A Difference Between Low-ses Families and Middle-ses Families Is That ________.

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

Published in final edited form equally:

PMCID: PMC3582035

NIHMSID: NIHMS411497

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

Abstract

This research revealed both similarities and hitting differences in early on language proficiency among infants from a broad range of advantaged and disadvantaged families. English language-learning infants (due north = 48) were followed longitudinally from xviii to 24 months, using real-fourth dimension measures of spoken linguistic communication processing. The first goal was to rail developmental changes in processing efficiency in relation to vocabulary learning in this diverse sample. The second goal was to examine differences in these crucial aspects of early language development in relation to family socioeconomic status (SES). The nearly important findings were that significant disparities in vocabulary and linguistic communication processing efficiency were already axiomatic at 18 months betwixt infants from higher- and lower-SES families, and past 24 months there was a six-month gap betwixt SES groups in processing skills disquisitional to language evolution.

In that location are hitting differences amid children in patterns of early on linguistic communication growth. Some infants start speaking before their first altogether, while others don't produce words until the end of the second twelvemonth (Fenson et al., 2006). Although some late talkers catch upwards in vocabulary a few months afterwards, others go along to show slower trajectories of linguistic communication growth and attain lower levels of language 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 afterwards academic success or failure (Lee & Burkum, 2002). In adults as well, SES differences in language proficiency are robust (Pakulak & Neville, 2010), reflecting the cumulative influence of a wide range of endogenous and environmental factors over a lifetime.

Despite such show for meaning differences among children in early on language learning, research 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: Offset, the search for similarities rather than differences amidst children is grounded in a philosophy of science that underlies psychological research more broadly – i 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 research on early language development favors between-grouping comparisons of infants at dissimilar ages, with express attending to variability inside historic period groups (Fernald, 2010). Third, the vast bulk of developmental studies in the U.S. rely on 'convenience samples' of children from college-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 verbal abilities amid school-age children varying in SES (e.thou., Dickinson & Tabors, 2001; Lee & Burkam, 2002), this literature is often viewed as 'practical' research with express relevance to 'basic' enquiry on language development. We argue here that understanding the extent and origins of variability among children in the emergence of early language proficiency should be primal to whatsoever developmental theory that acknowledges, at whatever level, the influence of children's early experience on language growth.

This perspective motivates the current study of differences likewise as similarities in early linguistic communication proficiency among children from college- and lower-SES families. In experimental studies using looking-time measures, nosotros accept shown that infants develop speed and efficiency in interpreting spoken language in existent time (Fernald, Pinto, Swingley, Weinberg, & McRoberts, 1998) and that private differences in early processing efficiency are strongly linked to variation in children's afterwards language outcomes (eastward.chiliad., Fernald, Perfors & Marchman, 2006; Marchman & Fernald, 2008). Still, in these previous studies, equally in many other university-based studies with English-learning children, nigh participants came from highly-educated and affluent families. The goal of the present written report was to examine the development of language processing efficiency in relation to vocabulary learning in English-learning infants from families varying in SES. Using existent-time processing measures, nosotros followed children longitudinally from xviii to 24 months, focusing on ii sets of questions: First, to what extent do infants across this broader SES range show parallel gains in processing efficiency and vocabulary between 18 and 24 months? And second, is there evidence that SES-related differences in processing skills critical to language development are already present in infancy?

SES Differences in Exact Abilities and their Long-Term Consequences

The finding that children from disadvantaged families kickoff kindergarten with lower linguistic communication and cerebral skills than those from more advantaged families is erstwhile news, emerging repeatedly in studies since the 1950'due south (e.g., Bereiter & Englemann, 1966; Deutsch, Katz, & Jensen, 1968). The robustness of such differences is confirmed in more recent research such every bit the Early on Childhood Longitudinal Study, Kindergarten Cohort (ECLS-One thousand), 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 60% above those in the lowest group. In terms of event size, children in the highest SES-quintile scored .7 standard-deviation (SD) units in a higher place heart-SES children in reading accomplishment, while children in the lowest SES-quintile scored most .5 SD units beneath the heart-SES hateful. Moreover, the disparities in children's cognitive performance at kindergarten entry that were owing to SES differences were significantly greater than those associated with race/ethnicity. Another contempo study institute that 65% of low-SES preschoolers in Head Kickoff programs had clinically significant language delays (Nelson, Welsh, Vance Trup, & Greenberg, 2011). This research revealed a systematic relation betwixt degree of language delay and other weaknesses in bookish and socio-emotional skills that were well established past 4 years of age. Socioeconomic gradients in linguistic communication proficiency are also found inside populations living in extreme poverty (Fernald, L., Weber, Galasso, & Ratsifandrihamanana, 2011).

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

Results showing that SES differences in verbal abilities are already axiomatic in the preschool years propose that these disparities must beginning to develop in the first years of life, setting children on particular trajectories with far-reaching consequences for later academic success. How early practice such differences begin to emerge? Research on this important developmental question has been limited for a diverseness of reasons - ranging from methodological challenges in evaluating language proficiency in young children, to the complexities of engaging in fence about politically sensitive issues related to social stratification. The methodological problem is easy to characterize: Until recently, measures available for assessing language and cerebral proficiency in children younger than 3 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 linguistic communication, contempo studies have revealed considerable variability in verbal skills among very young children - to be reviewed in the following department. Another set of issues that has discouraged enquiry on early origins of cognitive differences amid children from different backgrounds is more difficult to characterize. The legacy of a prolonged and bitter debate nigh the nature of racial and SES differences in the U.Southward. has reinforced the reluctance of researchers to pursue the question of early on origins of SES-related disparities in cognitive skills that are relevant to school success.

A brief history of this complex debate is relevant to the issues raised in the current study. The scientific consensus in the early on 20th century was that cerebral abilities were entirely genetically determined, a view that changed gradually with mounting evidence that experiential factors were also influential (run across Fernald & Weisleder, 2011). By the 1960's, when the Civil Rights motility focused national attention on inequities in educational opportunities for Blackness children, there was intense involvement in eliminating achievement gaps that could no longer be 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 domicile, rather than from immutable genetic differences. This 'cultural deprivation' argument appeared to offer hope for solutions through advisable intervention, although characterizing the home environment of minority children every bit scarce in cerebral stimulation clearly had negative implications. While this thought rallied political support for new programs such as Operation Caput Start, what came to exist known as the 'arrears model' too generated intense controversy among educators who objected that parents should not exist blamed for their children's difficulties in school. By the 1970'southward, politically motivated backfire to the deficit model converged with the ascent of nativist theories of language development, which focused on modal patterns of development presumed to be universal rather than on differences amongst children. Fernald and Weisleder (2011) argue that this convergence was influential in curtailing debate on questions that had generated extensive enquiry over the previous two decades – namely, whether SES differences in children's exact 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 amongst children in their later academic success.

Although involvement in variability in language learning had declined substantially by the 1980's, a few researchers began to explore in greater depth the potential contributions of early parent-child interaction to differences in linguistic communication development (e.grand., 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 communication that predict language event measures. Hart and Risley establish that past 36 months, the higher-SES children in their sample spoke twice as many words as the lower-SES children. But their virtually remarkable finding was the extreme variation in amounts of child-directed speech among families at different SES levels, differences that were correlated with children'south early on vocabulary and likewise predictive of later school performance (Walker, Greenwood, Hart & Carta, 1994). Co-ordinate to Hoff (2003), information technology was the quality of infants' early linguistic communication surround that actually mediated the link between SES and children's vocabulary noesis.

Assessing Differences in Language Proficiency in Very Young Children

These studies of variability in early language environments with small 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 knowledge in Black and White children from 36 months to 13 years of age, using a big, representative national data set. Their most striking finding was that near of the inequality in vocabulary growth owing to race and SES differences developed prior to 36 months. Moreover, the magnitude of the Black-White vocabulary gap that was already evident by the historic period of school-entry remained unchanged through the age of 13 years. These authors ended that by 36 months, SES differences in children's language experience have already led to significant vocabulary disparities, which then widen further in the preschool years and remain constant thereafter. Data from the NICHD Early Childhood Care Research Network also revealed that a substantial achievement gap between low-income Black and White children was already axiomatic by 3 years, and that family as well as schoolhouse characteristics contributed to maintaining this gap through elementary school (Burchinal et al., 2011). A third contempo report with a large, representative sample from the Early Childhood Longitudinal Study, Nascence Cohort (ECLS-B) showed that disparities between lower- and college-SES infants on linguistic communication and cognitive measures began to emerge by ix months, and that by 24 months there was a hateful departure of .5 SD units between SES groups on the Bayley Cognitive Assessment (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. But given these task demands, such assessments cannot exist used effectively with toddlers younger than 2 years. While parent reports of a kid's vocabulary tin can yield valuable information on early on language development (Fenson et al., 2006), they exercise non provide a direct measure of the kid'due south response. Until recently, these methodological limitations fabricated information technology difficult 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 fourth dimension course of language comprehension past very young linguistic communication learners, providing direct measures of early efficiency in language processing in real time.

Recent experimental studies on language processing in the second and 3rd years have used existent-time measures to assess how efficiently children place the referent of a familiar word in existent-time comprehension. In the looking-while-listening (LWL) process (Fernald, Zangl, Portillo & Marchman, 2008), children see pictures of two familiar objects as they heed to speech naming ane of the objects, and their responses are coded with millisecond-level precision. Cantankerous-sectional studies of both English- and Castilian-learning infants bear witness dramatic gains in the speed and accuracy of language understanding across the second yr (Fernald, Pinto, Swingley, Weinberg & McRoberts, 1998; Hurtado, Marchman & Fernald, 2007). Moreover, young children, like adults, are able to interpret incoming language incrementally, directing their attending to the appropriate picture as the spoken communication betoken unfolds in time (Fernald, Swingley & Pinto, 2001; Swingley, Pinto & Fernald, 1999). In a longitudinal report with English-learning toddlers from 15 to 24 months, these online processing measures were found to be stable over time, and processing speed at 24 months was robustly correlated with vocabulary growth over this menses (Fernald et al., 2006). Moreover, a follow-up study with the same children half dozen years later showed potent links betwixt processing efficiency in infancy and functioning on standardized tests of language and cerebral skills in simple schoolhouse (Marchman & Fernald, 2008). These existent-time processing measures have revealed consistent concurrent and predictive relations to language outcomes across studies of typically-developing children. They are also high in predictive validity in research with late-talkers, children at increased risk for persistent language delays (Fernald & Marchman, 2012). For these reasons, the LWL task is well suited for investigating both similarities and differences in early language processing skill among infants from different socioeconomic backgrounds.

Research Questions

The main goals in this research were to examine the early evolution of language processing efficiency in relation to vocabulary learning in English-learning infants from families across a broad demographic range, and to determine 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 academy laboratory in a prosperous urban surface area, where almost all the families who volunteer to participate in research are affluent and highly educated (Site i). To extend across this convenience sample of high-SES families, nosotros needed to establish an additional research site in an area where it is possible to recruit equivalent numbers of lower- and middle-SES English language-speaking families. Site 2 is located in an urban area comparable in population size to Site 1. Yet, considering these two areas differ substantially in terms of median family income, price-of-living, and percentage of children living in poverty, every bit shown in Table 1, we are able to include a much more diverse sample of English-learning children at Site 2 than is possible at the university lab.

Table 1

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

	Site i	Site 2
Total population a	90,200	90,500
% non-Hispanic white a	66%	83%
Median per capita income a	$69,000	$23,900
Cost-of-living index b	157.9	92.9
% children living below federal poverty level a,c	5.3%	22.9%

Method

Participants

Participants were 48 English-learning children (26 females), recruited through nativity records and day care centers at Site 1 (due north = xx) and Site 2 (n = 28). Exclusionary criteria at time of recruitment included preterm birth, nascency complications, hearing/visual impairments, medical issues, or a known developmental disorder. Reported ethnicity of participants was non-Hispanic White (66%), Asian (13%), Alaskan Native/American Indian (10%), Native Hawaiian/Pacific Islander (6%), or African American (4%). After receiving a brochure describing the projection, interested parents contacted us by telephone, website, or respond card. Parents were then interviewed by phone about their child's language background, wellness history, and family history of linguistic communication disorders. Qualifying families were invited to join the study if the child was non regularly exposed to a language other than English language. Six boosted participants were excluded from terminal analyses because the families could not attend the 24-calendar month testing session or did not complete both linguistic communication questionnaires.

Socioeconomic status

Although participants were all typically-developing infants from monolingual English-speaking families, they were diverse in socioeconomic background, as shown in Table 2. The mothers in these families had about 3 years of postal service-loftier school education, on boilerplate, nonetheless spanned a broad range of educational levels: 21% did non finish or were nonetheless attending high school, or did not continue their education by high schoolhouse, xix% had some higher, 33% completed a B.A. degree, and some other 27% also received some mail-B.A. training. Tabular array 2 also shows scores on the Hollingshead Four Factor Index of Socioeconomic Status (HI, Hollingshead, 1975). This widely-used index of family SES is based on a weighted average of both parents' education and occupation, with possible scores ranging from 8 to 66. The Howdy is divisible into 5 "strata" of social condition: unskilled worker, semi-skilled worker, skilled worker, semi-professional, and major professional person. In this sample, parents' occupations spanned the full range from unskilled worker to major professional. For some analyses, families were divided into Lower- (≤ 45, n = 23) and Higher-SES (> 47, n = 25) sub-groups based on a median split of Howdy scores, every bit shown in Table 2. Both groups included at to the lowest degree one mother with only a high schoolhouse educational activity, also as several mothers who had attended college. Nevertheless, the distributions of maternal education levels were substantially different in the two groups. Nearly 90% of the mothers in the College-SES grouping had at least a four-year college caste, with more than half completing masters or doctoral degrees, while only 30% of the mothers in the lower-SES group had completed college and 1 had a masters degree. Of the children from families in the Higher-SES group, nineteen were recruited at Site 1 and six at Site ii. Of those from families in the Lower-SES group, 1 was recruited at Site ane and 22 at Site 2.

Table 2

Mean (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.iv)	10 - 18	13.seven (ii.two)	10 - 18	xvi.7 (i.half dozen)	12 - eighteen
HI b	46.vi (15.i)	xiv - 66	33.9 (10.one)	fourteen - 45	58.three (7.3)	47 - 66

Offline Measures of Vocabulary

Reported expressive vocabulary

At xviii and 24 months, parents completed the MacArthur-Bates Chatty Development Inventory: Words & Sentences (CDI: Fenson et al., 2006). This parent-study musical instrument enquire parents to signal on a checklist (680 items) which words their child "understands and says". All parents were told to substitute words on the checklists with variants of those words specific to their family unit (east.g., nana for grandmother).

Procedure for Assessing Real-fourth dimension Linguistic communication Understanding

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 verbal and visual stimuli were identical at Sites ane and 2, and the same ii experimenters conducted exam sessions at both sites. On each trial, participants viewed ii pictures of familiar objects while listening to speech naming one of the pictures. Visual stimuli were colorful pictures (36 × l cm) of the target and distracter objects on gray backgrounds, aligned horizontally on a video display. Children sat on the caregiver's lap during the five-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 terminal position, followed by an attention-getter (e.g., Where's the auto? Practice you similar it?). The child's face up was video-recorded for later frame-by-frame coding. On each trial, the two pictures were shown simultaneously for ii s prior to speech communication onset, remaining on the screen during the auditory stimulus until 1 s after sound offset. Between trials, the screen was blank for approximately 1 south. Each trial lasted approximately 7 south.

Verbal stimuli

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

At 18 months, the target nouns were babe, doggy, birdie, kitty, ball, shoe, book, and car, object labels likely to exist familiar to English-speaking children at this age (Dale & Fenson, 1996). Each object was presented four times as target and four times equally distracter, yielding 32 experimental trials. Interspersed among the critical trials were 4 filler trials (due east.g., Practice you like those pictures?). At 24 months, children heard sentences containing the familiar target nouns baby, doggy, birdie, kitty, cookie, book, car, and juice each presented twice as target and twice as distracter, a total of sixteen experimental trials. These familiar give-and-take trials were interspersed with fillers (4 trials) and trials in which the target word was placed in a carrier frame with an adjective (16 trials) or a semantically-related verb (eight trials). These trials are non analyzed here. Trials on which the parent reported that the child did not understand the target discussion were excluded from analyses on a kid-by-kid basis.

Visual stimuli

Pictures corresponding to target words were presented in fixed pairs matched for visual salience, with each object serving equally oftentimes as target and distracter. All tokens were judged to represent objects typically familiar to young children. Position of target picture was counterbalanced beyond trials. Trials were presented in a pseudo-random order such that the same target word never occurred on adjacent trials, and the target picture did not announced on the aforementioned side more than two trials in a row.

Coding

Video records of children's gaze patterns were analyzed frame-by-frame by highly-trained coders bullheaded to target side and condition. All coding was conducted at Site i by coders who were non involved in running the sessions and were blind to testing site. On each frame, coders indicated whether the child was looking at the left picture, right picture, in between the two pictures or abroad from both. This yielded a high-resolution tape of eye movements for each 33-ms interval equally the stimulus sentence unfolded, aligned with the onset of the target substantive. Trials were after classified every bit target- or distracter-initial, depending on which picture the child was fixating at target-noun onset. To determine reliability, 25% of sessions were independently re-coded, with inter-observer agreement computed in ii means. Offset, the mean 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 one frame was likewise calculated, a more conservative measure out which also yielded loftier reliability (97%).

Calculation of accurateness and RT

Two measures of efficiency in real-time speech processing were calculated for each child. Starting time, accuracy was computed as the mean proportion of looking to the named picture on target- and distracter-initial trials, averaged over 300-1800 ms from noun onset. Mean accurateness was based on an average of 22.ix trials (SD = 5.iii) per child at 18 months and 12.ii trials (SD = two.9) at 24 months. 2d, reaction fourth dimension (RT) was computed on just those trials on which the child was looking at the distracter pic at the onset of the target word and shifted to the target movie within 300-1800 ms from target word onset. Trials on which the child shifted either inside the first 300 ms or later than 1800 ms from target word onset were excluded, since these early on and belatedly shifts were less likely to be in response to the stimulus judgement (Fernald et al., 2008). Mean RTs were based on an average of 8.8 trials (SD = iii.6) at 18 months and v.0 trials (SD = 2.1) at 24 months.

Results

Focusing on two crucial aspects of early linguistic communication proficiency – the development of expressive vocabulary and skill in real-time spoken language processing - this written report examined differences and similarities in patterns of developmental change from eighteen to 24 months in a diverse grouping of English-learning children. A central question was how variability in lexical development and real-time processing efficiency would relate to variability in family SES. The scatterplots in Effigy ane show that SES differences were significantly correlated with vocabulary likewise every bit with accuracy and reaction time, our two measures of processing efficiency: 18-month-olds growing up in families with college HI scores were more than advanced in vocabulary, r(48) = .34, p < .02, and were also more accurate, r(48) = .52, p < .001, and faster, r(47) = -.50, p < .001 in spoken give-and-take recognition in the LWL chore. Correlations betwixt SES and these three language measures were also significant at 24 months: vocabulary: r(48) = .29, p < .05; accuracy, r(48) = .thirty, p < .05; RT, r(48) = -.45, p < .001. For the next analyses, nosotros divided participants into 2 SES groups based on a median split of HI scores (see Table 2), to compare children from Lower- and Higher-SES families in their patterns of change with age in vocabulary and processing efficiency.

Scatter plots of Vocabulary, Accuracy and RT at 18 months with SES (HI). Dashed vertical line indicates median split of HI values.

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

Mean expressive vocabulary scores at 18 and 24 months for College- and Lower-SES children are shown in Table 3 and Effigy ii. In a 2 × 2 mixed assay of variance (ANOVA), with SES group every bit a between-Ss factor and age every bit a within-Ss cistron, the primary result of age was significant, F(1,46) = 163.5, p < .001, η _p ² = .78, reflecting larger vocabulary scores at 24 months than at 18 months across all children. On average, children's vocabulary size increased by about 225 words over this menses. The main event of SES group was as well meaning, F(i,46) = eight.6, p < .001, η _p ² = .16, confirming that children in the College-SES grouping were significantly more advanced in vocabulary than those in the Lower-SES group. Indeed, at xviii months, nearly one-half the children in the Lower-SES grouping (northward = 12) had fewer than 50 words in their reported vocabulary, while merely 8 children in the Higher-SES group had scores of l words or less. A similar tendency was evident at 24 months: Children from Higher-SES families produced nearly 450 words, on average, while children from Lower-SES families produced about 150 fewer words, consistent 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 (Hello). Error bars correspond SE of the mean over participants.

Table three

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

Age	All participants		Lower SES		Higher SES
18 months	141.9 (123.0)	5 - 503	107.0 (114.ii)	5 - 503	174.0 (124.3)	sixteen - 471
24 months	367.ix (180.2)	4 - 665	287.9 (163.three)	4 - 573	441.5 (165.4)	59 - 665

An even more hitting consequence was that the pattern of developmental modify in vocabulary differed as a function of SES, reflected in a significant historic period past SES group interaction, F(1,46) = 6.1, p < .02, η _p ² = .12. As illustrated in Figure ii, a group difference in vocabulary between children from Lower- vs. College-SES backgrounds was conspicuously evident at eighteen months, and by 24 months the between-grouping divergence was even larger. Children in the Higher-SES group made significantly greater gains (M = 268 words, SD = 116) over this menstruum than did children in the Lower-SES group (Chiliad = 180 words, SD = 127), t(46) = 2.5, p < .02.

Changes in Processing Efficiency from 18 to 24 Months in College- and Lower-SES Children

Adjacent we compared children at both ages in the ii SES groups on two measures of processing efficiency – mean accuracy and hateful RT (run into Table 4) – using ii (age) × two (SES grouping) mixed ANOVAs.

Table iv

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

	All participants	Lower SES	College SES
Accuracy a
18 months	.64 (.09) *	.59 (.08) *	.69 (.07) *
24 months	.73 (.10) *	.69 (.11) *	.77 (.08) *
RT b
xviii 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 correct moving-picture show than did eighteen-month-olds, F(one, 46) = 31.2, p < .001, η _p ^two = .40. There were besides significant between-group differences in accuracy: Higher-SES children were more accurate overall than the Lower-SES children, F(1, 46) = 22.eight, p < .001, η _p ^two = .33. The age × SES interaction was not reliable, p = .69, η _p ² = .003, reflecting comparable relative gains in accuracy from 18 to 24 months for infants in both groups.

The master effect of age is illustrated in Figure 3, which shows the fourth dimension form of looking to the target picture in the LWL task for children at 18 and 24 months. This graph plots change over time in the mean proportion of trials on which children overall fixated the target picture, averaged over participants at each 33-msec interval every bit the sentence unfolds. The proportion of looking to the target motion-picture show remained almost chance at least halfway through the target noun, when acoustic information potentially enabling identification of the right referent start became available. After this point, the hateful proportion of correct looking began to increment, continuing to rise afterward the offset of the target noun. Betwixt 18 and 24 months, children increased their proficiency in looking to the named target earlier the get-go of the target noun, reaching a higher level of accuracy at 24 months than six months earlier. Information technology is also important to notation that the proportion of looking to the named target movie was significantly above the chance level of .50 hazard at 18 months, t(47) = 11.2, p < .0001, and 24 months, t(47) = 15.half-dozen, p < .0001, indicating that children overall could correctly place the referents of familiar object names at both ages.

Mean proportion looking to the target film as a role of time in ms from noun onset at 18 and 24 months. Mistake bars correspond SE of the mean over participants. The vertical dashed line marks the audio-visual showtime of the target discussion.

Although accuracy improved with age for children in both SES groups, there was also a strong and early influence of SES. Figure iv plots the time course of looking to the correct target picture at 18 and 24 months for the Lower- and Higher-SES groups. The Higher-SES children responded past looking to the named target sooner in the stimulus sentence, and achieved substantially college levels of accuracy than those in the Lower-SES grouping. Only what is most remarkable about Figure four is that the curve for the Lower-SES children at 24 months essentially overlaps with the bend for the Higher-SES children at xviii months. Indeed the mean accurateness for Lower-SES children at 24 months (M = .69) was identical to that for Higher-SES children at xviii months (G = .69), indicating that 24-month-olds in the Lower-SES sample were performing at the same level overall as Higher-SES children who were half-dozen months younger.

Mean proportion of looking to the target every bit a part of time in ms from substantive onset for Lower-SES and Higher-SES learners. Open up squares/circles correspond the time class of correct looking at 18 months; filled squares/circles correspond the fourth dimension course of looking in the same children at 24 months. Error bars represent SE of the mean over participants.

Reaction Time

Similar patterns of developmental change were establish in analyses of processing speed, shown in Effigy 5. At 24 months, children were most 100 ms faster to initiate a shift from distracter to target picture, on average, than they were at 18 months, a significant master effect of age, F(1,45) = 15.two, p < .001, η _p ⁱⁱ = .25. The main event of SES on RT was also significant, F(1,45) = 27.5, p < .001, η _p ² = .38, confirming that children in the Higher-SES grouping were significantly faster overall in familiar word recognition than children in the Lower-SES group. There was no significant historic period × SES group interaction, p = .27, η _p ⁱⁱ = .03, reflecting parallel gains in response speed with increasing historic period in both groups of children. Nonetheless, consistent with the findings for accurateness, the accented differences in processing speed betwixt the 2 groups at each age were substantial: the mean RT for Lower-SES children at 24 months was comparable to the hateful RT for 18-month-olds in the Higher-SES grouping.

Mean RT to initiate a shift from the distracter to the target movie at 18 and 24 months for the Higher-SES and Lower-SES learners. Mistake bars stand for SE of the mean over participants.

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

The final assay explored whether variability in online processing skills aligned with vocabulary knowledge in this diverse sample. First-order correlations betwixt RT and accuracy in real-time comprehension and vocabulary scores at xviii and 24 months are shown in Table five. As in previous studies with more homogeneous samples of English-learning children from advantaged families, nosotros constitute reliable links between operation in the LWL task and expressive vocabulary size at both 18 and 24 months, although links were stronger and more than consistent at the afterward time point. At 24 months, accuracy and RT were correlated with both earlier 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-time interpretation of familiar words tend to be those who are besides reported to produce more words (Fernald et al., 2006; Fernald & Marchman, 2012; Hurtado et al., 2007).

Table 5

Beginning-order correlations (r) between processing efficiency and vocabulary at 18 and 24 months

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

Discussion

This inquiry revealed similarities but besides striking differences in early language proficiency amidst 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 second goal was to examine SES differences in these crucial aspects of early language development. The most of import finding was that meaning disparities in linguistic communication proficiency between infants from college- and lower-SES families were already evident at 18 months of age, and by 24 months there was a 6-month gap between the two groups.

Similarities and Differences Amidst Children in Early Processing Efficiency and Vocabulary

Although participants in this report came from very different backgrounds, they showed common patterns of change in the efficiency of real-fourth dimension language processing from 18 to 24 months. Older children were more than likely than younger children to interpret the incoming spoken language bespeak incrementally, fixating the target motion-picture show as soon equally they had plenty information to identify the referent. Nosotros likewise found reliable links between 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 language-learning children from a broader SES range. These results provide further evidence that real-time linguistic communication processing is aligned with early vocabulary development.

Extending before results showing consistent relations between early processing efficiency and vocabulary size to a more diverse grouping of English language-learning children was an important starting betoken. However, the more than surprising outcome of this study was that past the age of 18 months, there were already substantial differences among children as a part of SES. Children from lower-SES families had significantly lower vocabulary scores than children from higher-SES families at the same age, and they were also less efficient in real-time processing. Every bit seen in Tabular array 4, mean accuracy for the lower-SES children increased from .59 to .69 between the ages of 18 and 24 months; however, mean accuracy for the higher-SES children was already .69 at 18 months, increasing to .77 past 24 months. Measures of processing speed showed a similar pattern: in the lower-SES children, the hateful RT at 24 months (Grand = 802 ms) was still not equally fast as the mean RT at 18 months in the higher-SES children (One thousand = 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's Early Linguistic communication Proficiency

Where do these substantial differences come from? Variability amongst individuals in verbal abilities is influenced to some extent by genetic factors (Oliver & Plomin, 2007), but the contributions of early experience to differences in language proficiency are besides substantial. Research on language problems in twins has also shown that ecology factors are more powerful than genetic factors in accounting for similarities in language development in children in the same family (Oliver, Dale & Plomin, 2004). Other studies suggest that the contribution of environmental factors to variability in IQ has been underestimated in behavioral genetics studies, which tend to focus on children in centre-form families (Rowe, Jacobson & Van den Oord, 1999; Turkheimer, Haley, Waldron, D'Onofrio & Gottesman, 2003). In a report of twins from families various in SES, Turkheimer et al. (2003) found that 60% of the variance in cerebral abilities was deemed for past shared environmental factors among children living in poverty, with the genetic contribution close to zero; however, for children in higher-SES families, the opposite pattern of findings emerged. While the ability of SES to moderate the heritability of verbal and other cerebral abilities is nether debate (Hanscombe et al., 2012), there is consensus that infants' genetic potentials in these domains tin can only exist realized with advisable environmental support. In families where acceptable resources and support are consistently available, children are more likely to be buffered from agin circumstances than are children in impoverished families, then are more probable to exist able to achieve their developmental potential.

There are many different experiential factors associated with living in poverty that could contribute to variability in language learning. For example, the physical conditions of everyday life related to safety, sanitation, noise level, and exposure to toxins and dangerous conditions differ dramatically for children in lower- and higher-SES families, as does the access to crucial resources such equally acceptable nutrition and medical intendance (Bradley & Corwyn, 2002). Conditions of social and psychological back up vary too, with higher levels of stress and instability in disadvantaged families (Evans, Gonnella, Marcynyszyn, Gentile & Salpekar, 2005). All of these environmental factors are known to have consequences for cognitive and social outcomes in young children (eastward.thousand., Evans, 2004). At that place are likewise well known differences in the quality of parent-child interaction among families differing in SES related to these coexisting factors. For case, 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 be one important factor contributing to the well-documented SES differences in the amount 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 words directed to them than those growing up in poverty, a stunning difference that predicted important long-term outcomes (Walker, et al., 1994).

Could variation in early on linguistic communication experience also contribute to individual differences in infants' existent-time processing efficiency, every bit well equally in vocabulary learning? This question was explored in longitudinal inquiry with Spanish-speaking families, examining links betwixt maternal talk, children's processing efficiency, and lexical evolution (Hurtado, Marchman, & Fernald, 2008). Those infants whose mothers talked with them more at 18 months were those who learned more vocabulary by 24 months. But the nearly noteworthy finding was that those infants who experienced more than and richer linguistic communication were also more efficient in real-time language processing six months subsequently, compared to those who heard less maternal talk. One interpretation of these findings is that having the opportunity for rich and varied appointment with linguistic communication from an attentive flagman provides the babe not but with models for language learning, just also with valuable practice in interpreting language in real fourth dimension. Thus, kid-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 tin can free additional cognitive resources (e.chiliad., Salthouse, 1996), which may be particularly beneficial in the early stages of linguistic communication learning. The infant who tin interpret a familiar word more chop-chop has more than resources bachelor for attention to subsequent words, with advantages for learning new words that come up afterwards in the judgement. A slight initial edge in the efficiency of familiar give-and-take estimation could exist strengthened through positive-feedback processes, leading to faster growth in vocabulary that in plough leads to farther increases in receptive language competence. If rapid lexical admission of familiar words facilitates learning new words, and 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 support the idea that variability in both processing speed and vocabulary could accept long-term consequences. In enquiry with adults and children, mean RT beyond diverse tasks predicted success on cognitive assessments at every historic period (Kail & Salthouse, 1994). Because mean 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 business relationship fundamentally for developmental change with age in cognitive and language operation. This association has been characterized as a developmental cascade by Fry and Hale (1996), who proposed that increasing processing speed strengthens working retentivity, and that stronger working memory and then leads to greater cerebral competence. Since vocabulary size also predicts IQ in both adults and children (Matarazzo, 1972; Vance, West & Kutsick, 1989), an early advantage in lexical evolution could accept cascading benefits for other aspects of language learning every bit well (Bates et al., 1988). Vocabulary knowledge also serves as a foundation for later literacy (Lonigan, Burgess & Anthony, 2000), and language proficiency in preschool is predictive of bookish success (Alexander, Entwisle & Horsey, 1997). Information technology is clear from these findings that the early emerging differences we found in language proficiency between children from different SES backgrounds take serious implications for their long-term developmental trajectories.

Conclusions

In this research we found significant differences in both vocabulary learning and language processing efficiency that were already present by xviii months, with a six-month gap emerging between 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 testify that reliable differences in cognitive performance between children in lower- and higher-SES families were present past 24 months (Halle et al., 2009; Tucker-Drob, Rhemtulla, Harden, Turkheimer & Fask, 2011). What our findings add is the starting time bear witness that SES-related disparities in language skills emerge at an even earlier historic period. 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 accuracy accomplished by more advantaged children at 18 months, a six-month gap in the development of processing efficiency. Such a large disparity cannot simply be dismissed as a transitory delay, given that differences among children in trajectories of language growth established by 3 years of age tend to persist and are predictive of later school success or failure (Burchinal et al., 2011; Farkas & Beron, 2004).

Considering this difference tin be characterized as a lag in early on processing efficiency with potentially important long-term consequences, it is important to frame this finding in light 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 as embodied in middle-class practices, institutions, and values. At that time, little was known well-nigh the actual activities and practices of parents in different families, with even less scientific evidence on trajectories of cognitive and language development from infancy through childhood. Thus the term 'arrears' was used as a global indictment of parenting styles in impoverished families that were simply different from heart-class families - a well-intended but misguided attempt to assist teachers understand the difficulties minority children were experiencing in the recently desegregated school system.

At that place was obfuscating vagueness on both sides of the debate. Advocates of the deficit model proposed a causal account of the effects of children's early on life experience on after cognitive development in which both predictor and consequence variables were poorly specified. While many critics of the deficit model raised valid points urging greater respect for dissimilar cultural practices (e.grand., Heath, 1983), others countered with proposals that were simplistic and counterproductive, oftentimes reflecting a political agenda. These proposals ranged from calling a halt to research on parenting practices in minority families considering 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 non led to greater precision or insight (Gorski, 2006).

In an attempt to reframe this argument, we end with an case from diet, where cerebral consequences can exist linked to item deficits without evoking the reflexive opposition associated with arrears models in social science. Children with fe deficiency anemia (IDA) are typically depression in energy and have cognitive difficulties. For many years, the prevailing explanation for these symptoms was that parents treated lethargic children with IDA as if they were younger, which supposedly retarded their cognitive development (Pollitt, 1993). Thus differences among children in global measures of cognitive power were attributed to ill-defined problems in parenting behavior. However, recent research on IDA has led to a much more than precise specification of both causes and consequences. Studies with animal models show that iron deficiency in pre- and postnatal development disrupts the optimal course of myelination, which then reduces efficiency of neural transmission (Beard, Wiesinger, & Connor, 2003). And longitudinal enquiry measuring brain responses to auditory and visual stimuli shows that children with IDA have slower neural transmission, which is very likely to affect the efficiency of cognitive processing (Algarín, Peirano, Garrido, Pizarro, & Lozoff, 2003).

Resting on a foundation of research showing solid relations between a specific causal cistron and specific consequences, these discoveries of links betwixt atomic number 26 deficiency and long-term cognitive difficulties become valuable and highly relevant as public wellness information. If a mother was told that her child had a "cultural deficit in diet," such a broad, vague claim could only exist perceived as a perplexing insult. However, if she heard virtually new research showing that iron is absolutely critical for optimal brain development in infancy, and that salubrious brain evolution is vital to her child's success in school and in afterwards life, she might exist more than interested in learning about new ways to provide more iron in her child's diet.

While recent research on nutrition focuses on biological factors that influence early on cognitive evolution, at that place is increasing scientific evidence that experiential factors as well play a critical function in infants' early on language development – by nurturing vocabulary learning (Hart & Risley, 1995; Hoff, 2006) as well as strengthening skill in real-time language processing (Hurtado et al., 2008; Weisleder & Fernald, under review). Although the present study was non designed to explore causes of the variability we constitute among children, our results add to this literature by showing the potential benefits of early processing efficiency for vocabulary growth, and also revealing the potential cost to children with less efficient processing skills, in terms of missed opportunities for learning. From the perspective of bones research and theory in language acquisition, it is essential to investigate non just the typical developmental trajectories of children from privileged families, but also the wide range of variability that becomes apparent when children from more than diverse backgrounds are included. We address this goal hither by documenting substantial differences between infants from lower- and college-SES backgrounds that are already evident in the second year of life, using sensitive measures of early on 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 linguistic communication proficiency, and to examine the nature and timing of their influence in larger and more than diverse samples of children. From a policy perspective, the ultimate challenge is to frame these discoveries as a public wellness message (Knudsen, Heckman, Cameron, & Shonkoff, 2006), with the goal of helping caregivers sympathise the crucial role they 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 study, and to our customs partners in Northern California who enabled us to behave this study. Special thank you 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 Middle for Babe Studies at Stanford University.

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

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