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Foundations of Young Children’s
Vocabulary Development:
The Role of the Home Literacy
Environment (HLE)
Jorge E. Gonzalez
Vivina Y. Rivera
Matthew J. Davis
Aaron B. Taylor
Texas A&M University
College Station, Texas, USA
The current study investigated the relationship between home literacy environment (HLE) and parental belief systems and receptive and expressive vocabulary outcomes of preschool-aged children. We tested a modification of
a model initially proposed by DeBaryshe (1995) positing that family income
and maternal education are positively related to the HLE, that the HLE is positively associated with parental facilitative reading beliefs, and parental beliefs
are positively related to standardized measures of receptive and expressive
vocabulary. For standardized measures of vocabulary, findings revealed that
more educated mothers had greater literacy-enriched home environments
than other mothers. Furthermore, the more enriched the HLE, the more positive were parental facilitative reading beliefs. Positive reading beliefs were
related to higher child expressive vocabulary scores on the standardized
measure. Directions for future research and implications are discussed.
Key Words: preschool, literacy, home, environment, language, vocabulary
Early Childhood Services
Volume 4, Number 1, pp. 69–86
Copyright © 2010 Plural Publishing, Inc.
69
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Introduction
Researchers have long sought to identify
individual differences in the processes that
support emergent literacy and language in
children (Aaron, Joshi, Gooden, & Bentum,
2008; NICHD Early Child Care Research
Network, 2005; Scarborough, 2002). At the
center of much theorizing in this area is the
role of experience in explaining variation
in emergent literacy and language (Connor,
Morrison, & Slominski, 2006; Cunningham,
Stanovich, & West, 1994).
What we know is that significant variability in children’s literacy experiences (a)
emerges long before formal schooling (Belsky et al., 2007; Farver, Xu, Eppe, & Lonigan,
2006; NICHD Early Child Care Research Network, 2005); (b) is remarkably stable over
time (Scarborough, 2002); and (c) relates to
what theorists call “environmental opportunity hypothesis” (Stanovich, Cunningham,
& West, 1998). The presumption is that children whose homes provide less stimulating
environments and experiences for optimal
development of language and literacy are at
higher risk for reading difficulties than children whose homes are literacy rich (Snow,
Burns, & Griffin, 1998). However, the mechanisms through which the home environment exerts its influence on children’s language and literacy are not fully understood
(Weigel, Lowman, & Martin, 2007).
In recent years, researchers have sought
to identify specific dimensions of the home
literacy environment (HLE) that are linked
to child language, especially vocabulary,
and literacy development (Burgess, Hecht,
& Lonigan, 2002). One dimension that has
received attention is the parental belief system because parental beliefs are presumed
to provide a pathway to children’s opportunities for literacy (DeBaryshe, 1995; Perry,
Kay, & Brown, 2008).
Most parents strongly value being involved in their children’s learning (Drummond & Stipek, 2004). Parents who value
and express positive beliefs about literacy and reading engage their children in lit-
eracy activities (Weigel et al., 2007), such
as games, nursery rhymes, songs, conversations, and shared reading and writing
(Landry, Swank, Smith, Assel, & Gunnewig,
2006). By participating in these types of activities, children experience more “joint attention, adult modeling of new verbal forms,
frequent questions and contingent feedback
for children’s speech, and shared conversational topics” (DeBaryshe, 1995, p. 2), all
characteristics of adult speech linked to children’s linguistic competence. Indeed, the
degree to which children learn many concepts, skills, attitudes, and behaviors in their
homes has been linked to whether they participate in such asset-based activities (Purcell-Gates, 2000). These activities have been
found to account for as much as 27% of children’s receptive and expressive vocabulary
development (Weigel et al., 2007).
Studies indicate that parental literacy
habits, as well as sociodemographic characteristics of the home environment, are reflective of the beliefs and attitudes that parents
hold towards children’s literacy and language development (Debaryshe, 1995; Weigel et al., 2006). Together, HLE, sociodemographic characteristics, and parental beliefs
are thought to predict vocabulary development. In the current study, a hypothesized
path model was developed and tested to illustrate the relationships between sociodemographic and HLE characteristics, parental
beliefs, and child vocabulary outcomes. The
importance of vocabulary development is
underscored by research showing that major
vocabulary problems in young children develop during the preliterate period long before children are exposed to challenging vocabulary by reading texts (Biemiller, 2006).
It is also well documented that individual
and SES-related differences in early vocabulary development reflect the impact of differing language experiences (Hoff, 2006).
Home Literacy Environment
The HLE can be described as the “variety of resources and opportunities provided
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to children as well as by the parental skills,
abilities, dispositions and resources that determine the provision of these opportunities
for children” (Burgess et al., 2002, p. 413).
For many children, the source of early differences resides in their experiences with
language and literacy in the home (Foorman, Anthony, Seals, & Mouzaki, 2002; Hoff,
2006). Although studies vary, estimates of
variance in child language literacy accounted for by the HLE range from about 10% to
18% (Payne, Whitehurst, & Angell, 1994).
Furthermore, research shows that variation
in children’s HLE is related to differences
in opportunity for acquiring school readiness skills (Farver et al., 2006; Haney & Hill,
2004). Evidence shows that children experience more success in reading when the literacy practices in their homes “mirror” what
schools practice (Pellegrini, 2001; Perry et
al., 2008). The presumption is that exposure to literacy-rich home environments increases children’s readiness to benefit from
literacy and language instruction at entry to
schooling. By contrast, a lack of opportunity
to acquire school readiness skills is especially problematic at the lower levels of ability,
lower income, or for those from culturally
diverse backgrounds (Farver et al., 2006).
Hart and Risley (1995) examined differences in welfare, working class, and professional families. They reported that the “size
of the differences in families in the amount
of talk is enormous, and those differences
add up to massive advantages or disadvantages for children in language experience
long before they start school” (p. 14). More
important, they found that the amount of
home family talk taking place, especially social talk, was significantly related to large differences in the size of a child’s vocabulary
growth and intellectual achievement at ages
3 (r = .78) and 9 (r = .77).
Hart and Risley’s seminal works (e.g.,
Meaningful Differences in the Everyday
Experiences of Young American Children,
1995) have been supported in a variety of
contexts by researchers examining the HLE
and children’s school readiness. Much of the
research has centered on home literacy prac-
tices such as parent-child shared book reading as means for explaining the relationship
between the HLE and child language and
literacy outcomes (Bingham, 2007; Hood,
Conlon, & Andrews, 2008). For example, Sénéchal and colleagues (Sénéchal & LeFevre,
2002) differentiated between two aspects of
HLE, informal (i.e., exposure to storybooks)
and formal (i.e., parent and child explicit focus on print). Results of their longitudinal
study showed clear and distinct paths for
the two forms of literacy experiences: Story
book reading was related to children’s concurrent and longitudinal receptive language
development, whereas parental reports of
explicit teaching were related to children’s
early literacy skills.
In an expansion of Sénéchal and LeFevre’s model, Hood and colleagues (Hood et
al., 2008) also found that parent-child informal reading was related to receptive vocabulary, but that parent formal explicit literacy teaching was more important than book
reading in developing child emergent literacy skills in both the short and the long term.
Other researchers have shown that the relationship between the HLE and children’s
literacy and language is robust even when
developmental predictors (e.g., socioeconomic status) are controlled for (Burgess et
al., 2002).
Extant literature also supports Hart and
Risley’s findings (1995) across several dimensions of the HLE (Bracken & Fischel,
2008). For example, research has shown
that socioeconomic status (SES) predicts
language and literacy stimulation and maternal responsiveness (i.e., referred to as
parental investments), which in turn predict children’s cognitive outcomes (Mistry,
Biesan, Chien, Howes, & Benner, 2008).
Farver et al. (2006) found that after controlling for age and other variables that could
limit opportunities for learning, children’s
interest in literacy mediated the relationship
between HLE and receptive vocabulary. Further, the HLE’s effects on language and literacy are stronger early in child development.
For example, Melhuish et al. (2008) showed
that in the short term, the HLE of 5-year-old
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children was effective in differentiating under- and overachieving children from average children in language and numeracy.
However, by age 7, the HLE for both reading and math achievement only differentiated low-achieving children from average and
overachieving children, suggesting that earlier home experiences matter most.
Parental Involvement
Parental involvement refers to varied
parenting practices, ranging from educational beliefs and supporting academic performance to the HLE parents create to advance their child’s educational outcomes
(Seginer, 2006). By providing cognitively
stimulating tasks, fostering motivation for
learning, and helping with school-relevant
tasks, parents engage in “school-like” tasks
that support their children’s learning (Seginer, 2006). These school-like tasks involving
a parent and child generally take the form
of scaffolded nursery rhymes, games, songs,
conversations, and shared reading (Landry
et al., 2006). Among these, reading aloud to
children appears to be the single most important home learning activity in which parents can involve their young children (DeBaryshe, 1995). Specifically, interactions
around children’s experiences with book
reading promote familiarity with oral and
written language structures that relate to literacy (Hoff, 2006).
Parental Beliefs
Parental belief systems are a key to understanding parent differences in reading
practices with their children (DeBaryshe,
1995). DeBaryshe defined parental beliefs
on reading as “parents’ beliefs about reading
aloud to preschool-age children, . . . the extent to which parents endorse tenets consistent with current models of environmental
influences on language development and developmentally appropriate teaching practices in emergent literacy” (p. 3).
Parents differ in views about their role
in children’s literacy development, and
these differences are linked to children’s
HLE (Bingham, 2007; Haney & Hill, 2004).
In their work on parental beliefs, Weigel
et al. (2006) noted that children’s language
skills are much greater when parents value
their role, as demonstrated in supportive expectations and stimulating interactions, in
their child’s learning. Similarly, DeBaryshe
(1995) posited that the HLE, in addition to
the sociodemographic characteristics of the
home, predicts the types of beliefs parents
hold about children’s literacy and language
development.
Using path analyses, DeBaryshe (1995)
found that mothers with higher education,
better economic resources, and stronger literacy orientations had more facilitative language belief systems than other mothers.
These beliefs, in turn, were strongly related
to more parent-child reading experiences,
expanded child reading interest, and positive maternal belief systems about mothers’
roles. DeBaryshe’s model explained more
than 60% of the variance in beliefs, reading activities, and child interest. Unfortunately, the model did not explain any statistically significant variance in child language
outcomes.
In an expansion of DeBaryshe’s (1995)
model, Weigel and colleagues (Weigel et al.,
2006) tested the paths from parental literacy
habits and demographics to parental beliefs,
parent-child literacy and language activities
and, ultimately, preschool-aged children’s
language skills. The authors found statistically significant direct paths from parental
demographics to parental reading beliefs,
beliefs to parent-child activities, activities to
print knowledge and, finally, to children’s
reading interest. Like DeBaryshe, however, these authors found no statistically significant paths between parent-child activities and receptive or expressive language
outcomes.
In a one-year follow-up, the authors also
showed no statistically significant relationships between parent-child activities and
expressive or receptive language although
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parental reading beliefs were found to be directly related to receptive vocabulary.
Parent Education
Long-standing evidence documents that
parental education, especially maternal,
is one of the most consistent predictors
of child academic achievement (Melhuish
et al., 2008). Bracken and Fischel (2008)
showed that parental education level is a
strong predictor of children’s receptive vocabulary, print concepts, and general emergent literacy skills. Moreover, these authors
documented that parental education was
strongly associated with family reading behaviors and that higher parental education
was associated with increased parental interest in reading, child reading interest level,
and parent-child shared reading interactions.
In another study, Bingham (2007) found
that maternal education and literacy beliefs
were significantly related to the quality of
the home environment, accounting for 31%
of the variance. This literature is, however,
far from conclusive. For example, studies by
Payne et al. (1994) note that caregiver intelligence and education are biological and environmental factors that are unrelated to the
literacy environment. According to the authors, these factors influence children’s language skills and should be eliminated from
literacy environment estimated effects.
Socioeconomic Status
Although SES has frequently been used
as a predictor of outcomes (e.g., reading, vocabulary), it is best thought of as a marker
variable than a process variable (Payne et
al., 1994). As a marker variable, SES functions as a proxy for processes that are transmitted via SES and “its effects are strongest
when it is used to indicate the status of a
school or a community or a school district,
not the status of individuals” (Snow et al.,
1998, p. 127). In fact, converging evidence
documents that SES does not itself contrib-
ute most directly to reading outcomes; rather, other characteristics of the family context (e.g., expectations, conversations in
the home, materials, resources) are more
explanatory (Gunn, Simmons, & Kame’enui,
1998). In the present study, we used income
as a proxy for socioeconomic status.
Purpose of the Current Study
and Hypothesized Path Model
Due to varying patterns of parental support for literacy, preschool-age children do
not start formal schooling with the same
range of literacy experiences nor ability?
(Gunn et al., 1998). The HLE has long been
recognized as one of the possible pathways
through which SES, maternal education,
and parental beliefs impact a child’s academic achievement based in the belief that
through the HLE a child first encounters opportunities to participate in literacy activities (Bracken & Fischel, 2008).
One aspect of the HLE that has received
recent attention is the parental belief system. The importance of examining the effects of the HLE and parental beliefs about
child literacy and language development are
threefold: (a) from a practical perspective,
identifying important aspects of the HLE for
intervention can target programming, (b)
identifying parental beliefs about their roles
in children’s language and literacy development could assist schools in facilitating programs to meet student needs, and (c) as DeBaryshe (1995) noted, determining parental
beliefs may highlight important individual
differences in home reading practices.
Bronfenbrenner (1999) theorized that
human development takes place through
proximal processes-progressively more com­
plex, reciprocal, and enduring interactions
that occur in an immediate environmental context. He saw the differential impact
of proximal processes as a function of the
quality of the environment and viewed it
as potentially more powerful than the environment alone in terms of predicting developmental outcomes.
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In our hypothesized model we recognize that the family is both an interactional (e.g., routines, rituals) and ideological
(symbolically articulated belief systems) system (Wozniak, 1993). We adopt Bronfenbrenner’s bioecological paradigm to propose that the maternal beliefs are a potent
force in shaping a child’s cognitive development (Bronfenbrenner, 1995). Bronfenbrenner’s bioecological theory also posits
that proximal processes have corresponding
behaviors (e.g., shared reading) that transmit
belief systems and both proximal processes
and corresponding behaviors function as antecedents to child outcomes. In our hypothesized model, we treat belief systems—that
operate either to facilitate or impede child
development—as a proxy for proximal processes. Finally, Bronfenbrenner posits that
proximal processes differ in their developmental effects on children depending on the
quality of the environment in terms of available resources.
Recently, researchers have applied
Bronfenbrenner’s proximal processes proposition to understand parents’ beliefs about
their role in beginning reading. Evans et al.
(2004) pointed out that Bronfenbrenner’s
theory highlighted that the source of pa-
rental beliefs resided in the microsystem
(the system closest to the child containing
the structures with which the child has direct contact). Following recent thinking and
Bronfenbrenner’s theory, we hypothesized
that the source of parental beliefs about
their role in children’s language lies in the
HLE, as depicted in Figure 1.
Despite research on HLE, parent beliefs,
and vocabulary, more is needed to reach
more definitive conclusions. This study used
a path analytic approach to examine the relationships between variables that contribute to vocabulary development. More specifically, this approach was used to find the
strength of associations among demographic characteristics, the HLE, and parental beliefs, and their ability to predict preschoolaged children’s receptive and expressive
vocabulary development.
Path analysis allows for the simultaneous
estimation of several regression models. We
applied it as a means of modeling interrelationships between observed variables that
contribute to early literacy development.
These hypothesized relationships are reflected in the path diagram presented in Figure
1. As illustrated, the three primary paths hypothesized to be related to language devel-
Receptive
Vocabulary
e1
Income
.113
.133
HLE
.208*
e3
.243**
Parental
Beliefs
e2
.518**
.137†
Mother’s
Education
Expressive
Vocabulary
e4
Figure 1. A priori model (Model 1) relating family income and mother’s education to home
literacy environment, parental beliefs and receptive and expressive vocabulary outcomes.
The model was estimated using FIML; standardized coefficients for the estimated model are
shown; * p < .05; ** p <.01; † p < .10. Two variables, intervention condition and classroom
type, were included as covariates for receptive and expressive vocabulary, but are not shown.
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opment are as follows: (a) parental income
and maternal education predict the HLE; (b)
the HLE is positively related to parental beliefs; and (c) parental beliefs predict child
language outcomes.,
Methods
Participants
The current study was part of a larger
experimental study examining the effects
of teacher-delivered read-alouds on vocabulary knowledge of preschool-aged children
enrolled in classrooms in nine schools in
two ethnically diverse cities in south central
Texas. Participants were enrolled in either
an English or bilingual classroom and randomly assigned to an intervention or “usual practice” condition. As part of the larger
study, 136 families (65.1%) consented to fill
out the FAMILIA Inventory (Taylor, 2000)
and the Parent Reading Belief Inventory (PRBI; DeBaryshe & Binder, 1994); they were
included in the current study. Students’ age
at pretest ranged from 4 to 5.25 years (M =
4.52, SD = .32).
Two hundred and nine students were
initially selected to be part of the schoolbased study using a two-step process. In August 2007 parent consent forms were sent
home to students, and students were administered a measure of receptive vocabulary.
Two students were selected from each classroom whose scores on this measure most
closely approximated the 15th, 30th, and
50th percentiles, for a total of six students
from each classroom.
As reported earlier, of the 209 students
in the larger study, 136 adult caretakers
completed the FAMILIA Inventory and PRBI
measures. Of the 136 adults who completed
these measures, the majority were Hispanic (48.9%) and African American (31.6%),
with 15% white, 3% Asian, and 1.5% from
another ethnicity. The final sample of children included more females (59.6%) than
males, and the majority of students were
English language learners (51.1%) according to teacher report. All students were eligible for free or reduced-cost lunch; most
(75.6%) had annual family incomes of less
than $24,000.
Of the participating families, 64.3%
spoke English as their primary language at
home, and had a median of two children (M
= 2.6, SD = 1.2). The majority of mothers
(61.7%) and fathers (58.1%) had completed a General Equivalency Diploma (GED),
a high school diploma, or above. A small
number of fathers (11.5%) and over a third
of mothers (35.3%) were unemployed and
not in school. Fewer than half of the families
(46.2%) reported reading to their children
more than one or two times a week; a small
percentage (11.2%) stated that they read to
their children in both English and Spanish.
More than half the families (63.9%) reported that they kept more than 10 children’s
books in their home.
Measures and Data Collection
Several measures were used to assess
participants’ receptive and expressive vocabulary, HLE, and parental beliefs about literacy. Measures were administered individually by trained graduate and undergraduate
research assistants two weeks prior to the
start of the main study and two weeks after completion of the study. All data collectors were required to complete two days of
training, which included practice time. Data collectors had to reach 100% fidelity on
all study measures prior to being allowed to
conduct testing.
Outcome Measures
All outcome measures were given as preand posttest as part of a larger research project. The current study utilized the child language outcome posttest data collected one
year after the predictors (i.e., income, mother’s education, HLE, belief systems). This longitudinal design established temporal prece-
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dence: because the measures of children’s
language skills were taken after the predictive measures, alternative models in which
language skills affect parental beliefs can
be ruled out. This strengthens our ability to
draw causal inference about the effects of the
predictors on the outcomes, although it does
not do so for relations among the predictors,
which were measured simultaneously.
Receptive Vocabulary
The Peabody Picture Vocabulary TestThird Edition (PPVT-III), Form A (Dunn &
Dunn, 1997) was used to measure general
receptive vocabulary for students in English
classrooms. The PPVT-III is recommended for
measuring receptive vocabulary and screening for English language ability and general language development. Using the PPVTIII, the examiner names an object or action,
whereupon the child has to point to one of
four pictures on a panel that represents that
object or action. Alpha and split-half reliability coefficients reported in the manual range
from .86 to .98 for both forms A and B.
For students in bilingual classrooms, the
Test de Vocabulario en Imágenes Peabody
(TVIP; Dunn, Padilla, Lugo, & Dunn, 1986)
was used to measure general receptive vocabulary. The TVIP is a measure of Spanish vocabulary recommended for Spanishspeaking and bilingual students. The format
of the TVIP is identical to that of the PPVTIII; therefore, scores on the two instruments
are comparable as they measure the same
construct in the same way. Cronbach’s alphas reported in the manual range from .80
to .95 (M = .93) by age group.
Expressive Vocabulary
The Expressive One-Word Picture Vocabulary Test (EOWPVT; Brownell, 2000) was
used to assess expressive vocabulary for students in English classrooms. The EOWPVT is
recommended for assessment of expressive
vocabulary by requiring the child to name objects, actions, and concepts pictured in illustrations. Split-half coefficients reported in the
manual reflect a median of .98.
To measure the expressive vocabulary
of students in bilingual classrooms, a Spanish Bilingual Edition of the EOWPVT was
used (EOWPVT-SBE; Brownell, 2001). The
EOWPVT-SBE is an adaption of the EOWPVT
that allows the student to respond in English
or Spanish. As with the receptive measures,
the format of the EOWPVT-SBE is identical
to that of the EOWPVT; consequently, student scores on these measures can be compared to each other. Cronbach’s alphas reported in the manual range from .92 to .97
(M = .95) by age group.
Home Literacy Environment
The FAMILIA Inventory (Taylor, 2000) is
a 57-item diagnostic questionnaire in Forms
A and B (for pre- and posttesting) designed to
assess the multi-dimensional aspects of family literacy. The questionnaire is not timed,
but generally takes about 20 minutes. It can
be used with literate parents, as well as parents who are low-level readers. The inventory is available in both English and Spanish
and can filled out by one or both parents, or
in the presence of a family specialist or other trained individual. In this study, a trained
bilingual specialist interviewed parents. The
scoring software for the FAMILIA Inventory
generates an interpretive “family profile” to
be used by parent educators or other personnel working with families.
Scoring of the FAMILIA Inventory is
fairly straightforward, and norms are provided for the total standardization sample,
Euro-American Families, African-American
and Hispanic-American families as well as
for families with children ages 0 to 5, 6 to
9, 10 to 12, and families with children of
combination ages. Items are rated on a Likert scale ranging from 0 (never) to 5 (daily).
The questionnaire yields 10 discrete types of
family interactions related to home literacy.
Table 1 provides a description of subscales
and sample items. For the present study, we
only used the Shared Reading, Parental Modeling, Practical Reading and Shared Writing
subscales to form a HLE composite. These
scales were selected because they were con-
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Table 1. Familia Subscale and Sample Items
Subscale
Assesses
Sample Item
Subscale F: Family
Work and Play
Levels of family interaction in
shared labor
and recreation
“We go on family outings together,
walks, trips to the park.
Subscale T: Use of
Television
The regularity and levels of
television viewing in the family
“Our family has favorite TV programs
that we watch together.
Subscale V: Verbal
Interactions at
Home
The importance a family places
on talking with children
“We talk with our children as we
play, work, and carry out our daily
routine.
Subscale M:
Parental Modeling
and Reading
Levels of parental modeling of
literacy via activities aimed at
shaping child behavior
“Our children see us read books,
newspaper, and other materials.
Subscale P:
Practical Reading
in the Home
The family’s use of reading for
applied purposes
“We look up how to do things in
books and magazines when we make
things at home.
Subscale R: Shared
Reading by the
Family
How frequently the family
reading together
“The older children and/or relatives
read to the young children.
Subscale W:
Shared Writing by
the Family
The extent to which writing
skills and activities are used in
the family
“Our children use puzzles, mazes, dotto-dot, or other writing games.
Subscale E:
Support by
Extended Family
Interaction with extended family
like grandparents and other
relatives
“Our children spend time with their
grandparents.
Subscale L: Library
Use by Family
Frequency of use of school/
community library resources by
family members
“We go to the library with our
children.
Subscale S:
Parental Support
of School
How parents interact with
children and school around
homework and other school
activities
“We make sure our children complete
and understand their school work.
sistent with research showing that children’s
literacy and language develops from interactions with others in specific environments
of which reading, writing and oral language
are a part (Morrow & Brittain, 2003).
The FAMILIA Inventory yields raw scores
ranging from 0 to 30 for each of the 10 subscales. Percentile rank scores are available for
Euro-, African-, and Hispanic-American families. Cronbach’s’s alpha coefficient reliability
estimates for The FAMILIA Inventory subscales
from two samples (Wyoming Even Start Programs [n = 48] and Iowa Even start programs
[n = 50]) range from .64 to .95 (M =.89). Alphas were found to be within acceptable limits, suggesting good internal consistency.
Parental Beliefs
The Parental Reading Belief Inventory (PRBI; DeBaryshe & Binder, 1994) is a
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42-item measure designed to assess parents’
beliefs about reading aloud to preschool-age
children. The PRBI measures the degree to
which parents agree with current models of
environmental influence and teaching practices to promote language development.
Specific scales examine (a) teaching efficacy (i.e., “I am my child’s most important
teacher”), (b) positive affect (i.e., “Reading with my child is a special time that we
love to share”), (c) verbal participation (i.e.,
“When we read, I want my child to help me
tell the story”), (d) reading instruction (i.e.,
“When we read, I have my child point out
different letters or numbers that are printed in the book”), (e) knowledge base (i.e.,
“Reading helps children learn about things
they never see in real life like Eskimos and
polar bears”), (f) resources (i.e., “I don’t
read to my child because we have nothing
to read”), and (g) environmental influences
(i.e., “Some children are natural talkers, others are silent. Parents do not have much influence over this”). Parents score each item
on a four-point Likert type scale from 1 =
strongly disagree to 4 = strongly agree.
The PRBI has been translated and back
translated by the researchers to create a Spanish version. Participants could score a maximum of 168 points with higher scores indicating more positive parental facilitative reading
beliefs. According to the authors, Cronbach’s
alphas for the English version range from .50
to .85 by scale. An alpha coefficient of .90 for
the English version was found for the current
sample for the PRBI as a total score.
Data Analysis
Model Specification
To examine relationships between HLE,
parental reading beliefs, and vocabulary outcomes, Structural Equation Modeling (SEM)
was used. SEM models were estimated using Mplus (Muthén & Muthén, 2007). Full
information maximum likelihood (FIML) estimation was used because it allows for the
inclusion of cases having missing data (complete data were available for 118 students,
and at least 120 cases were available to estimate each covariance between variables).
Model fit was assessed using the chi-square
test, CFI (Bentler, 1990), RMSEA (Steiger,
1990), and SRMR (Hu & Bentler, 1998). CFI
is considered to show adequate fit when it
exceeds .95 (Hu & Bentler, 1999); RMSEA
when it is below .08 (and good fit when
below .05; Browne & Cudeck, 1993), and
SRMR to show good fit when below .05 (Hu
& Bentler, 1999).
Model 1 (the a priori model) is presented in Figure 1 (along with results from estimation of the model, which are discussed
below). In Model 1, it was hypothesized
that family income and mother’s education would predict the family’s HLE, which
would in turn predict parental reading beliefs. It was further hypothesized that parental reading beliefs would predict both
receptive and expressive vocabulary outcomes. The sequence of HLE and parental beliefs was hypothesized to fully mediate the relations between the demographic
variables (income and mother’s education)
and students’ vocabulary outcomes. In other words, income and mother’s education
were expected to have no effect on vocabulary outcomes other than the effects transmitted through the sequence of HLE and parental beliefs. This hypothesis can be seen
in Figure 1 in that there are no direct paths
from income or mother’s education to either
parental beliefs or the vocabulary measures.
In addition to the a priori model, we
tested two other possible models for the relations among the variables. Model 2 (Figure
2) was identical to Model 1 except that it
reversed the positions of HLE and parental
beliefs. In Model 2, the demographic variables were hypothesized to affect parental
beliefs, which in turn affected HLE, which
affected receptive and expressive vocabulary. This model was of interest because
it has been theorized in previous research
(e.g., Weigel et al., 2006). Finally, in Model
3 (Figure 3), rather than either HLE or parental beliefs serving as a predictor of the other, they were simply entered as correlated
predictors of the vocabulary measures. This
model was an application of the fact that
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Receptive
Vocabulary
e1
Income
.008
.151
.064
e3
Parental
Beliefs
.245**
HLE
e2
.527**
-.018
Mother’s
Education
Expressive
Vocabulary
e4
Figure 2. Model 2 relating family income and mother’s education to parental beliefs, home
literacy environment, and receptive and expressive vocabulary outcomes. Note that the positions of parental beliefs and home literacy environment have been exchanged from Model
1. The model was estimated using FIML; standardized coefficients for the estimated model
are shown; **p <.05. Two variables, intervention condition and classroom type, were included as covariates for receptive and expressive vocabulary, but are not shown.
HLE and parental beliefs were measured at
the same time. Unlike Models 1 and 2, Model 3 allowed for multiple mediated effects to
be tested, as the effect of each demographic
variable on each vocabulary measure could
be estimated passing through both HLE and
parental beliefs. Because the models were
not nested (the parameters estimated in one
were not a subset of the parameters estimated in another), their fit could not be compared using likelihood ratio tests. We therefore used the Bayesian Information Criterion
(BIC; Raftery, 1993) to compare the models.
In addition to the six variables of interest, all three models also included both
study condition (as discussed above) and
classroom type (i.e., bilingual, English) as
predictors of receptive and expressive vocabulary. Because these variables were included as covariates, and were not of theoretical interest, they are excluded from all
figures to simplify their presentation.
Results
Table 2 shows the correlation matrix,
means, and standard deviations of all variables used in the tested models. Parame-
ter estimates for Models 1 to 3 are shown
in Figures 1 to 3, respectively. Because of
the large differences in variability among
the variables (see standard deviations in Table 2), all coefficients are given in standardized form.
Model 1 (see Figure 1) fit the data well,
χ2 (12) = 8.29, p = .762, CFI = 1.00, RMSEA
= 0.00, SRMR = 0.04. This good fit suggested that the hypothesis that HLE and parental beliefs completely mediated any relation
between the demographic variables and the
vocabulary measures was correct (James,
Mulaik, & Brett, 2006). Mother’s education
was a significant predictor of HLE (β = .208,
p = .022), indicating that more educated
mothers had more positive HLE’s. HLE was a
significant predictor of parental beliefs (β =
.243, p = .003), indicating that a more positive HLE was associated with more positive
beliefs about reading. Parental beliefs was
a significant predictor of expressive vocabulary (β = .137, p = .050), indicating that
more positive parental beliefs about reading
predicted better expressive vocabulary performance for the child after one year. Taken
together, the significance of these three coefficients is evidence of a mediated effect of
mother’s education on expressive vocabu-
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80 —
1. Family income
1.19
SD
1.26
2.89
—
.400
2
20.22
89.37
—
.264
.231
3
19.22
138.27
—
.240
.124
.190
4
11.50
96.32
—
.083
–.021
.019
–.052
5
13.89
97.59
—
.530
.060
–.126
–.285
–.097
6
0.44
0.73
—
.276
.192
–.093
–.015
–.038
.074
7
0.44
0.27
—
.374
.551
.169
–.130
–.183
–.557
–.172
8
1
Variable entered as a covariate in predicting receptive and expressive vocabulary, but not show in Figures 1 to 3
Note. All values are estimated using expectation–maximization algorithm, which uses all cases, including those having missing data.
1.92
Mean
8. Bilingual status1
7. Condition1
6. Expressive vocabulary
5. Receptive vocabulary
4. Parental beliefs
3. HLE
2. Mother’s education
1
Variables
Table 2. Correlations, Means, and Standard Deviations for Variables in the Models
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.157
Income
.118
Parental
Beliefs
Receptive
Vocabulary
e3
-.024
.062
e1
.201*
.518**
e2
Mother’s
Education
.151*
.143
.206*
HLE
-.064
Expressive
Vocabulary
e4
Figure 3. Model 3 relating family income and mother’s education to parental beliefs, home
literacy environment, and receptive and expressive vocabulary outcomes. The model was
estimated using FIML; standardized coefficients for the estimated model are shown; *p <.05;
** p <.01. Two variables, intervention condition and classroom type, were included as covariates for receptive and expressive vocabulary, but are not shown.
lary through HLE and parental beliefs (using
the joint significance test; Taylor, MacKinnon, & Tein, 2008). Not consistent with our
hypotheses, income did not predict HLE,
and parental beliefs did not predict receptive vocabulary, although both effects were
in the expected direction.
Model 2 (see Figure 2) fit the data somewhat less well than did Model 1, but still adequately, χ2(12) = 18.88, p = .092, CFI = 0.94,
RMSEA = 0.07, SRMR = 0.06. As with Model 1, adequate fit suggested that the hypothesis of complete mediation of any relation
between the demographic variables and the
vocabulary measures by the sequence of parental beliefs and HLE was correct. The only significant path coefficient in this model,
though, was the relation between parental
beliefs and HLE (β = .245, p = .003), indicating that more positive parental beliefs about
reading were associated with a more positive HLE. HLE had very small and definitely
nonsignificant effects on both receptive and
expressive vocabulary.
Model 3 (see Figure 3) fit the data well,
χ2 (8) = 5.33, p = .722, CFI = 1.00, RMSEA
= 0.00, SRMR = 0.03. As with Models 1 and
2, the good fit in model 3 suggested that the
hypothesis that parental beliefs and HLE together completely mediated any relation be-
tween the demographic variables and the
vocabulary measures. In this model, mother’s education was significantly related to
HLE (β = .206, p = .023), and parental beliefs was significantly related to expressive
vocabulary (β = .151, p = .034). Given that
the significant associations did not link up
with each other (only the residuals of parental beliefs and HLE were correlated), no individually significant meditational chain of
variables could be identified.
BIC values are similar to chi square test
values in that smaller values indicate better
fit. BIC values for Models 1, 2, and 3 were
5530.4, 5541.0, and 5547.1. The BIC penalizes models that estimate too many parameters that only marginally improve fit. The
high BIC value for Model 3 (which estimated the most parameters) suggests that the
additional parameters did not improve model fit much. Model 1, the a priori model, fit
the data best by the BIC criterion.
Discussion
In this study we investigated the relationship between the HLE and parental beliefs
as predictors of receptive and expressive vo-
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cabulary outcomes of preschool-aged children. Specifically, we tested a modification
of a model initially proposed by DeBaryshe
(1995). Our model posited that: (a) family
income and maternal education predicted
the HLE, (b) the HLE is positively associated with parental facilitative reading beliefs,
and (c) parental beliefs predicted standardized measures of receptive and expressive
vocabulary after taking into account group
membership (i.e., intervention, contrast
classroom), and language of instruction (i.e.,
bilingual, English instruction). For standardized measures the findings suggested that
more educated mothers had greater literacy enriched home environments. Furthermore, the more enriched the HLE, the more
positively affected were parental facilitative
reading beliefs. Positive reading beliefs, in
turn, related to higher child expressive vocabulary scores. This finding also supports,
in part, Bronfenbrenner’s bioecological paradigm (Bronfenbrenner, 1995) by showing
that proximal processes (in terms of parental beliefs) had a greater impact (in terms of
child language competence) in more advantaged homes (in terms of the HLE).
We tested for indirect effects and found
that HLE and parental beliefs in turn mediated
the effect of mother’s education on expressive vocabulary. The model (Model 1) that
included this meditational chain fit the data
better than a model in which parental beliefs
preceded HLE or a model in which parental
beliefs and HLE were simply correlated.
The significant mediating paths identified in the present study also partially add
to our understanding of maternal level of
education and its effects on child outcomes
via the HLE and parental belief systems. Our
findings support long-standing evidence
that maternal education is among the most
potent contributors to children’s academic achievement (Melhuish et al., 2008). It is
possible that a mother’s level of education
predicts the way the HLE is structured, and
beliefs about her role in children’s education
and subsequently the quality and quantity of
facilitative learning experiences. These findings add to the growing body of research
suggesting that the HLE through parental beliefs has the potential for early, lasting, and
significant predictive power on the reading
and language development of young children in prekindergarten and beyond (Burgess et al., 2002; van Steensel, 2006).
Implications
A small but growing body of research
suggests that belief systems people hold
with regard to the desirability and importance of achievement are consequences of
their environments. In our original model,
the HLE through its impact on parental beliefs served as an important context for language outcomes. Identifying parental beliefs
and other factors about the HLE may guide
schools and teachers in adjusting or modifying teaching practices and programming to
meet the needs of all students. Understanding the relationship between maternal demographic characteristics, their relationship to
the HLE, and maternal reading beliefs is essential to designing and implementing homebased parent-child literacy interventions.
As others have shown (e.g., Weigel et al.,
2006), the present findings confirm the notion that the way to positively impact literacy development for very young children is
to focus on the HLE and attendant belief systems. However, as DeBaryshe (1995) pointed
out, family literacy programming (e.g., Even
Start) will only be successful if intervention
goals are consistent with preexisting parental beliefs about their role in their children’s
language and literacy development. Thus,
teachers may need to take the lead in parental involvement by asking parents about
their belief systems, meeting with them, providing suggestions, modeling effective strategies, and reinforcing positive parental beliefs about their roles in children’s academic
learning (Drummond & Stipek, 2004).
Limitations
This study has several limitations. One
limitation echoes concerns of other re-
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searchers (e.g., Bingham, 2007) in that the
Parent Reading Belief Inventory, due to a
composite score, fails to provide sufficient
information about which parental belief(s)
(e.g., efficacy beliefs, attitudes about reading, beliefs about parent role as teacher) are
most important in predicting parental behaviors. A related limitation is that we were
unable to identify the relative importance of
various aspects of the HLE to the vocabulary
outcomes. As other researchers have noted, different aspects of the HLE relate differentially to language and literacy outcomes
(Burgess et al., 2002). In addition, we only
measured limited aspects of the HLE related to reading facilitative behaviors. It is conceivable that other aspects of the HLE (e.g.,
Library Use by Family) might have related
differentially to language outcomes.
In our study, we were restricted to using only standardized measures acceptable
to the school district. As a result we were
unable to measure or explore any “corresponding behaviors” (e.g., frequency of
shared-reading) that might have provided
more insight into the predictive relationship
between parental beliefs and language outcomes. It is, however, important to note that
a hypothesized association between parentchild activities (e.g., frequency of shared
reading) has not been fully supported (see
DeBaryshe, 1995; Weigel et al., 2006). Moreover, other variables known to be mediating
factors (e.g., parental reports of children’s
interest, parental involvement, parent-child
activities) were not explored.
Also, a frequently cited limitation concerns the measurement of the HLE. We used
a self-report to assess the HLE. Self-reports
are notoriously susceptible to social desirability biases. Further, the study is correlational in nature. Therefore, although the
path model suggests directionality, caution should be taken when speaking of the
findings in causal terms. It is possible that
relevant causal factors that would have increased the explanatory power of our model were unmeasured (Melhuish et al., 2008).
Moreover, we did not measure the quality
and frequency of learning experiences. Research has shown that quality and frequen-
cy are pathways through which SES can mediate children’s emergent literacy outcomes
(Foster et al., 2005). We only measured oral
language in the form of receptive and expressive vocabulary. It is conceivable that
the HLE might relate to other language- and
literacy-related dimensions not measured
in this study (e.g., alphabet knowledge). Finally, caution should be taken before generalizing the results due to the initial study
design. Multiple groups of individuals were
combined for the path analyses, and despite
controlling for group statuses in the models,
such combination of individuals could create some bias in the results.
Directions for Future Research
This study suggests several directions
for future research to extend the findings.
For example, child interest was not measured in the current investigation; yet, some
studies have shown that child interest may
be related to parental motivation and frequency to engage in supportive literacy behaviors with their child (Hood et al., 2008).
Future research on child interest, therefore,
is clearly needed.
We did not measure parents’ behaviors
relative to their beliefs. Given the findings in
this study, it is important to examine how parental beliefs translate into actual behavior.
We also need to examine the emotional quality of the interactions in the HLE. Research
has shown that the socioemotional quality
of parent-child interactions around literacy
activities relates to child motivation, as well
as language and literacy outcomes (Serpell,
2005, as cited in Hood et al., 2008). Future
research should be directed at identifying
which aspects of the HLE (e.g., parental modeling, shared reading, shared writing) relate
to various language and literacy outcomes.
Conclusion
The present study sought to extend earlier works on the associations between the
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HLE and language and literacy outcomes in
preschool-aged children. Although our findings are promising, more research is needed to begin to disentangle the complex interconnections between the HLE and language
and literacy outcomes. Nevertheless, in
terms of influencing children’s preparedness
for school, the potential to affect a child’s
HLE has many implications for theories of educational achievement, policy, and practice.
We must begin by unraveling the “web
of correlations among the HLE via parental
beliefs, and various developmental and educational outcomes” (Burgess et al., 2002, p.
413). It is clear that most parents highly value
involvement in their children’s learning. Further, parental involvement in children’s academic careers figures prominently in the No
Child Left Behind (NCLB) Act of 2001, which
requires schools to develop ways to get parents more involved in their child’s education
and in improving the school. Acknowledging and understanding parents’ ideas about
their children’s language and literacy development is especially valuable given NCLB’s
emphasis on parental involvement.
Acknowledgments. Preparation of this
article was supported in part by Project
WORLD, Grant No. R305G050121 Reading
Comprehension and Reading Scale-Up
Research, Institute of Education Science
(IES), U.S. Department of Education. This
material does not necessarily represent the
policy of the U.S. Department of
Education, nor is the material necessarily
endorsed by the federal government.
Address Correspondence to: Jorge E.
Gonzalez, Ph.D., Texas A&M, Department
of Educational Psychology, MS 4225, College
Station, TX, 77842; Tel: 979-845-2324; Fax:
979-862-1256; E-mail: [email protected]
References
Aaron, P. G., Joshi, R. M., Gooden, R., & Bentum,
K. E. (2008). Diagnosis and treatment of read-
ing disabilities based on the component model of reading. Journal of Learning Disabilities, 41, 67-84.
Baron, R. M., & Kenny, D. A. (1986). The moderator-mediator variable distinction in social
psychological research: Conceptual, strategic
and statistical considerations. Journal of Personality and Social Psychology, 51, 11731182.
Belsky, J., Vandell, D. L., Burchinal, M., ClarkeStewart, A., McCartney, K., Owen, M. T., &
the NICHD Early Child Care Research Network. (2007). Are there long-term effects of
early child care? Child Development, 78,
681-701.
Bentler, P. M. (1990). Comparative fit indexes in
structural models. Psychological Bulletin,
107, 238-246.
Biemiller, A. (2006). Vocabulary development
and instruction: A prerequisite for school
learning. In D. K. Dickinson, & S. B. Neuman
(Eds.), Handbook of literacy research (Vol.
2, pp. 41-51). New York, NY: Guilford Press.
Bingham, G. E. (2007). Maternal literacy beliefs
and the quality of mother-child book-reading
Interactions: Associations with children’s early literacy development. Early Education
and Development, 18, 23-49.
Bracken, S. S., & Fischel, J. E. (2008). Family
reading behavior and early literacy skills in
preschool children from low-income backgrounds. Early Education and Development,
19(1), 45-67.
Bronfenbrenner, U. (1993). The ecology of cognitive development: Research models and fugitive findings. In R. H. Wozniak & K. W.
Fischer (Eds.), Development in context: Acting and thinking in specific environments
(pp. 3-44). Hillsdale, NJ: Lawrence Erlbaum
Associates.
Bronfenbrenner, U. (1995). Developmental ecology through space and time: A future Perspective. In P. Moen, G. H. Elder, & K Lüscher
(Eds.), Examining lives in context: Perspectives on the ecology human development
(pp. 619-647). Washington, DC: American
Psychological Association.
Bronfenbrenner, U. (1999) Environments in developmental perspective: Theoretical and operational models. In S. L. Friedman & T. D.
Wachs (Eds.), Measuring environment
across the life span: Emerging methods and
concepts (pp. 3-28). Washington, DC: American Psychological Association.
Browne, M. W., & Cudeck, R. (1993). Alternative
ways of assessing model fit. In K. A. Bollen &
REGISTERED COPY
FOUNDATIONS OF YOUNG CHILDREN’S VOCABULARY 85
This copy is registered to: Library Isothermal Community College <[email protected]>
J. S. Long (Eds.), Testing structural equation
models (pp. 136-162). Newbury Park, CA:
Sage.
Brownell, R. (2000). Expressive One-Word Picture Vocabulary Test. Novato, CA: Academic
Therapy Publications.
Brownell, R. (2001). Expressive One-Word Picture
Vocabulary Test: Spanish Bilingual Edition.
Novato, CA: Academic Therapy Publications.
Burgess, S., Hecht, S., & Lonigan, C. (2002). Relations of the home literacy environment (HLE)
to the development of reading-related abilities: A one-year longitudinal study. Reading
Research Quarterly, 37, 408-426.
Connor, C. M., Morrison, F. J., & Slominski, L.
(2006). Preschool instruction and children’s
literacy skill growth. Journal of Educational
Psychology, 98, 665-689.
Cunningham, A. E., Stanovich, K. E., & West, R.
F. (1994). Literacy environment and the development of children’s cognitive skills. In E.
M. H. Assink (Ed.), Literacy acquisition and
social context (pp. 70-90). London, UK: Harvester Wheatsheaf.
DeBaryshe, B. D. (1995). Maternal belief systems:
Linchpin in the home reading process. Journal of Applied Developmental Psychology,
16, 1-20.
DeBaryshe, B. D., & Binder, J. C. (1994). Development of an instrument for measuring parental beliefs about reading aloud to young
children. Perceptual and Motor Skills, 78,
1303-1311.
Drummond, K. V., & Stipek, D. (2004). Low-income parents’ beliefs about their role in children’s academic learning. Elementary School
Journal, 104, 197-213.
Dunn, L. M., & Dunn, L. M. (1997). Peabody Picture Vocabulary Test-Third Edition. Circle,
Pines, MN: American Guidance Service.
Dunn, L. M., Padilla, E. R., Lugo, D. E., & Dunn,
L. M. (1986). Test de Vocabulario en Imágenes Peabody. Circle Pines, MN: American
Guidance Service.
Evans, M. A., Fox, M., Cremas, L., & McKinnon,
L. (2004). Beginning reading: The views of
parents and teachers of young children. Journal of Educational Psychology, 96, 130-141.
Farver, J. A. M., Xu, Y., Eppe, S., & Lonigan, C. J.
(2006). Home environments and young Latino children’s school readiness. Early Childhood Research Quarterly, 21, 196-212.
Foorman, B. R., Anthony, J., Seals, L., & Mouzaki,
A. (2002). Language development and emer-
gent literacy in preschool. Seminars in Pediatric Neuropsychology, 9, 173-184.
Foster, M. A., Lambert, R., Abbot-Shim, M., McCarty, F., & Franze, S. (2005). A model of
home learning environment and social risk
factors in relation to children’s emergent literacy and social outcomes. Early Childhood
Research Quarterly, 20, 13-36.
Gunn, B. K., Simmons, D. C., & Kame’enui, E. J.
(1998). Emergent literacy: Research bases. In
D. C. Simmons & E. J. Kame’enui (Eds.), What
reading research tells us about children
with diverse learning needs (pp. 19-50). Majwah, NJ: Lawrence Erlbaum Associates.
Haney, M., & Hill, J. (2004). Relationships between parent-teaching activities and emergent literacy in preschool children. Early
Childhood Development and Care, 174(3),
215-228.
Hart, B., & Risley, T. R. (1995). Meaningful differences in the everyday experience of
young American children. Baltimore, MD:
Brookes Publishing.
Hoff, E. (2006). Environmental supports for language acquisition. In. D. K. Dickinson & S. B.
Neuman (Eds.), Handbook of early literacy
skills (Vol. 2, pp. 163-172). New York, NY:
Guilford.
Hood, M., Conlon, E., & Andrews, G. (2008). Preschool home literacy practices and children’s
literacy development: A longitudinal analyses.
Journal of Educational Psychology, 100,
252-271.
Hu, L., & Bentler, P. M. (1998). ������������������
Fit indices in covariance structure modeling: Sensitivity to underparameterized model misspecification.
Psychological Methods, 3, 424-453.
Hu, L., & Bentler, P. M. (1999). Cutoff criteria for
fit indexes in covariance structure analysis:
Conventional criteria versus new alternatives.
Structural Equation Modeling, 6, 1-55.
James, L. R., Mulaik, S. A., & Brett, J. M. (2006). A
tale of two methods. Organizational Research Methods, 9, 233-244.
Landry, S. H., Swank, P. R., Smith, K. E., Assel, M.
A., & Gunnewig, S. B. (2006). Enhancing early literacy skills for preschool children: Bringing a professional development model to
scale. Journal of Learning Disabilities,
39(4), 306-324.
Mistry, R. S., Biesan, J. C., Chien, N., Howes, C.,
& Benner, A. D. (2008). Socioeconomic status, parental investments, and the cognitive
and behavioral outcomes of low-income children from immigrant and native households.
REGISTERED COPY
86 EARLY CHILDHOOD SERVICES, VOL. 4, NO. 1
This copy is registered to: Library Isothermal Community College <[email protected]>
Early Childhood Research Quarterly, 23,
193-212.
Morrow, L. M., & Brittain, R. (2003). The nature
of storybook reading in the elementary
school: Current practices: In A. van Kleeck, S.
A. Stahl, & E. B. Bauer (Eds.), On reading
books to children (pp. 140-158). Mahwah,
NJ: Lawrence Erlbaum.
Muthén, B. O., & Muthén, L. K. (2007). Mplus
user’s guide (5th ed). Los Angeles, CA: Muthén & Muthén.
NICHD Early Child Care Research Network.
(2000). The relation of child care to cognitive
and language development. Child Development, 71, 960-980.
Payne, A. C., Whitehurst, G. J., & Angell, A. L.
(1994). The role of home literacy environment in the development of language ability
in preschool children from low-income families. Early Childhood Research Quarterly, 9,
427-440.
Pellegrini, A. (2001). Some theoretical and methodological considerations in studying literacy
in the social context. In S. Neuman & D. Dickinson (Eds.), Handbook of early literacy research (pp. 54-65). New York, NY: Guilford.
Perry, N. J., Kay, S. M., & Brown, A. (2008). Continuity and change in home literacy practices
of Hispanic families with preschool children.
Early Childhood Research Quarterly, 1,
99-113.
Preacher, K. J., & Hayes, A. F. (2008). Asymptotic and resampling strategies for assessing and
comparing indirect effects in multiple mediator models. Behavior Research Methods, 40,
879-891.
Purcell-Gates, V. (2000). Family literacy. In M. L.
Kamil, P. B. Mosenthal, P. D. Pearson, & R.
Barr (Eds.), Handbook of reading research
(Vol. III, pp. 853-870). Mahwah, NJ: Lawrence Earlbaum Associates.
Raftery, A. E. (1993). Bayesian model selection in
structural equation models. In K. A. Bollen &
J. S. Long (Eds.), Testing structural equation
models. Newbury Park, CA: Sage.
Scarborough, H. S. (2002). Connecting early language and literacy to later reading (dis) abilities: Evidence, theory and practice. In S. B.
Neuman & D. K. Dickinson (Eds.), Handbook
of early literacy research (pp. 97-110). New
York, NY: Guilford Press.
Seginer, R. (2006). Parents’ educational involvement: A developmental ecology perspective.
Parenting, Science and Practice, 6, 1-48.
Sénéchal, M., & LeFevre, J. (2002). Parental involvement in the development of children’s
reading skill: A five-year longitudinal study.
Child Development, 73(2), 445-460.
Snow, C. E., Burns, S., & Griffin, P. (Eds.). (1998).
Preventing reading difficulties in young
children. Washington, DC: National Academy
Press.
Stanovich, K. E., Cunningham, A. E., & West, R.
F. (1998). Literacy experiences and the shaping of cognition. In S. Paris & H. Wellman
(Eds.), Global prospects for education: Development, culture, and schooling (pp. 253288). Washington, DC: American Psychological Association.
Steiger, J. H. (1990). Structural model evaluation
and modification: An interval estimation approach. Multivariate Behavioral Research,
25, 173-180.
Taylor, A. B., MacKinnon, D. P., & Tein, J -Y.
(2008). Tests of the three-path mediated effect. Organizational Research Methods, 11,
241-269.
Taylor, R. (2000). The Familia Inventory user’s
manual and infant/toddler supplement.
Grandview, MO: Family Reading Resources.
van Steensel, R. (2006). Relations between sociocultural factors, the home literacy environment and children’s literacy development in
the first years of primary education. Journal
of Research in Reading, 29, 367-382.
Weigel, D. J, Lowman, J. L., & Martin, S. S.
(2007). Language development in the years
before school: A comparison of developmental assets in the home and child care settings.
Early Child Development and Care, 177(6),
719-734.
Weigel, D., J., Martin, S. S., & Bennett, K. K.
(2006). Contributions of the home literacy
to preschool-aged children’s emerging literacy
and language skills. Early Child Development
and Care, 176(3), 357-378.
Wozniak, R. H. (1993). Co-constructive metatheory for psychology: Implications for an analysis of families as specific contexts for development. In R. H. Wozniak & K. W. Fisher Eds.),
Development in context: Acting and thinking in specific environments (pp. 77-91).
Hillsdale, NJ: Lawrence Erlbaum.
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