Effects of The Home Learning Environment and Preschool Center Experience Upon Literacy and Numeracy Development in Early Primary School PDF
Effects of The Home Learning Environment and Preschool Center Experience Upon Literacy and Numeracy Development in Early Primary School PDF
Effects of The Home Learning Environment and Preschool Center Experience Upon Literacy and Numeracy Development in Early Primary School PDF
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Kathy Sylva
Department of Educational Studies, University of Oxford
Pam Sammons
School of Education, University of Nottingham
This study investigates the influence of aspects of home and preschool environments upon literacy and numeracy achievement at school entry and at the end
of the third year of school. Individuals with unexpected performance pathways
(by forming demographically adjusted groups: overachieving, average, and underachieving) were identified in order to explore the effects of the Home Learning
Environment and preschool variables on child development. Multilevel models
applied to hierarchical data allow the groups that differ with regard to expected
performance to be created at the child and preschool center levels. These multilevel analyses indicate powerful effects for the Home Learning Environment and
important effects of specific preschool centers at school entry. Although reduced,
such effects remain several years later.
Many research studies document the relationship of socioeconomic status
(SES) to cognitive development and academic achievement (e.g., Bloom, 1964;
Correspondence concerning this article should be addressed to Prof. Edward Melhuish, Institute
for the Study of Children, Families and Social Issues Birkbeck, University of London, 7 Bedford
Square, London WC1B 3RA UK [e-mail: e.melhuish@bbk.ac.uk].
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found that mothers with more intellectually stimulating jobs provided more support
and stimulating materials for their children, which was, in turn, linked to childrens
verbal skills. The argument linking low SES to lack of stimulation and lower
cognitive development has a long history and has regularly been supported by
evidence (e.g., Bradley, Corwyn, Burchinal, McAdoo, & Coll, 2001 2001; BrooksGunn, Duncan, & Aber 1997).
Parenting practices such as reading to children, using complex language, responsiveness, and warmth in interactions are all associated with better developmental outcomes (Bradley, 2002). This partly explains links between SES and
developmental outcomes, in that higher SES parents use more developmentally
enhancing activities (Hess et al., 1982). Stimulating activities may enhance development by helping children with specific skills (e.g., linking letters to sounds), but
also, and perhaps most importantly, by developing the childs ability and motivation concerned with learning generally. Additionally, it is possible that a feedback
loop is operating whereby parents are influenced by the childs level of attainment,
which would lead to children with higher ability possibly receiving more parental
stimulation.
Better understanding of the factors influencing childrens preparedness for
school and capacity for educational achievement has implications for (a) theories
of educational achievement and (b) educational policy and practice. A theory of
educational achievement must account for influences before schooling starts if
it is to be worthwhile, and this study considers modifiable factors in the early
years that can influence school readiness. Such evidence may be useful to governments wishing to maximize educational achievement and indicates appropriate
steps to facilitate childrens preparedness for school. Such policy changes may
operate locally although enabling policies may need central government planning
(Feinstein, Peck, & Eccles, in press). Findings from studies such as this may indicate the appropriate focus of such policies.
The study aims to advance research on parenting and preschool by considering
aspects of the home environment and preschool composition as partial explanations
for why home and preschool environments produce effects upon childrens literacy
and numeracy. To such ends, this study aims: to demonstrate that an interviewbased measure of the home environment is associated with academic achievement
at the start of school and in later years; to determine the influence of the childs
preschool center upon academic achievement; and to identify whether preschool
center composition is pertinent to developing literacy and numeracy during the
first years of school. Groups with unexpected levels of attainment (not achieving
as expected on the basis of demographic characteristics) were examined using
multilevel modeling to examine performance at the level of both individuals and
preschool centers. Thus, this study investigates sources of unexpected performance
that are linked to the immediate environment (meso-level) rather than due to individual or more macro-level variables.
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Method
Participants
One hundred and forty one preschool centers were randomly chosen in six
local authorities, identified as having a demographic make-up similar to that of
England overall. From these 141 centers 2857 children were recruited into a longitudinal study. Children already in preschools were recruited when they became
3 years old; children starting preschool after their third birthday were recruited
at entry to preschool. Their mean age at entry to the study was 3 years 5 months
(SD = 4.6 months). Full data exist for 2603 children and families at 3 and 5 years
and 2354 at 3, 5, and 7 years.
Measures
When children entered the study, they were assessed with four subscales from
the British Ability Scales II (BAS II; block building, picture similarities, verbal
comprehension, and naming vocabulary) (Elliot, Smith, & McCulloch, 1996) to
give a general cognitive ability (GCA) score. Upon entering primary school at
age 5, children were assessed again with the BAS II. In addition, literacy was
assessed by combining the Letter Recognition Test (Clay, 1993) and subscales
on the Phonological Awareness assessment (Bryant & Bradley, 1985); numeracy
was assessed by the Early Number Concepts subscale of the BAS II. At the end
of the third school year (7+ years) nationally standardized, teacher conducted,
national assessments of the childrens achievement in reading and mathematics
were obtained.
Shortly after initial child assessments, one of the childs parents or guardians
was interviewed (usually the mother). Most questions in the semistructured interview were precoded, with some open-ended questions coded post hoc. The interview covered: parents education; occupation and employment; family structure;
ethnicity and languages used; the childs birth weight, health, development, and
behavior; the use of preschool provision and childcare history; and significant life
events. The parental interview included questions concerning the frequency that
children engaged in 14 activities: playing with friends at home, playing with friends
elsewhere, visiting relatives or friends, shopping with parent, watching TV, eating
meals with the family, going to the library, playing with letters/numbers, painting
or drawing, being read to, learning activities with the alphabet, numbers/shapes,
and songs/poems/nursery rhymes, as well as having a regular bedtime. Frequency
of activities was coded on a 7-point scale (0 = not at all; 7 = very frequent).
A selection of these activities was used in the construction of a home learning
environment index as described later.
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Analytic Strategy
Children and families are clustered by preschool center and data are hierarchical. Using standard regression with such data can lead to inaccurate error variance
estimates. Potentially, there is greater similarity between participants within the
same centers so the independence of measurement assumption is violated and misestimating of levels of significance is likely. Hence, we used multilevel modeling
(Goldstein, 2003) to overcome such problems and to provide estimates of center
effects thus allowing the identification of preschool centers that were particularly
effective or ineffective in fostering childrens development.
Analyses focused on four outcomes: literacy and numeracy achievement at
age 5 (start of primary school) and reading and mathematics achievement at
7+ years. First, multilevel models of age 5 outcomes were run to assess the extent
of reliable variation in age 5 outcomes across preschool centers and to produce
child and center residuals after controlling for family and background characteristics. These multilevel models estimate the proportion of variance not only between
children within centers but also between centers. Childrens predicted achievement
in school was based on age, gender, birth weight, ethnic group, health, developmental or behavioral problems, mothers and fathers education, highest social
class of mother and father (family socioeconomic status, SES), number of siblings, deprivation (eligible for free school meals or not), household income, and
duration of preschool attendance. Several predictors were categorical (because the
interview provided categorical answers) with a reference category (lowest usually, but for ethnicity white UK group as reference), and other predictors were
continuous variables (i.e., birth weight, age, and duration of preschool).
Second, using multilevel model residuals at the individual level, three groups
were formed: unexpected overachieving, expected, and unexpected underachieving. Analyses explored how the 14 individual home activities influenced the probability of children performing better or worse than expected. Using the results
from these analyses, seven of the 14 home activities were selected to create a
home learning environment (HLE) index. Also, using multilevel model residuals
at the center level, the analyses explored how center composition predicted centers
that had higher or lower scores than expected. The categories of over-achievers,
average, and underachievers were calculated using the individual-level standardized residuals from the multilevel model. A child was considered to be performing
below expectation if the childs standardized residual was more than one standard
deviation below the mean of zero, above expectation if the standardized residual
was above one standard deviation from the mean, and as expected if their score was
within one standard error of the mean. Center effects were similarly categorized
from the center-level standardized residuals, which provided a measure of the extent to which the children attending a particular center were performing above or
below expectation. Multinomial models assessed the effect of the home learning
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taught letters, being taught numbers, songs/poems/rhymes) had significant positive effects on unexpected achievements. Since the items are conceptually and
statistically linked a combined measure, the home learning environment (HLE)
was created. The frequency of each of the seven activities was coded on a 07
scale (0 = not occurring, 7 = very frequent), and the seven scores were added to
produce an index with a possible range of 049, which was normally distributed
with a mean of 23.42 (SD = 7.71).
Center Composition
Center composition was considered in terms of the level of mothers education
and average child cognitive ability in center at age 3. The percentage of children
with a mother with a degree in each center was standardized about the median to
account for a negative skew, with a mean of.31 (SD = .94). Center average ability
was constructed as the standardized average of childrens 3-year-old cognitive
ability score, with a mean of .04 (SD = 1.00). Center mothers education and
center child ability are highly associated (r = .58).
Predicting Under- and Over-Achievement at the Start of School (Age 5)
The multilevel models for age 5 outcomes treated children as clustered by
preschool center, allowing the estimation and separation of residuals into individual
and center variance, and estimation of the amount of variance explained by adding
parameters to the model in stepwise fashion (see Table 1). For age 5 literacy and
numeracy, family and background characteristics explained significant individual
variation between children in centers: 16% for literacy and numeracy scores. Thus,
most variation in childrens achievement was not due to family or background
characteristics but to other unmeasured factors not considered in the demographic
model.
It was hypothesized that variations in predicted achievement based upon family and background characteristics (i.e., unexplained individual-level variance)
would be partially accounted for by the home learning environment and by center
composition. Firstly, the categories of over- and under-achievement for children
and centers were examined for a relationship with home learning environment at
the child level, and with center composition, at the center level. The mean HLE
scores for the over-achieving (mean = 26.44, SD = 7.26), average (mean = 23.61,
SD = 7.45) and underachieving (mean = 21.62, SD = 7.83) groups of children
appear to vary systematically for the demographically adjusted levels of achievement (i.e., unexpected overachieving, expected, and unexpected underachieving)
in literacy. Multinomial logistic regressions confirm, as hypothesized, that children
with a higher HLE are more likely to be overachievers (p < .0001), while lower
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77.63
(2.22)
4.67
(1.13)
.057
15.7%
.17
(1.08)
61.69
(1.77)
6.38
(1.26)
.094
16.7%
1.27
(.97)
75.718
(2.16)
5.18
(1.20)
.064
17.8%
.03
(1.07)
1.43
(.19)
58.89
(1.69)
7.49
(1.41)
.113
20.5%
1.07
(.96)
1.72
(.17)
75.572
(2.16)
4.00
(1.02)
.050
22.8%
(center level)
.002
(1.06)
1.54
(.19)
1.40
(.28)
58.81
(1.68)
4.87
(1.03)
.076
35.0%
(center level)
1.06
(.95)
1.83
(.17)
1.89
(.27)
75.61
(2.16)
4.35
(1.07)
.054
16.0%
(center level)
.52
(1.07)
1.50
(.19)
1.20
(.29)
58.79
(1.65)
5.32
(1.08)
.083
29.0%
(center level)
1.80
(1.00)
1.80
(.62)
1.77
(.28)
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92.08
(2.49)
15.24
(2.49)
.142
Random effects
Individual error variance ()
.04
(.38)
74.08
(2.07)
18.06
(2.68)
.196
Random effects
Individual error variance ()
.04
(.40)
Table 1. Fixed and Random Effects at Child and Center Levels for the Prediction of Age 5 Literacy and Numeracy Achievement (Standard Deviations in
Brackets)
Random
Demographic
With center
With center %
effects
model
Add HLE
ability
mothers with degree
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HLE scores are associated with underachievement (p < .0001). For numeracy, the
effects were also significant but not as strong as for literacy. Children with higher
HLEs had a greater likelihood of overachieving in numeracy, and those with lower
HLE had a greater likelihood of underachieving in numeracy.
Next the hypothesized link between center composition and differences at the
center level in predicted achievement was considered. The mean center child ability varied for the overachieving (mean = 2.86, SD 7.39), average (mean = .06,
SD = 5.68), and underachieving (mean = 4.09, SD = 6.08) categories in literacy.
For numeracy, mean center child ability also varied for the over-achieving (mean =
3.26, SD = 6.53), average (mean = 0.94, SD = 6.51), and underachieving
(mean = 2.69, SD = 6.65) categories. The mean center percent of mothers
with degree also varies for the overachieving (mean = 18.89, SD = 23.79), average (mean = 8.76, SD = 17.91), and underachieving (mean = .80, SD = 10.31)
categories in literacy and for numeracy (overachieving mean = 13.14, SD = 2.92;
average mean = 11.08, SD = 18.55; and underachieving mean = 4.88, SD =
17.20). Multinomial logistic regressions confirm that over- and underachievement
for centers is significantly associated with center composition. Center average
ability differentiated overachieving centers from average-achieving centers for literacy and numeracy, but only differentiated underachieving centers from averageachieving centers for literacy, with the difference for numeracy not statistically
significant. Center levels of degree-educated mothers increased the likelihood of
overachievement and reduced underachievement for literacy, but the differences
for numeracy were not significant.
To support the conclusions that the HLE and center composition added to the
prediction of achievement over that provided by family and background characteristics for children, new multilevel models for literacy and numeracy were created.
These models included HLE and either center average ability or center percent of
mothers with degree as predictors in addition to the significant family and child
background factors (see Table 1). By adding the HLE to the demographic model,
the explained variance at the child level showed a 21% increase for age 5 literacy
and an 18% increase for age 5 numeracy.
Although the magnitude of random variance between centers was relatively
small compared to that between children, after accounting for the potentially selective effects of family background on the choice of preschool centers in the
demographic model, variation in literacy and numeracy scores at the center level
were significantly reduced. For example, center variance in age 5 literacy scores
showed a 52% decrease due to selection effects. With HLE in the model, center variance for literacy was 11%. Adding center composition into the multilevel
models separately led to a 33% reduction in center-level variance with center
ability added and a 27% reduction with center percent of mothers with degree
added. With HLE in the model, center variance for numeracy was 6%. Adding
center composition into the multilevel models separately led to a 22% reduction
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Melhuish et al.
in center-level variance with center ability added and a 16% reduction with center
percent of mothers with degree added. While including center composition reduces
unexplained center level variance, there was still significant center level variation
remaining, suggesting that further unmeasured characteristics of preschool centers
need to be explored.
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(.006)
.081
16.5%
(.008)
.121
.286
(.009)
.025
.066
(.072)
.356
(.012)
.035
(.008)
.088
21.7%
.208
(.086)
.342
(.011)
.047
Random effects
Individual error variance ()
.052
(.016)
Preschool effectiveness
.452
(.015)
.064
(.011)
.124
Random effects
Individual error variance ()
.073
(.018)
Preschool effectiveness
(.006)
.084
17.5%
.282
(.009)
.026
.032
(.069)
.087
(.013)
.344
(.011)
.036
(.008)
.095
23.9%
.166
(.085)
.125
(.015)
(.006)
.083
18.6%
.281
(.009)
.025
.031
(.069)
.086
(.013)
.028
(.009)
.343
(.011)
.035
(.008)
.094
24.1%
.164
(.085)
.123
(.015)
.022
(.007)
(.006)
.083
18.6%
.281
(.009)
.025
.031
(.069)
.085
(.013)
.025
(.009)
.018
(.016)
.342
(.011)
.036
(.008)
.095
24.4%
.163
(.085)
.121
(.015)
.015
(.008)
.042
(.019)
(.009)
.026
(.006)
.084
18.7%
.014
(.019)
.281
.035
(.069)
.085
(.013)
.026
(.009)
.343
(.011)
.035
(.008)
.093
24.1%
.005
(.019)
.16
(.085)
.123
(.015)
.022
(.008)
Table 2. Fixed and Random Effects at Child and School Levels for the Prediction of Age 7 Reading and Mathematics Achievement (Standard Deviations in
Brackets)
Random
Demog.
With center
With center
With center %
effects
model
Add HLE
effect/ness
ability
mothers with degree
1
Home and Preschool Influences on Achievement
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Table 3. Effect Sizes for SES, Mothers and Fathers Education, Income, and HLE on 5- and 7-Year
Outcomes
5 year
SES
Mothers education
Fathers education
Earned income
HLE
7 year
Literacy
Numeracy
Reading
Mathematics
.29
.35
n.s.
.31
.73
.43
.23
n.s.
.28
.65
.37
.33
.19
.15
.60
.39
.33
.16
.15
.50
achievement scores was 21% and 18%, respectively. Hence the HLEs effects on
childrens achievement were reduced by age 7, but were still significant. Preschool
center effectiveness has significant effects for both 7-year reading and mathematics attainment. Adding center average ability reduced this effect to insignificance
for reading but had no impact for mathematics. The educational level of mothers
of children in a center had no significant effect for reading or mathematics.
Effect Sizes for Child Level Variables
The final multilevel models allow for the calculation of effect sizes for an
independent variable having allowed for the influence of all other variables in the
model. Effect sizes are calculated for the HLE variable and also the main aspects
of social class (i.e., family SES, mothers and fathers education, and household
income); these are shown in Table 3. For 5-year-old literacy achievement, the
effect size for HLE (bottom 10% compared with top 10%) was greater than that
for any of the variables reflecting social class. For 5-year-old numeracy, HLE again
had the largest effect size followed by SES, then household income and mothers
education. For both 7-year-old reading and mathematics, the largest effect size
was still for HLE, followed by SES, mothers education, fathers education, and
household income.
Discussion
The results clearly support the importance of the Home Learning Environment
(HLE) and the influence of the HLE was over and above that of standard proxy
measures of parental education and SES. The results also demonstrate that this
interview method is useful for identifying variability in parenting. While other
family factors such as parents education and SES are also important, the extent of
home learning activities exerts a greater and independent influence on educational
attainment.
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behaviors are learnable, and changes in parenting are associated with improved
child development. Similar conclusions derive from a study by Hannon, Nutbrown,
and Morgan (2005) in the United Kingdom, where children showed better literacy
progress when parents received a program on ways to improve child literacy during
the preschool period.
With primary school children, similar links between parenting and academic
achievement occur. DeGarmo, Forgatch, Martinez (1999) found that the effects
of parent education upon primary school achievement were primarily mediated
through parents provision of opportunities for building intellectual skills. Reviewing studies, Mason and Allen (1986) concluded that the quality and quantity
of interactions, not just reading materials and a story time routine, shaped early
literacy. Similarly, Zellman and Waterman (1998) found parent-child interaction
more important than other family variables for primary school childrens success
in reading or mathematics.
With secondary school children, similar effects are detectable. In the United
States, Siu-Chu and Willms (1996) analyzed data for 24,000 14-year-olds and
found that parental involvement was linked to academic achievement over and
above the effects of family demographics; in particular, parent-child interaction
seemed most important. Similarly, in the UK, Feinstein and Symons (1999) found
that indicators of parental interest and involvement with child learning were more
important in predicting academic achievement at 16 than parental education and
social class.
Such research indicates the importance of school readiness, and mounting evidence demonstrates the role of parenting for childrens school readiness skills and
ongoing achievement. Academic achievement in adolescence and beyond can be
linked to academic skills at school entry (Alexander, Entwisle, & Horsey, 1997),
and school entry ability can, in turn, be linked to preschool abilities (Agostin &
Bain, 1997). Possibly, preschool experience matters because behavior is more susceptible to the environment earlier rather than later in childhood or because starting
school is a critical social transition when ability predicts longer-term achievement
through creating expectations.
The influences upon parenting and how parenting may influence educational
achievement are not simple matters. Poverty, parental education, culture, ethnicity,
parental age, health, and other factors are all likely to be important, and multiple
factors will interact complexly as shown by Messersmith and Schulenberg (in
press) for college students. However, it is clear that parenting is influenced by
poverty. For instance, NICHD ECCRN (2005) reported that families in chronic
poverty have less stimulating home environments but that the home environment
improves as families move out of poverty. Also, families exposed to transient
poverty appear to manage to maintain adequate home stimulation despite restricted
resources. Wachs and Camli (1991) noted that crowding, the number of people
coming and going in the home, and noise level, may have adverse effects on
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380.
EDWARD MELHUISH has studied the development of preterm babies; the children of psychiatrically disturbed parents; social, linguistic and cognitive development; emergent literacy; day care and the evaluation of policy initiatives. Earlier
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work on day care influenced sections of the 1989 Children Act. He has collaborated with social, economic, biological, and medical scientists in studying child
development and the influence of experience. Currently, he is involved in longitudinal studies that are informing policy formation, such the 2004 Children Act and
the 2005 Childcare Act. He is a scientific advisor to the Nordic Research Council,
the Academy of Finland, the Portuguese Research Council, and the Australian
Research Council.
KATHY SYLVA is Professor of Educational Psychology at the University of Oxford, Department of Educational Studies. After earning a PhD at Harvard University she moved to Oxford. Her book Childwatching at Playgroup and Nursery
School broke new ground by questioning an unbridled free play ideology. She
has also carried out research on early literacy in Reception and Year 1. She is one
of the leaders of the DfES research on effective provision of preschool education. In 200/2001 and 20042007 she served as specialist adviser to the House of
Commons Select Committee on Education and Skills.
PAM SAMMONS is a Professor of Education at the University of Nottingham and
part of the Teacher and Leadership Research Centre there. Previously she was a
Professor at the Institute of Education University of London and Co-coordinating
Director of its International School Effectiveness & Improvement Centre (1999
2004). Her research over the last 25 years has focused on educational effectiveness and improvement, leadership and equity in education including preschool
influences, as well as primary and secondary school studies. She is a Principal
Investigator of the DfES-funded EPPSE longitudinal study.
IRAM SIRAJ-BLATCHFORD is Professor of Early Childhood Education at the
Institute of Education, University of London. Her research interests include early
childhood curriculum and pedagogy, the quality of early years provision and
parental engagement and childrens learning in the home. She is the co/author of
over 30 books, monographs, and major published research reports and over a 100
chapters, articles, and reports. She is a principal investigator of the DfES-funded
EPPSE longitudinal study.
BRENDA TAGGART has a background in preschool and primary education as
a teacher, Advisory Teacher, deputy and acting head teacher. She has worked
extensively in initial and continuous professional development for teachers. Her
research includes commissions for Research Bodies, Government Agencies, and
private funders as well and numerous Local Authorities. She has worked on a number of research projects that have investigated the impact of government initiatives
at school level. She is currently the Research Coordinator/ Principal Investigator
for the Effective Preschool, Primary, and Secondary Education Project (EPPSE
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314), a longitudinal study funded by the UKs Department for Education and
Skills.
MAI B. PHAN is a PhD candidate at the University of Kent, Canterbury. She is
the recipient of the Social Sciences and Humanities Research Council Canadian
Graduate Scholarship. Currently, she works as a researcher at the Institute for the
Study of Children, Families and Social Issues on a part-time basis.
Queries
Q1 Author: Please provide all author names in reference Love et al. 2005.