Family Matters No. 93 - December 2013

Early education and care experiences and cognitive skills development

A comparative perspective between Australian and American children
Rebekah Levine Coley, Caitlin McPherran Lombardi and Elizabeth Votruba-Drzal

Abstract

Australia and the US share many economic and cultural similarities, yet have policy differences in their support for children's early education and care (EEC) that may have differential implications for children's development. This study used nationally representative, longitudinal birth cohort studies from each country - the B cohorts of the Longitudinal Study of Australian Children (LSAC-B) and the Early Childhood Longitudinal Study (ECLS-B) - to assess patterns of EEC among young children and influence of EEC on children's cognitive skills following school entry. Results found that Australian parents were more likely to use part-time EEC for their children, and the children were more likely to be in centre care during their infant and toddler years than American children, whereas American parents were more likely to use informal, home-based care and full-time EEC. Infant EEC was neither promotive nor detrimental for later cognitive skills. In both countries, later centre care was promotive of cognitive skills after school entry. These benefits came from toddler centre care in Australia and from preschool centre care in the US. The policy implications of these findings are discussed.

Australia and the US, while sharing many cultural and economic similarities, show notable differences in policies and practices regarding children's early education and care (EEC). Although both countries rely on the private market for EEC, Australia has stronger supports for high-quality EEC and provides parents of all income levels greater financial support for EEC. Little research has compared the EEC experiences of young children in the two contexts and resultant links with children's readiness for formal schooling. This research uses nationally representative longitudinal birth cohort studies from Australia and the US to address two primary questions. First, what are the types and extent of EEC experiences during infancy, toddler and preschool years in the two contexts? Second, do EEC experiences promote the cognitive skills essential for children's success at school?

Empirical review of early childhood education and children's cognitive development

A growing literature, primarily from the US, has documented links between characteristics of EEC settings, including the type and extent of care, and children's development. Numerous studies of US children have found that attending centre-based EEC programs (e.g., preschool, nursery school, pre-kindergarten, and other centre-based child care programs) is predictive of greater reading and math skills in comparison to parental care or more informal home-based care settings (Gormley, Gayer, Phillips, & Dawson, 2005; Loeb, Bridges, Bassok, Fuller, & Rumberger, 2007; Magnuson, Meyers, Ruhm, & Waldfogel, 2004; Morrissey, 2010; National Institute of Child Health and Human Development Early Child Care Research Network [NICHD ECCRN], 2002, 2005; NICHD ECCRN & Duncan, 2003). Much of this research has focused explicitly on centre-based EEC programs for 3 and 4-year-olds in the year or two prior to entering primary school. The extent of EEC, or the number of hours per week that children spend in EEC settings, has not been associated consistently with early cognitive development, although studies have repeatedly demonstrated associations between both centre-based care and greater hours of care and elevations in children's behavior problems (for reviews, see Coley, Votruba-Drzal, Miller, & Koury, 2012; Phillips, McCartney, & Sussman, 2006). These elevations may have implications for children's cognitive skills development, given prior literature linking externalising problems to cognitive skills development (Li-Grining, Votruba-Drzal, Maldonado-Carreño, & Haas, 2010).

Some have argued that as children grow from infancy through early childhood the influence of EEC settings on children's development may change. These studies suggest that centre-based care during the later toddler and preschool years (e.g., after age 2) may be more beneficial for children's academic skills development than infant/early toddler centre-based care for children under the age of 2 (Loeb et al., 2007; NICHD ECCRN & Duncan, 2003; Votruba-Drzal, Coley, Koury, & Miller, 2012). For example, NICHD ECCRN and Duncan (2003) discovered that attending centre-based care between 3 months and 24 months of age was unrelated to cognitive and academic scores at kindergarten entry, whereas exposure to centre-based care between 27 months and 54 months of age conferred significant benefits. Similarly, Loeb and colleagues (2007) found that the greatest academic benefits of centre-based care were for children who began centre-based care between 2 and 3 years of age, rather than either earlier or later in the preschool years. Little attention has been paid to the differential effects of the extent of care during infancy versus later in early childhood.

The cognitive benefits of centre-based care also have been illustrated using data from the older child cohort of Growing Up in Australia: The Longitudinal Study of Australian Children (LSAC; Australian Institute of Family Studies, 2009). Using retrospective reports of EEC attendance in the year prior to primary school, research has found that participation in preschool programs was associated with enhanced literacy and numeracy skills in comparison to children not attending preschool programs (Claessens & Garrett, 2011; Harrison et al., 2009; Smart, Sanson, Baxter, Edwards, & Hayes, 2008). However, this research did not take into account children's earlier experiences of EEC prior to preschool, making it difficult to examine the differential effects of care during infancy versus later childhood, and leaving open questions concerning whether the cognitive skills boost is derived from preschool or from early experiences correlated with preschool care.

Several factors explain why there may be differences in the effects of centre-based care settings on children's cognitive development as children age. During the early infant and toddler years, children's cognitive, social and emotional skills develop rapidly. During this time, children may benefit most from one-on-one interactions and the warm, responsive caregiving that promotes secure child-caregiver attachments and provides rich language stimulation and opportunities for children to safely explore their environment (Early & Burchinal, 2001). The larger group sizes that are common in centre-based EEC setting may be stressful for young children. Indeed, prior studies have shown that in infancy and toddlerhood, children are at heightened risk of elevations in cortisol over the course of the school day when compared to their older counterparts, which may in turn have implications for their development of early cognitive skills (Dettling, Gunnar, & Donzella, 1999; Vermeer & van IJzendoorn, 2006; Watamura, Donzella, Alvin, & Gunnar, 2003). Thus, younger children may develop optimally with parental care or within smaller and more intimate non-parental care settings (such as home-based care by relatives or non-relatives), where there are fewer peers and greater adult-child ratios than centre-based programs (Dowsett, Huston, Imes, & Gennetian, 2008).

With enhanced language skills, greater emotional regulation, and more advanced social skills, older, preschool-aged children may benefit more from varied environments with a broad array of learning experiences and peers with which to engage. Centre-based EEC programs often provide trained caregivers, more peer interaction opportunities, and more structured and varied educational curricula than parental or home-based EEC settings for preschool-age children, which may enhance preschoolers' cognitive skills (Coley, Li-Grining, & Chase-Lansdale, 2006; Dowsett et al., 2008; Fuller, Kagan, Loeb, & Chang, 2004; Maccoby & Lewis, 2003). Also, with more advanced self-regulatory skills, preschool-aged children evidence less stress in the context of centre-based EEC settings (Dettling et al., 1999; Vermeer & van IJzendoorn, 2006; Watamura, et al., 2003). These factors suggest that for preschoolers, centre-based care may optimally promote school readiness skills.

Early childhood education policy in Australia and the United States

Although Australia and the US share many economic and child care market features, there are notable differences in governmental support for early education and care. According to the Organisation for Economic Co-operation and Development (OECD), both countries spend considerably less on families than most other peer countries in the OECD. However, the Australian Government provides parents with a variety of early childhood subsidies that exist only sparingly in the US. These differences begin at childbirth and may explain differences in the use of infant care between the two countries. Australia has long offered new parents one year of unpaid leave and a one-time "Baby Bonus" payment upon the birth of a child, and an 18-week paid leave option has been offered as an alternative to the Baby Bonus since 2011. In contrast, the US offers new parents 12 weeks of unpaid leave, with limited paid leave existing only within the private sector and in some individual states, suggesting that there would be a greater need in the US for EEC during infancy. The US also imposes work requirements for mothers receiving welfare, starting in their child's infancy, whereas in Australia, mothers receiving welfare are not required to return to work until their youngest child reaches six years of age (Department of Human Services [DHS], 2013b). In concert with these policy differences, maternal employment patterns differ notably between the two countries, with US mothers entering employment earlier and being notably more likely to work full-time than Australian mothers (Australian Bureau of Statistics [ABS], 2012; US Department of Labor, 2009).

Extensive differences also exist between the two countries when it comes to paying for EEC. In Australia, the federal government covers up to 50% of families' costs for centre-based care through the Child Care Rebate (up to a maximum of $7,500 per year), and also subsidises informal registered child care (DHS, 2013a; Michel, 2003). Furthermore, Australian state/territory governments directly fund public preschools for the year prior to primary school entry. In contrast, the US reserves direct subsidies for low-income and poor families, with middle and upper income families receiving less generous tax credits. US preschools have long existed primarily in the private market, although publicly funded pre-kindergarten programs have expanded rapidly in the US over the past decade. Finally, the differences also extend to quality regulations. Australia's National Quality Framework evaluates nearly all Australian care settings, even family day care centres, while in the US, nearly 25% of children experiencing EEC attend unregulated care settings (Zigler, Marsland, & Lord, 2009). In short, Australia offers richer public options for EEC and more heavily regulates and subsidises these options, whereas the US system relies primarily on the private market, with fewer regulations and subsidies (Michel, 2003).

Given these distinctions, it follows that access to and use of EEC may differ between the countries as well. Prior research has found that a more substantial proportion of Australian children (90%) attend an EEC setting at some point prior to school entry compared to their US peers (about 78%), and Australian families are likely to place their children, particularly preschool-aged children, in EEC programs regardless of maternal employment status (ABS, 2006; Harrison & Ungerer, 2005; Harrison et al., 2009; Votruba-Drzal, et al., 2012). Still, research indicates that the most disadvantaged families in both countries are less likely to use formal EEC settings than their more advantaged counterparts (Capizzano & Adams, 2004; Harrison & Ungerer, 2005). Australia has responded to this need by committing to provide all children with access to high-quality preschool programs in the year prior to primary school by 2013 (Department of Education, Employment and Workforce Relations [DEEWR], 2012). Australia also has made a recent commitment to improving quality and standardising quality standards across states and territories through the National Quality Framework, whereas the US retains a diverse range of state regulations. Overall, these differences in policies for young families may lead to heterogeneity in EEC experiences during the infancy, toddler, and preschool years. Moreover, they also may give rise to variability in the effects of EEC experiences on children's cognitive development.

Method

Sample

Data for this paper were drawn from two nationally representative birth cohort studies that follow children from birth through school entry: the Longitudinal Study of Australian Children Birth cohort (LSAC-B) from Australia, and the Early Childhood Longitudinal Study Birth cohort (ECSL-B) from the United States. These studies are particularly well suited for comparative research due to similarities in the sampling time frames and measures of EEC and children's functioning. Both studies have probability weights, making the samples nationally representative.

LSAC-B is a nationally representative study of a cohort of approximately 5,100 children born in Australia between March 2003 and February 2004. Births were sampled from the Medicare enrolment database, with stratification used to ensure proportional geographic representation for each state and territory. The survey sample excluded non-permanent residents, children with the same name as deceased children, and only allowed for one child per household. For more information on LSAC-B, see Sanson et al. (2002) and Soloff, Lawrence, and Johnstone (2005).

LSAC-B has so far collected four waves of data, with in-person interviews and direct assessments when children were, on average, 9 months (Wave 1), 3 years (Wave 2), 5 years (Wave 3), and 7 years (Wave 4), and with response rates of 58%,1 90%, 86% and 84% respectively. Data also were collected through mail-in written surveys in between the main waves, at average ages of nearly 2 years (Wave 1.5), nearly 4 years (Wave 2.5), and 6 years (Wave 3.5), and with response rates of 71%, 64% and 59% respectively. We selected four waves of the LSAC-B data that best matched the developmental timing of the ECLS-B data collection: Wave 1 (9 months), which we will refer to as the infant wave; Wave 1.5 (nearly 2 years), referred to as the toddler wave; Wave 2.5 (nearly 4 years), referred to as the preschool wave; and Wave 4 (7 years), the school-age wave.2 Due to a high amount of missing data in the LSAC-B analytic sample, due to attrition and missing data on individual measures, missing data were imputed in Stata 12 (Royston, 2004, 2005) using multiple imputation by chained equations. The final LSAC-B analytic sample consisted of all children from the Wave 1 sample, a total of 5,107 children.

The ECLS-B is a nationally representative birth cohort study of approximately 10,700 children3 born in the United States in the year 2001 (Flanagan & West, 2004). Children who died or were adopted prior to the age of 9 months and children born to mothers under age 15 were excluded from the sample. The ECLS-B collected four waves of data on the birth cohort at average ages of 10 months (Wave 1; infancy), 2 years (Wave 2; toddlerhood), 4 years (Wave 3; preschool) and 5 years, following the entry to primary school (Wave 4/5; school-age),4 with response rates of 74%, 93%, 91% and 92-93%. Our analytic sample contained approximately 6,250 children who remained in the ECLS-B sample in Wave 4 with complete data,5 with weights used to adjust for differential non-response and attrition.

Measures

Across all constructs, measures were created in a parallel fashion for the two datasets, except as noted.

EEC characteristics

In both studies, parents reported on regular non-parental care settings that their children experienced at each wave of the study. At each wave, data were coded into three mutually exclusive categories of care: centre (day care centre, preschool, Head Start), informal (relative, nanny, other non-relative, family day care, occasional care),6 or parent care (used as the reference category for later analysis). Due to the nature of the data availability and to extant literature suggesting the significant role of centre-based care in children's development, we "prioritised" centre-based care, coding the EEC type as "centre" if children received both centre-based and informal care. We considered separating out relative from non-relative informal care arrangements; however, these two types of care arrangements during infancy, toddlerhood or preschool stages were not related differently to children's later cognitive skills in either dataset. Thus, we used the combined measure of informal care arrangements. Because parent reports may not be reliable in differentiating subtypes of centre-based care arrangements (e.g., for-profit versus non-profit, or publicly funded pre-kindergarten versus private centres) and provider reports were not available across all waves of the two datasets, we also included all types of centres into one holistic group. At each wave, a dummy variable was created to denote whether children were in multiple concurrent non-parental care arrangements.

The extent to which children experienced EEC was measured at each wave using parent reports of the number of total hours per week children spent in care arrangements. Extent of care was categorised into full-time EEC (30 hours or more per week), part-time EEC (less than 30 hours), or no non-parental care.

Children's cognitive skills

Four measures of children's cognitive skills were assessed at age 7 in LSAC-B. Children's academic skills were assessed using the Academic Rating Scale (National Centre for Educational Statistics, 2002), in which teachers rated children's skills on a five-point scale (not yet = 1 to proficient = 5). The teachers reported on the subscales for Language and Literacy (9 items, α = .96) and Mathematical Thinking (9 items, α = .94). Children were directly assessed with the Matrix Reasoning test from the Wechsler Intelligence Scale for Children, 4th edition (WISC-IV) to assess non-verbal intelligence. Children's receptive vocabulary skills also were directly assessed by field interviewers using a shortened version of the Peabody Picture Vocabulary Test, 3rd edition (PPVT-III; Australian Council for Educational Research, 2000; Dunn & Dunn, 1997).

In the ECLS-B, children's cognitive skills at age 5 were measured using direct assessments to test children's reading, maths and language skills. The reading and maths skills assessments comprised items drawn from well-validated standardised instruments, including the PPVT-III (Dunn & Dunn, 1997), PreLAS 2000 (Duncan & De Avila, 1998), Preschool Comprehensive Test of Phonological & Print Processing (Lonigan, Wagner, Torgesen, & Rashotte, 2002), and Test of Early Mathematics Ability, 3rd edition (Ginsburg & Baroody, 2003). The early reading assessment (74 items, α = .92) assessed letter knowledge, word recognition, print conventions and phonological awareness. The maths assessment (58 items, α = .92) assessed number sense, properties, operations and probability. Children's expressive language skills were assessed using the Let's Tell Stories subscale of the PreLAS, using a 0 to 5 scale to indicate coherence, fluency and complexity of language use.

Child characteristics

Numerous child characteristics were drawn from the LSAC-B and ECLS-B, including age of assessment (in months) and gender. Child low birthweight status was represented with an indicator of whether the child was born of low birthweight (less than 2,500 grams) versus normal. Child health condition was also represented by an indicator that reflected whether the child was of fair or poor health based on parent reports at Wave 1. In LSAC-B, race/ethnicity was measured using two dummy variables that indicated whether the child had a parent of Asian origin or with an Indigenous background. Child race/ethnicity was captured in ECLS-B with dummy variables indicating non-Hispanic African American, Hispanic, Asian, American Indian or multiracial, with non-Hispanic White as the reference group.

Early cognitive ability was assessed in each study at Wave 1. In LSAC-B, the Communication and Symbolic Behavior Scales (CSBS) Developmental Profile: Infant-Toddler Checklist (Wetherby & Prizant, 2001) was used, with a 24-item parent report scale (α = .89) measuring children's early social, language and cognitive skills (Sanson, Misson, Hawkins, Berthelsen, & the LSAC Consortium Advisory Group, 2010). The ECLS-B used the Bayley Short Form - Research Edition (Bayley, 1993; Flanagan & West, 2004) to measure exploration of objects, early problem-solving and preverbal communication (α = .80).

Parental and household characteristics

Several parental and household characteristics also were assessed. Time-invariant variables were drawn from Wave 1, whereas time-varying characteristics were measured at Wave 1 and Wave 3 in both studies. Parental age was measured with age in years of the youngest parent in the household. Parental education was assessed using the highest level of educational attainment, delineated as less than a high school qualification, a high school qualification (reference group), trade certificate or some university, and a Bachelor's degree or higher. Maternal employment status was measured categorically indicating whether mothers were employed part-time (< 30 hours) or full-time (>= 30 hours) at Waves 1 and 3, in comparison to not being employed. A dichotomous variable indicated whether either of the child's parents was an immigrant. An additional dichotomous variable indicated whether the primary language of the household was non-English at Wave 1. Marital status was measured categorically, delineating whether the respondent was consistently married (versus single or cohabiting) at Waves 1 and 3, married at either wave, or not married at either wave. A continuous variable denoted the number of children under age 18 in the household, averaged over Waves 1 and 3. Finally, total annual household income was averaged over Waves 1 and 3, in units of $10,000.

Analytic approach

Associations between EEC and children's cognitive skills after school entry were modelled using a longitudinal lagged regression model, based on an accumulation of inputs framework (Blau, 1999; NICHD & Duncan, 2003). As shown in the following equation, cognitive skills following school entry (Wave 4 in LSAC-B and Waves 4/5 in ECLS-B) were expressed as a function of all EEC, child, maternal, and household inputs to a child's development prior to that point in time.

Child Outcomes4i = B0 + B1 Child Outcomes1i + B2EEC1,2,3i + B3Child1-3i + B4Maternal/Household1-3i + εi,

Because characteristics of children, parents, and families may affect use of EEC, and factors affecting family selection of EEC could also be related to children's cognitive skills, it is essential to adjust for such factors in seeking to isolate potentially causal connections between EEC experiences and children's cognitive skills. Thus, our analytic models included a rich set of child, maternal and household factors as covariates, chosen based on prior research. Models also included a Wave 1 measure of cognitive ability to control for unmeasured, time-invariant differences in children (Cain, 1975), thus further reducing concerns of omitted variable bias. For both studies, survey weights, which adjust for selection criteria and differential response, were incorporated in all analyses. The use of these weights makes each sample representative of infants born in each country at the time of the Wave 1 sample selection.

Prior to conducting the multivariate models, we adjusted the measures of cognitive skills to help control for the differences in measurement and child age at assessment across the LSAC-B and ECLS-B datasets. Raw outcome variables were adjusted for age by taking the residuals from a regression of the outcome score on child age, and then were standardised to have a mean of 0 and a standard deviation (SD) of 1 so that a one-unit difference represented a one standard deviation shift, as has been the practice in prior comparative child development research (e.g., Bradbury, Corak, Waldfogel, & Washbrook, 2010).

Results

Descriptive results

Table 1 presents weighted descriptive statistics on each of the samples. We note that for descriptive interpretation, we present the non-adjusted measures of children's cognitive skills. Children in the LSAC-B were slightly younger during the infant, toddler and preschooler waves, but slightly older at the final wave, in comparison to children in the ECLS-B. Considering child, parent and family characteristics, we see both similarities and differences across the datasets. Australian parents were slightly older, more likely to be married, more highly educated, and had higher incomes than their US counterparts. Mothers were more likely to be employed part-time in Australia and full-time in the US. Families in Australia were more likely to contain immigrant parents, but less likely to be non-English speaking than families in the US. Families in the US were more likely to be non-White, although we note that the LSAC-B did not explicitly ask for respondents' race and ethnicity beyond country of origin for immigrants and Aboriginal status.

Table 1: Child and family characteristics, LSAC-B and ECLS-B
  LSAC-B ECLS-B
% or M (SD) Range % or M (SD) Range
Child age (months)        
Infant 8.86 (2.57) 3-19 10.47 (1.96) 6-22
Toddler 21.49 (3.39) 15-29 24.39 (1.21) 17-38
Preschool 47.27 (3.34) 41-53 52.38 (4.09) 44-65
School-aged 81.98 (3.51) 73-93 68.18 (4.42) 57-84
Child outcomes        
Maths score 3.30 (0.80) 1-5 44.09 (10.16) 11-70
Reading score 3.35 (0.77) 1-5 44.02 (14.29) 12-82
Matrix Reasoning score 10.60 (3.02) 3-19 - -
Vocabulary/language score 73.99 (5.20) 54-92 3.46 (0.79) 0-5
Covariates        
Child male 51.2% 0-1 51.2% 0-1
Race/ethnicity        
White 86.9% 0-1 53.7% 0-1
African American - - 13.9% 0-1
Hispanic - - 25.2% 0-1
Asian 8.5% 0-1 2.8% 0-1
Indigenous 4.6% 0-1 - -
Native American - - 0.5% 0-1
Multiracial and other - - 4.0% 0-1
Child low birthweight 0.06% 0-1 7.5% 0-1
Child bad health 3.1% 0-1 2.4% 0-1
Child CSBS/Bayley score 25.88 (9.70) 0-57 50.37 (9.64) 0-99
Immigrant household 31.5% 0-1 24.3% 0-1
Non-English household 15.7% 0-1 18.5% 0-1
Child number of siblings a 0.99 (1.07) 0-10 1.19 (1.06) 0-9
Parental marital status        
Parent never married a 21.1% 0-1 27.3% 0-1
Parent sometimes married a 11.4% 0-1 10.9% 0-1
Parent always married a 67.5% 0-1 61.8% 0-1
Youngest parent's age 31.41 (5.29) 15-63 27.85 (6.13) 17-70
Parental education        
Parent < high school education a 4.8% 0-1 8.3% 0-1
Parent high school education a 4.5% 0-1 23.0% 0-1
Parent trade certificate/some university a 48.3% 0-1 34.2% 0-1
Parent Bachelor's degree a 42.3% 0-1 34.5% 0-1
Annual household income ($10,000s) a 8.39 (5.12) 0-54 5.41 (4.36) 0-20
Mother's employment status        
Part-time employed Wave 1 23.2% 0-1 18.0% 0-1
Part-time employed Wave 3 40.0% 0-1 17.3% 0-1
Full-time employed Wave 1 9.4% 0-1 35.0% 0-1
Full-time employed Wave 3 18.7% 0-1 42.2% 0-1

Notes: a Averaged over Wave 1 and Wave 3.

Table 2 presents descriptive statistics on children's EEC experiences. During infancy, only one-third of children in Australia were in non-parental EEC, compared to one-half of US infants. These differences were driven by informal care: in both datasets, approximately 10% of children were in centre-based care during infancy, while 24% of Australian and 41% of US infants were in informal EEC. US infants also were five times more likely to be in full-time EEC than their Australian counterparts (30% versus only 6% respectively). Some of these differences had evened out by the toddler wave, with close to half of the children in both datasets experiencing non-parental EEC. Australian toddlers were slightly more likely to be in centres and less likely to be in informal EEC than US toddlers.

Table 2: Types and extent of EEC experiences for infant, toddler and preschool children, LSAC-B and ECLS-B
  LSAC-B (%) ECLS-B (%)
Infant    
EEC type    
Parent 65.5 49.6
Centre 10.7 9.2
Part-time 8.1 2.4
Full-time 2.6 6.9
Informal 23.9 41.2
Part-time 20.0 17.7
Full-time 3.9 23.5
EEC extent    
Part-time 28.1 20.0
Full-time 6.4 30.4
Multiple EEC arrangements 8.4 5.0
Toddler    
EEC type    
Parent 47.4 51.3
Centre 26.2 16.8
Part-time 21.2 4.7
Full-time 4.9 12.1
Informal 26.5 31.9
Part-time 23.3 11.7
Full-time 3.2 20.2
EEC extent    
Part-time 45.2 17.2
Full-time 8.1 31.5
Multiple EEC arrangements 18.0 4.6
Preschool    
EEC type    
Parent 14.6 20.3
Centre 74.7 69.2
Part-time 63.2 34.7
Full-time 11.4 34.5
Informal 10.8 10.5
Part-time 9.6 4.5
Full-time 1.2 6.1
EEC extent    
Part-time 77.0 39.7
Full-time 12.7 40.6
Multiple EEC arrangements 36.7 20.6

In relation to EEC extent, large differences remained, with American toddlers being four times more likely than Australian toddlers to experience full-time EEC (32% vs 8% respectively). On the other hand, Australian children were much more likely than US children to be in multiple care arrangements (18% vs 5% respectively). Finally, at the preschool wave, Australian children were slightly more likely than their US counterparts to be in non-parental EEC (85% vs 80% respectively), with this being driven by the greater use of centre-based preschools. Australian preschoolers continued to be much more likely to be in EEC part-time rather than full time (77% part-time in Australia vs 40% in the US), and also to use multiple types of EEC (37% vs 21% respectively).

Before turning to associations between EEC experiences and children's later cognitive skills, we also assessed whether there were differences in the family socio-economic characteristics of children attending EEC programs in the two countries. Our results generally showed very similar patterns (results not shown). In both samples, families with greater income, higher parental education, and more full-time maternal employment were more likely to use centre-based and informal care than parent care. One difference was that in the Australian data, married mothers were less likely to use parent care than their single/cohabiting counterparts, whereas in the US data, married mothers were more likely to use parent care.

EEC experiences and children's cognitive skills

Table 3 presents results from ordinary least squares (OLS) regression models assessing differences in children's cognitive functioning following school entry as a function of the type of EEC they experienced during the infancy, toddlerhood and preschool years. We note that all child and family covariates described above were included in these models, but for the sake of parsimony we present coefficients only for the main EEC variables of interest (full tables available upon request).

Table 3: Predicted children's school-age cognitive skills by EEC timing and type, OLS regression models, LSAC-B and ECLS-B
Independent variables LSAC-B ECLS-B
Teacher-rated maths Teacher-rated literature Matrix Reasoning Vocabulary Math Reading Expressive language
Infant EEC              
Centre -0.08 (0.06) -0.06 (0.07) -0.00 (0.08) -0.06 (0.07) -0.05 (0.06) -0.07 (0.06) 0.06 (0.07)
Informal -0.01 (0.05) -0.01 (0.05) -0.00 (0.05) 0.01 (0.04) -0.03 (0.04) -0.04 (0.04) 0.01 (0.04)
Toddler EEC              
Centre 0.12 (0.05) * 0.10 (0.04) * 0.10 (0.05) * 0.11 (0.06) + -0.02 (0.05) -0.05 (0.06) 0.06 (0.04)
Informal 0.04 (0.05) 0.06 (0.05) 0.03 (0.04) 0.04 (0.04) 0.01 (0.03) -0.01 (0.04) 0.08 (0.03) *
Preschool EEC              
Centre 0.06 (0.06) 0.07 (0.06) 0.04 (0.05) -0.01 (0.06) 0.05 (0.05) a 0.07 (0.05) a 0.04 (0.06)
Informal 0.04 (0.08) 0.03 (0.08) -0.07 (0.07) -0.04 (0.07) -0.08 (0.07) a -0.18 (0.06) ** a 0.01 (0.08)
F of model 8.52 ** 13.01 ** 7.87 ** 16.69 ** 39.90 ** 38.91 ** 16.88 **
R 2 0.08 0.11 0.06 0.13 0.25 0.21 0.17

Note: Non-parental EEC groups are compared to the omitted category of parent EEC. All analyses controlled for the Wave 1 value of the age of youngest parent, highest education of parent, race, immigrant household, English spoken in household, child gender, child low birthweight, child in bad health, child early cognitive skills, child age at assessment, and multiple EEC arrangements at infancy, toddlerhood and preschool waves. Models also controlled for mother employed part-time and mother employed full-time at Waves 1 and 3, income averaged across Waves 1 and 3, number of children in household averaged across Waves 1 and 3, and marital status at Waves 1 and 3. Within each column, groups with shared superscript letters are different from each other at the p < .05 level. Other statistically signficant differences are noted: + p < .10, * p < .05, ** p < .01.

Results for LSAC-B are presented in the first four columns. In these models, we see that the type of EEC that Australian children experienced in infancy and preschool was not associated with their cognitive functioning at age 7, controlling for toddler EEC and the host of child, parent and family covariates. However, experiencing EEC during the toddler wave, at approximately age 2, was positively associated with children's cognitive functioning. Specifically, children who attended centre-based care at age 2 had significantly higher teacher-rated maths skills and literature skills, higher matrix reasoning scores, and marginally higher vocabulary skills than their peers who were in parental care during their toddler wave. No significant differences emerged between children in centre-based versus informal care during toddlerhood. Across all of these results, effect sizes were small, averaging about .10 of a standard deviation difference.

Turning to the results from the ECLS-B, shown in the final three columns of the table, we see a different pattern of results. Like in the LSAC-B, in the ECLS-B there were no significant associations between non-parental care during infancy and children's cognitive skills after school entry. In contrast to the Australian results, few significant results emerged in relation to toddler EEC, though US children in informal EEC during toddlerhood had better expressive language skills than their peers in parent care. A more consistent set of results emerged for preschool-age EEC. US children in centre-based preschools had higher maths and reading skills than their peers in informal EEC, as shown by the matched superscripts in Table 3. Children in informal preschool EEC also had lower reading scores than children in parent care. Effect sizes were again small, albeit slightly higher than in the LSAC-B results.

Many similarities emerged across the datasets in the associations between child, parent and family covariates and children's later cognitive skills (results not shown). In particular, male children and children born with low birthweight had lower cognitive skills. Racial/ethnic differences in cognitive skills were strong in the US, but not in Australia. Both datasets show notable continuity in cognitive skills from infancy until after school entry. Children in families with unmarried parents, families with more children, and families with younger parents showed lower cognitive functioning, as did children with less educated and lower income parents. Notably, almost no significant associations emerged between maternal employment and children's later cognitive functioning in either country, or between multiple EEC arrangements and children's cognitive functioning.

In summary, results indicate that centre-based EEC benefits Australian children during toddlerhood, but benefits US children during preschool. In Table 4, results are presented from models considering the extent rather than the type of care at each wave, splitting EEC into part-time or full-time non-parental EEC versus parent care. These models also include all child and family covariates (detailed results available upon request).

Results in Table 4 reiterate the finding that infant EEC is not associated with children's later cognitive functioning, regardless of whether the care is part-time or full-time. Similarly, when split by part-time and full-time, preschool EEC is not associated with later cognitive skills in either dataset, although we reiterate that in LSAC-B, relatively few children were in full-time care and hence these small groups have limited statistical power. Turning to EEC during toddlerhood, results from the LSAC-B show that both part-time and full-time care had benefits for Australian children's functioning. Part-time EEC during toddlerhood predicted higher teacher-rated literature skills and marginally higher teacher-rated maths skills at age 7 than parent care, and full-time toddler EEC predicted higher Matrix Reasoning skills than either parent care or part-time EEC. In the ECLS-B data, on the other hand, results show a more consistent benefit from full-time toddler care, predicting greater maths skills in comparison to part-time EEC and greater expressive language skills in comparison to either part-time EEC or parent care.

Table 4: Predicted children's school-age cognitive skills by EEC timing and extent, OLS regression models, LSAC-B and ECLS-B
Independent variables LSAC-B ECLS-B
Teacher-rated maths Teacher-rated literature Matrix Reasoning Vocabulary Maths Reading Expressive language
Infant EEC              
Part-time -0.02 (0.05) -0.02 (0.04) -0.01 (0.05) -0.01 (0.04) -0.04 (0.04) -0.04 (0.04) 0.03 (0.05)
Full-time -0.05 (0.09) -0.04 (0.1) 0.00 (0.09) 0.04 (0.08) -0.04 (0.05) -0.09 (0.05) + 0.00 (0.05)
Toddler EEC              
Part-time 0.08 (0.05) + 0.08 (0.04) * 0.05 (0.04) a 0.07 (0.04) -0.05 (0.04) a -0.07 (0.05) 0.01 (0.04) a
Full-time 0.04 (0.09) 0.06 (0.1) 0.22 (0.07) ** a 0.09 (0.08) 0.04 (0.04) a 0.00 (0.05) 0.13 (0.04) ** a
Preschool EEC              
Part-time 0.01 (0.06) 0.02 (0.06) -0.02 (0.06) -0.04 (0.07) 0.04 (0.05) 0.02 (0.05) 0.05 (0.06)
Full-time 0.01 (0.1) 0.01 (0.09) -0.08 (0.09) -0.1 (0.08) -0.01 (0.05) 0.05 (0.05) 0.02 (0.06)
F of model 8.64 ** 12.46 ** 7.85 ** 18.67 ** 39.90 ** 38.91 ** 16.88 **
R 2 0.08 0.11 0.06 0.14 0.25 0.21 0.17

Note: Non-parental EEC groups are compared to the omitted category of parent EEC. All analyses controlled for the Wave 1 value of the age of youngest parent, highest education of parent, race, immigrant household, English spoken in household, child gender, child low birthweight, child in bad health, child early cognitive skills, child age at assessment, and multiple EEC arrangements at infancy, toddlerhood, and preschool. Models also controlled for mother employed part-time and mother employed full-time at Waves 1 and 3, income averaged across Waves 1 and 3, number of children in household averaged across Waves 1 and 3, and marital status at Waves 1 and 3. Within each column, groups with shared superscript letters are different from each other at the p < .05 level. Other statistically signficant differences are noted: + p < .10, * p < .05, ** p < .01.

We also considered whether interactions between EEC type and extent are important in predicting different levels of children's cognitive skills after school entry. Caution is warranted in these results, however, since cell sizes were small in many cases. These models generally indicated that part-time centre-based EEC during toddlerhood was most beneficial in the LSAC-B data, whereas patterns were less consistent in the ECLS-B (results not shown). Additional models also assessed the effects of EEC type and extent while altering the inclusion of controls for maternal employment; results did not change.

Discussion

As one of the first studies directly comparing the effects of children's early education and care programs on their cognitive skill development in Australia and the US, this study provides important new information for scholars, policy-makers and practitioners. As maternal employment has increased and the benefits of early education programs have gained recognition, governments in numerous countries have increased the resources devoted to supporting and encouraging high-quality EEC programs for young children. Indeed, Australia has made significant strides in recent years, with the establishment of the National Quality Framework (a commitment to providing access to part-time preschool for all Australian children in the year prior to school entry), and the provision of financial support to help families self-care for their infants and pay for EEC programs for young children (DEEWR, 2012). In contrast, the system in the US is more decentralised, with less consistent regulations, more limited and targeted financial support, and states rather than the federal government beginning to take the lead on promoting universal access to preschool (Michel, 2003). In this study, we hypothesised that these policy differences, as well as higher rates of full-time maternal employment in the US than in Australia, might lead both to differences in the use of EEC, and to diverse effects on children's school readiness.

Indeed, patterns of EEC use were dissimilar in the two countries. Based upon representative samples of children born in 2003 in Australia and in 2001 in the US, results found that Australian children were more likely to be in part-time rather than full-time EEC when they were infants, toddlers and preschoolers compared to American children. Moreover, Australian children were more likely than their US peers to be in formal EEC centres during their toddler and preschool years (ages 2 and 4, respectively). In contrast, families in the US were more likely to use informal, home-based EEC options during infant and toddler years than Australians. These differences are likely important for children's healthy development, because extensive research has found that centres are more likely than informal EEC arrangements to provide high-quality care, characterised as they are by structured and stimulating early experiences, rich learning experiences, and warm and responsive care providers (Phillips et al., 2006), although some argue that for infants, higher quality care may be derived from home settings (Dowsett et al., 2008; NICHD ECCRN, 1996). On the other hand, informal arrangements may be more accessible and affordable for parents, particularly in the US, with its more limited financial supports (Coley et al., 2006; Li-Grining & Coley, 2006).

In addition to exploring patterns of EEC, this study provided innovative new information concerning associations between young children's EEC experiences and their core cognitive skills following school entry, skills that are essential for school achievement and eventual educational attainment and economic success (Heckman, 2000). Three primary patterns emerged from these results concerning the importance of EEC timing, type and extent. First, in both datasets, infant EEC was neither promotive nor detrimental to children's later cognitive skills, regardless of whether it was in centres or homes, or full- or part-time. This result may help to assuage concerns over growing maternal employment and EEC use during children's first year. Second, our results replicated other research in finding that formal centre-based EEC programs were more promotive of children's cognitive skills than were informal EEC settings such as relative, nanny and other home arrangements. Controlling for a broad array of child, parent and family characteristics, as well as for children's early cognitive skills, our models found that children who attended centre-based EEC programs in toddler or preschool years scored higher than their counterparts in other care settings in their later academic, reading and language skills. There were fewer differences in relation to the extent of EEC, with benefits accruing from both part-time and full-time EEC programs in Australia, but primarily from full-time programs in the US.

In considering the importance of these results, it is essential to consider the practical significance of the effects. Effect sizes for centre-based EEC were consistently small, averaging just over 10% of a standard deviation, similar to effect sizes found in other research on EEC from large national datasets (e.g., Coley et al., 2012; Loeb et al., 2007). To put these effects in context, the boost to children's cognitive skills from centre-based EEC was about the same size as that of a $10,000 differential in annual family income, and about half the size of the effect of having a parent with a university degree versus a high school qualification. In considering potential policy levers for increasing children's early cognitive skills, these results thus suggest that increasing centre-based EEC attendance may be as effective as increasing family income, albeit less effective than the more expensive and challenging goal of significantly increasing adult educational attainment.

The third pattern in our results found that the timing of centre-based EEC benefits differed between the two datasets. Specifically, in Australia, the benefits derived from centre-based EEC during toddlerhood, when children were about 2 years of age, whereas in the US, the benefits derived from centre-based preschool programs, when children were 4 years old. There are various potential reasons for these differences. First, in Australia, three-quarters of children attended centre-based programs at age 4, and hence there was limited statistical power in differentiating the effects of this experience from informal and parental care. This high rate is in spite of the fact that in some Australian states and territories children begin primary school at age 4, and hence had more limited opportunities to attend centre-based EEC at this age. In addition, few Australian children were in full-time EEC (for more than 30 hours a week), limiting the role of this type of care.

Beyond these issues, it is important to consider other potential mechanisms explaining the associations between centre-based EEC for toddlers in Australia and for preschoolers in the US with children's later cognitive skills and school success. One potential mechanism is the quality of EEC programs. Unfortunately, the LSAC-B study did not directly assess the quality of EEC arrangements using standardised observation measures.7 However, we can look to related structural factors to gain some insight into potential differences in quality across settings, times and countries. For example, within centres, 96% of toddler centres were accredited in Australia, compared to only 32% in the US, and these differences were similar for centres attended by preschoolers (100% vs 49% respectively). Notable differences emerged in teacher training as well, with 82% of Australian centre-based toddler teachers and 91% of centre-based preschool teachers reporting that they had a degree in early childhood education or a related field, whereas these proportions were 23% and 62% respectively in the US. However, the rates of teachers with a Bachelor degree or higher was similar in the two countries, as were the child-to-staff ratios. The aforementioned differences in centre accreditation and teacher training in early childhood development and educational practices might translate into higher quality educational contexts for young Australian children, an important question for future research to address. Although these structural markers of quality were greater for both toddler and preschool age children in Australia versus the US, it is possible that more highly trained caregivers and regulated settings are more influential for toddlers, who are still struggling with mastering basic communication, self-regulation and emotional skills, compared to their older counterparts.

In closing, it is important to acknowledge the limitations of this research. There are significant data limitations that are inherent in our reliance on the LSAC-B and ECLS-B, notably having incomplete information on all EEC settings attended, and information on EEC only being collected at distinct developmental periods rather than being continuously recorded from birth through school entry. As mentioned earlier, another important limitation is the lack of direct assessments of EEC quality. It is difficult to truly compare the experiences of children in EEC in Australia versus the US without a more detailed understanding of EEC program curricula, structure and quality, and how these differ between the two countries. Finally, although models included a broad array of child, parent and family covariates, and incorporated lagged OLS models to adjust for selection bias, correlational methods are not able to control for all unmeasured heterogeneity that may have biased measured links between EEC experiences and children's development.

Beyond these limitations, results of this research replicate a growing base of scientific evidence suggesting that centre-based EEC programs help to promote children's readiness for school by supporting growth in core early cognitive skills, such as language comprehension and production, and nascent reading and maths skills. These skills, in turn, help children to successfully transition into and flourish in formal school settings. As such, our results provide empirical support for the Australian Government's efforts to increase all children's access to centre-based EEC programs. Continued attention needs to be paid to the influence of these experiences on other arenas of children's functioning, such as emotional and behavioral skills, and to the EEC experiences of toddler-age children to determine whether government efforts to promote EEC should extend down to 2- and 3-year-olds.

Endnotes

1 Different response rates have been reported based on different calculations. This response rate includes non-response from all sources from the originally drawn sample (see Gray & Sanson, 2005).

2 We chose Wave 4 rather than Waves 3 or 3.5 to assess children's developmental outcomes because only 21% of Australian children had entered primary school at Wave 3, and there were no child assessments at Wave 3.5.

3 ECLS-B secure data rules require that all Ns be rounded to the nearest 50.

4 Not all children had entered primary school at the time of assessment at Wave 4. Accordingly, the ECLS-B reassessed those children the following year to capture their development at the start of primary school.

5 This represents 92% of the 6,800 children in the Wave 4/5 sample.

6 We included family day care in the informal category, in congruence with a host of prior research showing that such programs are less structured than centres and show associations with children's school readiness skills more akin to relative and non-relative home care than to centres. Similarly, though occasional care may be based in a centre context, it is unlikely to share the same structure and curriculum as centre programs and hence was included with informal care.

7 LSAC-B did link quality assurance data collected by the National Childcare Accreditation Council to some EEC settings at Wave 1, but the NCAC measures were altered by Wave 2, limiting our ability to identify stable measures across the waves. Moreover, the ECLS-B collected observational quality measures only at Waves 2 and 3, and only for a subset of EEC settings.

References

  • Australian Bureau of Statistics. (2006). Child care Australia (Cat. No. 4402.0). Canberra: ABS.
  • Australian Bureau of Statistics. (2012). Labour force, Australia: Detailed, quarterly, Nov. 2012 (Cat. No. 6291.0.55.003). Canberra: ABS. Retrieved from <www.abs.gov.au/AUSSTATS/abs@.nsf/DetailsPage/6291.0.55.003Nov%202012?OpenDocument>.
  • Australian Council for Educational Research. (2000). PPVT-III-LSAC Australian short-form developed by S Rothman. Melbourne: ACER.
  • Australian Institute of Family Studies. (2009). The Longitudinal Study of Australian Children: An Australian Government initiative. Data user guide. Melbourne: AIFS.
  • Bayley, N. (1993). Bayley Scales of Infant Development (2nd ed.). San Antonio, TX: The Psychological Corporation.
  • Blau, D. M. (1999). The effect of child care characteristics on child development. Journal of Human Resources, 34, 786-822.
  • Bradbury, B., Corak, M., Waldfogel, J., & Washbrook, E. (2010). Inequality during the early years: Child outcomes and readiness to learn in Australia, Canada, United Kingdom, and United States. Paper presented at the 31st General Conference of the International Association for Research in Income and Wealth, August 2010. Retrieved from <www.iariw.org/papers/2010/4bBradbury.pdf>.
  • Cain, G. (1975). Regression and selection models to improve nonexperimental comparisons. In C. A. Bennett & A. A. Lumsdaine (Eds.), Evaluation and experiments: Some critical issues in assessing social programs (pp. 297-317). New York: Academic Press.
  • Capizzano, J., & Adams, G. (2004). Children in low-income families are less likely to be in center-based child care (Snapshots of America's Families Vol. 16). Washington, DC: Urban Institute.
  • Claessens, A., & Garrett, R. (2011, November). The role of preschool readiness skills and later achievement in Australia. Paper presented at the Association for Public Policy Analysis & Management Fall Research Conference, Washington, DC.
  • Coley, R. L., Li-Grining, C., & Chase-Lansdale, P. L. (2006). Low-income families' child care experiences: Meeting the needs of children and families. In N. Cabrera, R. Hutchins, & E. Peters (Eds.), From welfare to child care: What happens to children when mothers exchange welfare for work (pp. 149-170). Mahway, NJ: Lawrence Erlbaum Associates.
  • Coley, R. L., Votruba-Drzal, E., Miller, P. L., & Koury, A. (2012, 17 December). Timing, extent, and type of child care and children's behavioral functioning in Kindergarten. Developmental Psychology. Advance online publication. doi: 10.1037/a0031251
  • Department of Education, Employment and Workforce Relations. (2012). Universal access to early childhood education. Canberra: DEEWR.
  • Department of Human Services. (2013a). Child Care Rebate. Canberra: DHS. Retrieved from <www.humanservices.gov.au/customer/services/centrelink/child-care-rebate>.
  • Department of Human Services. (2013b). Parenting Payment. Canberra: DHS. Retrieved from <www.humanservices.gov.au/customer/services/centrelink/parenting-payment>.
  • Dettling, A. C., Gunnar, M. R., & Donzella, B. (1999). Cortisol levels of young children in full-day childcare centers: Relations with age and temperament. Psychoneuroendocrinology, 24, 519-536.
  • Dowsett, C. J., Huston, A. C., Imes, A. E., & Gennetian, L. (2008). Structural and process features in three types of child care for children from high and low income families. Early Childhood Research Quarterly, 23, 69-93.
  • Duncan, S. E., & De Avila, E. A. (1998). PreLAS. Monterey, CA: CTB/McGraw-Hill.
  • Dunn, L. M., & Dunn, L. M. (1997). Examiner's manual for the PPVT-III: Peabody Picture Vocabulary Test Third Edition. Circle Pines, MN: American Guidance Service.
  • Early, D. M., & Burchinal, M. R. (2001). Early childhood care: Relations with family characteristics and preferred care characteristics. Early Childhood Research Quarterly, 16, 475-497.
  • Flanagan, K., & West, J. (2004). Children born in 2001: First results from the base year of the Early Childhood Longitudinal Study, Birth Cohort (ECLS-B) (NCES 2005-036). Washington, DC: National Centre for Education Statistics.
  • Fuller, B., Kagan, S. L., Loeb, S., & Chang, Y. (2004). Child care quality: Centers and home settings that serve poor families. Early Childhood Research Quarterly, 19, 505-527.
  • Ginsburg, H. P., & Baroody, A. J. (2003). TEMA-3: Test of Early Mathematics Ability (3rd ed.). Austin, TX: Pro-Ed.
  • Gormley, W. T., Gayer, T., Phillips, D., & Dawson, B. (2005). The effects of universal pre-K on cognitive development. Developmental Psychology, 41, 872-884.
  • Gray, M. & Sanson, A. (2005). Growing up in Australia: the Longitudinal Study of Australian Children. Family Matters, 72, 4-9.
  • Harrison, L., & Ungerer, J. (2005). What can the Longitudinal Study of Australian Children tell us about infants' and 4 to 5-year-olds' experiences of early childhood education and care? Family Matters, 72, 26-35.
  • Harrison, L., Ungerer, J., Smith, G., Zubrick, S., & Wise, S., with Press, F., Waniganayake, M., & the LSAC Research Consortium. (2009). Child care and early education in Australia: The Longitudinal Study of Australian Children (Social Policy Research Paper No. 40). Canberra: Department of Families, Housing, Community Services and Indigenous Affairs. Retrieved from <www.fahcsia.gov.au/sites/default/files/documents/05_2012/sprp_40.pdf>.
  • Heckman, J. J. (2000). Invest in the very young. Chicago: Ounce of Prevention Fund and the University of Chicago Harris School of Public Policy Studies.
  • Li-Grining, C. P., & Coley, R. L. (2006). Child care experiences in low-income communities: Developmental quality and maternal views. Early Childhood Research Quarterly, 21, 125-141.
  • Li-Grining, C. P., Votruba-Drzal, E., Maldonado-Carreño, C., & Haas, K. (2010). Children's early approaches to learning and academic trajectories through fifth grade. Developmental Psychology, 66, 1062-1077.
  • Loeb, S., Bridges, M., Bassok, D., Fuller, B., & Rumberger, R. W. (2007). How much is too much? The influence of preschool centres on children's social and cognitive development. Economics of Education Review, 26, 52-66.
  • Lonigan, C., Wagner, R., Torgesen, J., & Rashotte, C. (2002). Preschool Comprehensive Test of Phonological & Print Processing (Pre-CTOPPP). Tallahassee, FL: Department of Psychology, Florida State University.
  • Maccoby, E. E., & Lewis, C. C. (2003). Less day care or different day care? Child Development, 74, 1069-1075.
  • Magnuson, K. A., Meyers, M. K., Ruhm, C., & Waldfogel, J. (2004). Inequality in preschool education and school readiness. American Educational Research Journal, 41, 115-157.
  • Morrissey, T. W. (2010). Sequence of child care type and child development: What role does peer exposure play? Early Childhood Research Quarterly, 25(1), 33-50.
  • Michel, S. (2003). Roots and branches: Comparing child care policymaking in the US and Australia. Australian Journal of Early Childhood, 28(3), 1-6.
  • National Centre for Education Statistics. (2002). Early Childhood Longitudinal Study: Kindergarten class of 1998-99 (ECLS-K). Psychometric report for kindergarten through first grade (NCES 2002-2005). Washington, DC: US Department of Education.
  • National Institute of Child Health and Human Development Early Child Care Research Network. (1996). Characteristics of infant child care: Factors contributing to positive caregiving. Early Childhood Research Quarterly, 11, 296-306.
  • National Institute of Child Health and Human Development Early Child Care Research Network. (2002). Early child care and children's development prior to school entry: Results from the NICHD Study of Early Child Care. American Education Research Journal, 39, 133-164.
  • National Institute of Child Health and Human Development Early Child Care Research Network (2005). Child care and child development: Results from the NICHD Study of Early Child Care and Youth Development. New York: Guilford Press.
  • National Institute of Child Health and Human Development Early Child Care Research Network, & Duncan, G. J. (2003). Modeling the impacts of child care quality on children's preschool cognitive development. Child Development, 74, 1454-1475.
  • Phillips, D. A., McCartney, K., & Sussman, A. (2006). Child care and early development. In K. McCartney, & D. A. Phillips (Eds.), Blackwell handbook of early childhood development. Malden, MA: Blackwell.
  • Royston, P. (2004). Multiple imputation of missing values. The Stata Journal, 4, 227-241.
  • Royston, P. (2005). Multiple imputation of missing values: Update of ice. The Stata Journal, 5, 527-536.
  • Sanson, A., Nicholson, J., Ungerer, J., Zubrick, S., Wilson, K., & the LSAC Consortium Advisory Group. (2002). Introducing the Longitudinal Study of Australian Children (LSAC Discussion Paper No. 1). Melbourne: Australian Institute of Family Studies.
  • Sanson, A. V., Misson, S., Hawkins, M. T., Berthelsen, D., & the LSAC Research Consortium. (2010). The development and validation of Australian indices of child development: Part 1. Conceptualisation and development. Child Indicators Research, 3, 275-292.
  • Soloff, C., Lawrence, D., & Johnstone, R. (2005). Sample design (LSAC Technical Paper No. 1). Melbourne: Australian Institute of Family Studies.
  • Smart, D., Sanson, A., Baxter, J., Edwards, B., & Hayes. A. (2008). Home-to-school transitions for financially disadvantaged children. Commissioned report. Sydney: The Smith Family.
  • US Department of Labor (2009). Women in the labor force: A databook. Washington, DC: US Department of Labor. Retrieved from <www.bls.gov/cps/wlf-databook2009.htm>.
  • Vermeer, H. J. & van IJzendoorn, M. H. (2006). Children's elevated cortisol levels at daycare: A review and meta-analysis. Early Childhood Research Quarterly, 21, 390-401.
  • Votruba-Drzal, E., Coley, R. L., Koury, A., & Miller, P. (2012). Center-based child care and cognitive skills development: Importance of timing and household resources. Manuscript submitted for publication.
  • Watamura, S. E, Donzella, B., Alwin, J., & Gunnar, M. R. (2003). Morning-to-afternoon increases in cortisol concentrations for infants and toddlers at child care: Age differences and behavioral correlates. Child Development, 74, 1006-1020.
  • Wetherby, A. M., & Prizant, B. M. (2001). Communication and Symbolic Behavior Scales developmental profile: Infant-Toddler Checklist. Baltimore, MD: Brookes.
  • Zigler, E., Marsland, K., & Lord, H. (2009). The tragedy of child care in America. New Haven, CT: Yale University Press.

Dr Rebekah Levine Coley is a Professor of Applied Developmental and Education Psychology at Boston College, Caitlin McPherran Lombardi and Jacqueline Sims are doctoral students at Boston College, and Dr Elizabeth Votruba-Drzal is an Associate Professor of Psychology at the University of Pittsburgh.

This paper uses confidentialised unit record data from Growing Up in Australia: The Longitudinal Study of Australian Children. The study is conducted in partnership between the Australian Government Department of Social Services (DSS), the Australian Institute of Family Studies (AIFS) and the Australian Bureau of Statistics (ABS). The findings and views reported in this paper are those of the authors and should not be attributed to DSS, AIFS or the ABS.

This research was supported in part by a grant to the fourth author from the Foundation for Child Development as part of the Young Scholars Program. Address correspondence to: Dr Rebekah Levine Coley, Applied Developmental & Educational Psychology, Boston College, Campion Hall 239A, 140 Commonwealth Ave, Chestnut Hill MA, USA 02467. Phone: +1 617 552 6018. Fax: +1 617 552 1981. Email address: <coleyre@bc.edu>.

The authors are grateful to Dr Linda Harrison for her helpful insights into the LSAC-B data.

Suggested citation:

Levine Coley, R., McPherran Lombardi, C., & Votruba-Drzal, E. (2013). Early education and care experiences and cognitive skills development: A comparative perspective between Australian and American childrenFamily Matters, 93, 27-35.