Children From Lower-ses Families Have _____ Compared With Higher-ses Children.

Dev Sci. Author manuscript; available in PMC 2014 Mar 1.

Published in final edited form as:

PMCID: PMC3582035

NIHMSID: NIHMS411497

SES differences in language processing skill and vocabulary are evident at 18 months

Abstract

This research revealed both similarities and striking differences in early language proficiency amid infants from a broad range of advantaged and disadvantaged families. English-learning infants (n = 48) were followed longitudinally from 18 to 24 months, using real-time measures of spoken language processing. The first goal was to runway developmental changes in processing efficiency in relation to vocabulary learning in this various sample. The 2nd goal was to examine differences in these crucial aspects of early language evolution in relation to family socioeconomic status (SES). The most important findings were that pregnant disparities in vocabulary and language processing efficiency were already axiomatic at eighteen months between infants from college- and lower-SES families, and by 24 months there was a half dozen-calendar month gap between SES groups in processing skills critical to linguistic communication development.

There are hitting differences among children in patterns of early language growth. Some infants commencement speaking earlier their first birthday, while others don't produce words until the finish of the second year (Fenson et al., 2006). Although some late talkers catch up in vocabulary a few months later, others continue to show slower trajectories of language growth and reach lower levels of linguistic communication proficiency (Bates, Dale & Thal, 1994; Fernald & Marchman, 2012). Differences in socioeconomic condition (SES) are strongly associated with variation in language outcomes. By the time they enter kindergarten, children from disadvantaged backgrounds differ substantially from their more than advantaged peers in verbal and other cognitive abilities (Ramey & Ramey, 2004), disparities that are predictive of later academic success or failure (Lee & Burkum, 2002). In adults too, SES differences in linguistic communication proficiency are robust (Pakulak & Neville, 2010), reflecting the cumulative influence of a wide range of endogenous and environmental factors over a lifetime.

Despite such evidence for significant differences among children in early language learning, enquiry on acquisition has tended to focus much more on elucidating common patterns of language growth than on understanding the causes and consequences of variability. This emphasis has been driven by several factors: Kickoff, the search for similarities rather than differences among children is grounded in a philosophy of science that underlies psychological research more than broadly – 1 that gives priority to processes assumed to be universal rather than to endogenous and experiential factors that can atomic number 82 to variability (Arnett, 2008). 2nd, the use of controlled experimental methods in enquiry on early language development favors between-group comparisons of infants at unlike ages, with limited attending to variability within age groups (Fernald, 2010). Third, the vast bulk of developmental studies in the U.South. rely on 'convenience samples' of children from higher-SES families that are unrepresentative of the larger population and thus are inherently restricted in variability (Henrich, Heine & Norenzayan, 2010). Fourth, although educational researchers have documented robust differences in exact abilities among school-age children varying in SES (eastward.m., Dickinson & Tabors, 2001; Lee & Burkam, 2002), this literature is often viewed equally 'practical' inquiry with limited relevance to 'basic' enquiry on linguistic communication development. We debate here that understanding the extent and origins of variability among children in the emergence of early language proficiency should exist central to whatsoever developmental theory that acknowledges, at whatever level, the influence of children'south early on experience on language growth.

This perspective motivates the current study of differences likewise equally similarities in early language proficiency amidst children from higher- and lower-SES families. In experimental studies using looking-time measures, nosotros take shown that infants develop speed and efficiency in interpreting spoken language in real time (Fernald, Pinto, Swingley, Weinberg, & McRoberts, 1998) and that individual differences in early processing efficiency are strongly linked to variation in children'due south later language outcomes (east.thousand., Fernald, Perfors & Marchman, 2006; Marchman & Fernald, 2008). However, in these previous studies, every bit in many other university-based studies with English-learning children, most participants came from highly-educated and affluent families. The goal of the present study was to examine the development of language processing efficiency in relation to vocabulary learning in English-learning infants from families varying in SES. Using real-time processing measures, we followed children longitudinally from 18 to 24 months, focusing on 2 sets of questions: Get-go, to what extent do infants across this broader SES range show parallel gains in processing efficiency and vocabulary between 18 and 24 months? And 2nd, is in that location testify that SES-related differences in processing skills disquisitional to language evolution are already present in infancy?

SES Differences in Verbal Abilities and their Long-Term Consequences

The finding that children from disadvantaged families start kindergarten with lower language and cerebral skills than those from more than advantaged families is old news, emerging repeatedly in studies since the 1950's (e.thousand., Bereiter & Englemann, 1966; Deutsch, Katz, & Jensen, 1968). The robustness of such differences is confirmed in more contempo inquiry such as the Early Childhood Longitudinal Study, Kindergarten Accomplice (ECLS-K), a comprehensive analysis of young children'due south achievement scores in literacy and mathematics based on a large and nationally representative sample (Lee & Burkam, 2002). Even before they entered kindergarten, children in the highest SES-quintile group had scores that were lx% above those in the everyman group. In terms of result size, children in the highest SES-quintile scored .7 standard-divergence (SD) units above middle-SES children in reading achievement, while children in the everyman SES-quintile scored almost .5 SD units below the middle-SES mean. Moreover, the disparities in children'due south cerebral performance at kindergarten entry that were attributable to SES differences were significantly greater than those associated with race/ethnicity. Another recent study found that 65% of low-SES preschoolers in Head Beginning programs had clinically pregnant language delays (Nelson, Welsh, Vance Trup, & Greenberg, 2011). This enquiry revealed a systematic relation between degree of language delay and other weaknesses in academic and socio-emotional skills that were well established past 4 years of age. Socioeconomic gradients in language proficiency are too found inside populations living in farthermost poverty (Fernald, Fifty., Weber, Galasso, & Ratsifandrihamanana, 2011).

A Challenging and Controversial Question: When Do SES Differences Begin to Emerge?

Results showing that SES differences in verbal abilities are already evident in the preschool years suggest that these disparities must start to develop in the commencement years of life, setting children on particular trajectories with far-reaching consequences for later academic success. How early practice such differences begin to emerge? Enquiry on this of import developmental question has been limited for a diversity of reasons - ranging from methodological challenges in evaluating linguistic communication proficiency in young children, to the complexities of engaging in argue well-nigh politically sensitive problems related to social stratification. The methodological problem is easy to narrate: Until recently, measures available for assessing linguistic communication and cognitive proficiency in children younger than three years have not been high in predictive validity, limiting their effectiveness in linking characteristics in infancy to long-term outcomes. But with the refinement of more sensitive methods for evaluating early on language, contempo studies have revealed considerable variability in verbal skills amongst very immature children - to exist reviewed in the following department. Another ready of bug that has discouraged research on early on origins of cognitive differences among children from dissimilar backgrounds is more difficult to narrate. The legacy of a prolonged and biting fence about the nature of racial and SES differences in the U.S. has reinforced the reluctance of researchers to pursue the question of early origins of SES-related disparities in cognitive skills that are relevant to school success.

A brief history of this circuitous debate is relevant to the problems raised in the current study. The scientific consensus in the early 20th century was that cognitive abilities were entirely genetically determined, a view that changed gradually with mounting evidence that experiential factors were as well influential (encounter Fernald & Weisleder, 2011). Past the 1960'south, when the Civil Rights movement focused national attention on inequities in educational opportunities for Black children, there was intense interest in eliminating achievement gaps that could no longer exist ignored. Riessman (1962) argued that SES disparities in schoolhouse success resulted from cultural differences in minority children'due south early on experience with parents in the home, rather than from immutable genetic differences. This 'cultural deprivation' statement appeared to offer hope for solutions through appropriate intervention, although characterizing the home environment of minority children as deficient in cognitive stimulation clearly had negative implications. While this thought rallied political support for new programs such as Performance Head Get-go, what came to exist known as the 'deficit model' as well generated intense controversy amidst educators who objected that parents should not be blamed for their children's difficulties in schoolhouse. Past the 1970'south, politically motivated backlash to the deficit model converged with the rise of nativist theories of language development, which focused on modal patterns of development presumed to be universal rather than on differences amidst children. Fernald and Weisleder (2011) argue that this convergence was influential in curtailing debate on questions that had generated extensive research over the previous two decades – namely, whether SES differences in children's verbal abilities are rooted to some extent in differences in their early linguistic communication experience at home, and if so, whether these experiential differences contribute to the substantial disparities observed among children in their later academic success.

Although interest in variability in linguistic communication learning had declined substantially by the 1980'due south, a few researchers began to explore in greater depth the potential contributions of early parent-child interaction to differences in language development (e.g., Hart & Risley, 1995; Hoff-Ginsberg, 1998; Huttenlocher, Haight, Bryk, & Seltzer, 1991). Based on detailed analyses of mothers' speech to infants at home, these studies used longitudinal designs to identify features of maternal speech that predict language result measures. Hart and Risley found that by 36 months, the college-SES children in their sample spoke twice equally many words as the lower-SES children. But their nearly remarkable finding was the farthermost variation in amounts of child-directed speech communication among families at different SES levels, differences that were correlated with children's early vocabulary and too predictive of later on school performance (Walker, Greenwood, Hart & Carta, 1994). Co-ordinate to Hoff (2003), it was the quality of infants' early on language environment that actually mediated the link between SES and children's vocabulary noesis.

Assessing Differences in Linguistic communication Proficiency in Very Immature Children

These studies of variability in early on language environments with small-scale samples of families laid the foundation for research exploring the early emergence of cognitive disparities in much larger and more than diverse samples of advantaged and disadvantaged children. Farkas and Beron (2004) examined the monthly growth trajectory of oral vocabulary cognition in Black and White children from 36 months to 13 years of age, using a large, representative national data set. Their almost striking finding was that most of the inequality in vocabulary growth attributable to race and SES differences developed prior to 36 months. Moreover, the magnitude of the Blackness-White vocabulary gap that was already axiomatic by the historic period of school-entry remained unchanged through the historic period of 13 years. These authors concluded that by 36 months, SES differences in children's language feel take already led to significant vocabulary disparities, which then widen further in the preschool years and remain abiding thereafter. Data from the NICHD Early on Babyhood Care Research Network also revealed that a substantial accomplishment gap between low-income Black and White children was already evident past iii years, and that family besides as school characteristics contributed to maintaining this gap through uncomplicated school (Burchinal et al., 2011). A third contempo study with a large, representative sample from the Early on Childhood Longitudinal Study, Birth Accomplice (ECLS-B) showed that disparities between lower- and higher-SES infants on language and cognitive measures began to emerge by 9 months, and that by 24 months there was a hateful difference of .5 SD units between SES groups on the Bayley Cognitive Cess (Halle et al. 2009).

These large-sample studies of SES disparities in cognitive skills emerging early in life have all been based on standardized assessments of language abilities, using measures which crave the child to follow instructions and execute an unambiguous response by speaking or pointing. Just given these task demands, such assessments cannot be used finer with toddlers younger than 2 years. While parent reports of a child's vocabulary can yield valuable data on early on language development (Fenson et al., 2006), they exercise not provide a direct measure of the child's response. Until recently, these methodological limitations made it hard to investigate the origins of individual differences in linguistic communication proficiency in infants younger than 24 months. However, refinements in experimental techniques now allow researchers to monitor the time form of linguistic communication comprehension by very immature linguistic communication learners, providing straight measures of early efficiency in language processing in existent time.

Recent experimental studies on language processing in the second and 3rd years have used real-time measures to assess how efficiently children identify the referent of a familiar word in real-time comprehension. In the looking-while-listening (LWL) procedure (Fernald, Zangl, Portillo & Marchman, 2008), children run across pictures of two familiar objects every bit they mind to speech communication naming i of the objects, and their responses are coded with millisecond-level precision. Cross-sectional studies of both English- and Spanish-learning infants show dramatic gains in the speed and accurateness of linguistic communication understanding across the 2d year (Fernald, Pinto, Swingley, Weinberg & McRoberts, 1998; Hurtado, Marchman & Fernald, 2007). Moreover, young children, like adults, are able to interpret incoming linguistic communication incrementally, directing their attention to the appropriate moving picture every bit the speech indicate unfolds in time (Fernald, Swingley & Pinto, 2001; Swingley, Pinto & Fernald, 1999). In a longitudinal study with English-learning toddlers from fifteen to 24 months, these online processing measures were found to be stable over fourth dimension, and processing speed at 24 months was robustly correlated with vocabulary growth over this period (Fernald et al., 2006). Moreover, a follow-upward study with the same children half dozen years later showed strong links between processing efficiency in infancy and performance on standardized tests of language and cerebral skills in uncomplicated school (Marchman & Fernald, 2008). These existent-fourth dimension processing measures have revealed consistent concurrent and predictive relations to linguistic communication outcomes across studies of typically-developing children. They are besides high in predictive validity in enquiry with late-talkers, children at increased take a chance for persistent linguistic communication delays (Fernald & Marchman, 2012). For these reasons, the LWL task is well suited for investigating both similarities and differences in early language processing skill amid infants from different socioeconomic backgrounds.

Research Questions

The primary goals in this enquiry were to examine the early development of language processing efficiency in relation to vocabulary learning in English-learning infants from families across a broad demographic range, and to decide whether SES differences in processing efficiency are already evident in infancy, at a younger age than has been reported in previous research. Our previous studies with English-learning children were all conducted at a university laboratory in a prosperous urban surface area, where almost all the families who volunteer to participate in research are flush and highly educated (Site ane). To extend beyond this convenience sample of loftier-SES families, nosotros needed to establish an boosted research site in an area where it is possible to recruit equivalent numbers of lower- and middle-SES English-speaking families. Site 2 is located in an urban area comparable in population size to Site i. However, because these two areas differ substantially in terms of median family income, cost-of-living, and pct of children living in poverty, as shown in Tabular array one, we are able to include a much more diverse sample of English-learning children at Site 2 than is possible at the university lab.

Tabular array ane

Demographic information on population, median income, cost-of-living index, and poverty rate in the two research sites

	Site i	Site 2
Full population a	ninety,200	xc,500
% non-Hispanic white a	66%	83%
Median per capita income a	$69,000	$23,900
Toll-of-living index b	157.9	92.nine
% children living below federal poverty level a,c	five.three%	22.nine%

Method

Participants

Participants were 48 English-learning children (26 females), recruited through nascency records and day intendance centers at Site i (due north = 20) and Site 2 (n = 28). Exclusionary criteria at time of recruitment included preterm birth, birth complications, hearing/visual impairments, medical issues, or a known developmental disorder. Reported ethnicity of participants was non-Hispanic White (66%), Asian (xiii%), Alaskan Native/American Indian (10%), Native Hawaiian/Pacific Islander (6%), or African American (4%). Later on receiving a brochure describing the projection, interested parents contacted us past phone, website, or reply menu. Parents were then interviewed by phone about their child's linguistic communication background, wellness history, and family history of language disorders. Qualifying families were invited to join the study if the kid was non regularly exposed to a language other than English. Vi additional participants were excluded from final analyses because the families could not attend the 24-month testing session or did not complete both linguistic communication questionnaires.

Socioeconomic status

Although participants were all typically-developing infants from monolingual English language-speaking families, they were diverse in socioeconomic groundwork, as shown in Table 2. The mothers in these families had about three years of mail service-loftier schoolhouse educational activity, on average, yet spanned a broad range of educational levels: 21% did not terminate or were nonetheless attending high school, or did not continue their education past high school, 19% had some college, 33% completed a B.A. degree, and some other 27% also received some post-B.A. grooming. Table 2 also shows scores on the Hollingshead Four Factor Index of Socioeconomic Status (Hello, Hollingshead, 1975). This widely-used index of family unit SES is based on a weighted average of both parents' teaching and occupation, with possible scores ranging from 8 to 66. The Hello is divisible into five "strata" of social status: unskilled worker, semi-skilled worker, skilled worker, semi-professional, and major professional. In this sample, parents' occupations spanned the full range from unskilled worker to major professional person. For some analyses, families were divided into Lower- (≤ 45, due north = 23) and Higher-SES (> 47, northward = 25) sub-groups based on a median split of HI scores, every bit shown in Table ii. Both groups included at to the lowest degree one mother with merely a high school education, also as several mothers who had attended higher. Nevertheless, the distributions of maternal education levels were substantially different in the ii groups. Nearly ninety% of the mothers in the Higher-SES group had at least a 4-year college degree, with more than than half completing masters or doctoral degrees, while merely xxx% of the mothers in the lower-SES group had completed college and i had a masters degree. Of the children from families in the Higher-SES group, nineteen were recruited at Site 1 and vi at Site 2. Of those from families in the Lower-SES group, 1 was recruited at Site i and 22 at Site ii.

Table 2

Hateful (SD) and range for maternal education and Hollingshead Index for full sample and lower-SES and higher-SES sub-groups

	All participants		Lower SES		Higher SES
Maternal Ed a	15.3 (2.4)	x - eighteen	13.7 (ii.2)	10 - eighteen	sixteen.7 (1.vi)	12 - eighteen
HI b	46.half-dozen (15.1)	14 - 66	33.9 (10.1)	fourteen - 45	58.3 (seven.3)	47 - 66

Offline Measures of Vocabulary

Reported expressive vocabulary

At 18 and 24 months, parents completed the MacArthur-Bates Communicative Evolution Inventory: Words & Sentences (CDI: Fenson et al., 2006). This parent-written report instrument ask parents to indicate on a checklist (680 items) which words their kid "understands and says". All parents were told to substitute words on the checklists with variants of those words specific to their family unit (e.grand., nana for grandmother).

Process for Assessing Real-fourth dimension Language Agreement

Children'southward real-time comprehension of familiar words was assessed at 18 and 24 months using the looking-while-listening (LWL) procedure (Fernald et al., 2008). The testing apparatus, recording procedures, and exact and visual stimuli were identical at Sites 1 and 2, and the same 2 experimenters conducted test sessions at both sites. On each trial, participants viewed ii pictures of familiar objects while listening to speech naming 1 of the pictures. Visual stimuli were colorful pictures (36 × 50 cm) of the target and distracter objects on gray backgrounds, aligned horizontally on a video brandish. Children saturday on the caregiver's lap during the 5-min session, and caregivers wore darkened sunglasses to restrict their view of the images. Each stimulus sentence consisted of a carrier phrase with the target word in concluding position, followed past an attention-getter (e.g., Where'south the car? Do yous like it?). The kid's face up was video-recorded for later frame-past-frame coding. On each trial, the two pictures were shown simultaneously for two s prior to speech onset, remaining on the screen during the auditory stimulus until 1 due south after audio beginning. Betwixt trials, the screen was blank for approximately 1 south. Each trial lasted approximately 7 s.

Verbal stimuli

A female native speaker of English recorded several tokens of each sentence. Candidate stimuli were acoustically analyzed; final stimulus sentences were selected to exist comparable in naturalness and pitch contour and edited so that carrier frames and target words were matched for elapsing. At 18 months, the mean length of the target noun was 614 ms (range = 604 - 623 ms). At 24 months, mean noun duration was 640 ms (range = 565 -769).

At 18 months, the target nouns were baby, doggy, baboon, kitty, brawl, shoe, book, and automobile, object labels probable to be familiar to English-speaking children at this age (Dale & Fenson, 1996). Each object was presented 4 times as target and four times as distracter, yielding 32 experimental trials. Interspersed among the disquisitional trials were 4 filler trials (e.g., Practise you similar those pictures?). At 24 months, children heard sentences containing the familiar target nouns babe, doggy, birdie, kitty, cookie, book, auto, and juice each presented twice as target and twice as distracter, a total of xvi experimental trials. These familiar word trials were interspersed with fillers (four trials) and trials in which the target give-and-take was placed in a carrier frame with an adjective (16 trials) or a semantically-related verb (8 trials). These trials are not analyzed hither. Trials on which the parent reported that the child did not understand the target word were excluded from analyses on a child-by-child basis.

Visual stimuli

Pictures corresponding to target words were presented in fixed pairs matched for visual salience, with each object serving equally often as target and distracter. All tokens were judged to correspond objects typically familiar to immature children. Position of target picture was balanced across trials. Trials were presented in a pseudo-random order such that the aforementioned target give-and-take never occurred on next trials, and the target motion-picture show did non appear on the same side more two trials in a row.

Coding

Video records of children'due south gaze patterns were analyzed frame-by-frame past highly-trained coders bullheaded to target side and status. All coding was conducted at Site 1 by coders who were not involved in running the sessions and were bullheaded to testing site. On each frame, coders indicated whether the child was looking at the left motion-picture show, correct movie, in between the two pictures or away from both. This yielded a loftier-resolution tape of eye movements for each 33-ms interval as the stimulus sentence unfolded, aligned with the onset of the target noun. Trials were later classified every bit target- or distracter-initial, depending on which picture the kid was fixating at target-substantive onset. To determine reliability, 25% of sessions were independently re-coded, with inter-observer understanding computed in ii ways. First, the hateful proportion of frames on which coders agreed on gaze location averaged 98%. Second, the mean proportion of shifts in gaze on which coders agreed within 1 frame was also calculated, a more conservative measure which too yielded high reliability (97%).

Calculation of accuracy and RT

Two measures of efficiency in real-time speech processing were calculated for each child. Outset, accurateness was computed as the mean proportion of looking to the named picture show on target- and distracter-initial trials, averaged over 300-1800 ms from noun onset. Mean accurateness was based on an boilerplate of 22.9 trials (SD = 5.3) per kid at 18 months and 12.ii trials (SD = 2.ix) at 24 months. 2nd, reaction time (RT) was computed on merely those trials on which the kid was looking at the distracter pic at the onset of the target discussion and shifted to the target picture within 300-1800 ms from target word onset. Trials on which the child shifted either within the first 300 ms or later on than 1800 ms from target word onset were excluded, since these early and belatedly shifts were less likely to be in response to the stimulus sentence (Fernald et al., 2008). Hateful RTs were based on an average of 8.8 trials (SD = 3.6) at 18 months and v.0 trials (SD = two.1) at 24 months.

Results

Focusing on ii crucial aspects of early language proficiency – the development of expressive vocabulary and skill in real-fourth dimension spoken linguistic communication processing - this study examined differences and similarities in patterns of developmental modify from 18 to 24 months in a diverse grouping of English-learning children. A cardinal question was how variability in lexical evolution and real-fourth dimension processing efficiency would chronicle to variability in family unit SES. The scatterplots in Effigy 1 show that SES differences were significantly correlated with vocabulary as well every bit with accurateness and reaction time, our 2 measures of processing efficiency: 18-month-olds growing upward in families with college Hello scores were more advanced in vocabulary, r(48) = .34, p < .02, and were also more authentic, r(48) = .52, p < .001, and faster, r(47) = -.50, p < .001 in spoken word recognition in the LWL job. Correlations between SES and these iii language measures were also significant at 24 months: vocabulary: r(48) = .29, p < .05; accuracy, r(48) = .30, p < .05; RT, r(48) = -.45, p < .001. For the next analyses, we divided participants into two SES groups based on a median split of HI scores (see Tabular array 2), to compare children from Lower- and Higher-SES families in their patterns of change with age in vocabulary and processing efficiency.

Besprinkle plots of Vocabulary, Accuracy and RT at xviii months with SES (Hullo). Dashed vertical line indicates median dissever of How-do-you-do values.

Change in Vocabulary from xviii to 24 Months in Lower- and Higher-SES Children

Mean expressive vocabulary scores at xviii and 24 months for College- and Lower-SES children are shown in Table 3 and Figure 2. In a 2 × 2 mixed analysis of variance (ANOVA), with SES group as a between-Ss factor and historic period as a within-Ss factor, the main outcome of age was meaning, F(i,46) = 163.5, p < .001, η _p ² = .78, reflecting larger vocabulary scores at 24 months than at 18 months across all children. On boilerplate, children'southward vocabulary size increased by about 225 words over this flow. The main event of SES grouping was too pregnant, F(1,46) = viii.6, p < .001, η _p ⁱⁱ = .xvi, confirming that children in the Higher-SES group were significantly more avant-garde in vocabulary than those in the Lower-SES grouping. Indeed, at 18 months, nearly one-half the children in the Lower-SES group (n = 12) had fewer than 50 words in their reported vocabulary, while simply 8 children in the Higher-SES group had scores of l words or less. A like tendency was evident at 24 months: Children from Higher-SES families produced most 450 words, on boilerplate, while children from Lower-SES families produced about 150 fewer words, consequent with previous reports of SES differences in reported vocabulary in this age range (e.g., Arriaga, Fenson, Cronan & Pethick, 1998).

Hateful number of spoken words reported on the MacArthur/Bates CDI by age and SES (HI). Error bars stand for SE of the hateful over participants.

Table 3

Mean (SD) and range of expressive vocabulary ^a at 18 and 24 months for all participants and by SES sub-grouping ^b

Historic period	All participants		Lower SES		Higher SES
18 months	141.nine (123.0)	5 - 503	107.0 (114.2)	5 - 503	174.0 (124.3)	16 - 471
24 months	367.9 (180.2)	4 - 665	287.ix (163.three)	iv - 573	441.5 (165.4)	59 - 665

An even more hitting result was that the design of developmental change in vocabulary differed as a function of SES, reflected in a pregnant age by SES grouping interaction, F(i,46) = vi.one, p < .02, η _p ² = .12. Every bit illustrated in Figure 2, a group difference in vocabulary between children from Lower- vs. Higher-SES backgrounds was clearly evident at 18 months, and by 24 months the betwixt-group difference was even larger. Children in the College-SES group made significantly greater gains (Grand = 268 words, SD = 116) over this menstruum than did children in the Lower-SES group (M = 180 words, SD = 127), t(46) = two.v, p < .02.

Changes in Processing Efficiency from eighteen to 24 Months in College- and Lower-SES Children

Side by side nosotros compared children at both ages in the 2 SES groups on two measures of processing efficiency – mean accuracy and hateful RT (come across Tabular array 4) – using 2 (historic period) × two (SES group) mixed ANOVAs.

Tabular array 4

Hateful (SD) of accurateness and reaction time (RT) in the looking-while-listening task at 18 and 24 months for all participants and the lower- and higher-SES sub-groups

	All participants	Lower SES	Higher SES
Accuracy a
18 months	.64 (.09) *	.59 (.08) *	.69 (.07) *
24 months	.73 (.10) *	.69 (.eleven) *	.77 (.08) *
RT b
18 months	841 (185)	947 (151)	746 (162)
24 months	738 (162)	802 (166)	666 (108)

Accuracy

Across SES groups, 24-month-olds spent a greater proportion of time looking at the right picture show than did 18-calendar month-olds, F(1, 46) = 31.two, p < .001, η _p ² = .40. In that location were too meaning between-group differences in accuracy: Higher-SES children were more accurate overall than the Lower-SES children, F(i, 46) = 22.8, p < .001, η _p ² = .33. The age × SES interaction was not reliable, p = .69, η _p ² = .003, reflecting comparable relative gains in accurateness from eighteen to 24 months for infants in both groups.

The main effect of age is illustrated in Figure three, which shows the fourth dimension course of looking to the target picture in the LWL task for children at xviii and 24 months. This graph plots modify over time in the mean proportion of trials on which children overall fixated the target picture, averaged over participants at each 33-msec interval as the sentence unfolds. The proportion of looking to the target picture remained near chance at least halfway through the target noun, when acoustic information potentially enabling identification of the right referent offset became available. Afterward this point, the hateful proportion of right looking began to increment, continuing to ascension after the offset of the target substantive. Betwixt 18 and 24 months, children increased their proficiency in looking to the named target before the showtime of the target noun, reaching a higher level of accurateness at 24 months than six months earlier. It is besides important to annotation that the proportion of looking to the named target motion picture was significantly above the adventure level of .l chance at 18 months, t(47) = 11.2, p < .0001, and 24 months, t(47) = xv.6, p < .0001, indicating that children overall could correctly identify the referents of familiar object names at both ages.

Hateful proportion looking to the target picture as a function of fourth dimension in ms from noun onset at 18 and 24 months. Error confined stand for SE of the hateful over participants. The vertical dashed line marks the acoustic outset of the target word.

Although accuracy improved with age for children in both SES groups, there was also a strong and early on influence of SES. Effigy 4 plots the time class of looking to the correct target moving picture at 18 and 24 months for the Lower- and Higher-SES groups. The Higher-SES children responded by looking to the named target sooner in the stimulus sentence, and achieved substantially higher levels of accuracy than those in the Lower-SES group. But what is about remarkable about Effigy four is that the curve for the Lower-SES children at 24 months substantially overlaps with the curve for the Higher-SES children at xviii months. Indeed the mean accuracy for Lower-SES children at 24 months (Yard = .69) was identical to that for College-SES children at eighteen months (M = .69), indicating that 24-month-olds in the Lower-SES sample were performing at the same level overall every bit College-SES children who were six months younger.

Mean proportion of looking to the target equally a function of time in ms from noun onset for Lower-SES and Higher-SES learners. Open squares/circles represent the fourth dimension course of right looking at eighteen months; filled squares/circles represent the time course of looking in the same children at 24 months. Error bars represent SE of the hateful over participants.

Reaction Time

Similar patterns of developmental modify were found in analyses of processing speed, shown in Figure v. At 24 months, children were well-nigh 100 ms faster to initiate a shift from distracter to target movie, on boilerplate, than they were at xviii months, a significant main effect of age, F(1,45) = 15.2, p < .001, η _p ^two = .25. The main effect of SES on RT was also meaning, F(1,45) = 27.v, p < .001, η _p ² = .38, confirming that children in the College-SES grouping were significantly faster overall in familiar discussion recognition than children in the Lower-SES grouping. There was no significant historic period × SES group interaction, p = .27, η _p ² = .03, reflecting parallel gains in response speed with increasing age in both groups of children. Notwithstanding, consistent with the findings for accuracy, the accented differences in processing speed between the two groups at each age were substantial: the hateful RT for Lower-SES children at 24 months was comparable to the mean RT for 18-month-olds in the Higher-SES group.

Mean RT to initiate a shift from the distracter to the target moving-picture show at 18 and 24 months for the Higher-SES and Lower-SES learners. Error bars represent SE of the mean over participants.

Relations betwixt Online Processing Skill and Vocabulary in a Diverse Sample of Children

The final analysis explored whether variability in online processing skills aligned with vocabulary knowledge in this diverse sample. First-order correlations betwixt RT and accuracy in existent-time comprehension and vocabulary scores at 18 and 24 months are shown in Table 5. As in previous studies with more homogeneous samples of English language-learning children from advantaged families, nosotros establish reliable links between performance in the LWL task and expressive vocabulary size at both xviii and 24 months, although links were stronger and more than consistent at the later fourth dimension point. At 24 months, accuracy and RT were correlated with both before and concurrent vocabulary scores, accounting for 15 - 23% of the variance. These results echo the recurring finding that those children who are faster and more accurate in real-fourth dimension interpretation of familiar words tend to be those who are also reported to produce more words (Fernald et al., 2006; Fernald & Marchman, 2012; Hurtado et al., 2007).

Tabular array v

First-guild correlations (r) between processing efficiency and vocabulary at xviii and 24 months

	xviii months		24 months
	Accurateness	RT	Accuracy	RT
Vocabulary
xviii months	.35 *	-.25 #	.43 **	-.42 **
24 months	.43 **	-.18	.48 **	-.47 **

Word

This research revealed similarities merely also striking differences in early on linguistic communication proficiency among infants from advantaged families and from less advantaged families. Our first goal was to track developmental changes in language processing efficiency in relation to vocabulary learning in this diverse sample of English-learning children. Our 2d goal was to examine SES differences in these crucial aspects of early on language development. The most important finding was that pregnant disparities in language proficiency betwixt infants from higher- and lower-SES families were already evident at 18 months of age, and past 24 months there was a 6-month gap between the two groups.

Similarities and Differences Among Children in Early Processing Efficiency and Vocabulary

Although participants in this study came from very different backgrounds, they showed mutual patterns of change in the efficiency of real-fourth dimension language processing from 18 to 24 months. Older children were more probable than younger children to interpret the incoming spoken communication indicate incrementally, fixating the target picture every bit soon every bit they had plenty information to place the referent. We also establish reliable links betwixt skill in early spoken communication processing and vocabulary development, replicating results previously shown in children from affluent, highly educated families (Fernald et al., 2006; Fernald & Marchman, 2012), but never before in English-learning children from a broader SES range. These results provide further evidence that real-time language processing is aligned with early vocabulary development.

Extending earlier results showing consistent relations between early processing efficiency and vocabulary size to a more diverse group of English-learning children was an important starting point. Withal, the more surprising issue of this report was that by the age of 18 months, there were already substantial differences among children as a office of SES. Children from lower-SES families had significantly lower vocabulary scores than children from college-SES families at the aforementioned historic period, and they were besides less efficient in real-time processing. As seen in Tabular array 4, mean accurateness for the lower-SES children increased from .59 to .69 betwixt the ages of 18 and 24 months; however, mean accuracy for the higher-SES children was already .69 at 18 months, increasing to .77 by 24 months. Measures of processing speed showed a similar pattern: in the lower-SES children, the mean RT at 24 months (Yard = 802 ms) was yet not as fast equally the mean RT at eighteen months in the college-SES children (1000 = 746 ms). These differences were equivalent to a six-month disparity betwixt the higher- and lower-SES children, in vocabulary size and in both measures of language processing efficiency.

Exploring Sources of Variability in Immature Children'due south Early Language Proficiency

Where do these substantial differences come from? Variability among individuals in verbal abilities is influenced to some extent past genetic factors (Oliver & Plomin, 2007), but the contributions of early experience to differences in linguistic communication proficiency are also substantial. Research on language problems in twins has also shown that ecology factors are more than powerful than genetic factors in bookkeeping for similarities in language development in children in the same family (Oliver, Dale & Plomin, 2004). Other studies advise that the contribution of ecology factors to variability in IQ has been underestimated in behavioral genetics studies, which tend to focus on children in middle-grade families (Rowe, Jacobson & Van den Oord, 1999; Turkheimer, Haley, Waldron, D'Onofrio & Gottesman, 2003). In a study of twins from families diverse in SES, Turkheimer et al. (2003) found that 60% of the variance in cerebral abilities was accounted for by shared environmental factors among children living in poverty, with the genetic contribution shut to zero; nevertheless, for children in college-SES families, the opposite design of findings emerged. While the power of SES to moderate the heritability of verbal and other cognitive abilities is nether debate (Hanscombe et al., 2012), there is consensus that infants' genetic potentials in these domains can only be realized with appropriate environmental back up. In families where adequate resources and support are consistently available, children are more likely to exist buffered from adverse circumstances than are children in impoverished families, and so are more likely to exist able to achieve their developmental potential.

There are many unlike experiential factors associated with living in poverty that could contribute to variability in language learning. For case, the concrete weather condition of everyday life related to safety, sanitation, racket level, and exposure to toxins and dangerous conditions differ dramatically for children in lower- and college-SES families, as does the access to crucial resources such as adequate diet and medical intendance (Bradley & Corwyn, 2002). Weather of social and psychological support vary as well, with higher levels of stress and instability in disadvantaged families (Evans, Gonnella, Marcynyszyn, Gentile & Salpekar, 2005). All of these environmental factors are known to accept consequences for cognitive and social outcomes in young children (e.one thousand., Evans, 2004). There are also well known differences in the quality of parent-child interaction among families differing in SES related to these coexisting factors. For example, parents under greater stress tend to respond less sensitively to their children (Mesman, van IJzendoorn, & Bakermans-Kranenburg, 2011), and provide less adequate social and cognitive stimulation. This is likely to exist one of import factor contributing to the well-documented SES differences in the corporeality and quality of child-directed speech (Hoff, 2003; 2006). Hart and Risley (1995) estimated that by 36 months, the children they observed from advantaged families had heard xxx million more than words directed to them than those growing up in poverty, a stunning deviation that predicted of import long-term outcomes (Walker, et al., 1994).

Could variation in early language experience also contribute to individual differences in infants' existent-time processing efficiency, too equally in vocabulary learning? This question was explored in longitudinal inquiry with Castilian-speaking families, examining links between maternal talk, children's processing efficiency, and lexical development (Hurtado, Marchman, & Fernald, 2008). Those infants whose mothers talked with them more at xviii months were those who learned more than vocabulary by 24 months. But the most noteworthy finding was that those infants who experienced more and richer language were also more efficient in real-time language processing six months afterward, compared to those who heard less maternal talk. One interpretation of these findings is that having the opportunity for rich and varied engagement with language from an circumspect caretaker provides the infant non only with models for linguistic communication learning, but also with valuable exercise in interpreting language in real time. Thus, child-directed talk sharpens the processing skills used in online comprehension, enabling faster learning of new vocabulary.

Long-term Consequences of Early on Differences in Language Skills

How would an advantage in processing efficiency facilitate vocabulary learning? Studies with adults show that faster processing speed can gratis boosted cognitive resources (due east.chiliad., Salthouse, 1996), which may exist peculiarly benign in the early stages of linguistic communication learning. The infant who tin interpret a familiar give-and-take more rapidly has more resource bachelor for attending to subsequent words, with advantages for learning new words that come up afterward in the sentence. A slight initial border in the efficiency of familiar word interpretation could be strengthened through positive-feedback processes, leading to faster growth in vocabulary that in turn leads to further increases in receptive linguistic communication competence. If rapid lexical access of familiar words facilitates learning new words, then greater efficiency in language processing at 18 and 24 months could have cascading advantages that result in further vocabulary growth.

Results from several studies back up the idea that variability in both processing speed and vocabulary could have long-term consequences. In inquiry with adults and children, mean RT across diverse tasks predicted success on cognitive assessments at every age (Kail & Salthouse, 1994). Considering hateful RT in adults correlates so consistently with measures of memory, reasoning, language, and fluid intelligence, Salthouse (1996) has argued that gradual increases in processing speed account fundamentally for developmental modify with age in cerebral and language functioning. This clan has been characterized as a developmental cascade by Fry and Unhurt (1996), who proposed that increasing processing speed strengthens working memory, and that stronger working memory then leads to greater cognitive competence. Since vocabulary size also predicts IQ in both adults and children (Matarazzo, 1972; Vance, Westward & Kutsick, 1989), an early on advantage in lexical development could have cascading benefits for other aspects of language learning every bit well (Bates et al., 1988). Vocabulary noesis also serves every bit a foundation for afterwards literacy (Lonigan, Burgess & Anthony, 2000), and linguistic communication proficiency in preschool is predictive of academic success (Alexander, Entwisle & Horsey, 1997). It is clear from these findings that the early on emerging differences we found in language proficiency between children from unlike SES backgrounds have serious implications for their long-term developmental trajectories.

Conclusions

In this enquiry nosotros institute significant differences in both vocabulary learning and language processing efficiency that were already present past 18 months, with a six-month gap emerging betwixt higher- and lower-SES toddlers by 24 months. These results mirror findings from new analyses of the ECLS-B information set, which used more global measures to show that reliable differences in cognitive performance between children in lower- and higher-SES families were nowadays past 24 months (Halle et al., 2009; Tucker-Drob, Rhemtulla, Harden, Turkheimer & Fask, 2011). What our findings add is the first evidence that SES-related disparities in language skills emerge at an even earlier age. Using high-precision measures of infants' real-time responses to familiar words, information technology was not until 24 months that the less advantaged children reached the same levels of speed and accurateness achieved by more advantaged children at xviii months, a six-month gap in the development of processing efficiency. Such a large disparity cannot merely exist dismissed as a transitory delay, given that differences amidst children in trajectories of language growth established by iii years of age tend to persist and are predictive of later on schoolhouse success or failure (Burchinal et al., 2011; Farkas & Beron, 2004).

Considering this difference tin be characterized equally a lag in early on processing efficiency with potentially important long-term consequences, it is important to frame this finding in lite of scientific discoveries that reveal the weaknesses of the controversial 'deficit model' of the 1960's. The view that children from disadvantaged homes were inherently 'culturally deprived' (Riessman, 1962) was based on a vague notion of civilization equally embodied in middle-class practices, institutions, and values. At that fourth dimension, fiddling was known about the actual activities and practices of parents in different families, with even less scientific show on trajectories of cognitive and language development from infancy through childhood. Thus the term 'deficit' was used as a global indictment of parenting styles in impoverished families that were merely different from center-form families - a well-intended simply misguided endeavour to help teachers sympathise the difficulties minority children were experiencing in the recently desegregated schoolhouse system.

There was obfuscating vagueness on both sides of the debate. Advocates of the arrears model proposed a causal account of the effects of children'south early life experience on later cognitive development in which both predictor and effect variables were poorly specified. While many critics of the arrears model raised valid points urging greater respect for unlike cultural practices (east.g., Heath, 1983), others countered with proposals that were simplistic and counterproductive, ofttimes reflecting a political agenda. These proposals ranged from calling a halt to research on parenting practices in minority families because information technology was inherently paternalistic and racist, to focusing on eliminating poverty rather than on 'blaming the victim' (Ryan, 1971). The deficit model was incoherent at the time, and the continuing debate on this construct has not led to greater precision or insight (Gorski, 2006).

In an try to reframe this statement, we end with an example from nutrition, where cognitive consequences can be linked to particular deficits without evoking the reflexive opposition associated with arrears models in social scientific discipline. Children with iron deficiency anemia (IDA) are typically low in energy and accept cognitive difficulties. For many years, the prevailing explanation for these symptoms was that parents treated lethargic children with IDA equally if they were younger, which supposedly retarded their cognitive development (Pollitt, 1993). Thus differences among children in global measures of cognitive ability were attributed to sick-divers problems in parenting behavior. However, contempo research on IDA has led to a much more precise specification of both causes and consequences. Studies with animal models bear witness that iron deficiency in pre- and postnatal evolution disrupts the optimal course of myelination, which then reduces efficiency of neural transmission (Bristles, Wiesinger, & Connor, 2003). And longitudinal research measuring brain responses to auditory and visual stimuli shows that children with IDA have slower neural transmission, which is very likely to touch the efficiency of cerebral processing (Algarín, Peirano, Garrido, Pizarro, & Lozoff, 2003).

Resting on a foundation of enquiry showing solid relations between a specific causal factor and specific consequences, these discoveries of links between iron deficiency and long-term cognitive difficulties become valuable and highly relevant as public health data. If a mother was told that her child had a "cultural arrears in nutrition," such a wide, vague claim could simply exist perceived as a perplexing insult. However, if she heard almost new enquiry showing that iron is admittedly critical for optimal brain development in infancy, and that healthy brain development is vital to her child's success in schoolhouse and in later life, she might be more interested in learning about new ways to provide more iron in her child'due south diet.

While contempo research on nutrition focuses on biological factors that influence early cerebral development, there is increasing scientific evidence that experiential factors also play a disquisitional part in infants' early language development – by nurturing vocabulary learning (Hart & Risley, 1995; Hoff, 2006) as well as strengthening skill in existent-time language processing (Hurtado et al., 2008; Weisleder & Fernald, under review). Although the present study was not designed to explore causes of the variability we plant amongst children, our results add together to this literature by showing the potential benefits of early processing efficiency for vocabulary growth, and also revealing the potential toll to children with less efficient processing skills, in terms of missed opportunities for learning. From the perspective of basic research and theory in language acquisition, it is essential to investigate non simply the typical developmental trajectories of children from privileged families, just as well the wide range of variability that becomes credible when children from more diverse backgrounds are included. Nosotros address this goal hither by documenting substantial differences between infants from lower- and higher-SES backgrounds that are already evident in the second year of life, using sensitive measures of early language proficiency known to be predictive of later outcomes. The next step is to explore the powerful sources of variability in early experience that contribute to such differences in infants' emerging language proficiency, and to examine the nature and timing of their influence in larger and more diverse samples of children. From a policy perspective, the ultimate challenge is to frame these discoveries as a public health bulletin (Knudsen, Heckman, Cameron, & Shonkoff, 2006), with the goal of helping caregivers understand the crucial office they tin can play in enabling infants to build and strengthen skills essential for optimal development.

Acknowledgments

This research was supported by grants from the National Institutes of Health (HD42235 and DC008838). We are grateful to the children and parents who participated in this written report, and to our community partners in Northern California who enabled us to conduct this written report. Special thanks to Krisa Bruemer, Jillian Maes, Viviana Limón, Lucia Martínez, Nereyda Hurtado, Poornima Bhat, Ricardo Hoffmann Bion, Kyle McDonald, Katherine Adams, Mofeda Dababo, and the staff of the Heart for Infant Studies at Stanford University.

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Source: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3582035/

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