significantly different across programs, F(2, 168) =5.02, pb.01, partial η
2
=.06.
4
Simple
Planned Contrasts showed a significant difference between Classic Montessori and both other types of pro-
gram (difference=4.47, p=.002 between Classic and Supplemented Montessori, with a difference of
5.19, p=.006 between Classic Montessori and Conventional).
3.2.2. Picture Vocabulary
Children in Classic Montessori programs gained an average of 2.92 points (SD=2.03) in Picture Vocab-
ulary scores, children in Supplemented Montessori programs an average of 0.95 (SD = 1.95), and children
in Conventional programs an average of 1.08 (SD =2.22), F(2, 168)= 4.41, p=.01, partial η
2
=.05. Simple
Planned Contrasts showed a significant difference of 1.07, p= .04, between the Classic Montessori and
Supplemented Montessori programs. The Conventional programs did not differ from Classic Montessori.
3.2.3. Applied Problems
On the Applied Problems task, children in Classic Montessori programs gained an average of 4.58 points
(SD=3.12), children in Supplemented Montessori programs gained an average of 3.09 points (SD =2.98),
and children in Conventional programs gained an average of 3.53 points (SD=2.36). Because raw scores
on the Applied Problems task do not reflect an interval scale, the Kruskal–Wallis test was conducted, re-
vealing a significant difference (p=.02) whereby children in Classic Montessori programs gained more
in scores over the year than the children in Supplemented Montessori programs, Mann–Whitney
U=1220, p=.01.
4
Effect sizes for partial η
2
are interpreted as follows: small =0.01, medium = 0.06, and large =0.14 (Kittler, Menard, & Phillips,
2007; see also Cohen, 1988; Olejnik & Algina, 2000).
391A.S. Lillard / Journal of School Psychology 50 (2012) 379–401
Author's personal copy
3.2.4. Head-Toes-Knees-Shoulders
Children in Classic Montessori programs gained an average of 13.72 points (SD =11.42), whereas chil-
dren in Supplemented Montessori programs gained on average 7.34 points (SD=10.92), and those in Con-
ventional programs 7.85 points, SD =7.85, F(2, 167)=18.12, pb.001, partial η
2
=.18. Simple Planned
Contrasts showed the significant differences were between the Classic Montessori and both the Supple-
mented Montessori (11.03, pb.001) and Conventional programs (7.60, p= .004).
3.2.5. Social problem solving
Children in the Classic Montessori programs increased references to sharing and justice by an average
of 0.33 points (SD =1.01), whereas children in the Supplemented Montessori programs did not change,
M=0.01, SD=0.96, and those in the Conventional programs declined in the number of such references,
M=−0.07, SD=0.69. The analysis indicated a small-medium effect size, F(2, 170)=2.30, p=.03, partial
η
2
=.03; Simple Planned Contrasts showed a significant difference between the Classic Montessori and the
Conventional programs (0.54, p=.04).
3.2.6. Theory of mind
Children in the Classic Montessori programs gained an average of 0.39 points (of a possible 3,
SD=0.84) on the Theory of Mind scale, children in Supplemented Montessori programs an average of
0.26 points (SD =0.84), and children in Conventional programs an average of 0.12 points (SD = 1.25).
These differences were not statistically significant.
3.3. Prediction of Montessori scores from fidelity
The third set of analyses examined whether the proportion of children in one's classroom who were
using Montessori materials at snapshots predicted spring scores, after taking children's fall scores and
Table 3
Stepwise regression on spring scores entering fall scores, inter-test interval, and proportion of children using Montessori materials.
Model 1 Model 2 Model 3
ΔR
2
b (SEb) βb (SE b) βb (SE b) β
Head-Toes-Knees-Shoulders spring score
Step 1 .39**
Fall score .53 (.06) .63** .51(.06) .60 .49(.06) .58
Step 2 .03*
Test interval 2.47 (1.02) .17* −1.62(1.44) −.11
Step 3 .06**
Montessori work 4.41 (1.15) .37**
Total R2 .48**
Letter-Word Identification spring score
Step 1 .78**
Fall score 1.21 (.06) .89** 1.22 (.05) .89** 1.19 (.05) .87**
Step 2 .02**
Test interval 2.48(.65) .15 .43(.96) .03
Step 3 .01**
Montessori work 2.19(.76) .16**
Total R2 .82**
Picture Vocabulary spring score
Step 1 .61**
Fall score .78(.05) .78** .80 (.05) .81** .80 (.05) .81**
Step 2 .06**
Test interval 1.04(.21) .25** .45(.32) .11
Step 3 .02*
Montessori work .61(.25) .19*
Total R2 .69**
*pb.05 **; pb.01.
392 A.S. Lillard / Journal of School Psychology 50 (2012) 379–401
Author's personal copy
inter-test interval into account. The proportion of children using Montessori materials was entered into
the regression at the third step, with fall score at the first step, and inter-test interval at the second
step. These analyses showed that degree of materials usage within Montessori classrooms was a signifi-
cant predictor for three of the six outcome variables: Head-Toes-Knees-Shoulders, Letter-Word Identifica-
tion, and Picture Vocabulary (see Table 3). Thus, even within the set of Montessori programs, the more
children in one's class engaged in Montessori work, the more one gained over the school year on these
three variables.
4. Discussion
Although Montessori is a fairly common alternative form of schooling, there is little research on its out-
comes, and what research exists is inconsistent. This study sought to examine whether different child out-
comes are associated with differences in implementation fidelity. Across a variety of outcomes, children
attending Classic Montessori programs gained significantly more across the school year than did demo-
graphically similar children in Supplemented Montessori programs and Conventional programs in schools
that their parents said they would enroll the children in were Montessori programs unavailable. Impor-
tantly, at the beginning of the school year, there was no advantage for children in Classic Montessori pro-
grams, suggesting that unobserved selection effects are not at play. The larger gains were accrued on
outcomes ranging from executive function and social problem-solving to common academic achievement
measures. These findings are important because early advantages in these areas predict success in school
and social relations (Baron-Cohen, 2000; Mischel et al., 1989; Pianta, La Paro, Payne, Cox, & Bradley, 2002;
Razza, 2005; Watson et al., 1999). In addition, among the Montessori programs, the percentage of children
in each classroom using Montessori materials predicted executive function, early reading, and vocabulary.
For the other variables, this measure of fidelity was not predictive. Closer examination of what children
were doing in each classroom might be necessary to determine why these variables and not the others
were predicted by the measure.
From this study, Montessori education appears to reflect a pattern noted in the fidelity of implementa-
tion literature. In this literature, programs last to the degree that they are flexible and adaptive (Goodman
& Steckler, 1989). Montessori has significant representation in America after 100 years, whereas many
other alternative school programs that existed 100 years ago are no longer very visible—for example,
one rarely sees Froebel or Pestalozzi or Dewey or Dalton Plan schools today (Beatty, 1995; Cunningham
& Duffy, 1996; Edwards, 1991). American Montessori education's very adaptability, including openness
to supplementary materials, might be key to its endurance. On the other hand, the fidelity of implemen-
tation literature also shows that lower fidelity is associated with less positive outcomes (O'Donnell,
2008), and this study indicates this might also be the case for Montessori. It is ironic that the very element
that might enhance survival of a program might also reduce its effectiveness, although it is important to
note that the supplemented Montessori programs were generally on a par with the highly regarded con-
ventional comparison programs studied here. In the section that follows, I discuss each result in turn, ex-
amining some elements of the Classic Montessori program that I hypothesize might have contributed.
4.1. Executive function
The most notable result in this study was the school-year gain in executive function observed in chil-
dren in the Classic Montessori program. In prior studies, children in this age range in conventional public
preschool programs gained about 2 to 5 points on this task over a school year (Ponitz et al., 2008, 2009),
whereas children in the private Supplemented and Conventional programs in this study gained 7 to
8 points. By contrast, children in the Classic Montessori program gained almost 14 points, and the statis-
tical tests indicated a large effect size (Cohen, 1988). This gain in executive function is of practical impor-
tance, because children with stronger executive function skills in kindergarten are concurrently and
subsequently more academically (Blair & Razza, 2007; Bull et al., 2008) and socially competent (Riggs et
al., 2006). Increasingly executive function skills are seen as key not only to school readiness but to success
in life (Blair, 2002; Diamond & Lee, 2011).
Theoretically, using Montessori materials would seem to exercise many aspects of executive function.
For example, one of the first Montessori materials with which a child is presented is the Pink Tower, a set
393A.S. Lillard / Journal of School Psychology 50 (2012) 379–401
Author's personal copy
of 10 wooden pink blocks ranging in size from a 1-cm cube to a 10-cm cube, with each cube 1-cm larger on
each face than the previous one. In using this material, the children's task is to carry the cubes one by one
from a display to a rug that they have previously rolled out on the floor, then rebuild the tower. To do this
task entails planning. Second, each time a child chooses a block, she or he must do so with reference to its
relation to all the other blocks: Is there another one in between the size of this one and the last one placed
on the tower? This step requires working memory. Third, the child must inhibit the prepotent tendency to
grab the closest block, and fourth, the child must pay strict attention to how he or she places each block on
the one below it, creating a symmetrical tower. After building the tower, the child takes it down, returns
the blocks to their stand by the shelves (in the proper order), and then tightly rolls up the rug and returns
it to its place. This step requires flexibility and task switching. Consider the difference between this and
engaging with ordinary blocks. With ordinary blocks, one can do anything, without necessarily having
any set plan, and one does not have to think about the blocks in relationship to each other. A preschool
might not have a requirement that children put items away right after use (instead, there often is a single
clean-up time right before going home), and there may well be no set way to arrange blocks when return-
ing them to their place (often, they get put haphazardly into a large basket or box). The executive function
demands are much reduced, and this difference in executive function demands applies across many other
activities as well.
4.2. Reading and vocabulary
Children in the Classic Montessori programs also gained the most in early reading and vocabulary, with
effect sizes of .05 and .06. Although not nearly as large as the effect size for executive function, these are
considered medium effect sizes (Cohen, 1988). In raw terms, the gains in Letter-Word Identification scores
for the children in Classic Montessori programs were twice what they were for the other two groups (11
vs. 5–6). The latter gains just exceeded those seen in a large scale public prekindergarten study in Oklaho-
ma (Gormley, Gayer, Phillips, & Dawson, 2005), in which the gain of about 5 points rendered a large effect
size of .80 compared to no preschool. Thus, it seems that the score gain seen in children in Classic Montes-
sori programs, which was twice that, is certainly meaningful. Early gains of this magnitude would be
expected to have lasting benefits to children and society (Camilli, Vargas, Ryan, & Barnett, 2010; Pianta,
Barnett, Burchinal, & Thornburg, 2009).
One possible reason for the gains in Letter-Word Identification is the materials used to teach writing
and reading in Montessori programs, and the fact that the children were using those materials more
often in Classic than in Supplemented programs. The conventional school programs in this study taught
reading by teaching children to identify letters and words at circle time; they also provided plentiful liter-
acy materials (e.g., magnetic letters, books, and writing workbooks, the latter of which were also available
in Supplemented programs). Montessori reading instruction begins by having children trace sandpaper
letters with their index finger while reciting the phonetic sounds, and then also putting words together
with a cardboard Moveable Alphabet; these materials are used before children learn to read. The phonetic
approach to reading is well-supported (Rayner, Foorman, Perfetti, Pesetsky, & Seidenberg, 2001). Haptics
or using the hand to trace letters has been much less studied, but findings from embodied cognition would
suggest it would be helpful (see Lillard, 2005), and at least one study finds tracing letters improves their
learning (Bara, Gentaz, & Cole, 2007). For Picture Vocabulary, emphasis on nomenclature in Montessori
might play a role. Programs with abundant supplementary materials would have fewer children engaged
in the Montessori nomenclature exercises (for example, creating labels and placing them besides the ob-
jects they name).
4.3. Social problem-solving
Children in Classic Montessori programs showed larger gains in using more mature social problem
solving strategies, particularly ones centering on justice and taking another person's goals into consider-
ation. For example, children in Classic Montessori programs were more likely to offer object acquisition
strategies like, “Can I please look at that book while you are looking at another book you might want to
look at?”and “Maybe we could each have turns for 10 minutes?”One possible reason why children in
Classic Montessori programs might show greater school-year gains in the use of these strategies is the
394 A.S. Lillard / Journal of School Psychology 50 (2012) 379–401
Author's personal copy
provision of only one set of each Montessori material, which might create frequent needs to consider how
to resolve conflicts over limited resources. Social competence in preschool is associated with better out-
comes in social and academic domains (Capage & Watson, 2001; Ladd et al., 1999; Malecki & Elliott,
2002; Welsh et al., 2001), and thus this finding seems to be of practical significance.
4.4. Theory of mind
One domain in which gains were not significant was Theory of Mind. This is interesting in part because
theory of mind is related to executive function (Carlson, Moses, & Claxton, 2004), so much so that some
consider it an executive function task (Blair & Razza, 2007), and performances on both types of task (a
similar Executive Function task and False Belief) were higher in Montessori children in the low-income
lottery study (Lillard & Else-Quest, 2006). For these middle-income children, program type made no dif-
ference in performance on Theory of Mind tasks.
4.5. Math
The Applied Problems task showed significant program differences with a nonparametric rank test, ap-
propriate because score intervals for this task are not uniform. The extent and sophistication of the Montes-
sori math materials might be expected to result in differences, and they have been found in prior research
(Dohrmann et al., 2007; Lillard & Else-Quest, 2006). A consideration for why only the rank test revealed dif-
ferences concerns the Applied Problems task itself. For children in Conventional and in Classic Montessori
programs, the spring scores averaged 20 to 21 points. At a score of 19, the Applied Problems task presents
its first clock face, and at item 24, it begins to present pictures of coins. If a child has not had a specific lesson
on decoding these cultural artifacts, the child will not pass these items no matter how adequate the child's
basic math skills. In between these items, Applied Problems embarks on word problems with extraneous
information: a child must know what to ignore. This ignoring of extraneous information is a sophisticated
skill that could well stump young children who have not specifically been taught that adults sometimes
give problems with extraneous information. A second concern with the Applied Problems task is that its
early problems assess superficial computation, and although the Montessori program was associated
with better simple computation skills in low-income populations, more conceptual tasks might be needed
to reveal differences at higher levels of the task, such as were achieved in middle-income samples here.
4.6. Fall scores
Looking across the data set generally, the equality of fall scores is puzzling. If Classic Montessori does
produce more school-year gains, one might expect 4- and 5-year-old children, in their second and third
years in these programs, to be different at the fall test as well. We see three possibilities. First, the scores
of children in Classic Montessori programs were higher in the fall than those of children in other programs,
but when combined with the scores of the 3-year-old children, the averages are not different. Unfortu-
nately, the sample sizes for some narrow age groups were too small to render meaningful statistical re-
sults, but children in Classic Montessori programs scored slightly higher on Letter-Word Identification
and Head-Toes-Knees-Shoulders at 4 and 5 but not at 3 years of age. A second possibility is that the
older children's scores really are equal in the fall, implying that school-year gains are not sustained over
summer vacation. A meta-analysis of studies of the impact of summer vacation on achievement test scores
found that at least older students (4th to 9th graders) generally lose about a month's portion of their
school-year gain score over the summer, although middle-income children do not show a loss in reading
scores (Cooper, Nye, Charlton, Lindsay, & Greathouse, 1996). A third but related possibility that would ex-
plain equal means at older ages, but only in this study, stems from fall test date: by necessity children in
the Classic Montessori were tested earlier in the school year than children in the other programs. This po-
tential confound was controlled for statistically in terms of its possible impact on gain scores, but it might
have masked fall differences in the older groups if being less well adjusted to school after summer vacation
leads to lower scores. Further research could address this by including larger numbers of children at each
age level so each age level can be examined separately, and by testing the same children at the end of one
school year and then repeatedly at the same time for the first few months of the next school year to see
395A.S. Lillard / Journal of School Psychology 50 (2012) 379–401
Author's personal copy
whether there is a difference in summer reversion for children at different age levels in different types of
school program. Regardless, in this study differences in gains across programs were observed, taking fall
scores and test–retest interval into account.
4.7. Implications
These results are important for parents considering school choices, especially since Montessori educa-
tion is increasingly offered in public school districts. Although Montessori education is growing, there is a
paucity of research on its outcomes (Walsh & Petty, 2007), and what exists is contradictory. These results
suggest a source of the inconsistencies could be implementation, indexed here by use of Montessori ma-
terials. These results could also spur research promoting better understanding of children's development
in educational settings, because they suggest that some elements of classic Montessori preschool pro-
grams are particularly helpful to development. Whereas Classic Montessori was associated with larger
gains than were seen in either Supplemented Montessori or Conventional programs, it still could be the
case that even some Conventional programs could be improved by incorporating certain Montessori-
like practices, such as use of haptic materials for early reading (rather than workbooks) and more
executive-function-taxing activities. Exactly what those elements would be is a topic for further research.
This research also has important implications for teacher training. Implementing a program to a high
standard of fidelity requires deep understanding of that program, which can take months or even years
of study depending on the depth and complexity of the system. Teachers who fully understand the mate-
rials offered in a given program that supplies a broad, inclusive, and intertwined set, as does Montessori,
should be less inclined to try to supplement those materials with others that do not fit into the set.
Teachers who take less intensive and more superficial training courses might be more inclined to supple-
ment materials, possibly resulting in less effective classrooms.
Finally, this research connects with a recent emphasis in school psychology on what is termed the 3-
tiered model of intervention, where the top tier is individualized instruction for individual students, the
middle is interventions for groups of students with special needs, and the bottom or universal tier is for stu-
dents generally (Tilly, 2008). This research is aimed at that universal tier, examining the core curriculum of
Montessori education and its impact on child outcomes, both academic and social-behavioral. Research like
this across a variety of educational programs, from Steiner to Responsive Classrooms, looking at how uni-
versal instruction and the integrity of an individual program is related to child outcomes, is important as
schooling practices become increasingly evidence-based. This research makes one contribution to this base.
4.8. Limitations
A significant weakness of this study is lack of random assignment to program. Several analyses were
done to mitigate this concern: the conventional schools were selected as ones that parents who chose
Montessori education would also have chosen; analyses showed no differences in parent education or in-
come across classrooms; neither teacher experience nor type of Montessori teacher training was associat-
ed with child outcomes; and there were no differences in children's scores in the fall except on Picture
Vocabulary, and this difference favored the Conventional programs and was subsequently used as a covar-
iate. Despite these efforts, nonrandom designs cannot rule out third variables. Perhaps particular parents
are more attracted to classic Montessori. Parents are known to have tremendous influence on child out-
comes (NECCRN, 2004; Shonkoff & Phillips, 2000), and for obvious reasons: they confer genes to their chil-
dren, provide the home environment where most children spend most of their time, select neighborhoods,
and pick schools. The ultimate test for whether parents are responsible for the differences between schools
programs found here would have children who were placed by lottery in these schools, as in Lillard and
Else-Quest (2006) that found a similar pattern of differences comparing low-income children. Further
studies using randomized controls are necessary to allow for causal conclusions.
A second limitation of this study is that we know little about what was actually happening in the class-
rooms that might have contributed to the results. Montessori classrooms were classified by the number of
children using Montessori materials, but this classification could simply be an indicator variable for other
differences that might have been more central contributors to children's outcomes. Further research must
examine what aspects of the classic program are important to children's gains. For example, it is possible
396 A.S. Lillard / Journal of School Psychology 50 (2012) 379–401
Author's personal copy
that teachers who choose not to bring supplementary materials into their classroom also interact with
children differently; other studies have shown that teacher interaction (particularly warmth and sensitiv-
ity, and asking thought-scaffolding questions) is a major factor in children's achievement (Hamre & Pianta,
2007; Mashburn et al., 2008). Further studies should expand classroom observations to include other fea-
tures like styles of teacher interaction that might go along with eschewing supplementary materials, and
which might be responsible for the larger gains seen here. An alternative but promising strategy would be
to randomly assign supplemented Montessori programs to retain or be stripped of their supplementary
materials and measure subsequent gains. A small pilot study did this, and found significantly larger
gains in the stripped classrooms in Letter-Word Identification and Head-Toes-Knees-Shoulders over just
4 months (Lillard, unpublished raw data), but sample sizes were small.
A third limitation is that the sample here was well-educated, middle- to high-income, and mostly
White, and one might argue that the findings are relevant only to this group. The Lillard and Else-Quest
(2006) study and the Dohrmann et al. (2007) study described in the Introduction showed benefits of clas-
sic Montessori for low-income children as well. Dohrmann et al. (2007) showed that children who had
previously gone to Milwaukee public Montessori schools, many of whom were on free lunch programs,
scored higher on math and science composite score in high school. Lillard and Else-Quest (2006) showed
that lower-income children who were randomly chosen to attend Montessori or went to other schools did
better on a range of academic and social measures at ages 5 and 12. This study even showed benefits on
many of the same outcomes as were observed in the middle-income children in the Classic Montessori
programs studied here. A final limitation is that this study included only children from 3 to 6 years of
age. The extent to which these early gains are carried over as children transfer into elementary school
and beyond is an important question for further research.
4.9. Conclusion
The research presented here suggests that Classic Montessori is associated with significant gains in stu-
dent achievement and development relative to Supplemented Montessori and highly regarded conven-
tional school programs. What aspects of the Classic Montessori programs might have been responsible
for the advantages is not clear; further research could shed light on this by randomly assigning supple-
mented programs to remove their additional materials and by more closely observing the micro level in-
teractions of teachers and students in such environments.
As early childhood educators search for ways to improve the academic and social outcomes of children
in American schools, Montessori education might be worthy of more consideration (Walsh & Petty, 2007).
But Classic Montessori is the rarer form; a recent survey of 85 public Montessori schools in the United States
(about a third of the total number) showed that only 28% of school heads strongly agreed with the state-
ment, “Our school implements elementary education according to the original vision of Maria Montessori”
(Murray & Peyton, 2009, p. 28). With any alternative educational program, fidelity is an important consid-
eration. Variations could in principle improve or demote program quality; the present research suggests
that a very common variation in Montessori programs, supplementing the core set of materials with
ones typically used in conventional preschool programs, or something associated with their use, can de-
mote it. School districts and parents considering Montessori education should be aware of these differences
in implementation and their possible effects. Montessori education appears to reflect a pattern in the fidel-
ity of implementation literature, whereby the very feature that might be responsible for its strong repre-
sentation 100 years after its development—its adaptability—might also compromise its effectiveness.
References
American Montessori Society (2009). School accreditation standards and criteria. Retrieved July 2, 2011, from. http://www.amshq.
org/School%20Resources/AMS%20%20School%20Accreditation.aspx
American Montessori Society (2011). AMS and the Montessori Movement: A new emphasis. Retrieved July 2, 2011, from. http://www.
amshq.org/Montessori%20Education/History%20of%20Montessori%20Education/
AMS%20and%20the%20Montessori%20Movement.aspx
Aschersleben, G., Hofer, T., & Jovanovic, B. (2008). The link between infant attention to goal-directed action and later theory of mind
abilities. Developmental Science,11(6), 862–868.
Bara, F., Gentaz, E., & Cole, P. (2007). Haptics in learning to read with children from low socio-economic status families. British Journal
of Developmental Psychology,25, 643–663.
397A.S. Lillard / Journal of School Psychology 50 (2012) 379–401
Author's personal copy
Baron-Cohen, S. (2000). Autism. In M. S. Gazzaniga (Ed.), The new cognitive neurosciences (pp. 1167–1270). (2nd ed.). Cambridge,
MA: MIT Press.
Beatty, B. (1995). Preschool education in America: The culture of young children from the colonial era to the present. New Haven, CT: Yale
University Press.
Besancon, M., & Lubart, T. (2008). Differences in the development of creative competencies in children schooled in diverse learning
environments. Learning and Individual Differences,18, 381–389, doi:10.1016/j.lindif.2007.11.009.
Blair, C. (2002). School readiness. American Psychologist,57, 111–127.
Blair, C., & Diamond, A. (2008). Biological processes in prevention and intervention: The promotion of self-regulation as a means of
preventing school failure. Development and Psychopathology,20, 899–911.
Blair, C., Knipe, J., Cummings, E., Baker, D. P., Gamson, D., Eslinger, P., et al. (2007). A developmental neuroscience approach to the
study of school readiness. In R. C. Pianta, M. J. Cox, & K. L. Snow (Eds.), School readiness and the transition to kindergarten
(pp. 149–174). Baltimore, MD: Brookes.
Blair, C., & Razza, R. P. (2007). Relating effortful control, executive function, and false belief understanding to emerging math and lit-
eracy ability in kindergarten. Child Development,78, 647–663.
Blakely, C. H., Mayer, J. P., Gottschalk, R. G., Schmitt, N., Davidson, W. S., Roitman, D. B., et al. (1987). The fidelity-adaptation debate:
Implications for the implementation of public sector social programs. American Journal of Community Psychology,15, 253–268.
Bronson, M. (2001). Self-regulation in early childhood: Nature and nurture. New York, NY: Guilford Press.
Bull, R., Espy, K. A., & Wiebe, S. A. (2008). Short-term memory, working memory, and executive functioning in preschoolers: Longi-
tudinal predictors of mathematical achievement at age 7 years. Developmental Neuropsychology,33, 205–228.
Camilli, G., Vargas, S., Ryan, S., & Barnett, W. S. (2010). Meta-analysis of the effects of early education interventions on cognitive and
social development. Teachers College Record,112, 579–620.
Capage, L., & Watson, A. C. (2001). Individual differences in theory of mind, aggressive behavior, and social skills in young children.
Early Education & Development,12, 613–628.
Carlson, S. M., Moses, L. J., & Claxton, L. J. (2004). Individual differences in executive functioning and theory of mind: An investigation
of inhibitory control and planning ability. Journal of Experimental Child Psychology,87, 299–319.
Carroll, C., Patterson, M., Wood, S., Booth, A., Rick, J., & Balain, S. (2007). A conceptual framework for implementation fidelity. Imple-
mentation Science,2,40–49.
Cohen, J. (1988). Statistical power for the behavioral sciences. Hillsdale, NJ: Erlbaum.
Cooper, H., Nye, B., Charlton, K., Lindsay, J., & Greathouse, S. (1996). The effects of summer vacation on achievement test scores: A
narrative and meta-analytic review. Review of Educational Research,66, 227–268.
Cossentino, J. (2005). Ritualizing expertise: A non-Montessorian view of the Montessori method. American Journal of Education,111,
211–244.
Cox, M. V., & Rowlands, A. (2000). The effect of three different educational approaches on children's drawing ability: Steiner, Mon-
tessori and traditional. British Journal of Educational Psychology,70, 485–503.
Cunningham, D., & Duffy, T. (1996). Constructivism: Implications for the design and delivery of instruction. In D. Jonassen (Ed.),
Handbook of research on educational communications and technology (pp. 170–198). New York: Simon & Schuster.
Diamond, A., Barnett, W. S., Thomas, J., & Munro, S. (2007). Preschool program improves cognitive control. Science,318, 1387–1388.
Diamond, A., & Lee, K. (2011). How can we help children succeed in the 21st century? What the scientific evidence shows aids ex-
ecutive function development in children 4–12 years of age. Science,333, 959–964.
Dohrmann, K. R., Nishida, T. K., Gartner, A., Lipsky, D. K., & Grimm, K. J. (2007). High school outcomes for students in a public Mon-
tessori program. Journal of Research in Childhood Education,22, 205–217.
Dowsett, S. M., & Livesey, D. J. (2000). The development of inhibitory control in preschool children: Effects of “executive skills”train-
ing. Developmental Psychobiology,36, 161–174.
Dunn, J., & Hughes, C. (2001). “I got some swords and you're dead”: Violent fantasy, antisocial behavior, friendship, and moral sen-
sibility in young children. Child Development,72, 491–505.
Durlak, J. A., & DuPre, E. P. (2008). Implementation matters: A review of research on the influence of implementation on program
outcomes and the factors affecting implementation. American Journal of Community Psychology,41, 327–350.
Early, D. M., Maxwell, K. L., Burchinal, M., Bender, R. H., Ebanks, C., Henry, G. T., et al. (2007). Teachers' education, classroom quality,
and young children's academic skills: Results from seven studies of preschool programs. Child Development,78, 558–580.
Edwards, J. (1991). To teach responsibility, bring back the Dalton plan. Phi Delta Kappan,72(5), 398–401.
Epstein, A. S. (2006). Essentials of active learning in preschool: Getting to know the High/Scope curriculum. Ypsilanti, MI: High/Scope Press.
Erwin, P. (1993). Social problem solving, social behavior, and children's peer popularity. The Journal of Psychology,128, 299–306.
Espy, K., McDiarmid, M., Cwik, M., Stalets, M., Hamby, A., & Senn, T. (2004). The contribution of executive functions to emergent
mathematic skills in preschool children. Developmental Neuropsychology,26, 465–486.
Farrant, B., Fletcher, J., & Maybery, M. (2006). Specific language impairment, theory of mind, and visual perspective taking: Evidence
for simulation theory and the developmental role of language. Child Development,77, 1842–1853.
Garon, N., Bryson, S., & Smith, I. (2008). Executive function in preschoolers: A review using an integrative framework. Psychological
Bulletin,134,31–60.
Glenberg, A. M., Jaworski, B., Rischal, M., & Levin, J. (2007). What brains are for: Action, meaning, and reading comprehension. In D. S.
McNamara (Ed.), Reading comprehension strategies: Theories, interventions, and technologies (pp. 221–240). Mahwah, NJ: Erlbaum.
Goodman, R. M., & Steckler, A. (1989). A model for the institutionalization of health promotion programs. Family & Community
Health,11,63–78.
Gormley, W. T., Gayer, T., Phillips, D., & Dawson, B. (2005). The effects of universal pre-K on cognitive development. Developmental
Psychology,41, 872–884.
Graue, E. (2006). The answer is readiness—Now what is the question? Early Education & Development,17,43–56.
Greenwald, R., Hedges, L., & Laine, R. (1996). The effect of school resources on student achievement. Review of Educational Research,
66, 361–396.
Guo, S. (2005). Analyzing grouped data with hierarchical linear modeling. Children and Youth Services Review,27, 637–652.
Hamre, B. K., & Pianta, R. C. (2007). Learning opportunities in preschool and early elementary classrooms. In R. C. Pianta, M. J. Cox, &
K. L. Snow (Eds.), School readiness and the transition to kindergarten (pp. 49–84). Baltimore, MD: Brookes.
398 A.S. Lillard / Journal of School Psychology 50 (2012) 379–401
Author's personal copy
Hojnoski, R. L., Margulies, A. S., Barry, A., Bose-Deakins, J., Sumara, K. M., & Harman, J. L. (2008). Analysis of two early childhood ed-
ucation settings: Classroom variables and peer verbal interaction. Journal of Research in Childhood Education,23, 193–209.
Hongwanishikul, D., Happeny, K. R., Lee, W. S. C., & Zelazo, P. D. (2005). Assessment of hot and cool executive function in young chil-
dren: Age-related changes and individual differences. Developmental Neuropsychology,28, 617–644.
Howes, C., Burchinal, M., Pianta, R., Bryant, D., Early, D., Clifford, R., et al. (2008). Ready to learn? Children's pre-academic achieve-
ment in pre-kindergarten programs. Early Childhood Research Quarterly,23,27–50.
Hughes, C. (1998). Executive function in preschoolers: Links with theory of mind and verbal ability. British Journal of Developmental
Psychology,16, 233–253.
Hughes, C., Adlam, A., Happe, F., Jackson, J., Taylor, A., & Caspi, A. (2000). Good test–retest reliability for standard and advanced false-
belief tasks across a wide range of abilities. Journal of Child Psychology and Psychiatry,41, 483–490.
Huizinga, M., Dolan, C. V., & van der Molen, M. W. (2006). Age-related change in executive function: Developmental trends and a
latent variable analysis. Neuropsychologia,44(11), 2017–2036.
Humphryes, J. (1998). The developmental appropriateness of high-quality Montessori programs. Young Children,53,4–16.
Karnes, M., Shewedel, A., & Williams, M. (1983). A comparison of five approaches for educating young children from low-income
homes. In Consortium for Longitudinal Studies (Ed.), As the twig is bent: lasting effects of preschool programs (pp. 133–171).
Hillsdale, NJ: Erlbaum.
Kendeou, P., van den Broek, P., White, M. J., & Lynch, J. S. (2009). Predicting reading comprehension in early elementary school: The
independent contributions of oral language and decoding skills. Journal of Educational Psychology,101, 765–778.
Kittler, J. E., Menard, W., & Phillips, K. A. (2007). Weight concerns in individuals with body dysmorphic disorder. Eating Behaviors,8,
115–120.
Krafft, K. C., & Berk, L. E. (1998). Private speech in two preschools: Significance of open-ended activities and make-believe play for
verbal self-regulation. Early Childhood Research Quarterly,13, 637–658.
Kramer, R. (1976). Maria Montessori: A biography. New York, NY: Putnam.
Ladd, G. W., Birch, S. H., & Buhs, E. S. (1999). Children's social and scholastic lives in kindergarten: Related spheres of influence? Child
Development,70, 1373–1400.
Lillard, A. S. (2005). Montessori: The science behind the genius. New York, NY: Oxford University Press.
Lillard, A. S. (2011a). Materials: What belongs in a Montessori primary classroom? Results from a survey of AMI and AMS teacher
trainers. Montessori Life,22,18–32.
Lillard,A. S. (2011b). Mindfulness practices in education: Montessori's approach.Mindfulness,2,78–85, doi:10.1007/s12671-011-0045-6.
Lillard, A. S., & Else-Quest, N. (2006). The early years: Evaluating Montessori education. Science,313, 1893–1894.
Lillard, A. S., & Peterson, J. (2011). The immediate impact of different types of television on young children's executive function. Pe-
diatrics,128, 644–649, doi:10.1542/peds.2008-1536.
Lopata, C., Wallace, N. V., & Finn, K. V. (2005). Comparison of academic achievement between Montessori and traditional education
programs. Journal of Research in Childhood Education,20,5–13.
Malecki, C., & Elliott, S. (2002). Children's social behaviors as predictors of academic achievement: A longitudinal analysis. School Psy-
chology Quarterly,17,1–23.
Mashburn, A., Pianta, R., Hamre, B., Downer, J., Barbarin, O., Bryant, D., et al. (2008). Measures of classroom quality in prekindergarten
and children's development of academic, language, and social skills. Child Development,79, 732–749.
McClelland, M. M., Acock, A. C., & Morrison, F. J. (2006). The impact of kindergarten learning-related skills on academic trajectories at
the end of elementary school. Early Childhood Research Quarterly,21, 471–490.
McClelland, M. M., Cameron, C. E., Connor, C. M., Farris, C. L., Jewkes, A. M., & Morrison, F. J. (2007). Links between behavioral regu-
lation and preschoolers' literacy, vocabulary, and math skills. Developmental Psychology,43, 947–959.
McDonald Connor, C., Son, S., Hindman, A., & Morrison, F. (2005). Teacher qualifications, classroom practices, family characteristics,
and preschool experience: Complex effects on first graders' vocabulary and early reading outcomes. Journal of School Psychology,
43, 343–375.
McGrew, K. S., & Woodcock, R. W. (2001). Woodcock-Johnson III technical manual. Itasca, IL: Riverside Publishing.
Miller, L. B., & Bizzell, R. P. (1984). Long-term effects of four preschool programs: Ninth- and tenth-grade results. Child Development,
55, 1570–1587.
Miller, L. B., & Dyer, J. L. (1975). Four preschool programs: Their dimensions and effects. Monographs of the Society for Research in
Child Development,40(5–6) Serial No. 162.
Mischel, W., Shoda, Y., & Rodriguez, M. L. (1989). Delay of gratification in children. Science,244, 933–938.
Miyake, A., Friedman, N. P., Emerson, M. J., Witzki, A. H., & Howerter, A. (2000). The unity and diversity of executive functions and
their contributions to complex ‘frontal lobe’tasks: A latent variable analysis. Cognitive Psychology,41,49–100.
Montessori, M. (1966). The secret of childhood (M. J. Costello, Trans.). New York, NY: Ballantine.
Montessori, M. (1967). The discovery of the child. (M. J. Costello, Trans.). New York, NY: Ballantine.
Montessori, M. (1989a). Creative development in the child I (R. Ramachandran, Trans.). Madras, India: Kalakshetra Press.
Montessori, M. (1989b). Creative development in the child II (R. R, Trans.). Madras, India: Kalakshetra Press.
Montessori, M. (1989c). The child, society, and the world: Unpublished speeches and writings. (Vol. 7). Oxford, England: Clio.
Montessori, M. (1997). The California lectures of Maria Montessori, 1915. Oxford, England: Clio.
Murray, A., & Peyton, V. (2009). Public Montessori elementary schools: A delicate balance. Montessori Life,20,26–30.
National Early Child Care Research Network (2002). Child-care structure–>process–>outcome: Direct and indirect effects of child-
care quality on young children's development. Psychological Science,13, 199–206.
National Early Child Care Research Network (2003). Social functioning in first grade: Associations with earlier home and child care
predictors and with current classroom experiences. Child Development,74, 1639–1662.
National Early Child Care Research Network (2004). Multiple pathways to early academic achievement. Harvard Educational Review,
74,1–28.
Odom, S. L. (2009). The tie that binds. Topics in Early Childhood Special Education,29,53–62.
O'Donnell, M. (2007). Continuum library of educational thought: Maria Montessori. (Vol. 7). London, England: Continuum.
O'Donnell, C. (2008). Defining, conceptualizing, and measuring fidelity of implementation and its relationship to outcomes in K-12
curriculum intervention research. Review of Educational Research,78,33–84.
399A.S. Lillard / Journal of School Psychology 50 (2012) 379–401
Author's personal copy
Olejnik, S., & Algina, J. (2000). Measures of effect size for comparative studies: Applications, interpretations, and limitations. Contem-
porary Educational Psychology,25, 241–286.
Passolunghi, M. C., Vercelloni, B., & Schadee, H. (2007). The precursors of mathematics learning: Working memory, phonological
ability and numerical competence. Cognitive Development,22, 165–184.
Peterson, C. C., & Wellman, H. M. (2009). From fancy to reason: Scaling deaf and hearing children's understanding of theory of mind
and pretence. British Journal of Developmental Psychology,27, 297–310.
Pettit, G., Dodge, K., & Brown, M. (1988). Early family experience, social problem solving patterns, and children's social competence.
Child Development,59, 107–120.
Piaget, J. (1970). Science of education and the psychology of the child (D. Coltman, Trans.). New York, NY: Orion Press.
Pianta, R. C., Barnett, W., Burchinal, M., & Thornburg, K. R. (2009). The effects of preschool education. Psychological Science in the Pub-
lic Interest,10,49–88.
Pianta, R. C., Cox, M. J., & Snow, K. L. B. (Eds.). (2007). School readiness and the transition to kindergarten in the era of accountability.
Baltimore, MD: Brookes.
Pianta, R. C., La Paro, K. M., Payne, C., Cox, M. J., & Bradley, R. (2002). The relation of kindergarten classroom environment to teacher,
family, and school characteristics and child outcomes. The Elementary School Journal,102, 225–238.
Ponitz, C. C., McClelland, M. M., Jewkes, A. M., Connor, C. M., Farris, C. L., & Morrison, F. J. (2008). Touch your toes: Developing a direct
measure of behavioral regulation in early childhood. Early Childhood Research Quarterly,23, 141–158, doi:
10.1016/j.ecresq.2007.01.004.
Ponitz, C. C., McClelland, M. M., Matthews, J. S., & Morrison, F. J. (2009). A structured observation of behavioral self-regulation and its
contribution to kindergarten outcomes. Developmental Psychology,45, 605–619, doi:10.1037/a0015365.
Povell, P. (2009). Montessori comes to America. Lanham, MD: University Press of America.
Rathunde, K. R., & Csikszentmihalyi, M. (2005a). Middle school students' motivation and quality of experience: A comparison of
Montessori and traditional school environments. American Journal of Education,111, 341–371.
Rathunde, K. R., & Csikszentmihalyi, M. (2005b). The social context of middle school: Teachers, friends, and activities in Montessori
and traditional school environments. The Elementary School Journal,106,59–79.
Raver, C. C., Garner, P. W., & Smith-Donald, R. (2007). The roles of emotion regulation and emotion knowledge for children's academ-
ic readiness: Are the links causal? In R. C. Pianta, M. J. Cox, & K. L. Snow (Eds.), School readiness and the transition to kindergarten
(pp. 121–148). Baltimore, MD: Brookes.
Rayner, K., Foorman, B. R., Perfetti, C. A., Pesetsky, D., & Seidenberg, M. S. (2001). How psychological science informs the teaching of
reading. Psychological Science in the Public Interest,2,31–74.
Razza, R. A. (2005). Relations among false-belief understanding, executive function, and social competence: A longitudinal analysis.
Dissertation Abstracts International: Section B: The Sciences and Engineering,66(5-B), 2859.
Riggs, N. R., Jahromi, L. B., Razza, R. P., Dillworth-Bart, J. E., & Mueller, U. (2006). Executive function and the promotion of social-
emotional competence. Journal of Applied Developmental Psychology,27, 300–309.
Rodriguez, L., Irby, B. J., Brown, G., Lara-Alecio, R., & Galloway, M. M. (2005). An analysis of second grade reading achievement related to
pre-kindergarten Montessori and transitional bilingual education. Mahwah, NJ: Erlbaum.
Rosenthal, R., & Rosnow, R. L. (1985). Contrast analysis: Focused comparisons in the analysis of variance. Cambridge: Cambridge University Press.
Rubin, K. (1988). The Social Problem-Solving Test-Revised. Waterloo, Ontario: University of Waterloo.
Rubin, K., & Clark, M. L. (1983). Preschool teachers' ratings of behavioral problems: Observational, sociometric, and social-cognitive
correlates. Journal of Abnormal Child Psychology,11, 273–286.
Rubin, K., & Daniels-Beirness, T. (1983). Concurrent and predictive correlates of sociometric status in kindergarten and grade 1 chil-
dren. Merrill-Palmer Quarterly,29, 337–351.
Rueda, M. R., Rothbart, M. K., McCandliss, B. D., Saccomanno, L., & Posner, M. I. (2005). Training, maturation, and genetic influcences
on the development of executive attention. Proceedings of the National Academy of Science,102, 14931–14936.
Salovey, P., & Mayer, J. (1990). Emotional intelligence. Imagination, cognition and personality,9, 185–211.
Schwarz, J. C., Schrager, J. B., & Lyons, A. E. (1983). Delay of gratification by preschoolers: Evidence for the validity of the choice par-
adigm. Child Development,54, 620–625.
Shapiro, D. (2007, June). How many Montessori schools? Jola Newsletter,2,1.
Shonkoff, J., & Phillips, D. (2000). From neurons to neighborhoods: The science of early childhood development. New York, NY: National
Academy Press.
Siegel, S., & Castellan, N. J. (1988). Nonparametric statistics for the behavioral sciences. New York, NY: McGraw-Hill.
Spivak, G., & Shure, M. B. (1974). Social adjustment of young children. San Francisco, CA: Jossey-Bass.
Tager-Flusberg, H. (2003). Exploring the relationship between theory of mind and social-communicative functioning in children
with autism. In B. Repacholi, & V. Slaughter (Eds.), Individual differences in theory of mind: Implications for typical and atypical de-
velopment (pp. 197–212). New York, NY: Psychology Press.
Thorell, L., Lindqvist, S., Nutley, S., Bohlin, G., & Klingberg, T. (2009). Training and transfer effects of executive functions in preschool
children. Developmental Science,12, 106–113.
Tilly, W. D., III (2008). The evolution of school psychology to science-based practice: Problem solving and the three-tiered model.
Best practices in school psychology,Vol. V. (pp. 17–36)Bethesda, MD: National Association of School Psychologists.
Toner, I. J., Holstein, R. B., & Hetherington, E. M. (1977). Reflection-impulsivity and self-control in preschool children. Child Develop-
ment,48, 239–245.
Walsh, B. A., & Petty, K. (2007). Frequency of six early childhood education approaches: A 10-year content analysis of early childhood
education journal. Early Childhood Education Journal,34, 301–305, doi:10.1007/s10643-006-0080-4.
Watson, A. C., Nixon, C. L., Wilson, A., & Capage, L. (1999). Social interaction skills and theory of mind in young children. Developmen-
tal Psychology,35, 386–391.
Wellman, H. M. (1990). The child's theory of mind. Cambridge, MA: Bradford Books/MIT Press.
Wellman, H. M., Fang, F., Liu, D., Zhu, L., & Liu, G. (2006). Scaling of theory-of-mind understandings in Chinese children. Psychological
Science,17, 1075–1081.
Wellman, H. M., Fang, F., & Peterson, C. C. (2011). Sequential progressions in a theory-of-mind scale: Longitudinal perspectives. Child
Development,83, 780–792.
400 A.S. Lillard / Journal of School Psychology 50 (2012) 379–401
Author's personal copy
Wellman, H. M., & Liu, D. (2004). Scaling of theory-of-mind tasks. Child Development,75, 523–541.
Welsh, M., Parke, R., Widaman, K., & O'Neil, R. (2001). Linkages between children's social and academic competence a longitudinal
analysis. Journal of School Psychology,39, 463–482.
Woodcock, R. W., McGrew, K. S., & Mather, N. (2001). Woodcock-Johnson III Tests of Achievement. Rolling Meadows, IL: Riverside
Publishing.
401A.S. Lillard / Journal of School Psychology 50 (2012) 379–401
