Journal of Educational Psychology
2006, Vol. 98, No. 4, 665– 689
Copyright 2006 by the American Psychological Association
0022-0663/06/$12.00 DOI: 10.1037/0022-0663.98.4.665
Preschool Instruction and Children’s Emergent Literacy Growth
Carol McDonald Connor
Frederick J. Morrison and Lisa Slominski
Florida State University
University of Michigan
Preschoolers’ (N ⫽ 156) classroom language and literacy experiences, defined across multiple dimensions, and their vocabulary and emergent literacy development were investigated. Videotaped classroom
observations revealed substantial variability in amount and types of language and emergent literacy
activities, across classrooms and for individual children within classrooms. Generally, more time in
emergent code-focused activities was associated with preschoolers’ alphabet and letter–word recognition
growth, whereas more time in meaning-focused activities (e.g., book reading) was related to vocabulary
growth. Only teacher- and teacher– child-managed activities were associated with alphabet and letter–
word growth, whereas child-managed experiences, including play, were also associated with vocabulary
growth. Overall, the effect size for student-level, code-focused instruction (small group) was about 10
times greater than was its classroom-level (whole-class) counterpart. There were Child ⫻ Instruction
interactions, with the impact of different activities varying with preschoolers’ incoming vocabulary and
emergent literacy.
Keywords: prekindergarten, language development, reading, early childhood development
special education and to enhance overall educational attainment
(Barnett, 1995; Conyers et al., 2003; Nelson et al., 2003; Reynolds
& Ou, 2004; Reynolds et al., 2004). However, there is substantial
variability in classroom practices and resulting child outcomes
across programs and studies (Barnett, 1995; Nelson et al., 2003),
and research seeks to understand how specific types of preschool
classroom experiences relate to child outcomes. Teachers’ sensitivity and responsiveness (National Institute of Child Health and
Human Development [NICHD] Early Child Care Research Network [ECCRN] studies), their use of cognitively challenging talk
and rare words (e.g., Dickinson & Tabors, 2001), and their styles
of book reading including dialogic reading (Whitehurst, Arnold, et
al., 1994; Whitehurst, Epstein, et al., 1994) as well as childinitiated practices (Schweinhart & Weikart, 1988), for example,
are related to positive child outcomes, and these findings have
been consistent in multiple settings (Conyers et al., 2003; NICHD
ECCRN, 2002). Generally, there is less research and evidence that
a focus on academic skills provides consistently stronger child
outcomes (Graue et al., 2004; Stipek et al., 1998; Stipek, Feiler,
Daniels, & Milburn, 1995). Yet attention to the content of and
amount of time spent in specific preschool emergent literacy
activities and the relation of these activities to preschoolers’ emergent literacy development may be important, especially with the
inauguration of new universal prekindergarten initiatives and the
recent findings regarding Head Start efficacy (U.S. Department of
Health and Human Services, 2005).
The purpose of this study was to closely examine the language,
emergent literacy, and other learning experiences that are provided
to preschoolers and to investigate the contribution of these experiences to students’ language and emergent literacy skill development. It is generally agreed that emergent literacy “involves the
skills, knowledge, and attitudes that are developmental precursors
to conventional forms of reading and writing. These skills are the
basic building blocks for how students learn to read and write”
(Connor & Tiedemann, 2005, p. 1). An emergent literacy perspec-
Accumulating evidence reveals that high-quality preschool experiences may lead to stronger student academic outcomes, especially for children at risk for academic underachievement (Campbell, Pungello, Miller-Johnson, Burchinal, & Ramey, 2001;
Conyers, Reynolds, & Ou, 2003; Graue, Clements, Reynolds, &
Niles, 2004; Nelson, Benner, & Gonzalez, 2003; Reynolds & Ou,
2004; Reynolds, Ou, & Topitzes, 2004; Reynolds, Temple, Robertson, & Mann, 2003). This finding is important because in the
United States, fully one third of children fail to read at basic levels
by fourth grade (National Assessment of Educational Progress,
2003, 2005), and the percentage is higher for children living in
poverty or who belong to certain ethnic minorities. High-quality
preschool interventions have been shown to reduce referral to
Carol McDonald Connor, Florida Center for Reading Research, Florida
State University; Frederick J. Morrison and Lisa Slominski, Department of
Psychology, University of Michigan.
This work was supported by National Institute of Child Health and
Human Development Grant R01 HD27176 and National Science Foundation Grant 0111754. Additional support was provided by U.S. Department
of Education, Institute for Education Sciences Grant R305H04013. Any
opinions, findings, conclusions, or recommendations expressed in this
article are those of the authors and do not necessarily reflect the views of
these agencies.
We thank Claire Cameron for her help developing and coordinating the
video coding; Abby Jewkes, Shayne Piasta, and Phyllis Underwood for
their comments on drafts of this article; the members of the University of
Michigan Pathways to Literacy project; the Florida State University Individualizing Student Instruction Project; the Florida State University writing
group; and the participating families, teachers, and school district administration and personnel without whom this study would not have been
possible.
Correspondence concerning this article should be addressed to Carol
McDonald Connor, Florida Center for Reading Research, Florida State
University, 227 North Bronough, Suite 7250, Tallahassee, FL 32301.
E-mail: cconnor@fcrr.org
665
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CONNOR, MORRISON, AND SLOMINSKI
tive departs from a reading readiness model. In the readiness
model, learning to read begins with formal school-based reading
instruction. From an emergent literacy perspective, there is no
boundary between what is considered to be the conventional
reading that students learn in school and everything that comes
before. Rather, the emergent literacy perspective views literacyrelated behaviors that occur in the preschool period as legitimate
and important features on a developmental continuum of literacy
(Bowman, Donovan, & Burns, 2001; Shonkoff & Phillips, 2000;
Teale & Sulzby, 1986).
Short- and Long-Term Benefits of Preschool Intervention
Research on preschool interventions has revealed short-term and
long-term social and cognitive gains for students who may experience academic underachievement because of poverty, disabilities, and other risk factors. Documented advantages include reduced referral to special education, reduced grade retention, higher
rates of high school graduation, and reduced levels of juvenile
delinquency (Barnett, 1995; Barnett, Young, & Schweinhart,
1998; Bryant, Peisner-Feinberg, & Clifford, 1993; Burchinal,
Peisner-Feinberg, Pianta, & Howes, 2002; Campbell et al., 2001;
Dickinson & Smith, 1994; Durlak, 2003; Lazar, Darlington, Murray, Royce, & Snipper, 1982; Morrison, Bachman, & Connor,
2005; see also Nelson et al., 2003; Peisner-Feinberg & Burchinal,
1997).
Perhaps the most compelling long-term positive outcomes come
from research on model programs like the High Scope/Perry
Preschool project, the Abecedarian project, and the Chicago
Child–Parent Centers (or Chicago Title I Project; Barnett, 1995).
These studies, initiated 20 or more years ago, each independently
provide evidence of short- and long-term benefit to their participants relative to a control group of students. Most recently, for
example, the Chicago Child–Parent Centers calculated that for
every dollar spent on the preschool intervention, society realized a
$7.14 return in saved education and societal costs from reduced
referral to special education, reduced grade retention, and reduced
juvenile delinquency (Reynolds, Temple, & Ou, 2003; Reynolds,
Temple, Robertson, & Mann, 2003).
Still, in light of society’s substantial investment in public preschool programs, such as Head Start, Early Reading First, Title I,
and universal preschool, as Reynolds and colleagues noted (2004),
“greater attention to how the long-term effects come about is
needed to inform program improvement and expansion efforts” (p.
1301). Accumulating evidence indicates that children’s early language and literacy experiences in the classroom make an important
contribution to the long-term effects. Studies, such as the NICHD
Study of Early Child Care and Youth Development (e.g., NICHD
ECCRN, 2002), Harvard Home-School Study (Dickinson & Tabors, 2001; Smith & Dickinson, 1994), intervention studies
(Torgesen et al., 2001; Whitehurst, Arnold, et al., 1994; Whitehurst, Epstein, et al., 1994), and others (Nelson et al., 2003) have
clearly revealed that cognitively challenging talk (Dickinson &
Tabors, 2001; Smith & Dickinson, 1994), exposure to rare words
(Beals & Tabors, 1995; Huttenlocher, Vasilyeva, Cymerman, &
Levine, 2002), shared book reading, reading to students using
dialogic reading techniques (Cook-Gumperz, 1986; CrainThoreson & Dale, 1999; Dickinson & Tabors, 2001; Lonigan &
Whitehurst, 1998; Whitehurst, Arnold, et al., 1994; Whitehurst,
Epstein, et al., 1994), play (Pelligrini & Galda, 1993), and use of
playful activities to stimulate learning (Bowman et al., 2001;
Howes & Smith, 1995; Roskos & Christie, 2000) all enhanced
children’s language and early reading skills.
Virtually none of these studies, however, focused on the explicit
instruction of emergent literacy in preschool.(Graue et al., 2004),
and the published findings are mixed. For example, preschoolers in
programs that provided explicit instruction in basic reading skills
showed stronger skills but less positive feelings about themselves
and less motivation than did students in child-centered programs,
which encouraged children’s learning through play (Stipek et al.,
1995). In still another study, preschoolers in classrooms that focused on basic skills demonstrated weaker cognitive and motivation outcomes than did preschoolers in classrooms that deemphasized basics skills and had more positive social climates
(Stipek et al., 1998). However, these studies tended to pit one kind
of curriculum against the other, which may oversimplify the complex effects of classroom experiences on students’ outcomes. New
evidence, using teacher report, suggests that curricula that were
high in teacher-directed instruction with specific content and simultaneously high in child-initiated, teacher-responsive approaches yielded more positive short- and long-term educational
and social outcomes for preschoolers than did programs that emphasized one over the other or neither (Graue et al., 2004). Hence,
using two or more dimensions of instruction coupled with direct
observation of preschool classroom language and literacy activities
may yield a more nuanced view of preschool experiences and their
effect on students’ outcomes.
Dimensions of Instruction
One challenge facing researchers is how to capture the complexities of preschoolers’ classroom experiences while also permitting statistical analysis of the effects of these experiences on
student outcomes. Much of preschool research has compared the
relative effectiveness of three curriculum types based on different
theories of learning (Bowman et al., 2001, pp. 138 –139): (a) direct
instruction, in which the teacher uses drill and practice lessons that
teach specific skills incrementally; (b) traditional approaches,
which assume that children will learn when they are ready as long
as stimulating environments are provided; and (c) cognitive curriculum, in which learning is viewed as an active exchange between children and their environment, which includes the teacher.
However, during any given school day, teachers may provide a
variety of experiences that transcend all three of these major
curriculum types. The teacher may use direct instruction for teaching letters but a cognitive curriculum approach during sharing time
and more traditional approaches as she or he sets up the dramatic
play center. Comparing one curriculum with another may overlook
the complexity of learning activities preschoolers actually experience in their classroom. Thus, for this study, we sought to examine
the content or focus of the learning experiences, using multiple
dimensions, rather than the type of curriculum being utilized.
Additionally, accumulating evidence indicates that emergent
literacy is a multidimensional construct (Senechal, 2006; Senechal
& LeFevre, 2001) rather than a more global construct as originally
proposed by Teale and Sulzby (1986). As Senechal and LeFevre
(2001) observed, there is striking evidence that emergent literacy
is distinct from oral language and metalinguistic awareness (Ma-
CHILDREN’S EMERGENT LITERACY GROWTH
son & Stewart, 1990; Whitehurst & Lonigan, 1998). Different
components of the home literacy environment—formal versus
informal emergent literacy experiences— differentially predict the
distinct components of emergent literacy (Senechal & LeFevre,
2002; Senechal, LeFevre, Thomas, & Daley, 1998). Using a parallel argument, we contend that if emergent literacy has multiple
dimensions, then examining sources of classroom instruction’s
influence multidimensionally should prove more informative than
examining the impact of instruction more globally. Thus, we
examined the content of classroom literacy activities across four
dimensions: teacher managed (TM) versus teacher– child managed
(TCM) versus child managed (CM), code focused versus meaning
focused, explicit versus implicit, and student- versus classroomlevel instruction. Each dimension is discussed below.
TM Versus TCM Versus CM
The dimension TM versus TCM versus CM considers who is
focusing the child’s attention—the teacher or the student (Connor,
Morrison, & Katch, 2004; Connor, Morrison, & Petrella, 2004;
Morrison et al., 2005) or whether the attention is jointly focused
(teacher and students interacting). This dimension may be confused with teacher-directed and child-centered (Bowman et al.,
2001, chap. 5) or child-initiated learning (Schweinhart & Weikart,
1988), but it is substantially different. In the framework used in
this study, child-centered or child-initiated learning may be TM or
CM or managed jointly: TCM. What is at issue is who is directing
the child’s attention, the teacher and/or the child. A teacher reading
a book to students without discussion, even if the children selected
the book, would be considered TM because the teacher is focusing
the children’s attention and is doing most of the talking. Sharing,
scaffolding, or interactive read-alouds are considered to be TCM
within this framework because the teacher is actively involved
with and responsive to the child. There is good evidence that
warmer and more responsive teacher– child interactions are associated with stronger student outcomes (Connor, Son, Hindman, &
Morrison, 2005; Graue et al., 2004).
In contrast, activities in which the child is working independently or with peers, such as completing worksheets and pretend
reading alone or with a friend in the library corner, are considered
CM because the student is directing his or her own attention
without the support of the teacher. Peer interactions are considered
CM because students, not teachers, are supporting each other’s
learning. There is evidence that such peer-managed activities are
substantially different from TM activities (Palincsar, Collins, Marano, & Magnusson, 2000).
Code-Focused Versus Meaning-Focused Activities
The code-focused versus meaning-focused dimension captures
the content focus of language and emergent literacy activities.
Although clearly preschoolers are not taught to read as such, there
is evidence that appropriate preschool activities can enhance their
emergent literacy—including letter knowledge and phonological
awareness. These kinds of activities may be considered emergent
code-focused activities (Foorman, Francis, Fletcher, Schatschneider, & Mehta, 1998; Rayner, Foorman, Perfetti, Pesetsky, & Seidenberg, 2001). These would include teaching children how to
name and write letters, to rhyme words (Torgesen, Burgess, Wag-
667
ner, & Rashotte, 1994; Torgesen et al., 1999), to relate letters to the
sounds they make, and to sound out words (phonological decoding). In the preschool literature, many of these activities would be
associated with curricula that focus on basic skills (Graue et al.,
2004; Stipek et al., 1995) or direct instruction (Schweinhart &
Weikart, 1988).
In contrast, activities designed to help students understand
words and passages, comprehend what is read to them or what they
are reading, and enhance receptive and expressive language skills
including listening comprehension, which support emerging reading comprehension (Scarborough, 1990), may be considered
meaning-focused activities (Dahl & Freppon, 1995; Foorman et
al., 1998; Juel & Minden-Cupp, 2000). Such activities include
explaining the meaning of a word (i.e., vocabulary activities),
(National Reading Panel, 2000), reading aloud to children (Whitehurst, Arnold, et al., 1994; Whitehurst, Epstein, et al., 1994),
discussion and sharing (Snow, 2001), and children’s emergent
reading and writing activities (National Reading Panel, 2000;
Sulzby, 1985).
Explicit Versus Implicit
The dimension explicit versus implicit speaks to the specificity
of learning (Senechal, 2006; Senechal & LeFevre, 2001, 2002;
Senechal et al., 1998) and incorporates the idea that activities can
be explicitly or implicitly focused on promoting a specific outcome; in this study, either language or emergent literacy. This
dimension is defined depending on the outcome being explored.
So, for example, if the outcome is language or vocabulary, activities that directly focus on language development (e.g., reading to
children; Senechal & LeFevre, 2002) would be considered explicit
language activities. If the outcome is learning letters and phonological decoding, then activities that focus on these outcomes (e.g.,
rhyming games) would be explicit emergent literacy or emergent
decoding activities. However, children may learn letters and letter
sounds indirectly through activities like shared storybook reading.
Thus, reading to children would be an implicit emergent literacy
activity, although it is an explicit language activity. This dimension is similar to the formal versus informal framework presented
by Senechal and LeFevre (2002), in which parents explicitly
teaching their children letters is considered formal literacy exposure, whereas parents reading to children is considered informal
literacy exposure.
Play (e.g., child-selected activities such as dramatic play, building blocks, etc.) is implicit for both emergent literacy and language
outcomes because children are focusing on having fun (e.g., when
they pretend to write birthday party invitations) rather than, for
example, learning letters. Researchers might expect such implicit
activities to impact children’s emergent literacy and language,
although they do not specifically target skills associated with
emergent literacy or language (Bowman et al., 2001; Pelligrini &
Galda, 1993; Rowe, 1988). Note that within our coding system,
play has a precise definition and is distinct from games, fine and
gross motor activities, art, and music, which each have their own
codes (see Appendix A). Math, science, or social studies activities,
although coded, are beyond the scope of this study, although one
might argue that focus on these content areas might implicitly
contribute to children’s vocabulary development, for example.
CONNOR, MORRISON, AND SLOMINSKI
668
Future studies will focus on the role of these activities in
preschool.
Classroom Level Versus Student Level
The dimension classroom level versus student level considers
the extent to which instruction is the same or different for each
student in the classroom. Language and literacy activities may be
classroom level, such as when the teacher is reading aloud during
circle time. All of the students are doing substantially the same
thing at the same time. Even if the students are working in small
groups or individually, if they are all doing substantially the same
thing (e.g., play), then that is classroom-level instruction.
In contrast, for student-level instruction, students in one classroom are engaged in substantially different activities at the same
time. Teachers may provide student-level instruction in small
groups or they may work with children individually (e.g., centers
with different activities, tutoring one child while the rest do other
activities). The video coding system permits coding of individual
student participation in specific activities so that researchers can
examine this dimension of instruction.
Note that specific types of activities can be the same across the
classroom-level versus student-level dimension. Teachers can read
aloud to the entire class (TM–meaning focused– classroom level)
or can read aloud to a small group of children while the rest of the
children engage in substantially different activities (TM–meaning
focused–student level).
Putting the Dimensions Together
A key feature of these dimensions is that they are operating
simultaneously. Thus, activities fall in sectors for classroom-level
activities and student-level activities with, potentially, 12 combinations in all (see Table 1).
Because our coding system was designed to capture the content
of the activities observed rather than the motivator (teacher or
child), we did not focus specifically on teacher-directed versus
child-initiated, teacher-responsive instruction (Bowman et al.,
Table 1
Observed Language and Literacy Activities Categorized by Dimensions of Instruction—Teacher Versus Child Managed, Explicit
Versus Implicit, and Code Versus Meaning Focused, for Classroom-Level and Student-Level Instruction
Dimension
Teacher managed (TM)
Teacher–child managed (TCM)
Child managed (CM)
Classroom-level instruction
Explicit decoding, code focused or implicit
language–vocabulary, code focused
Implicit decoding, code focused or explicit
language–vocabulary, meaning focused
MF–cl
Teacher read-aloud
CF–cl
Spelling
Phonological awareness
Alphabet activity
Letter–sound correspondence
Initial consonant stripping
MF–cl
Chorale reading aloud
Discussion
Teacher read-aloud–discussion
combined
Conventions of print
Vocabulary activities
Other language arts activities
Sharing
Implicit decoding and implicit language–
vocabulary, meaning focused
MF–cl
Sustained silent reading
MF–play–cl
Play
Student-level instruction
Explicit decoding, code focused or implicit
language–vocabulary, code focused
Implicit decoding, code focused or explicit
language–vocabulary, meaning focused
Implicit decoding and implicit language–
vocabulary, meaning focused
MF–cl
Teacher read-aloud
CF–st
Alphabet activity
Handwriting practice
MF–st
Teacher read-aloud–discussion
combined
Discussion
Conventions of print
Vocabulary activities
Other language arts activities
Sharing
Scaffolded sustained silent
reading
CF–st
Handwriting
Alphabet activity
MF–st
Writing (invented spelling)
Small group
Sustained silent reading
Individual sustained silent reading
CM–MF–st play
Play
Note. CM–MF–st and CM–MF–st play are summed to create the CM implicit-decoding variable. MF ⫽ meaning focused; CF ⫽ code focused; st ⫽
student level; cl ⫽ classroom level.
CHILDREN’S EMERGENT LITERACY GROWTH
2001, chap. 5). We did record the activities such approaches might
generate, however, using our other dimensions (explicit vs. implicit; TCM vs. CM). Thus, we do not distinguish between teacher
read-aloud activities initiated by the child (the child asks the
teacher to read the book or the teacher notices that Demario
[pseudonym] is interested in fish and selects a book on that topic)
or by the teacher (the teacher selects the book and reads it to the
children). We do capture how interactive the read-aloud was by
distinguishing teacher read-aloud and teacher read-aloud with discussion, for example.
Child Characteristics
Accumulating evidence reveals a number of child literacy skills
in preschool and kindergarten that consistently predict later reading and academic success, including alphabet knowledge, phonological awareness, letter–word recognition, and phonological decoding (NICHD ECCRN, 2005; Poe, Burchinal, & Roberts, 2004;
Rayner et al., 2001; Scarborough, 1998; Schatschneider, Fletcher,
Francis, Carlson, & Foorman, 2004; Snow, Burns, & Griffin,
1998). Language skills, particularly vocabulary, also appear to be
consistent predictors of later reading success, especially as comprehension of what is read becomes important (Anderson & Freebody, 1981; Loban, 1976; National Reading Panel, 2000; NICHD
ECCRN, 2005; Poe et al., 2004; Scarborough, 1990, 2001; Snow
et al., 1998; Storch & Whitehurst, 2002). In contrast to early
decoding skills, research reveals that growth in vocabulary skills
may be highly stable and resistant to intervention and the effect of
schooling (Hart & Risley, 1995; Morrison, Smith, & DowEhrensberger, 1995). There is evidence, however, that rich literacy
(meaning-focused) experiences at home (Beals & DeTemple,
1993; Senechal et al., 1998), during storybook reading (Robbins &
Ehri, 1994), and in preschool (Dickinson, Anastasopolous, McCabe, Peisner-Feinberg, & Poe, 2003; Dickinson & Tabors, 2001)
can contribute to young children’s language growth. In this study,
we examined variability in preschoolers’ alphabet naming, letter–
word recognition, and vocabulary growth and how such growth
might be affected by variation in preschool classroom literacy
activities.
The effect of amount and types of classroom activities, however,
may depend on the language and early reading skills with which
children begin school. Child ⫻ Instruction interactions have been
observed in first grade (Connor, Morrison, & Katch, 2004; Foorman et al., 1998; Juel & Minden-Cupp, 2000), in third grade
(Connor, Morrison, & Petrella, 2004), and in interventions for
children with learning disabilities (Torgesen, 2000). One study of
first-grade classrooms (Connor, Morrison, & Katch, 2004) found
that students with lower fall decoding and vocabulary skills demonstrated greater decoding skill growth in classrooms that spent
more time in TM explicit decoding activities, with small amounts
of CM meaning-focused activities in the fall that increased
throughout the school year. Yet the opposite was the case for
students with stronger fall decoding and vocabulary skills. For
them, time spent in explicit decoding instruction had little impact,
yet students demonstrated greater decoding skill growth when they
were in classrooms with higher amounts of CM meaning-focused
activities all year long. In this study, we investigated whether there
are similar Child ⫻ Instruction interaction effects for preschoolers.
669
Research Questions
The purpose of this study was to examine the association of
amount and type of preschool language and literacy activities with
students’ vocabulary and emergent reading skill growth. The following research questions were posed: (a) What is the nature of
variation (amount and type) in preschool language and literacy
activities (both explicit and implicit) observed in preschool classrooms relative to other activities (art, music, math, etc.)? (b) How
are differing amounts of time spent in language and literacy
activities related to preschoolers’ vocabulary and emergent literacy
growth, and does the effect of specific types of preschool language
and literacy activities, across multiple dimensions, depend on the
outcome of interest? For example, do preschool activities that
predict letter–word knowledge also contribute to vocabulary
growth? and (c) Does the effect of amount and type of preschool
language and literacy activities depend on the language and early
reading skills children bring to the classroom? Are there Child ⫻
Instruction interactions?
For the first research question, we hypothesized that in these
high-quality preschool classrooms, at least some time would be
devoted to explicit and implicit emergent literacy and language
activities but that much of the day would include other activities
such as art, math, and noninstructional time.
With regard to the second research question, we hypothesized
that language and literacy instructional activities, both explicit and
implicit, would be associated with growth in preschoolers’ language and emergent literacy. On the basis of previous research
findings, we anticipated that explicit and implicit meaning-focused
activities might have a positive effect on students’ vocabulary
growth but not on letter–word or alphabet knowledge growth in
light of the specificity found in other studies with preschoolers
(Senechal & LeFevre, 2002; Senechal et al., 1998). Predictions
regarding the effect of explicit, emergent, code-focused instruction
were more difficult given the equivocal research findings in this
area. We conjectured, relying on studies with parents (Senechal &
LeFevre, 2002) and preschool curriculum comparisons (Graue et
al., 2004; Stipek et al., 1995), that more time spent in explicit
code-focused instruction would be associated with greater growth
in students’ emergent literacy skill growth (e.g., alphabet and
letter–word) but would not be systematically related to children’s
vocabulary growth.
With regard to our third research question, we hypothesized that
the effect of specific language and literacy activities would depend
on students’ entering vocabulary, alphabet, and letter–word recognition skills. We anticipated that children with weaker early literacy and vocabulary scores would demonstrate greater skill growth
when they spent greater amounts of time in TM and TCM activities focused on activities explicitly related to a given outcome. We
anticipated that students with weaker alphabet and letter–word
scores would demonstrate greater growth when they experienced
more time in TCM, explicit, code-focused activities than would
students with stronger alphabet and letter–word skills. Students
with weaker entering vocabulary skills would demonstrate greater
vocabulary growth when they spent more time in TCM meaningfocused activities that focused explicitly on language development
than would students with stronger fall vocabulary skills.
CONNOR, MORRISON, AND SLOMINSKI
670
Method
Participants
This study was conducted in a transitioning economically and ethnically
diverse community, located on the urban fringe of a major midwestern city,
in a school district serving over 6,400 children from preschool through high
school. The district is fairly unique in that, in addition to Head Start and
state-funded programs for preschool-age children at risk for academic
underachievement, the district provides state-licensed preschool (full-day
and half-day) programs for typically developing 3- and 4-year-old students
on a fee-for-service basis. Classrooms are housed in six elementary schools
throughout the district. The district has open borders, which means that
students living in the neighboring communities (including the major city)
could attend district schools.
Student participants were recruited at the beginning of the school year
through direct and backpack mail. Any child who attended the school
district preschool program was eligible to join the study. Approximately
38% of the parents who were invited agreed to participate. Eighty child
participants were girls and 76 were boys (N ⫽ 156). Children were, on
average, 4 years of age and ranged from 3 to 5 years of age in the fall. They
represented the diversity of the district fairly well. Frequent interactions
with teachers and participating children in the schools indicated that
children whose parents returned the consent form did not differ appreciably
from children whose parents did not. We deliberately reached out and
extended multiple invitations to parents of children in the Head Start and
state-supported preschool programs. On the basis of parent report, 28 of
131 children belonged to ethnic minorities including African American
(n ⫽ 8), Hispanic (n ⫽ 4), Middle Eastern (n ⫽ 8), and Asian (n ⫽ 8).
Parents reported the remaining children to be European, European American, or White (n ⫽ 103). Ten parents reported that a language other than
English was spoken in the home. Overall, all mothers but one graduated
from high school, 27 had 1–3 years of college, 57 completed college, and
49 had postgraduate experience; the remaining mothers did not report their
education level. Fathers demonstrated a similar distribution. All but one
completed high school, 19 had some college experience, 59 completed
college, and 45 had postgraduate experience. Missing data analyses revealed no significant difference in fall and spring outcomes or for amount
and type of literacy instruction received between students for whom parent
education and ethnicity was reported (i.e., the questionnaire returned or
parent did not answer question) and for whom they were not. Race– ethnic
group and a language other than English spoken at home did not predict
child outcomes once students’ fall scores were entered into the model
during model building.
Children were followed into 1 of 34 classrooms taught by 25 teachers (9
teachers taught morning and afternoon classes or classes that met on
different days of the week). There were, on average, 4 child participants per
class, although this varied from 1 to 10. Class size maximum was 16
children. Three of the classrooms provided preschool intervention for
children identified as at risk of underachievement because of poverty or
other risk factors. Two of these classrooms were Head Start programs, and
one was a state-funded, school-readiness program. The state-funded program was part of a statewide initiative that served over 25,700 4-year-old
students statewide, that cost approximately $3,300 per enrolled child, and
that was ranked 13th in access and 19th in resources among states nationwide (National Institute for Early Education Research, 2004).
Analyses revealed that children in the Head Start and state-funded
classrooms (Head Start–state) and children in the fee-for-service classrooms did not enter preschool with significantly different scores on the
letter–word recognition or vocabulary measures (Wilks’s ␭ ⫽ .969), F(3,
149) ⫽ 1.57, p ⫽ .198, nor were there age differences. Indeed, only about
10% of the students in this sample whose scores fell in the lowest quartile
(W score ⬍ 312; as discussed below, the W score is a transformation of the
Rasch ability scale) on the fall Woodcock–Johnson—III Tests of Achievement (McGrew, Werder, & Woodcock, 1991) letter–word recognition
assessment attended the Head Start–state classrooms, although as a percentage, a greater number of the children in Head Start–state programs
(44%) had letter–word scores in the lowest quartile compared with the
fee-for-service classrooms (22%). Similar patterns were observed for fall
vocabulary skills; only 2 of the 26 children with the lowest fall vocabulary
scores (W score ⬍ 456) attended the Head Start–state classrooms. Post hoc
analyses revealed that children in the Head Start–state classrooms knew
significantly fewer letters than did children attending fee-for-service classrooms (about 5 compared with 11), t(151) ⫽ –2.14, p ⬍ .05, although a
multivariate analysis by school revealed no significant difference in fall
alphabet, letter–word recognition, or vocabulary scores by school (Wilks’s
␭ ⫽ .857), F(15, 400.7) ⫽ 1.54, p ⫽ .088.
Teachers met all state and district certification requirements and, in
general, were well qualified to be preschool teachers. They had, on average, 5.83 years of experience (SD ⫽ 5.29) and all had a 4-year degree. Four
teachers had a master’s degree. Teachers for the intervention programs
(e.g., Head Start) met the same district certification requirements as the
other preschool teachers.
Procedure
This study was conducted during the 1st year (2002–2003) of a 5-year
longitudinal study on children’s transition to school. Students were individually assessed in the fall and again in the spring on a battery of language
and literacy tasks. Testing was conducted by research staff in a quiet place
in the school building. Parents and teachers completed questionnaires,
which were sent to them in the winter and spring of the school year. Parent
questionnaires were designed to obtain information regarding parents’
education levels and other sociocultural information about their children,
including race and native language. Teacher questionnaires were designed
to gather information about teachers’ qualifications including educational
level, certification, and years of experience teaching. We conducted informal classroom observations throughout the school year and a midyear
half-day videotaped observation in each classroom to closely examine the
language and literacy activities in which teachers and preschool students
were engaged, in addition to other activities (e.g., math, games, noninstructional time, etc.).
Measures
Child Assessment
Alphabet task. In this informal task, children were asked to name each
of the 26 lowercase letters in the alphabet as they were presented one at a
time using shuffled flash cards. The raw score represents the number of
letters the child identified correctly.
Letter–word recognition. Children’s letter and word recognition skills
were assessed using the Woodcock–Johnson—III Tests of Achievement
(McGrew et al., 1991; Mather & Woodcock, 2001) Letter–Word Identification test. In this task, children were first asked to identify letters in large
type. The remaining items required the child to read words, which were
listed approximately eight to a page and were increasingly unfamiliar. For
analysis purposes, raw scores were converted to W scores, which are a
“special transformation of the Rasch ability scale” (Mather & Woodcock,
2001, p. 72). Rasch ability scale scores provide equal-interval measurement
characteristics. W scores are centered at 500, which represents the achievement of a typical 10-year-old child. The test sample has a W score mean
of 327.23 (SD ⫽ 34.18, SEM ⫽ 3.69) for a child 4 years of age, with a
median reliability of .98 for children in this age range (McGrew et al.,
1991).
Vocabulary. Children’s vocabulary was assessed using the Woodcock–
Johnson—III Tests of Achievement Picture Vocabulary test. In this task,
children are asked to name pictures of increasingly unfamiliar items.
Primarily an expressive vocabulary task, it was designed to assess children’s oral language and lexical knowledge, with a median reliability of
CHILDREN’S EMERGENT LITERACY GROWTH
.81. Again, W scores were used in the analyses, which for this test have a
test sample mean of 460.63 (SD ⫽ 17.46, SEM ⫽ 7.70) for 4-year-old
children (McGrew et al., 1991).
Classroom Observations
Classrooms were observed informally throughout the school year. During the winter (January, February, or March), the classrooms were videotaped for the entire morning or afternoon (approximately 2 hr). Taping
sessions were scheduled at the teachers’ convenience and avoided days that
students participated in special activities such as physical education and
library. If the teacher was absent or there were unforeseen events (e.g., fire
drill), the observation was rescheduled. In all cases, research observers
reported that the videotaped classroom observation was representative of
the informal observations conducted throughout the school year. All-day
classes were observed only in the morning following the recommendations
of teachers and school staff. On the basis of researchers’ preliminary
671
observations of all-day classes, during the afternoons, children spent substantial time napping, snacking, and in free-play activities.
Two high-quality digital video cameras (Panasonic Model PV-DV102D
and Sony Model DCR-TRV17) were used to capture the classroom activities. One was set on a tripod and located so as to capture as much of the
classroom as possible. The other camera was hand held by an observer in
a corner of the classroom to capture multiple groups and to follow participating children if they wandered out of range of the stationary camera. For
some classrooms, a third camera was used. All cameras had high-quality
microphones that successfully captured the teachers’ and students’ voices.
Observers also recorded detailed field notes including descriptions of the
participating children (clothing, distinctive hair styles), which were used to
supplement and confirm the video and audio recording during coding.
Videos were coded using the Noldus Observer Pro system (Noldus
Information Technology, 2001), which permits direct coding of video (see
Figure 1). All videotapes for each classroom were viewed, and the tape
providing the most complete information was selected for coding. These
Figure 1. A screenshot of the Noldus Observer Pro work space. Note the video on the right with video controls,
the coded states on the upper left, and the available codes on the lower left. From “Suzanne and Erin on
Sidewalk.mpg [Video],” by A. Spink (Producer), 2002, Ede, the Netherlands: Noldus Information Technology.
Copyright 2002 by Noldus Information Technology. Reprinted with permission.
672
CONNOR, MORRISON, AND SLOMINSKI
videos were viewed repeatedly as they were coded. Coders utilized information from the other videos and field notes as needed to identify specific
student and teacher activities. Only the time that the children were in the
classroom was coded. For example, recess outside was not coded. Relevant
excerpts from the coding manual, including a list of the language arts
activities, are provided in Appendix A; a screen shot of the software is
provided in Figure 1.
The coding scheme tracks the amount of time, in minutes:seconds, that
teachers and participating students spend in both academic and nonacademic activities. Language–literacy, math, science, art, play, and music
compose the main instructional areas. Noninstructional codes include ritual
(e.g., pledge of allegiance), transition (e.g., waiting in line to go to recess),
and orient– organize (e.g., teacher explaining the various center activities).
In order to be coded, any activity must have lasted at least 15 s. Codes were
designed to be used longitudinally as participating students were followed
longitudinally through their transition to first grade.
Intercoder reliability was computed by the Noldus software by comparing time and activity for the same classroom videotape coded by two
different researchers for 25% of the tapes selected at random. For each
comparison, reliability exceeded 85% and ranged from 86% to 92%.
A key advantage of this system is that activities may be coded for each
individual student. Students in the same classroom experience different
amounts and types of activities, and this difference is recorded. Thus, there
is student-level instruction with unique amounts and types of instruction
for each student, and there is classroom-level instruction, in which all of
the students in the classroom share the same amount and type of instruction. So, for example, 1 target student (Student A) might participate in a
small-group activity with the teacher focusing on learning letters, while
another target student (Student B), in the same classroom at the same time,
is reading a book quietly to herself. In this case, students are participating
in student-level instructional activities. Student A is participating in a
TCM, code-focused, student-level activity, and Student B is participating
in a CM, meaning-focused, student-level activity. If, during circle time, a
whole-class activity, the teacher discusses the meaning of the word of the
day, then that is a TCM, meaning-focused, classroom-level activity; all of
the students, including the 2 target students, are participating in the same
amount and type of instruction at the same time. The dimensions of
instruction are described further in the next section. Selected excerpts from
the coding manual are included in Appendix A. Actions of the primary and
assistant teachers and aides were coded separately. Generally, the primary
teacher provided the classroom-level instruction, whereas the assistant
teachers and aids helped during small-group activities. Preliminary analyses revealed that activities conducted by the primary teacher or the assistant
teacher did not have significantly different effects on children’s learning
and so both were considered teachers in the analyses.
Classroom Variables
Instruction. For every class, the amount of each classroom-level and
student-level instructional activity was identified and coded using the
dimensions of instruction— explicit versus implicit, TM versus TCM versus CM, and meaning focused versus code focused—and placed in their
appropriate sector (see Table 1).
Instruction variables, representing minutes per day, were computed by
adding the amounts of time (in minutes) spent in each sector (see Table 2).
Negligible amounts of TM, explicit meaning-focused, student-level instruction were observed and so TM and TCM amounts were summed.
For alphabet and letter–word outcomes, there are four classroom-level
variables and three student-level variables (see Table 1) expressed in
minutes per day. Descriptive statistics are provided in Table 2. For vocabulary, there are four classroom-level variables and five student-level variables. Except for CM, implicit meaning-focused activities, the variables for
alphabet, letter–word, and vocabulary are the same and differ only in
whether they are implicit or explicit for the specific outcome of interest. In
other words, activities that are explicit for vocabulary are implicit for
Table 2
Descriptive Statistics (Minutes per Day) for Classroom- and
Student-Level Instruction Variables
Variable
M
SD
Minimum
Maximum
0.00
0.00
0.00
0.00
0.00
15.00
7.35
30.68
3.93
6.18
0.00
0.00
0.00
0.00
0.00
6.35
65.02
17.57
7.57
66.20
Classroom level
TCM–code focused
TM–meaning focused
TCM–meaning focused
CM–meaning focused
CM–meaning-focused play
2.91
0.57
8.90
0.16
0.48
3.83
1.65
7.69
0.72
1.53
Student level
TCM–code focused
TM–TCM meaning focused
CM–code focused
CM–meaning focused
CM–meaning-focused play
0.07
0.89
0.38
0.21
11.62
0.58
6.11
1.75
0.94
15.00
Note. CM meaning focused and CM meaning-focused play are summed
to create CM implicit decoding. TCM ⫽ teacher– child managed; TM ⫽
teacher managed; CM ⫽ child managed.
alphabet and letter–word and vice versa. To simplify the variable names,
we used shorter sector names so that each sector has the same name,
regardless of which outcome is the one of interest, keeping in mind that
explicit and implicit varies for our decoding and vocabulary outcomes.
Sector labels are provided in Table 1 and include both classroom and
student levels of play—TCM code focused, CM code focused, TM meaning focused, TCM meaning focused, CM code focused, CM meaning
focused, and CM meaning focused. Note that for alphabet and letter–word
recognition, CM meaning-focused and CM play are summed (CM implicit
meaning focused), whereas for vocabulary, they are separate variables
(play is implicit vocabulary).
Type of classroom, teacher, and home variables. A variable, Head
Start–state, was created to account for the effect of enrollment in a
preschool intervention program for children at risk of underachievement.
Students in the three Head Start–state classrooms were coded 1; students in
all other classrooms were coded 0 (Cohen & Cohen, 1983). Teacher and
parent variables were created on the basis of information from their
respective questionnaires and included teachers’ years of experience and
education as well as parents’ years of education.
Results
Analytic Strategies
Hierarchical linear modeling (HLM; Version 6.0; Raudenbush
& Bryk, 2002) was used to control for the nested nature of the data
(i.e., students are nested in classrooms). The effects of instruction
may be misestimated if the shared variance among children who
share the same teacher and classroom environment is not considered. Although classrooms were nested in teachers (e.g., some
teachers taught a morning and an afternoon class), three-level
models with students nested in classrooms nested in teachers
revealed no significant variance at the level of the teacher, so more
parsimonious two-level models were used except to test specific
teacher-level variables (e.g., years of experience). Student variables (e.g., fall score, small group, and individual instruction),
including Student-Level Instruction ⫻ Child interaction terms
CHILDREN’S EMERGENT LITERACY GROWTH
(e.g., Fall Letter–Word Score ⫻ TCM, Code-Focused, StudentLevel Variables) were entered at Level 1, and classroom variables
(e.g., classroom-level instruction) were entered at Level 2. In
HLM, interactions can be modeled between Levels 1 and 2 (e.g.,
␥21 . . . n[classroom instruction variables]j). Nonsignificant variables were trimmed to create more parsimonious models. A model
was built for each child outcome—alphabet, letter–word recognition, and vocabulary. A model for letter–word recognition, as an
exemplar, and additional information on interpreting HLM results
are provided in Appendix B.
The outcomes represent growth in scores (i.e., spring score
controlling for fall score). All continuous variables were centered
at the grand mean for the sample. Thus, coefficient values represent the effect of variable values above or below the mean for the
sample. In the exemplar model (see Appendix B), ␥00, the mean
spring letter–word recognition, is the fitted score for a child with
typical fall scores (i.e., the child’s score falls at the mean for the
sample), who is not enrolled in either a Head Start or state-funded
program and who receives typical amounts of instruction. Except
for the instruction variables and fall score, nonsignificant variables
were trimmed to create more parsimonious models.
On average, the preschoolers in this study exhibited ageappropriate gains in alphabet, letter–word, and vocabulary skills
(see Table 3). Children who began the year with stronger fall
scores generally demonstrated greater growth in alphabet, letter–
word, and vocabulary skills, whereas children who began the year
with weaker scores demonstrated less skill growth (see Tables 4, 5,
and 6). Mother’s education and whether children attended a Head
Start classroom had no systematic relation with any of the child
outcomes. The child outcomes were positively correlated (see
Table 7), with alphabet and letter–word most strongly positively
correlated with each other.
In this study, we asked (a) what is the nature of and variation in
amounts and types of language and literacy-related activities observed in these preschool classrooms? (b) In what ways are these
activities related to growth in preschoolers’ alphabet, letter–word
recognition, and vocabulary growth, and is there indication of
specificity of learning? In other words, do meaning-focused activities tend to predict vocabulary rather than alphabet or letter–word
recognition, and do emergent code-focused activities tend to predict alphabet and letter–word but not vocabulary growth? and (c)
Are there Child ⫻ Instruction interactions? We discuss our findings for each question below.
673
Nature and Variation in Preschool Language, Literacy,
and Other Activities
Overall, our hypothesis regarding amounts of language and
literacy activity was supported. Appreciable amounts of time were
spent in language and literacy activities, including play, relative to
other instruction and noninstructional activities (see Figure 2, top).
However, there was important variability among classrooms. On
average, children spent almost 15 min in language and literacy
activities and another 12 min in CM meaning-focused play, which
represents fully 30% of the observed classroom time. However, the
amount of language and literacy ranged from 0 to 81 min across
classrooms. On average, about 16 min were spent in transition,
which includes lining up to go outside or to the bathroom, changing activities, and so forth. About 15 min were spent listening to
the teacher explain an activity, talk about what was going to
happen throughout the day or week, establish class rules, and so
forth, which all fall within the code of orient– organize. Generally,
about 12 min were spent in art-related activities, another 5 min in
ritual (pledge of allegiance, etc.), and 4 min in music. Much less
time was spent in science and other activities (health related, gross
and fine motor, etc.).
A closer look at amounts of language and literacy activities (see
Figure 2, bottom) revealed that most of the activities were
meaning-focused activities. Excluding CM meaning-focused play,
most of the language and literacy activities were TCM. Only a very
small proportion of the instructional time was solely TM. Indeed,
the mean time for TM meaning-focused activities was only 0.57
min during whole-class activities (range ⫽ 0.00 –7.35) and even
less during small groups (0.02 min; range ⫽ 0.00 –2.62 min). Most
of the TCM activities occurred within a whole-class (i.e.,
classroom-level) context, whereas most of the CM activities occurred within a small-group–individual (i.e., student-level)
context.
Classroom-level instruction (all of the children in the class are
doing the same thing at the same time) consisted primarily of TCM
meaning-focused activities (9.5 min per day; see Figure 3, top). In
general, teachers spent about 4 min per day reading aloud with
students (less than 1 min of this time was without teacher– child
interaction), 3 min in discussion with students, 1.5 min sharing,
with the remaining time, about 1 min, split among vocabulary,
comprehension, concepts of print, and other language arts activities. Again, there was substantial variability among classrooms.
Table 3
Fall and Spring Descriptive Statistics for Student Outcomes
Fall
Spring
Student outcome
M
SD
Range
M
SD
Range
Alphabet naming
Letter–word recognition W
Letter–word standard score
Vocabulary W
Vocabulary standard score
11.21
334.80
118.00
466.59
112.00
8.19
25.08
21.00
15.79
12.00
0–26
270–400
71–191
374–502
67–141
15.79
350.27
118.00
472.82
112.00
8.13
31.98
17.00
13.36
12.00
0–26
130–464
79–193
417–506
63–148
Note.
Standard score test sample mean ⫽ 100 (SD ⫽ 15).
CONNOR, MORRISON, AND SLOMINSKI
674
Table 4
Hierarchical Linear Modeling Results for Alphabet Naming
Fixed effect
For intercept, ␤0
Mean spring alphabet raw score, ␥00
Overall amount (hours/week), ␥01
TCM–code focused–classroom level, ␥02
TCM–meaning focused–classroom level, ␥03
TM–meaning focused–classroom level, ␥04
CM–implicit code focused–classroom level, ␥05
For fall letter–word recognition score, ␤1
Effect, ␥10
For fall vocabulary score, ␤2
Effect, ␥20
For fall alphabet score, ␤3
Effect, ␥30
Effect of Overall Amount ⫻ Alphabet, ␥31
Effect of TCM–code focused–classroom level, ␥32
For TCM–code focused–student level, ␤4
Effect, ␥40
For TM–TCM–meaning focused–student level, ␤5
Effect, ␥50
For CM–code focused–student level, ␤6
Effect, ␥60
For CM–implicit code focused–student level, ␤7
Effect, ␥70
Random effects
Intercept, u0
Level 1, r
Coefficient
SE
15.72
0.12
0.20
⫺0.08
⫺0.0006
0.03
0.35
0.04
0.07
0.06
0.12
0.13
0.11
0.03
3.380(135)
.001
0.005
0.05
0.116(135)
.908
0.55
⫺0.008
⫺0.017
0.07
0.003
0.007
2.17
t(df)
45.28(28)
3.07
2.92
⫺1.42
⫺0.005
0.20
p
.000
.005
.007
.168
.996
.841
7.72(135)
⫺2.97
⫺2.33
.000
.004
.021
0.40
5.47(135)
.000
0.01
0.03
0.393(135)
.694
⫺0.09
0.14
⫺0.69(135)
.489
⫺0.01
0.02
⫺0.79(135)
.433
Variance
component
0.01
15.78
df
28
␹2
28.60
p
.433
Note. Deviance ⫽ 839.61. TCM ⫽ teacher– child managed; TM ⫽ teacher managed; CM ⫽ child managed;
u ⫽ classroom-level error; r ⫽ student-level error.
For example, time spent on vocabulary activities ranged from 0 to
4 min, although the mean for the sample was about 8 s per day.
TCM, code-focused, classroom-level activities accounted for
less than 3 min per day of class time, on average (see Figure 3,
bottom). Of this time, about 1 min 10 s per day was spent on
phonological awareness activities such as rhyming, elision, and
blending. Forty seconds were spent on alphabet activities, with an
additional 50 s on letter–sound correspondence activities. About
10 s per day, on average, were spent on spelling activities. Here
too, classrooms differed in, for example, time spent in phonological awareness activities varying from 0 to 10 min and time on
alphabet activities ranging from 0 min to about 5 min.
Time in CM, meaning-focused, classroom-level activities
ranged from 0 to 4 min (M ⫽ 9 s), and all of this time was spent
in independent emergent reading activities. For example, the students in the class selected a book from the classroom library and
read it (for most, this was emergent reading; Sulzby, 1985) or
looked at the pictures. There was some CM meaning-focused
play– classroom-level activity (0.5 min per day, range ⫽ 0 – 6 min
per day). There were no observed CM, code-focused, classroomlevel activities (e.g., phonics worksheets).
Student-level instruction accounted for a smaller proportion of
the time spent in language and literacy instruction, but this varied
substantially among classrooms. Most of this time was comprised
primarily of CM meaning-focused play (11.3 min per day, range ⫽
0.0 – 66.2). Much less time was spent on TCM meaning-focused
activities (see Figure 3, bottom), but, again, there was variability in
amount across classrooms (M ⫽ 0.88 min, range ⫽ 0 – 65 min per
day). Of this time, almost half (46 s) was spent in small-group
sharing time. A generally negligible amount of time was spent on
TCM code-focused activities (M ⫽ 0.07 min; see Figure 3, bottom), but this varied across classrooms ranging from 0 min to more
than 6 min per day. Most of this time was spent in alphabet
activities and included writing the letters of the alphabet. CM
code-focused activities (M ⫽ 0.37 min, range ⫽ 0.0 –17.5 min)
included alphabet and handwriting activities. CM meaningfocused activities (M ⫽ 0.21 min, range ⫽ 0.0 –7.6 min per day),
including independent emergent reading activities, split evenly
between individual student and small-group contexts; each context
ranged from 0 min to more than 4 min per day across classrooms.
Children within the same classroom experienced widely different amounts and types of language and literacy activities. For
example, in one classroom with 3 target children, Child A spent
more than 17 min in CM, code-focused, student-level activities;
almost 2 min in CM meaning-focused play; and just over 3 min in
TCM code-focused activities. In contrast, Child B spent just 3 min
in CM, code-focused, student-level activities; 16 min in CM
meaning-focused play; and more than 6 min in TCM code-focused
activities. This was while, at the same time, Child C spent 0 min
in CM code-focused activities, 3 min in CM meaning-focused
play, and 0 min in TCM code-focused activities (most of the time
was spent in art activities). It is interesting to note that Child C
CHILDREN’S EMERGENT LITERACY GROWTH
675
Table 5
Hierarchical Linear Modeling Results for Letter–Word Recognition
Fixed effect
For intercept, ␤0
Mean spring letter–word W, ␥00
Overall amount (hours/week), ␥01
TCM–code focused–classroom level, ␥02
TCM–meaning focused–classroom level, ␥04
TM–meaning focused–classroom level, ␥03
CM–implicit code focused–classroom level, ␥03
For fall letter–word recognition W score, ␤1
Effect, ␥10
Effect of TCM–Code Focused–Classroom Level ⫻ Fall Letter–Word Score, ␥11
Effect of TCM–Meaning Focused–Classroom Level ⫻ Fall Letter–Word Score, ␥12
For fall vocabulary score, ␤2
Effect, ␥20
Effect of Overall Amount (hours/week) ⫻ Fall Vocabulary Score, ␥21
For fall alphabet score, ␤3
Effect, ␥30
For TCM–code focused–student level, ␤4
Effect, ␥40
For TM–TCM–meaning focused–student level, ␤5
Effect, ␥50
For CM–code focused–student level, ␤6
Effect, ␥60
For CM–implicit code focused–student level, ␤7
Effect, ␥70
For boy, ␤8
Effect, ␥80
Random effect
Intercept, u0
Level 1, r
Coefficient
SE
t(df)
p
345.64
0.44
0.38
⫺0.15
2.08
⫺0.13
2.08
0.11
0.38
0.25
1.11
1.14
165.93(28)
4.45
1.01
⫺0.60
1.87
⫺0.12
.000
.000
.324
.555
.08
.910
0.55
⫺0.03
0.02
0.08
0.01
0.009
6.45(137)
⫺2.20
2.41
.000
.029
.018
0.27
⫺0.02
0.14
0.009
2.02(137)
⫺2.43
.045
.017
1.08
0.30
3.80(137)
.000
3.70
1.67
2.22(137)
.028
⫺0.28
0.09
⫺3.05(137)
.003
0.80
0.86
0.93(137)
.355
⫺0.03
0.07
⫺0.49(137)
.622
7.64
3.22
2.38(139)
.019
Variance
df
␹2
0.12
390.53
28
14.77
p
⬎.50
Note. Deviance ⫽ 1,356. TCM ⫽ teacher– child managed; TM ⫽ teacher managed; CM ⫽ child managed; u ⫽ classroom-level error; r ⫽ student-level
error.
began the school year knowing all the letters in the alphabet,
whereas Child A and Child B knew only 1 and 7 letters, respectively. By the end of the year, they knew 19 and 18 letters,
respectively.
Correlations Among Instructional Strategies
There was some systematic pattern among the instructional
strategies. None of the student-level instruction variables were
correlated, with one notable exception. Teachers who spent more
time in TM, meaning-focused, student-level activities also tended
to provide more time in CM, meaning-focused play, student-level
activities (r ⫽ .43, p ⫽ .011). At the classroom level, teachers who
provided more time in TCM, meaning-focused, classroom-level
activities also provided more time in CM, meaning-focused,
classroom-level activities (r ⫽ .46, p ⬍ .001). Plus, teachers who
provided more time in TCM, code-focused, classroom-level activities also tended to provide more time in CM, code-focused,
classroom-level activities.
Associations between classroom- and student-level instruction
variables were computed using HLM, with each student-level
instruction type as the outcome and each classroom-level instruction type as a predictor. Because this required 30 separate models,
a Bonferroni correction was applied only to these analyses, and
alpha was set at .001 (http://home.clara.net/sisa/bonfer.htm). Re-
sults revealed that teachers who provided more time in CM,
meaning-focused, student-level activities also provided more time
in CM, meaning-focused, classroom-level activities (␥01 ⫽ .605,
p ⬍ .001).
There did not appear to be any trade-off between code- and
meaning-focused activities at either the student or classroom level.
For example, teachers who provided children with more time in
meaning-focused activities were no more or less likely to provide
more time in code-focused activities.
Overall Amount of Preschool
Children could attend either half- or whole-day classrooms and
could attend anywhere from 2 to 5 days per week on a regular
basis. Thus, the overall amount of time preschool children could
attend varied by classroom from 6 to 30 hr per week, with a mean
of 15 hr per week. The number of hours per week children attended
preschool related to both alphabet and letter–word recognition
score growth but not vocabulary growth (see Tables 4, 5, and 6 and
Figures 4, top, and 5, top). Generally, children who attended
preschool more hours per week achieved stronger alphabet and
letter–word score growth than did children who attended preschool
for fewer hours per week. There was no significant relation between hours per week attended and vocabulary score growth.
Generally, however, children with weaker fall vocabulary scores
CONNOR, MORRISON, AND SLOMINSKI
676
Table 6
Hierarchical Linear Modeling Results for Spring Vocabulary
Fixed effect
For intercept, ␤0
Mean spring vocabulary W score, ␥00
Overall amount (hours/week), ␥01
TCM–code focused–classroom level, ␥02
TCM–meaning focused–classroom level, ␥03
TM–meaning focused–classroom level, ␥04
CM–meaning focused–classroom level, ␥05
CM–meaning-focused play–classroom level, ␥05
For child age, ␤1
Effect, ␥10
For fall vocabulary score, ␤2
Effect, ␥20
Effect of TCM–Code Focused–Classroom Level ⫻ Fall Vocabulary, ␥21
Effect of TCM–Meaning Focused–Classroom Level ⫻ Fall Vocabulary, ␥22
Effect of TCM–Meaning-Focused Play–Classroom Level ⫻ Fall Vocabulary, ␥23
For fall alphabet score, ␤3
Effect, ␥30
For TCM–code focused–student level, ␤4
Effect ␥40
For TM–TCM–meaning focused–student level, ␤5
Effect, ␥50
For CM–code focused–student level, ␤6
Effect, ␥60
For CM–meaning focused–student level, ␤7
Effect, ␥70
For CM–meaning-focused play–student level, ␤8
Effect, ␥80
Coefficient
SE
t(df)
473.04
⫺0.02
0.12
0.13
0.79
2.05
0.60
0.94
0.10
0.18
0.11
0.35
0.93
0.46
501.88(27)
⫺0.15
0.70
1.23
2.27
2.21
1.29
.000
.882
.497
.228
.031
.036
.210
3.17
1.65
1.91(33)
.063
0.035
0.007
0.005
0.03
12.10(137)
4.15
⫺2.72
⫺3.54
.000
.000
.008
.001
0.43
0.03
⫺0.01
⫺0.09
Random effect
p
0.23
0.10
2.45(137)
.015
⫺1.26
0.76
⫺1.64(137)
.102
0.06
0.06
0.89(137)
.377
⫺0.10
0.30
⫺0.33(138)
.742
⫺0.56
0.52
⫺1.07(137)
.285
⫺0.02
0.04
0.48(137)
.631
Variance
df
␹2
p
10.69
0.73
66.98
25
31
37.34
21.49
.053
⬎.50
Intercept, u0
Child age, u1
Level 1, r
Note. Deviance ⫽ 1,102.55. TCM ⫽ teacher– child managed; TM ⫽ teacher managed; CM ⫽ child managed; u ⫽ classroom-level error; r ⫽ student-level
error.
and vocabulary skills. Moreover, the relations were specific. In
all cases, when there was a main effect of instruction (the
instruction had an effect on student growth regardless of child
characteristics), explicit code-focused activities positively predicted alphabet and letter–word recognition, and explicit
meaning-focused activities positively predicted vocabulary. For
example, children who spent more time in classroom- and
student-level TCM code-focused instruction, on average,
learned more letters of the alphabet than did children who spent
were more likely to spend more hours per week attending preschool than were children with stronger fall vocabulary scores
(␥01 ⫽ –.34, p ⬍ .001).
Relations Among Instructional Strategies and Child
Outcomes
The language and literacy activities that we observed in these
classrooms had a systematic and significant relation with students’ growth in alphabet knowledge, letter–word recognition,
Table 7
Correlations Among Child Outcome Variables
Variable
1.
2.
3.
4.
5.
6.
Letter–word identification W fall
Vocabulary W fall
Alphabet raw score fall
Letter–word identification W spring
Vocabulary W spring
Alphabet raw score spring
* p ⬍ .05.
** p ⬍ .01.
1
2
3
4
5
6
—
.314**
—
.837**
.277**
—
.692**
.224**
.680**
—
.345**
.654**
.377**
.358**
—
.752**
.193*
.806**
.696**
.287**
—
CHILDREN’S EMERGENT LITERACY GROWTH
677
18
16
Minutes per day
14
12
10
8
6
4
2
O
th
er
Tr
an
sit
io
n
nt
O
rie
it u
al
R
M
us
ic
Ar
t
en
ce
Sc
i
M
at
h
ay
Pl
La
ng
ua
g
e
&
Li
te
ra
cy
0
class
student
14
Minutes per day
12
10
8
Student
6
Class
4
2
0
TCM-CF
TM-MF TCM-MF CM-CF
CM-MF
CM-MFPlay
Figure 2. Top: Mean amounts (minutes per day) of all activities coded. Between 60 and 120 min of classroom
time was coded for each classroom. Time spent outside of the classroom was not coded. Bottom: Mean amounts
(minutes per day) for each of the instructional strategies. Classroom-level activities are shown in black, and
student-level activities are shown in white. TCM ⫽ teacher– child managed; CF ⫽ code focused; TM ⫽ teacher
managed; MF ⫽ meaning focused; CM ⫽ child managed.
less time in these activities (see Table 4). For letter–word
recognition, children who spent more time in TCM, codefocused, student-level activities demonstrated greater growth in
scores than did children who spent less time in these activities
(see Table 5).
For vocabulary, children who spent more time in TCM,
meaning-focused, classroom-level activities and less time in TCM,
code-focused, student-level activities exhibited greater vocabulary
growth than did children who spent less time in the meaningfocused activities and more time in the code-focused activities.
The effect size for amount (minutes/day) of TCM, code-focused,
student-level instruction was negligible (see Table 8). The effect
size for amount of TCM, meaning-focused, classroom level instruction was greater for children with weaker fall vocabulary
skills than it was for children with stronger fall vocabulary skills
(see Figure 6 and Table 8).
Child ⫻ Instruction Interactions
Although there was evidence of specificity of learning in the
main effects, our hypothesis regarding specificity of instruction
as it related to child outcomes was not entirely supported. As
we anticipated, there were Child ⫻ Instruction interactions; the
effect of some instructional strategies depended on children’s
skills at the beginning of the year. Because of these interactions,
generally, the specificity of instruction was less apparent for
children with stronger fall language and literacy skills. For
example, children with stronger fall vocabulary scores demon-
CONNOR, MORRISON, AND SLOMINSKI
678
4
TCM-MF Minutes per Day
3.5
3
2.5
2
1.5
1
0.5
0
Read aloud w discussion
Read aloud
Discussion
Class
Sharing
Vocabulary,
comprehension, COP,
other
Student
1.4
TCM-CF Minutes per day
1.2
1
0.8
0.6
0.4
0.2
0
Phonological awareness
Alphabet
Letter-sound
Class Student
Spelling
CHILDREN’S EMERGENT LITERACY GROWTH
For each of our outcomes—alphabet, letter–word recognition,
and vocabulary—there were Child ⫻ Instruction interactions. Because these Child ⫻ Instruction interactions differed for each of
the outcomes, we present the results for each model separately
below.
Spring Alphabet Score
26.00
Higher fall alphabet score
21.00
Alphabet
16.00
Lower fall alphabet score
11.00
6.00
6.00
12.00
18.00
24.00
30.00
Hours per Week
26.00
Spring Alphabet Score
679
Children in classrooms that spent more time in TCM, codefocused, classroom-level activities achieved stronger spring alphabet scores, on average, but these effects were greater for students
who knew fewer letters in the fall (e.g., 4) compared with children
who knew more letters (e.g., 18; see Table 4 and Figure 4, bottom).
TCM, code-focused, student-level activities had a greater effect
size (d ⫽ .28 for 1 min) than its classroom-level counterpart. For
every 10 min per day above the mean of TCM, code-focused,
student-level activities students received, their alphabet score increased by almost 3 letters by spring, and, on average, this was the
case for all students regardless of their fall alphabet score.
Higher fall alphabet score
21.00
Letter–Word Recognition
16.00
Lower fall alphabet score
11.00
6.00
2.25
6.00
9.75
13.50
TCM-CF-cl Minutes/day
Figure 4. Predicting spring alphabet knowledge. Top: Student Fall Alphabet ⫻ Overall Amount (hours per week) interaction effect on fitted
spring alphabet scores. Bottom: Student Fall Alphabet ⫻ TCM, CodeFocused, Classroom-Level Amount (minutes per day) interaction effect on
spring alphabet scores. Higher fall alphabet scores (boldface line) fall at the
75th percentile for the sample (about 18 letters), whereas lower fall
alphabet scores fall at the 25th percentile of the sample (about 4 letters). All
other variables are held constant at their sample mean. TCM ⫽ teacher–
child managed; CF ⫽ code focused; cl ⫽ classroom level.
strated greater vocabulary growth when they spent more time
in TCM meaning-focused activities and more time in TCM
code-focused activities. In contrast, for children with
weaker fall vocabulary scores, TCM meaning-focused activities, but not TCM code-focused activities, were related to
increases in vocabulary growth. Similar findings held for children’s letter–word recognition skill growth. The details are
provided below.
Students who began the preschool year with lower letter–word
recognition scores tended to demonstrate greater letter–word
growth in classrooms that spent more time in TCM, code-focused,
classroom-level activities, whereas students with higher letter–
word recognition scores exhibited less growth (see Table 5 and
Figure 5, middle). The opposite pattern was observed for amount
of time spent in TCM, meaning-focused, classroom-level activities
(see Table 5, bottom). Students with lower letter–word recognition
scores in the fall demonstrated less letter–word growth in classrooms in which a greater amount of time was spent in TCM
meaning-focused activities. In contrast, students with higher fall
letter–word recognition scores demonstrated greater letter–word
recognition growth when they participated in classrooms with
greater amounts of TCM, meaning-focused, classroom-level
activities.
Vocabulary
Although classroom-level activities systematically related to
students’ vocabulary growth, student-level instructional activities
had no significant relation. On average, students in classrooms that
spent more time in TM, TCM, and CM, meaning-focused,
classroom-level activities as well as CM, meaning-focused play,
classroom-level activities showed stronger vocabulary score
growth than did students in classrooms that spent less time in such
activities, but there were Child ⫻ Instruction interactions (see
Table 6 and Figure 6). Children with weaker fall vocabulary scores
demonstrated less vocabulary growth when they spent more time
in TCM, code-focused, classroom-level activities, whereas students with stronger fall vocabulary scores demonstrated greater
Figure 3 (opposite). Top: Mean amounts of time in specific activities for teacher– child-managed, meaningfocused (TCM–MF) activities. Bottom: Mean amounts of time in specific activities for TCM code-focused (CF)
activities. Classroom-level activities are shown in black, and student-level activities are shown in white. COP ⫽
concepts of print.
CONNOR, MORRISON, AND SLOMINSKI
680
356.3
Higher fall vocabulary score
Spring Letter-Word
352.5
Lower fall vocabulary score
348.7
344.9
341.1
6.00
12.00
18.00
24.00
30.00
Hours per Week
360.0
Discussion
This study examined the nature of specific preschool activities
in which teachers and children engaged and the relation of these
activities to preschoolers’ alphabet, letter–word recognition, and
vocabulary growth. Our discussion focuses on two key findings:
(a) There was substantial variability in the amounts and types of
language and literacy activities children experienced, and (b) these
activities systematically related to preschoolers’ language and
emergent literacy skills in a complex, interactive fashion.
Higher letter-word recognition
score
Spring Letter-Word
353.7
347.4
Lower fall letter-word recognition
score
341.2
334.9
2.25
6.00
9.75
13.50
TCM-CF-cl Minutes/day
Higher fall letter-word
recognition score
365.5
355.3
Spring Letter-Word
vocabulary growth when they spent more time in such activities
(see Table 6 and Figure 6, top). In general, all students achieved
greater vocabulary growth in classrooms that spent more time in
CM and TM, meaning-focused, classroom-level activities, regardless of fall vocabulary score. More time in TCM, meaningfocused, classroom-level activities (see Figure 6, middle) and CM,
meaning-focused play, classroom-level activities (see Figure 6,
bottom) was related to greater student vocabulary growth, but
students with lower fall vocabulary scores demonstrated greater
growth in classrooms with more time in such activities than did
students with higher fall vocabulary scores. Overall, students with
lower fall vocabulary scores exhibited greater vocabulary growth
only when they experienced more time in TCM, TM, and CM,
meaning-focused, classroom-level activities, including play,
whereas students with higher vocabulary scores demonstrated
stronger vocabulary growth, with more time spent in TCM codefocused activities and/or TCM, TM, and CM, meaning-focused,
classroom-level activities.
Variability in Amount and Type of Instruction
Although, overall, these preschool classrooms would be judged
high quality on the basis of the teachers’ credentials and years of
experience, teacher– child ratios, physical facilities, and certification, there was substantial variability across and within classrooms
in the amount and type of language and literacy learning opportunities offered to students. One class spent almost 90 min in
language and literacy activities, including play, whereas another
spent only 4 min. Thus, children, even in the same school district,
had widely different preschool language and literacy experiences.
Classrooms met anywhere from 2 to 5 days per week and from
3 to 6 hr per day. Children who attended preschool for more hours
per week demonstrated stronger alphabet and letter–word growth,
overall, than did children who attended for less time per week.
345.0
Lower fall letter-word recognition
score
334.8
324.5
6.00
13.67
TCM-MF-cl
21.34
29.01
Minutes/day
Figure 5. Predicting spring letter–word recognition. Top: Student Fall
Vocabulary ⫻ Overall Amount (hours per week) interaction effect on fitted
spring letter–word recognition scores. Higher fall vocabulary scores (boldface line) fall at the 75th percentile for the sample, whereas lower fall
vocabulary scores fall at the 25th percentile of the sample. All other
variables are centered at their sample mean. Middle: Student Fall Letter–
Word Recognition Score ⫻ Amount (minutes per day) of TM, CodeFocused, Classroom-Level Instruction. Bottom: Student Fall Letter–Word
Recognition Score ⫻ Amount (minutes per day) of TM, Meaning-Focused,
Classroom-Level Instruction. Higher fall letter–word recognition scores
(boldface line) fall at the 75th percentile for the sample, whereas lower fall
letter–word recognition scores fall at the 25th percentile of the sample. All
other variables are centered at their sample mean. TM ⫽ teacher managed;
TCM ⫽ teacher– child managed; CF ⫽ code focused; cl ⫽ classroom level.
CHILDREN’S EMERGENT LITERACY GROWTH
681
Table 8
Summary of Effects of Amount and Type of Instruction on Student Spring Outcomes
Letter–word
recognition
Alphabet
Child fall score status
outcome
Lower
fall
Higher
fall
Lower
fall
Vocabulary
Higher
fall
Lower
fall
Higher
fall
⫺
⫹
0
⫹⫹
.06
.16
⫹⫹
⫹
⫹
.06
.16
0
Classroom level (minutes/day)
TCM–code focused
TCM–meaning focused
TM–meaning focused
CM–meaning focused
CM–meaning focused play
⫹
⫹⫹
⫹
⫺
Student level (minutes/day)
TCM–code focused
TM–TCM–meaning focused
CM–code focused
CM–meaning focused
CM–MF play
.28
.28
.12
⫺.008
.12
⫺.008
Note. Exact effect size depends on the amount of instruction and, when there is an interaction, the students’
fall scores. Unless there is a significant Child ⫻ Instruction interaction, effect sizes are for 1 min per day, above
the sample mean for students whose fall scores lie at the mean for the sample. For Child ⫻ Instruction interaction
effects, ⫹ indicates generally positive effect, ⫹⫹ indicates relatively more positive effect, ⫺ indicates generally
negative effect, and 0 indicates no significant effect for amounts of instruction or overall amount above the
sample mean. Please refer to the interaction graphs (see Figures 4 – 6) for more precise estimates. All effects are
significant at p ⬍ .05. TCM ⫽ teacher– child managed; TM ⫽ teacher managed; CM ⫽ child managed.
Moreover, this difference was stronger for students who knew
fewer letters and had weaker vocabulary scores at the beginning of
the school year than it was for students who began the school year
with stronger skills. This finding supports research demonstrating
that greater amounts of time per week in high-quality preschool
overall (i.e., intensity; Nelson et al., 2003) is related to stronger
outcomes for preschoolers.
In a few classrooms, there was virtually no focus on language
and emergent literacy, either explicit or implicit, whereas in other
classes, the entire day was filled with meaningful opportunities for
children to engage with written text and oral language. It is
interesting to note that there was also appreciable variability in
language and literacy activities, including play, within classrooms.
Children in the same classroom at the same time were experiencing different learning opportunities. Some children experienced
predominately nonliteracy learning opportunities (e.g., art or transition), whereas others spent substantial amounts of time in explicit
and implicit literacy activities. These findings are important because language and literacy activities related to children’s vocabulary, alphabet, and decoding skill growth. This kind of variability
has been observed in other preschool classrooms (NICHD
ECCRN, 2003; Whitehurst, Epstein, et al., 1994).
Multiple Dimensions of Instruction and Student Outcomes
The types of language and literacy activities preschoolers experienced, when viewed multidimensionally, related to their language and literacy skill growth.
Meaning Focused Versus Code Focused and Explicit
Versus Implicit
Overall, explicit code-focused activities predicted alphabet and
letter–word growth, whereas explicit meaning-focused activities
predicted vocabulary growth. This finding directly parallels findings for parent and home literacy involvement in children’s literacy development (Senechal & LeFevre, 2002). Formal or explicit
code-focused parent– child interactions are related to children’s
growth in emergent reading, whereas informal or implicit codefocused (i.e., meaning-focused) interactions related to growth in
vocabulary and language skills.
However, the specificity was most evident for children who
started the school year with weaker skills for whom only amount
of explicit code-focused activities positively related to growth in
their letter–word skills. For children with stronger fall letter–word
skills, both code-focused and meaning-focused activities contributed to their letter–word growth. A similar pattern was observed
for vocabulary— only meaning-focused activities positively predicted vocabulary growth for children with weaker fall vocabulary
skills, whereas both code- and meaning-focused activities related
to vocabulary growth for children with stronger fall scores. These
findings may offer one possible reason that reading and vocabulary
skills are observed to be highly stable, especially after kindergarten
(Hart & Risley, 1995; Lonigan, Burgess, & Anthony, 2000). Children with stronger language and emergent literacy skills may have
more opportunities to learn during both code- and meaningfocused activities (Tuyay, Jennings, & Dixon, 1995), which may
contribute to the Matthew effect (Stanovich, 1986). The practical
implication is that children with weaker skills need more, not
CONNOR, MORRISON, AND SLOMINSKI
682
Spring Vocabulary Score
480.5
Higher fall vocabulary
score
477.6
474.8
471.9
Lower fall vocabulary score
469.0
0
3.75
7.50
11.25
15.00
TCM-CF-cl Minutes per day
477.0
Spring Vocabulary Score
Higher fall vocabulary score
474.8
472.6
Lower fall vocabulary score
470.4
468.2
0
7.67
15.34
23.01
30.68
TCM-MF-cl Minutes per day
477.0
fewer, opportunities to gain critical language and emergent literacy
skills in preschool through explicit targeted experiences.
Play, an implicit meaning-focused activity, positively contributed to children’s vocabulary growth but was not associated with
the code-focused outcomes, alphabet or letter–word recognition.
This finding runs counter to claims that play directly supports
children’s emergent literacy (Rowe, 1988) if language and emergent literacy are considered two discrete constructs (Lonigan et al.,
1999; NICHD ECCRN, 2005; Senechal & LeFevre, 2002). The
amount of time children spent in play did predict vocabulary
growth, which makes sense as one considers the language development implications of symbolic play (Pelligrini & Galda, 1993)
and peer interactions. Thus, play appears to relate to preschoolers’
emergent literacy growth indirectly through its relation with vocabulary growth.
An intriguing finding is that the positive association between
play and vocabulary growth was greater for children with weaker
fall vocabulary skills than it was for children with stronger vocabulary skills. It is possible that interactions during dramatic play
with more able peers and with the teacher may have supported
students’ vocabulary growth. It may also be that children with
strong fall vocabulary skills already had the core vocabulary made
available in the dramatic play centers, for example, whereas for
children with weaker vocabulary skills, these experiences provided
access to vocabulary not available to them previously through
home or child-care literacy experiences. Another possible explanation may be that because the rate of vocabulary development is
highly variable among children during the preschool years (Locke,
1997; Scarborough, 2001), children with weaker vocabulary skills
in the fall may have just started the documented burst of vocabulary development (Bates, 1999; Fenson et al., 1993; Scarborough,
2001). Opportunities for play may have offered additional support
for their vocabulary development leading to greater growth. Children with stronger fall vocabulary skills may have completed this
developmental burst, and thus play had a less evident effect on
their vocabulary growth. More research is needed.
Higher fall vocabulary
Spring Vocabulary Score
Classroom-Level Versus Student-Level Instruction
475.2
473.3
Lower fall vocabulary
471.5
469.6
0
1.55
3.09
4.64
6.18
Although student-level instruction did not relate to preschoolers’ vocabulary growth, whole-class instruction did. Both
classroom- and student-level instruction were positively related to
alphabet and letter–word growth. Whole-class, rather than smallgroup–individual, meaning-focused activities may have provided
more opportunities for students to interact with peers in meaningful ways, offering a bridge to more complex vocabulary and syntax
(Wharton-McDonald, Pressley, & Hampston, 1998), which would
tend to support vocabulary development. It is also possible that this
finding is an artifact of our naturalistic observational procedures.
With the exception of play, most of the language and emergent
literacy instruction was classroom level, and most of this was
TCM-MF-Play-cl Minutes per day
Figure 6. Top: Predicting spring vocabulary. Student Fall Vocabulary
Score ⫻ Amount (minutes per day) of TCM, Code-Focused, ClassroomLevel Instruction. Middle: Student Fall Vocabulary Score ⫻ Amount
(minutes per day) of TCM, Meaning-Focused, Classroom-Level Instruction. Bottom: Student Fall Vocabulary ⫻ Amount (minutes per day) of
Child-Managed/Meaning-Focused Play, Classroom-Level Instruction.
Higher fall vocabulary scores (boldface line) fall at the 75th percentile for
the sample, whereas lower fall vocabulary scores fall at the 25th percentile
of the sample. All other variables are centered at their sample mean.
TCM ⫽ teacher– child managed; CF ⫽ code focused; cl ⫽ classroom level;
MF ⫽ meaning focused.
CHILDREN’S EMERGENT LITERACY GROWTH
meaning focused. There may not have been sufficient variability in
student-level, explicit meaning-focused instruction within classrooms to detect effects on vocabulary.
With regard to preschoolers’ alphabet and letter–word skill
growth, overall, student-level instruction yielded a much larger
effect size, almost tenfold, for children’s alphabet and letter–word
recognition skill growth than did whole-class instruction (see
Table 7). Moreover, although there were Child ⫻ Instruction
interactions at the classroom level, there were none at the student
level. Thus, instructional strategies provided in small-group–
individual settings were related to greater alphabet and letter–word
skill growth for all children, regardless of their entering skill level,
in contrast to whole-class activities. Small-group–individual instruction and providing extra help to school-age children who need
it are hallmarks of effective teachers (Wharton-McDonald et al.,
1998), and these results appear to support these findings for
preschool-age students. It may be that small-group–individual
settings are more conducive to implementing effective instruction.
In these settings, teachers who are cognizant of their students’
academic strengths and weaknesses may be better able to individualize instruction, targeting instructional strategies to each student’s needs, including providing more time for those who need it.
TCM, TM, and CM Instruction
TM, TCM, and CM activities were all positively associated with
vocabulary growth, whereas only TCM activities were associated
with alphabet and letter–word growth. These findings reinforce
current notions about the differing sources of language versus
literacy development (Geary, 1995; Snow, 1983). Language acquisition is universal across cultures and appears to be learned
implicitly through interactions with others—teachers, parents, and
peers. In contrast, reading varies across cultures and must be
explicitly taught to most children. Thus, according to our findings,
the active involvement of the teacher with the students was important for alphabet and letter–word growth.
Limitations
There are limitations to our study and hence to our interpretations. First, we videotaped only 1 day of instruction and although
these videotaped observations appeared to align with more frequent informal observations, still, they provided only a snapshot of
the activities the preschoolers experienced. Second, we examined
the amount and type of preschool emergent literacy activities
multidimensionally but did not describe how this instruction was
implemented beyond attempting to capture the extent to which
teachers and children interacted during the activity. How these
activities are implemented, the degree to which the teacher is
organized and clear in her or his instruction, and her or his warmth
and sensitivity to students, among others, are nonetheless important predictors of child outcomes that we did not consider (NICHD
ECCRN, 2002, 2003, 2004) but will in future studies.
Third, the present study design does not permit strong causal
inferences. We used naturally occurring variation in teachers’
practices and students’ characteristics to identify the correspondence between classroom instruction and student outcomes. Thus,
other unmeasured variables may have been responsible for the
effects we documented. For example, preschool experiences may
683
have had nominal effects for students who began the year with
strong vocabulary and emergent literacy skills. Rather, their parents and the home literacy environment provided may have been
responsible for their language and literacy development. Additionally, we did not take into account nonacademic classroom practices
(like organization) or child social outcomes (such as selfregulation), which, research indicates, contribute to the classroom
environment and student outcomes (Cameron, 2004; McClelland
& Morrison, 2003). Ultimately, rigorous intervention studies with
random assignment of participants to treatment and control are
needed to make strong causal claims.
The Role of Explicit Instruction and Play in Preschool
There is a diversity of beliefs about teaching preschoolers how
to read (Bowman et al., 2001; Bredekemp & Copple, 1997; Connor, 2002; Graue et al., 2004; Roskos & Christie, 2000; Stipek et
al., 1995). Our results, along with other preschool research (Graue
et al., 2004; Whitehurst, Epstein, et al., 1994), support the idea that
explicitly teaching students letters, letter sounds, phonological
decoding, and phonological awareness, in conjunction with rich
meaning-focused experiences, including play, may yield stronger
student outcomes than programs that focus solely on one to the
exclusion of the other. Explicit code-focused activities, in which
teachers and students work together, may be especially important
for students with weaker literacy skills at the beginning of the year.
On the basis of our observations of the classrooms in this study,
these explicit code-focused activities were consistently delivered
in interactive and supporting ways. No drilling of students’ skills
or long time spent completing worksheets was observed. Rather,
alphabet and letter–sound activities, for example, were embedded
in songs, craft activities, and games. Opportunities to practice
these skills were provided in dramatic play centers (e.g., reading
menus or writing a prescription when pretending to be a doctor),
although, our results suggest that, relative to emergent reading
development, the greater potential benefit to students provided
through play is in vocabulary development.
Explicit meaning-focused activities contributed significantly to
students’ decoding and vocabulary growth as well. Thus, reading
to children, sharing, discussion, and other meaning-focused activities found in high-quality preschool programs should not be
abandoned in favor of an exclusive focus on code-related
activities.
Our results reveal that the impact of selected patterns of instruction—particularly when provided in whole-class settings—may
depend on preschoolers’ entering vocabulary and emergent reading skills. Thus, designing effective instruction for all children,
particularly in light of the substantial heterogeneity across and
within preschool classrooms, may prove challenging. One suggestion for practice may be to provide explicit and implicit meaningfocused activities primarily in whole-class settings, in which their
impact appears to be greater on students’ vocabulary growth. In
contrast, another suggestion is to provide emergent code-focused
activities in small-group settings in which they can be tailored for
each student on the basis of their vocabulary and emergent reading.
Additionally, no CM code-focused activities related to student
outcome growth, but TCM code-focused activities did. This suggests that explicit code-focused instruction might be more effective when teacher and students interact with each other, whereas
CONNOR, MORRISON, AND SLOMINSKI
684
children working alone on phonics worksheets, for example,
should be avoided. All of this would need to be tested. Efforts are
underway to develop appropriate literacy-based preschool curricula. These data were collected in classrooms that used one preschool curriculum. Indeed, other curricula might provide alternative patterns of experience for children and generate different
student outcomes. More research regarding the efficacy of such
efforts to improve students’ short- and long-term literacy outcomes
using randomized field trials, such as the Individualizing Student
Instruction project (Connor & Morrison, 2006), is warranted.
Research Implications
As we strive to define high-quality preschool experiences, these
results reveal that what might be considered high quality for a
typically developing child or a preschooler with stronger vocabulary and decoding skills may differ substantially from a highquality preschool experience for a preschooler at risk for underachievement because of poverty or other risk factors. Students at
risk typically begin preschool with weaker vocabulary and emergent literacy skills (Hart & Risley, 1995; Snow et al., 1998).
Observing preschool classrooms across multiple dimensions and
measuring the effectiveness of preschool experiences in improving
students’ cognitive and social outcome growth may offer more
precise metrics of quality than a focus solely on more global
curriculum-level measures (e.g., teacher directed vs. child centered) and resources (staff:child ratios).
The video-coded classroom observation methods utilized in this
study demonstrate that systematic, multidimensional, and multilevel examination of classroom participants (teachers and students)
and the activities in which they engage are both feasible and
important. As our results show, children in the same classroom do
not experience the same amounts and types of language and
literacy activities. This kind of analysis would not have been
possible without new technology— both statistical (e.g., HLM)
and observational (video and software). Although still expensive
and time consuming, the technology is continuing to improve.
Achieving a detailed understanding of exactly what is occurring in
classrooms, rather than continuing to treat this important proximal
influence like a “black box,” appears to be worth the time and
expense, especially given society’s real and potential investment in
preschool interventions (Gormley, Gayer, Phillips, & Dawson,
2004; Sawhill, 1999) and new universal prekindergarten initiatives
(e.g., Florida).
The children in this study represent a more diverse sample than
is found in many preschool studies (e.g., Conyers et al., 2003;
Reynolds et al., 2004). For example, 5% of our sample attended
Head Start classrooms and the rest attended fee-for-service classrooms, parent educational levels ranged from less than high school
to advanced degrees, and fully 10% of the children spoke a
language other than English at home. This should be kept in mind
as these results are interpreted. A more homogenous sample (e.g.,
only children enrolled in Head Start) would certainly have yielded
very different results. Indeed, finding Child ⫻ Instruction interactions may have been related to having a more diverse sample. We
consider this a strength of this study, especially as policymakers
call for universal prekindergarten and expanded preschool experiences for all children (Disimone, Payne, Fedoravicius, Henrich, &
Finn-Stevenson, 2004; Saluja, Early, & Clifford, 2001; Sawhill,
1999; Snow et al., 1998). Preschool research that moves beyond a
specific focus on children at risk for academic underachievement
offers the opportunity to better understand how to deliver effective
preschool instruction to all children and the underlying causal
mechanism of the benefits associated with high-quality preschool
experiences.
In summary, this study examined more closely the language and
literacy activities preschoolers experienced in their classrooms and
the relation of these experiences to their alphabet, letter–word
recognition, and vocabulary development. Our purpose was to
begin to elucidate the underlying causal mechanisms of the clearly
documented benefits of high-quality preschool experiences on
students’ later academic success. Part of students’ growth in alphabet, letter–word recognition, and vocabulary observed in this
study was explained by the vocabulary and early reading skills
they brought to the classroom. These were, presumably, a result of
home, sociocultural, and other life experiences prior to the beginning of the school year (Bronfenbrenner, 1986; Morrison et al.,
2005). However, specific and identifiable language and literacy
activities children experienced in the observed classrooms also
predicted alphabet, letter–word recognition, and vocabulary
growth, controlling for fall achievement and other child, teacher,
and classroom characteristics. This is encouraging because how
teachers and students interact and the kinds of language and
literacy experiences children encounter in preschool classrooms
can be modified and improved. Designing effective preschool
language and literacy instruction—taking into account that the
effect of language and literacy activities are fairly specific and may
depend on each student’s skills— has the potential to improve
short-term and, potentially, long-term academic achievement for
all children.
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Appendix A
Excerpts from the Pathways to Literacy Coding Manual
General Description
This coding scheme for classroom- and student-level activities is a
modified form of the coding scheme used in previous studies and was
designed to follow children from preschool through first grade. For this
reason, some activities are described that were not observed in the preschool classrooms in this study. Codes are hierarchical and begin with
general areas (activities), such as ritual, language arts, or math. For each
general area, there is a list of subactivities that describe the behaviors in
more detail, such as teacher read-aloud or student independent reading. All
of these activities are considered states, that is, they have a duration and the
relevant unit of analysis is the time (in minutes or seconds) that participants
spent in them. Activities may be either instructional or noninstructional.
(Note that the following are excerpted. Please contact Carol McDonald
Connor for the complete coding manual.)
Classroom Versus Student Level
These activity codes can be applied to the whole class (when everyone
in the class is engaged in basically the same activity— classroom-level
activity) or to individual target children (when different children in the
class are engaged in significantly different activities; for example, they
may be in different small groups—student-level activity).
Teacher Managed (TM) Versus Teacher–Child Managed
(TCM) Versus Child Managed (CM)
All instructional activities can be further specified as TM, assistant TM,
TCM, or CM and also as whole class (classroom level), small group, or
individual.
TM activity. This is an activity in which the teacher (or aide) is
focusing the students’ attention, and the children are doing very little
talking. A good example would be the teacher reading aloud to the students
without discussion. If the teacher is encouraging the students to talk (e.g.,
using questions, probing for knowledge), then this is a TCM activity (see
below).
TCM activity. TCM instruction includes activities in which the teacher
or the assistant teacher is the primary director of the children’s attention but
in which children are active participants (e.g., teacher and student discussions surrounding a particular book). Other TCM activities include teachers
reading aloud with discussion and instruction in letter–sound relations.
These can be directed toward the whole class, small groups, or individual
children.
CM activity. CM instruction includes those instructional activities in
which the student is primarily controlling his or her focus of attention, for
example, reading independently (e.g., sustained silent reading) and completing worksheets independently. These activities can be conducted in
small groups or individually. Peer activities are included under this code.
However, they are considered separated in the revised version of this
coding scheme.
Activities
Play–Free Time
Time spent engaged in activities of the students’ choice that are not
specifically literacy or other content area (e.g., math, science) focused.
Typically this includes time spent in the dramatic play area, playing with
blocks, building with LEGOs, playing housekeeping, and the cooperative
(Appendixes continue)
688
CONNOR, MORRISON, AND SLOMINSKI
peer interactions that occur during play. It is distinct from time spent
looking at or reading books (which is coded as sustained silent emergent
reading), games, art, music activities, and recess (which typically occurs
outside the classroom and is not coded). In all cases, these activities are
CM.
Language Arts
Time spent engaged in activities that require reading, writing, or
reading- and writing-related things but that are not focused on gaining
information about another content area (science, social studies, math,
drama, etc.). Remember that text is anything that can be read, including
signs, labels, directions on the board, and so forth. Print, on the other hand,
refers to printed matter such as books, newspapers, and so forth. Specific
subactivities follow.
Teacher read-aloud. The teacher reads from a picture book, a chapter
book, or magazine, and so forth; provides a book-on-tape for the class to
listen to (children are not under headphones); or shows a video wherein a
story is presented and is present during the activity (otherwise it is a CM
activity). The read-aloud is done from beginning to end, without breaks to
discuss or ask questions. However, the teacher may make brief clarification
comments (especially during a book-on-tape) or ask rhetorical questions,
without really expecting a response from the children.
Teacher read-aloud– discussion combination. The teacher reads a
book out loud but stops frequently (once every one or two pages) to discuss
or ask questions. This occurs during the reading of the book and is clearly
interactive, with both the teacher and the children participating in reading
and understanding the book.
*Think of teacher read-aloud and the teacher read-aloud– discussion
combination as two different styles of reading a book. Some teachers like
to go from beginning to end, and others like to stop along the way and
discuss. Rarely will the same book-reading activity be coded for both of
these styles.
Student read-aloud, individual. A single child reads aloud, in a small
group or whole class, from a picture book, chapter book, magazine, or his
or her own writing. (Note that although the description is provided, this
activity was not observed in the target preschool classrooms.)
Student read-aloud, choral. More than 1 child reads aloud from a
picture book, chapter book, magazine, poster, and so forth. (Note that
although the description is provided, this activity was not observed in the
target preschool classrooms.)
Silent sustained reading. Children sit quietly and read to themselves.
In preschool, this may include emergent reading and looking at pictures.
What is important is that children are interacting with books independently.
TM group writing. The teacher is at the blackboard– easel, working
with children on a group writing activity. Children offer the content of the
written piece, but the teacher puts the ideas into complete sentences, with
appropriate punctuation and so forth.
Writing instruction. The teacher tells the children how to do things that
will help them to become independent writers, such as how to engage in
advanced organizing (e.g., webbing, outlining), how to move from outline
to written product, and how to proofread and edit. This also includes
instruction in the different forms of writing (expository vs. demonstration,
etc.). At the preschool level, this will include invented spelling activities.
(Note that although the description is provided, this activity was not
observed in the target preschool classrooms.)
Teacher model writing. The teacher, without input from the children,
stands at the blackboard– easel and produces some sort of written product
(depending on the level of the students, it could be as small as a sentence).
The intent of the writing must be to model the act of writing and an
appropriate product. (Note that although the description is provided, this
activity was not observed in the target preschool classrooms.)
Student group writing. The children are working in pairs or small
groups to produce a written product (such as a story). Not all of the children
will actually be doing the writing, but they should be engaged in discus-
sions about what will be written. Writing may include invented spelling
and other emergent writing activities.
Student independent writing. Children are quietly writing a story,
poem, or journal entry by themselves. Writing may include invented
spelling and other emergent writing activities.
Handwriting practice–instruction. Children are doing an activity intended to help improve their handwriting, or they are receiving instruction
in good handwriting skills.
Spelling. Children are taking a spelling test, copying words, or being
asked to spell words (without seeing the word). (Note that although the
description is provided, this activity was not observed in the target preschool classrooms.)
Reading comprehension activity. These activities apply both to material children have read to themselves and material read to them. Children
are completing worksheets related to material or are writing in response to
something they have read or heard. (Note that although the description is
provided, this activity was not observed in the target preschool classrooms.)
Reading comprehension strategies: TCM. This applies both to material
children have read to themselves and material read to them. The teacher
describes or models specific strategies such as summarization, predicting,
inferring, monitoring comprehension, and relating story to self. This includes explicitly teaching children strategies to enhance active construction
of meaning from text— either read aloud or silently. In addition, children
are asked to recall details about a story that has been read to them. Specific
questions from the teacher about the story or elements of the story are also
reading comprehension strategies.
Reading comprehension strategies: CM. Children read in small groups
and discuss material they have read or that has been read to them. It is the
CM counterpart to reading comprehension strategies. (Note that although
the description is provided, this activity was not observed in the target
preschool classrooms.)
Discussion. Children are previewing a book the teacher is about to read
or reviewing a storyline from a book the teacher has read aloud. Children
are responding to and asking questions of both each other and the teacher.
Discussion is more reciprocal and interactive than reading comprehension
strategies and does not involve explicit–implicit teaching of comprehension strategies.
Alphabet activity. Children are engaged in learning the names of the
letters or focusing their attention on a particular letter of the alphabet. For
example, they might have to make a letter out of clay, color a paper that
shows a particular letter and items that begin with that letter, or put their
body in the shape of a letter.
Initial consonant. Children are identifying the beginning (initial) consonant sound of words, aurally and not visually. If the activity is visual and
aural, then code the activity as letter sight–sound. An example of initial
consonant is when the teacher asks “What letter does the word Valentine
begin with?” If she has children say Valentine without the v, that is word
segmentation.
Letter sight–sound. Children are engaged in activities that focus their
attention on the relationship between the written form of individual letters
and the sound those letters represent. Included here are activities such as
“signs for sounds” wherein the teacher orally produces a single letter
sound, and the children circle the letter (from an array of letters on a
prepared paper) that represents that sound. This subactivity must combine
the written form and oral sounds that represent the written form. If no
written form is used, then the activity is more appropriately coded as initial
consonant or word segmentation. Identifying individual letters embedded
in a word (such as spelling February while looking at the word) is also
letter sight–sound.
Phonological awareness. Activities that focus on the sounds of the
English language, including rhyming games and songs. This should be
coded when phonological awareness appears to be the only purpose of the
activity. A rhyming song such as “Five Little Monkeys Jumping on the
CHILDREN’S EMERGENT LITERACY GROWTH
Bed” would not be coded as language arts, subactivity phonological awareness, because the main purpose of the song is related to mathematics.
Word segmentation. Children are engaged in activities wherein they
break words into subcomponents (syllables, subsyllables, or phonemes),
orally; or they are charged with constructing whole words from orally
presented word segments. Included here are activities such as learning
word families (children are presented with a rime and must find onsets that
make real words; this is often an oral–written activity, but the initial
response is oral). For an activity to be coded as word segmentation rather
than letter sight–sound, the intent of the activity should be at the word level
and not the letter level.
Vocabulary. The teacher and/or children are discussing the meaning of
a word(s) or phrase (for longer than the 15-s interval).
Conventions of print. Conventions of written text such as where to start
reading, reading from left to right or anything related to directionality,
upper- and lowercase, identify punctuation symbols, talk about what–who
author and illustrators are.
Grammar and punctuation. The children are engaged in activities
focused on grammar or punctuation. (Note that although the description is
689
provided, this activity was not observed in the target preschool classrooms.)
Computer. Children are working at the computer with a language
arts-oriented software, and the intent is unclear. Where possible, time spent
at the computer is coded as the intent of the computer-based activity (e.g.,
for accelerated reader, children answer reading comprehension questions
about specific books to earn points—this would be coded as reading
comprehension activity rather than computer). Note that this is currently
coded as CM. (Note that although the description is provided, this activity
was not observed in the target preschool classrooms.)
Sharing with class. Students or the teacher talk about personal
business to the group. Code for sharing not only during “show and tell”
or a formal sharing activity but also when the class is in a circle just
chatting with the teacher. Sharing should include both teacher and
student input, and it should be clear that both expect the other to speak
in a reciprocal way. A child who bursts out with news from home during
calendar is interrupting, unless the teacher takes that opportunity to ask
whether other children have things to share and continues the conversation with the class.
Appendix B
Description of Hierarchical Linear Models and Exemplar Model
Level 1
Yij ⫽ ␤0j ⫹ ␤1j (fall letter–word)ij ⫹ ␤2j (fall vocabulary)ij
⫹ ␤3j (fall alphabet)ij ⫹ ␤4j (boy)ij ⫹ ␤5j (Head Start–state)ij
⫹ ␤6 . . . nj (student-level instruction variables)ij ⫹ rij
Level 2
␤ 0j ⫽ ␥00 ⫹ ␥01(total hours/week)
⫹ ␥02 . . . n (classroom-level instruction variables)j ⫹ u0j
␤ 1j ⫽ ␥10
␤ 2j ⫽ ␥20 ⫹ ␥21 . . . n (classroom instruction variables)j
␤ 3j ⫽ ␥30
␤ 4j ⫽ ␥40
␤ 5j ⫽ ␥50
␤ 6 . . . nj ⫽ ␥60 . . . n0
Yij, which is the spring letter–word recognition score for child i in class
j, is a function of the respective coefficients (␤j) at Level 1 as they
pertain to child i’s fall vocabulary, letter–word recognition, and alphabet scores; age; and minutes of small-group–individual instruction types
as well as a residual (rij). ␤0j is a function of the fitted mean spring
letter–word recognition score for the sample of students (␥00) plus the
effect of the total hours per week and the whole classroom instruction
variables for classroom j, plus error (uj). ␥10 represents the effect of fall
vocabulary on spring reading comprehension. ␥20 represents the effect
of fall letter–word score on spring letter–word score. ␥30 represents the
effect of fall alphabet score, and ␥40 represents the effect of child age
on spring letter–word score; ␥50 represents the effect of enrollment in
a preschool intervention on spring letter–word score; ␥60 . . . n0 represents the effect of amount and type of small-group–individual instruction; ␥21 represents the interaction between classroom-level instruction
variables and student fall letter–word recognition score. The error at the
level of the classroom is represented by uj. Residuals (u, r) were
assumed to be normally distributed with a mean of zero.
Hierarchical linear modeling results are interpreted in much the same
way as are regression results. Referring to Table 5, ␥00 represents the fitted
mean letter–word score (345.64). The other gamma (␥) coefficients represent the effects of the particular independent variables (e.g., fall vocabulary score, fall alphabet score, etc.) and interactions (e.g., effect of TCM,
Code-Focused, Classroom-Level Activity ⫻ Fall Letter–Word Score, ␥11).
The t tests identify which effects are significantly greater or less than zero.
For example, ␥01 represents the effect of overall hours per day spent in
preschool. The value .44 indicates that for every hour per week students are
in preschool, on average, their letter–word score will be .44 points higher
than a student in preschool the average number of hours per week. The p
value (⬍.001) indicates that there is a 99% chance that this value is greater
than zero. This indicates that children who spend 25 hr per week in
preschool (10 hr above the mean of 15) will achieve letter–word scores 4
points higher, on average, than will students who attend preschool for the
mean amount of time, 15 hr per week. The implications of interaction
coefficients (e.g., ␥11— effect of TCM, Code-Focused, Classroom-Level
Activity ⫻ Fall Letter–Word Score) are best understood by referring to the
figures.
Received January 10, 2006
Revision received April 11, 2006
Accepted April 14, 2006 䡲