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Social environments shape children's language experiences, strengthening language processing and building vocabulary


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How does language experience influence the development of language skills known to be critical for academic success? In this chapter, we build on a long history of research examining sources of variability in children’s lexical development, and offer a new perspective that focuses on the development of efficiency in real-time language processing. Examining origins of individual differences in language proficiency, we review new research showing that the amount and quality of child-directed speech in infancy contributes to the development of language processing skills, which in turn facilitate vocabulary growth. These findings reveal that early language experience can have cascading effects for later learning and school success.
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Language experience, processing and vocabulary 7/16/13 1
Social environments shape children’s language experiences,
strengthening language processing and building vocabulary
Adriana Weisleder1 and Anne Fernald2
1New York University School of Medicine
2Stanford University
Word total: 5440
Language experience, processing and vocabulary 7/16/13 2
How does language experience influence the development of language skills known
to be critical for academic success? In this chapter, we build on a long history of research
examining sources of variability in children’s lexical development, and offer a new
perspective that focuses on the development of efficiency in real-time language
processing. Examining origins of individual differences in language proficiency, we
review new research showing that the amount and quality of child-directed speech in
infancy contributes to the development of language processing skills, which in turn
facilitate vocabulary growth. These findings reveal that early language experience can
have cascading effects for later learning and school success.
Language experience, processing and vocabulary 7/16/13 3
Social environments shape children’s language experiences,
strengthening language processing and building vocabulary
The claim that talking to children is somehow important for language
development seems hard to disagree with. Yet questions about whether, how, and why
particular aspects of children’s success in language learning might depend on particular
aspects of their early experience with language are quite controversial. Over the course
of a long and influential career, Eve Clark approached these questions with original
insights that often met with strong headwinds. She began her work at a time when the
dominant theoretical perspectives focused on the quest for universal patterns in early
language growth, which were assumed to be propelled by innate grammatical knowledge
and highly constrained strategies for lexical learning. Clark (1979; 1987; 1993)
challenged some of these assumptions by showing how infants learn new words through
social and conversational interactions with attentive caregivers who provide structure for
learning, a view that emphasized an important role for experience. This theme also
resonates in more recent work, where Clark argues that identifying and elucidating
sources of the striking differences observed among children in their trajectories of
language learning – which vary substantially with differences in early experience – is as
important as searching for similarities in patterns of development (Clark, 2003; Arnon &
Clark, 2011).
Here we present research exploring how children’s early experience with
language from caregivers influences the development of language skills in infancy and
later childhood. The first section reviews research on how SES differences in speech to
children are linked to vocabulary learning. The next two sections describe the early
Language experience, processing and vocabulary 7/16/13 4
development of language processing efficiency, why it matters, and how the development
of this critical language skill varies in different SES groups. The fourth section
examines the origins of differences in early language proficiency, with new data showing
remarkable variability among low-SES families in the amount of verbal engagement with
infants. We also provide evidence that richer language experience strengthens language
processing skill, which in turn facilitates language growth. In the final section we discuss
implications of the finding that early language experience can have cascading effects for
later learning and school success. By showing how the amount and quality of child-
directed speech in infancy contribute both to language processing skill and to lexical
development over time, we affirm the value of the intuitive word-teaching strategies
Clark has illuminated in her studies of higher-SES mothers (Clark, 2010; Clark &
Estigarribia, 2011). However, our results also reveal that such supportive behaviors are
used much less frequently by mothers from lower-SES populations, and that these
differences have potentially serious consequences for their children’s language learning.
1. Sources of variability in children’s language learning
Although all typically-developing children in normal environments learn to talk,
there is substantial variability among them in rates of language learning and in the
linguistic proficiency they eventually achieve. To some extent, these differences are part
of the normal variation that exists in all human abilities. But differences in trajectories of
language learning are revealing about where children come from and what their futures
will look like, and thus are of considerable social relevance. Individual differences in
language development mirror divisions in our societies, with children from disadvantaged
families learning language more slowly, on average, than those from families higher in
Language experience, processing and vocabulary 7/16/13 5
socioeconomic status (SES) (Farkas & Beron, 2004; Hart & Risley, 1995; Huttenlocher,
Waterfall, Vasilyeva, Vevea, & Hedges, 2010; Rowe, Raudenbush, & Goldin-Meadow,
2012). Moreover, these differences have far-reaching consequences for children’s
academic and later life (Durham, Farkas, Hammer, Tomblin, & Catts, 2007; Senechal,
2006; Tramontana, Hooper, & Selzer, 1988; Walker, Greenwood, Hart, & Carta, 1994).
What is it about socioeconomic background that leads to disparities among
children in their language skills? Many experiential factors associated with living in
poverty could contribute to variability in language learning. Aspects of the physical
environment, such as sanitation, noise level, and exposure to toxins and dangerous
conditions, differ dramatically in lower- and higher-SES families (Evans, 2004). There
are also SES differences in access to adequate nutrition and health care, and in the
availability of social and psychological support (Bradley & Corwyn, 2002; Engle &
Black, 2008; Huston, Mcloyd, & Garcia Coll, 1994). These environmental factors are all
implicated in children’s physical, cognitive and social development (Bradley, Corwyn,
Burchinal, McAdoo, & Coll, 2001; Brooks-Gunn & Duncan, 1997; Evans, 2006), and
thus are likely to have consequences for children’s language outcomes.
The quality of parent-child interaction is also related to SES. Parents under
greater stress tend to be less nurturing and to respond less sensitively to their children
(Conger, McCarty, Yang, Lahey, & Kropp, 1984; McLoyd, 1990; Mesman, van
IJzendoorn, & Bakermans-Kranenburg, 2012). In addition, parents who are more affluent
and better educated tend to invest more time and resources in their children’s intellectual
development (Phillips, 2011; Ramey & Ramey, 2009), buying more books and
Language experience, processing and vocabulary 7/16/13 6
educational toys for their children, and engaging with them more often in cognitively
enhancing activities (Bradley, Corwyn, McAdoo, & Coll, 2001; Raikes et al., 2006).
One of the most significant differences in the early experiences of lower- and
higher-SES children is the amount and nature of the language they hear. Hart and Risley
(1995) estimated that by 36 months, children from high-SES families had heard 30
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). In
interactions with their children, higher SES mothers gesture more, use more diverse
vocabulary and more complex syntax, ask more questions and use fewer directives, and
respond more contingently to their infants’ vocalizations than do lower SES mothers
(Hart & Risley, 1995; Hoff-Ginsberg, 1991, 1998; Huttenlocher, Vasilyeva, Waterfall,
Vevea, & Hedges, 2007). These differences in the quantity and quality of language input
have been shown to account, at least in part, for disparities in children’s lexical and
grammatical development (Hoff, 2003; Huttenlocher, Waterfall, Vasilyeva, Vevea, &
Hedges, 2010; Rowe & Goldin-Meadow, 2009).
How is it that child-directed speech promotes children’s lexical development? One
explanation proposed for the association between exposure to more child-directed speech
and faster vocabulary growth has been that more language from caregivers provides
children with more models to learn from as they begin to build a lexicon. Children who
hear more speech from their caregivers are exposed to more different words and to more
instances of those words in a variety of contexts. Thus, they have more opportunities to
learn new word forms and more information to figure out the meanings of these words,
leading to growth in vocabulary (e.g., Hoff & Naigles, 2002). Another explanation for
Language experience, processing and vocabulary 7/16/13 7
how child-directed speech promotes lexical development emphasizes socio-pragmatic
aspects of conversation, such as joint attention and maternal responsiveness (e.g., Akhtar
& Tomasello, 2000). According to this view, children learn language in the context of
mutually understood social interactions (Clark & Clark, 1977), or joint attentional
formats (Bruner, 1983), during which they can leverage inferences about speakers’
communicative intentions to learn word meanings. Thus, children will exhibit faster
vocabulary growth when they have more opportunities to interact with an attentive
caregiver and engage in more episodes of joint attention.
In this chapter, we argue that language experience contributes to lexical
development in another way as well. By hearing words used repeatedly in a variety of
contexts, children have more opportunities for practice processing words they already
know, and for interpreting the meanings of words in relation to the linguistic and extra-
linguistic context. As a result, infants with more exposure to child-directed speech are
faster and more accurate in interpreting familiar words in real time. Recent evidence from
our lab supports the idea that practice with language strengthens children’s processing
skill, which then helps to drive vocabulary growth (Weisleder & Fernald, in press)
2. What is processing efficiency? And why does it matter?
Next we describe new ways to characterize developmental gains in verbal ability
by assessing infants’ fluency in interpreting spoken language, and show that variability in
language-processing efficiency predicts both concurrent and later language and cognitive
outcomes. Many studies of comprehension in young children have relied on offline
measures, responses made after the offset of the speech stimulus. While offline measures
can provide evidence that a child responds systematically in a way that indicates
Language experience, processing and vocabulary 7/16/13 8
understanding, they do not tap into the dynamic nature of language understanding and
thus reveal little about the child’s developing efficiency in interpreting familiar words in
fluent speech. In contrast, most studies of adult speech processing rely on online
measures that monitor the time course of the listener's response to spoken words in
relation to key points in the speech signal. Because comprehension happens quickly and
automatically, it is revealing to study the listener's interpretation during processing of the
speech signal rather than waiting until processing is complete.
Here we describe recent research using the “looking-while-listening” (LWL)
paradigm (Fernald, Zangl, Portillo, & Marchman, 2008) to monitor the time course of
comprehension by very young language learners. In the LWL procedure, infants look at
pairs of pictures while listening to speech naming one of the pictures, and their gaze
patterns are video-recorded as the sentence unfolds in time. Using this paradigm, we have
shown that speed and efficiency in infants' recognition of familiar words increase
substantially over the second year for English- and Spanish-learning children (Fernald,
Pinto, Swingley, Weinberg, & McRoberts, 1998; Hurtado, Marchman, & Fernald, 2007),
that young children make use of linguistic information at multiple levels in real-time
processing (Lew-Williams & Fernald, 2007; Swingley, Pinto, & Fernald, 1999), and that
individual differences in early processing efficiency are related to lexical and
grammatical development, both concurrently and at later ages (Fernald & Marchman,
2011; Fernald, Perfors, & Marchman, 2006; Marchman & Fernald, 2008).
What is fluency in understanding?
To follow a conversation, adults process 10-15 phonemes per second as they
continuously integrate acoustic information with linguistic and conceptual knowledge.
Language experience, processing and vocabulary 7/16/13 9
Fluent understanding of a speaker's meaning requires the ability to listen predictively,
anticipating what is coming next in the speech stream by integrating different sources of
linguistic knowledge with nonlinguistic information from the context in which the words
are spoken. Many studies show that adult listeners exploit linguistic and nonlinguistic
knowledge on multiple levels in anticipating upcoming words, and that these predictions
are made continuously and instantaneously as the speech signal unfolds (Allopenna,
Magnuson, & Tanenhaus, 1998; Altmann & Kamide, 1999).
In cross-sectional and longitudinal studies using the LWL task, we have shown
that infants make dramatic gains in receptive language skill over the second year of life,
by increasing the speed and accuracy with which they identify familiar words in spoken
language and match them with the appropriate referent (Fernald et al., 2006, 1998, 2008)
Figure 1 shows one representation of the data from a study of children at 3 different age
points; 18, 24, and 36 months (Zangl & Fernald, 2007). The x-axis shows time in ms
from the onset of the target noun; the y-axis shows the mean proportion of fixations to the
target picture. As the figure shows, older children shifted to the target picture sooner –
indicating faster processing of the familiar words – and they reached a higher asymptote
– indicating higher accuracy.
Studies have also shown that young children, like adults, are already able to make
use of potentially informative sources of contextual information, processing speech
incrementally from moment to moment (Henderson, Weighall, Brown, & Gaskell, 2013;
Swingley et al., 1999). One example illustrates incremental processing at the lexical
level, when the listener identifies a word based on partial phonetic information without
waiting to hear the whole word. A child who hears Where’s the dog? in the presence of a
Language experience, processing and vocabulary 7/16/13 10
dog and a doll is confronted with a temporary ambiguity, since dog and doll overlap
phonetically and thus are indistinguishable for the first 300 ms or so. In this situation, 24-
month-olds delayed their response by about 300 ms until disambiguating information
became available (Swingley et al., 1999), parallel to findings from studies on adult
speech processing (Allopenna et al., 1998).
A second example illustrates incremental processing at a morphosyntactic level.
In languages such as Spanish, all nouns have grammatical gender, with obligatory
gender-marking on preceding articles. To explore whether children could exploit
grammatical gender cues in real-time sentence interpretation, Lew-Williams and Fernald
(2007) tested Spanish-learning children in the LWL procedure. Children saw pairs of
pictures with names of either the same (e.g., la pelota, ‘ball’, la galleta, ‘cookie’) or
different grammatical gender (e.g., la pelota, el zapato, ‘shoe’), as they heard sentences
referring to one of the pictures (e.g., Encuentra la pelota, ‘Find the ball’). On same-
gender trials, the article could not be used to identify the referent before the noun was
spoken; on different-gender trials, the gender-marked article was potentially useful in
predicting the subsequent noun. This study showed that children were reliably faster to
identify the referent on different-gender trials, as were native Spanish-speaking adults
tested in the same procedure. Thus, young children learning Spanish as their first
language already demonstrated a processing advantage that is typical of adult native
speakers but not of second-language learners (Guillelmon & Grosjean, 2001; Grüter,
Lew-Williams & Fernald, 2012). This ability to exploit morphosyntactic information in
incremental processing reveals another dimension of children’s early emerging fluency in
Language experience, processing and vocabulary 7/16/13 11
Stability and predictive validity of online processing measures
Another central goal in our research is to characterize the causes and
consequences of variation in language proficiency among young children. We know that
at every age, there is substantial variation among children in offline measures of
vocabulary and grammar (Bates, Dale, & Thal, 1995; Fenson et al., 1994). Research
using online processing measures of language understanding can also address important
questions about differences among children: Is speed of lexical processing a stable
measure across age for individual children? And if so, how do individual differences in
early speech processing efficiency relate to later language growth, as assessed by
standardized measures of lexical and grammatical knowledge?
We first addressed these questions in a longitudinal study of 59 English-learning
infants tested four times in the LWL procedure between 15 and 25 months (Fernald et al.,
2006). Children’s efficiency in identifying familiar words increased significantly over
this period, and measures of early processing skill were moderately stable from one age
to the next. That is, children who responded more quickly on average in identifying
familiar words at earlier ages also responded relatively more quickly at later ages.
Parental reports of vocabulary and grammar on the MacArthur-Bates Communicative
Development Inventory (CDI; Fenson et al., 2006) were also gathered across the second
year, enabling us to explore the relation of online measures of speech processing skill to
more traditional measures of linguistic development. Speed and accuracy in speech
processing at 25 months were robustly related to lexical and grammatical development
across a range of measures from 12 to 25 months, and those children who had faster RTs
at 25 months also showed more accelerated vocabulary growth across the second year.
Language experience, processing and vocabulary 7/16/13 12
We have recently replicated this finding in a prospective longitudinal study, showing that
early processing efficiency predicts vocabulary growth in a larger sample of typically-
developing children and in children who showed delays in the onset of productive
vocabulary (Fernald & Marchman, 2011).
Given the stability and short-term predictive validity of these online measures in
the infancy period, the next question was to what extent individual differences in early
processing efficiency predict long-term language and cognitive outcomes. In a follow-up
study, 30 children from the original Fernald et al. (2006) longitudinal sample were tested
at 8 years of age on two standardized assessments of cognitive and language skills
(Marchman & Fernald, 2008). Multiple regression analyses were used to evaluate the
predictive validity of processing speed and expressive vocabulary in infancy, in relation
to school-age outcomes. Vocabulary size at 25 months was correlated with later cognitive
and language skills, but knowing mean RT in addition to CDI doubled the predictive
power, accounting for 58% of the variance in working memory at 8 years. This
longitudinal study was the first to reveal the long-term predictive validity of early
measures of real-time processing efficiency, showing that individual differences in
fluency of understanding at two years predict children’s cognitive and language outcomes
in later childhood.
3. SES-differences in language processing skill
In the research described above, language-processing skill was studied in English-
learning children from families high in SES (Fernald et al., 2006; Marchman & Fernald,
2008) as well as in Spanish-learning children from families low in SES (Hurtado et al.,
2007; Hurtado, Marchman, & Fernald, 2008). These studies revealed age-related
Language experience, processing and vocabulary 7/16/13 13
increases in processing efficiency in both populations, with comparable links between
processing efficiency and vocabulary. However, this research did not allow us to
determine whether variation in language-processing skill was related to socio-economic
differences, given that SES was confounded with both language background and ethnicity
in the families that participated in these studies.
To examine the influence of SES on the development of language-processing
skill, we needed to recruit English-speaking families from a much broader demographic
range than is typical of most psychological research (Arnett, 2008; Fernald, 2010). With
the goal of extending our research beyond the convenience sample of high-SES families
available as participants at our university-campus lab (Site 1), we outfitted a mobile lab
to enable us to conduct research in areas where it is possible to recruit equivalent
numbers of lower- and middle-SES English-speaking families. Site 2 is in an urban area
comparable in population size to the area in which Site 1 is located. However, these two
regions differ substantially in median family income, cost-of-living, and percentage of
children living in poverty, allowing us to include a much more diverse sample of English-
learning children in our research.
In the first study to examine SES differences in the development of processing
efficiency and vocabulary, Fernald, Marchman, and Weisleder (2013) recruited 48
children from monolingual English-speaking families in which maternal education
ranged from less than a high school degree to post-BA training. Based on the
Hollingshead Four Factor Index of Socioeconomic Status (HI; Hollingshead, 1975),
families were divided into lower- (n = 23) and higher-SES (n = 25) groups. Of the
Language experience, processing and vocabulary 7/16/13 14
children from families in the higher-SES group, 19 were recruited at Site 1 and six at Site
2; of those in the lower-SES group, one was recruited at Site 1 and 22 at Site 2.
In both groups we found common developmental patterns, with increases in
vocabulary and in language-processing skill from 18 to 24 months. Older children had
larger vocabularies, and were more likely than younger children to interpret incoming
speech incrementally, fixating the target picture as soon as they had enough information
to identify the referent. In both groups we also found reliable links between skill in early
language processing and vocabulary development, replicating previous studies (Fernald
et al., 2006; Fernald & Marchman, 2011). But the differences between higher- and
lower-SES children in language-processing skill and vocabulary were striking. By the
age of 18 months, children from higher-SES families were faster and more accurate in
identifying referents of familiar words than were children from lower-SES families. As
shown in Figure 2, mean accuracy for 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 by 24 months. Similar patterns
were observed for reaction time and vocabulary. Thus, these findings revealed the
equivalent of a 6-month gap in processing efficiency between higher- and lower-SES
children, which was already well established by the age of 24 months.
4. Where do these differences come from?
What explains these disparities in children’s language-processing skills? Many
studies described earlier have shown that variability in lexical and grammatical
development is linked to differences in children’s exposure to language from caregivers.
But is variation in early language experience also related to individual differences in
Language experience, processing and vocabulary 7/16/13 15
children’s real-time language processing? Two different studies from our lab shed light
on this question.
In the first study, Hurtado, Marchman, and Fernald (2008) recorded 27 Latina
mothers interacting with their 18-month-old infants during a short play session in the
laboratory. Most of the mothers were native Spanish speakers with limited English
proficiency who had recently immigrated from Mexico. At both 18 and 24 months, the
children were assessed in the LWL procedure, and mothers completed a Spanish-
language CDI. Hurtado et al. then examined links between features of maternal talk and
children’s vocabulary size and speech processing efficiency. Measures of mothers’
speech included total number of utterances, word tokens, word types, and mean length of
Consistent with previous findings with English-learning children, the quantity and
quality of maternal speech were associated with children’s vocabulary outcomes. Infants
who heard more, more varied, and more complex speech from their mother at 18 months
had larger vocabularies at 24 months, even when controlling for early vocabulary
differences. Vocabulary size was also related to speech-processing efficiency, as in
previous studies with English-learning children (Fernald et al. 2006); thus 18-month-old
children who were faster to identify familiar words in fluent speech made greater gains in
vocabulary from 18 to 24 months. But the important new finding from this study was
that those children whose mothers spoke more words and used more complex utterances
during the play session at 18 months were significantly faster in online comprehension at
24 months, as compared to those who had heard less maternal talk – even after
controlling for differences in mean RT at 18 months. This research provided the first
Language experience, processing and vocabulary 7/16/13 16
evidence that variability in maternal speech predicts children’s efficiency in language
In a more recent study, we extended this research in three important ways
(Weisleder & Fernald, in press): First, rather than relying on short samples of mothers’
speech in dyadic interactions with infants, we collected more extensive and representative
recordings of infants’ language environments during a 10-hour day at home, capturing
children’s interactions with different family members in diverse settings and activities.
Second, we used unobtrusive technology to record families in their natural home
environments, minimizing artifacts introduced by the presence of an observer or by
parents’ reactions to an unfamiliar laboratory setting. And third, by focusing on a
relatively homogeneous group of low-SES, Latino families, we examined variability in
the daily language experiences of children from similar socioeconomic and cultural
backgrounds, focusing on within-group rather than between-group differences.
By examining how measures of spontaneous caregiver speech at home relate to
measures of both language processing and expressive vocabulary, we could address three
sets of questions: 1) How much do children’s daily language experiences vary within this
population of low-SES Latino families? 2) How is children’s exposure to speech related
to differences in their vocabulary development? Is vocabulary predicted only by adult
speech that is directed to the child, or is speech overheard by the child also linked to
vocabulary outcomes? 3) Does early language experience explain differences in
children’s language-processing skills? And if so, do differences in processing skill help
explain the link between language experience and vocabulary development?
Language experience, processing and vocabulary 7/16/13 17
Parents in the 29 participating families were all native Spanish speakers. Most had
not completed high school, and the majority reported a yearly family income below the
federal poverty line. To measure the amount of adult speech their children were routinely
exposed to, audio-recordings were made during a typical day at home when the child was
19 months old. These audio-recordings were made using a LENATM digital language
processor (DLP;, a digital recorder that is placed in the
chest pocket of specialized clothing worn by the child and is designed to record the audio
environment surrounding the child for up to 16 hours (Ford, Baer, Xu, Yapanel, & Gray,
2009). This allowed us to unobtrusively collect whole-day recordings of children’s
natural language environments. At 19 and 24 months, children’s efficiency in online
comprehension was assessed in the LWL procedure and mothers completed a Spanish-
language CDI.
The recordings were first processed by LENA (Language ENvironment Analysis)
software, which provides reliable estimates of different components of the infant’s
language environment, including the number of adult word tokens identified as
potentially accessible to the child (Oller et al., 2010; Xu et al., 2008). Native Spanish-
speaking coders then listened to each of the recordings in order to differentiate between
speech directed to the target child and speech directed to other adults or children nearby.
Each 5-min segment of speech was classified as predominantly “child-directed” or
“overheard” based on the content of the speech. When speech was directed to a group of
people that included the target child, the segment was classified as “child-directed”.
However, speech that was clearly directed to a child other than the target child was
classified as “overheard”. The number of adult word tokens in segments classified as
Language experience, processing and vocabulary 7/16/13 18
child-directed, divided by the duration of the recording, served as our measure of “child-
directed speech”. The number of adult word tokens in segments classified as overheard,
divided by the duration of the recording, served as our measure of “overheard speech.”1
We found striking variability among families in the total amount of adult speech
accessible to children, which ranged from almost 29,000 adult words to fewer than 2,000
words over a 10-hour day, as shown in Figure 3. These differences were even more
extreme when we included only child-directed speech. In one family, caregivers spoke
more than 12,000 words to the infant, while in another the infant heard only 670 words of
child-directed speech over an entire day – an 18-fold difference. This shows that although
differences in the quantity and quality of caregiver speech are consistently linked to
factors related to SES, there is also considerable variability in children’s language
experiences within a social class.
Our next question was whether differences in child-directed speech were related
to differences in children’s lexical development. Consistent with previous studies (Hoff,
2003; Hurtado et al., 2008), children who heard more child-directed speech at 19 months
had larger vocabularies at 24 months, showing that even among families similar in SES
and cultural background, differences in amount of caregiver speech are related to
children’s lexical development. However, differences in exposure to overheard speech
were not related to vocabulary size, consistent with recent studies of children in middle-
class English-speaking families in the U.S. (Shneidman, Arroyo, Levine, & Goldin-
1 It is important to keep in mind that language “input” does not necessarily imply language “uptake” by the
child. In an audiorecording it is fundamentally impossible to know whether a child is actually paying
attention to the speaker, regardless of whether the speech is directed to the child or to someone else present.
Thus, the category of “child-directed speech” designates all speech that is potentially accessible and
directed to the target child, while the category of “overheard speech” designates all speech that is
potentially accessible to the target child but not directed to them.
Language experience, processing and vocabulary 7/16/13 19
Meadow, 2012) and in Yucatec Mayan families (Shneidman & Goldin-Meadow, 2012).
These results provide compelling evidence that language spoken directly to the child is
more supportive of early lexical development than speech simply overheard by the child.
There are several reasons why child-directed speech might be more effective than
overheard speech in fostering children’s early lexical development. First, prosodic
properties of infant-directed speech (IDS) may play a role in engaging infants’ attention,
which is critical for learning in natural settings. A number of experiments have shown
that very young infants prefer to listen to infant-directed speech as compared to adult-
directed speech (Cooper & Aslin, 1990; Fernald, 1985, 1992; Fernald & Kuhl, 1987), and
that phonetic information is more clearly specified in IDS (Kuhl et al., 1997). Speech
directed to children is also more likely to occur in contexts that are relevant to the child’s
attentional focus than overheard speech, thereby facilitating word learning. Experimental
studies have shown that it is easier for children to learn new labels when the speaker
follows in on the infant’s focus of attention (Tomasello & Todd, 1983), something that
middle-class American parents often do when introducing new words to their children
(Clark & Estigarribia, 2011; Clark, 2010). Observational studies have also shown that
children who spend more time in joint attention with their mothers have more advanced
vocabulary development than children who spend less time in episodes of joint attention
(Akhtar, Dunham, & Dunham, 1991; Tomasello & Farrar, 1986). Finally, speech directed
to children typically uses simpler syntax, fewer unique word types, and contains more
single-word utterances than speech directed to adults (Phillips, 1973; Soderstrom, 2007).
This may be helpful because the meaning of specific referents may be clearer to children
when presented in simple and familiar syntactic frames (Cameron-Faulkner, Lieven, &
Language experience, processing and vocabulary 7/16/13 20
Tomasello, 2003). Indeed, in some studies, these kinds of simplifications have been
shown to facilitate children’s early lexical development (Brent & Siskind, 2001; Furrow,
Nelson, & Benedict, 1979; Murray, Johnson, & Peters, 1990).
Finally, we used mediation analysis to examine whether processing skill at 19
months helped to explain the link between child-directed speech and 24-month
vocabulary (while controlling for maternal education, recording length, and infant
vocalizations at 19 months). The scatter plots in Fig. 4 illustrate the first three steps of
the mediation analysis: 1) Exposure to child-directed speech at 19 months predicted
vocabulary at 24 months, 2) Exposure to child-directed speech also predicted processing
efficiency at 19 months, and 3) 19-month processing efficiency predicted 24-month
vocabulary, even when controlling for child-directed speech. Finally, as shown at the
bottom of Figure 4, the path coefficient between the predictor variable (child-directed
speech) and the outcome variable (vocabulary) was significantly reduced when the
mediator variable (processing efficiency) was included in the model. This final step
confirms that the mediation was significant, showing that 19-month processing efficiency
mediated the link between child-directed speech and 24-month vocabulary.
These results suggest that a critical factor in the path from early language
experience to later vocabulary knowledge is the influence of language exposure on
infants’ speech-processing skill. Infants who hear more talk have more opportunities to
interpret language, and to exercise skills such as segmenting speech and accessing lexical
representations that are vital to word learning (Saffran, Newport, & Aslin, 1996;
Gershkoff-Stowe, 2002). As a result, infants with more exposure to child-directed speech
Language experience, processing and vocabulary 7/16/13 21
are faster and more accurate to orient to familiar words in real time, enabling them to
learn new words more quickly and facilitating rapid vocabulary growth.
5. Conclusions
The studies reviewed here build on a long history of research examining how
language experience supports language development. By using gradient experimental
measures of efficiency in moment-to-moment processing that are robustly related to a
range of long-term language and cognitive outcomes, we have moved a step closer to
understanding the mechanisms underlying the association between early language
experience and the development of verbal proficiency. One central insight emerging
from this research is that early language experience influences language development
through multiple and mutually influential pathways. Previous studies have identified
features of parent-child interactions that provide important supports for language
learning, including semantic, syntactic, and pragmatic cues to word meaning (Clark,
2010; Clark & Estigarribia, 2011; Frank, Tenenbaum, & Fernald, 2012; Goodman,
McDonough, & Brown, 1998; Hoff & Naigles, 2002). What the current studies contribute
is evidence that everyday verbal interactions with caregivers also provide opportunities
for exercise in interpreting language, enabling children to practice skills such as
segmenting speech, accessing lexical representations, and monitoring cues to word
meaning. In this way, exposure to child-directed speech helps children become faster and
more accurate in identifying familiar words in increasingly complex contexts, sharpening
processing skills that enable faster language growth.
However, the story doesn’t end there. New results affirming that verbal
engagement with young children is beneficial for language learning in multiple ways are
Language experience, processing and vocabulary 7/16/13 22
certainly consistent with demonstrations of how middle-class parents provide valuable
scaffolding for early word learning. But because our work included a much broader
sample of young children than is typically represented in laboratory studies of language
development, the results force us to confront another implication of these classic studies –
namely that a relative lack of parental support for word learning could potentially have
adverse consequences. What we found was that the amount and nature of parental
support for language learning varied significantly among families even within a low-SES
sample, and that these differences were linked to early emerging and consequential
differences in both processing efficiency and lexical development.
Numerous studies have shown that variability in both processing speed and
vocabulary could have long-term developmental consequences. Since vocabulary size
predicts IQ in both adults and children (Matarazzo, 1972; Vance, West & Kutsick, 1989),
an early advantage in lexical development could have cascading benefits for other aspects
of language learning as well (Bates et al., 1988). Vocabulary knowledge also provides a
foundation for later literacy (Lonigan, Burgess & Anthony, 2000), and preschool
language skills are predictive of academic success (Alexander, Entwisle & Horsey,
1997). These findings make it clear that the early emerging differences we found in
language proficiency between children from different SES backgrounds have potentially
serious implications for their future developmental trajectories. However, these findings
also suggest that offering young language learners more opportunities for verbal
interaction has the potential to strengthen critical processing skills, which in turn would
enable more efficient learning. In our ongoing research, an important goal is to show that
interventions designed to increase parents’ verbal engagement with their infants could
Language experience, processing and vocabulary 7/16/13 23
change the course of early vocabulary growth and improve long-term outcomes for
disadvantaged children.
Language experience, processing and vocabulary 7/16/13 24
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Figure captions
Figure 1. Mean proportion of trials on which children in three age groups are looking at
the target picture at each 33-msec interval as the stimulus sentence unfolds.
The dashed vertical line represents target noun offset; error bars represent SEs
over participants.
Figure 2. Mean proportion of looking to the target as a function of time in ms from
noun onset for Lower- and Higher-SES children. Open squares/circles
represent the time course of correct looking at 18 months; filled
squares/circles represent the time course of looking in the same children at 24
months. Error bars represent SE of the mean over participants. Adapted from
Fernald et al., 2012.
Figure 3. Variability across 29 families in amount of adult speech during a typical day
at home. The height of each bar indicates the total number of adult words
spoken near the target child in one family, calculated by averaging the word
counts per waking hour and extrapolating to a 10-hr day. The proportion of
words that was child-directed speech is indicated in gray, with overheard
speech in white. Adapted from Weisleder & Fernald (in press).
Figure 4. The scatter plots show zero-order correlations between (a) child-directed
speech (CDS) at home and vocabulary size at 24 mos, (b) CDS and processing
efficiency at 19 mos, and (c) processing efficiency at 19 mos and vocabulary
at 24 mos. The bottom portion of the figure (d) represents the analysis
showing that processing efficiency mediates the relation between CDS and
24-mo vocabulary. Adapted from Weisleder & Fernald (in press).
Language experience, processing and vocabulary 7/16/13 32
Figure 1
36 mos
24 mos
18 mos
Language experience, processing and vocabulary 7/16/13 33
Figure 2
Language experience, processing and vocabulary 7/16/13 34
Figure 3
Language experience, processing and vocabulary 7/16/13 35
Figure 4
(19 mos)
(24 mos)
(19 mos)
! = .76* ! = 6.85*
! = 12.61**
! = 7.41
*p<.05, **p<.01
!" #" $"
... Specifically, we were interested in whether parent speech that intersperses multiple clusters of talk about an object over time in a single interaction may constitute a particularly effective training schedule. Such a training schedule provides close clustered repetitions of words in time, which may help learners resolve ambiguity of reference in the moment and help support initial encoding and short-term retention of word-object mappings (Kachergis, Yu, & Shiffrin, 2009;Suanda et al., 2016b;Vlach & Johnson, 2013;Weisleder & Fernald, 2014). Such a schedule also provides delays between clustered repetitions, which may support longer-term retention of those mappings (Atkinson & Shiffrin, 1968;Benjamin & Tullis, 2010;Brainerd & Reyna, 2002;Glenberg, 1979;Haebig et al., 2019;Landauer, 1969;Melton, 1970;Vlach et al., 2012;Wickelgren, 1970). ...
... Those attentional and memory processes, in turn, may have the properties they do because human behaviors in generaland many natural phenomena in the worldhave a bursty temporal structure. More specifically for toddler word learning, bursty talk combines repeated references to the same object, which helps word learners resolve ambiguity of reference in the moment and promotes encoding and short-term retention of word-object mappings (Kachergis et al., 2009;Suanda et al., 2016b;Vlach & Johnson, 2013;Weisleder & Fernald, 2014), with spacing of these repetitions, which promotes longer-term retention of those mappings (Atkinson & Shiffrin, 1968;Benjamin & Tullis, 2010;Brainerd & Reyna, 2002;Glenberg, 1979;Haebig et al., 2019;Landauer, 1969;Melton, 1970;Vlach et al., 2012;Wickelgren, 1970). ...
Toddlers learn words in the context of speech from adult social partners. The present studies quantitatively describe the temporal context of parent speech to toddlers about objects in individual real-world interactions. We show that at the temporal scale of a single play episode, parent talk to toddlers about individual objects is predominantly, but not always, clustered. Clustered speech is characterized by repeated references to the same object close in time, interspersed with lulls in speech about the object. Clustered temporal speech patterns mirror temporal patterns observed at longer timescales, and persisted regardless of play context. Moreover, clustered speech about individual novel objects predicted toddlers' learning of those objects' novel names. Clustered talk may be optimal for toddlers' word learning because it exploits domain-general principles of human memory and attention, principles that may have evolved precisely because of the clustered structure of natural events important to humans, including human behavior.
... Increased financial capital may also allow parents to engage with their children to a greater extent. Past studies have suggested that infants from higher-SES families hear more infant-directed speech than those from lower-SES families (Weisleder & Fernald, 2014). In addition to the amount of input, those who are from higher-SES environments also enjoy greater quality of communication: within lower-SES families, responsive and sensitive caregiving was shown to protect against further risk for communication and language development (Hirsh-Pasek et al., 2015). ...
Infants undergo fundamental shifts in perception that are reported to be critical for language acquisition. In particular, infants’ perception of native and non‐native sounds begins to align with the properties of their native sound system. Thus far, empirical evidence for this transition – perceptual narrowing – has drawn from socio‐economically and linguistically narrow populations from limited world regions. In this study, infants were sampled across diverse socio‐economic strata and linguistic development in Singapore. One hundred and 16 infants were tested on their ability to discriminate both a native phonetic contrast (/ba/ versus /da/) and a non‐native Hindi contrast (/ta/ versus /ʈa). Infants ranged in age from 6 to 12 months. Associations between age and discrimination varied by contrast type. Results demonstrated that infants’ native sensitivities were positively predicted by family SES, whereas non‐native sensitivities were not. Maternal socio‐economic factors uniquely predicted native language sensitivity. Findings suggest that infants’ sensitivity to native sound contrasts is influenced by their family socio‐economic status. Research Highlights We investigated effects of socio‐economic status on infant speech perception. Infants were tested on native and non‐native speech discrimination. Socio‐economic status predicted native speech discrimination. Maternal occupation was a key predictor of native speech discrimination.
... To summarize, we sought to identify predictors of vocabulary size in a multilingual setting with a focus on SES and the home literacy envi- Fernald et al., 2013;Weisleder & Fernald, 2014). Of the different components of SES, from studies predominantly published in Western settings, there is also abundant evidence that parental education (most notably, maternal education) is a profoundly influential factor in predicting infants' language scores (Hoff, 2013). ...
It is well attested that high socio‐economic status (SES) is associated with larger vocabulary size estimates in young children. This has led to growing interest in identifying associations and mechanisms that may contribute to this relationship. In this study, parent‐child reading behaviors were investigated in relation to vocabulary size in a large‐scale study of linguistically and socio‐economically diverse families. This study sampled 902 infants in Singapore, a multilingual society. Both single‐language (dominant and non‐dominant) and dual‐language vocabulary size estimates were obtained and related to family SES, demographic details, and home literacy activities. Results demonstrated that both single‐language (dominant and non‐dominant) and dual‐language infant vocabulary size estimates were predicted by parental education levels. Further analyses revealed that parent‐child book reading activities mediated the relationship between parental education and infant vocabulary size. Findings suggest that shared book reading may narrow effects of socio‐economic disparities on early language development. Research Highlights Socio‐economic status (SES) was examined in relation to infant vocabulary size in a linguistically and socio‐economically diverse setting. Mediating effects of the home literacy environment on infant vocabulary size were measured. Socio‐economic factors, notably parental education, had both direct and indirect effects on vocabulary size. The home literacy environment mediated effects of SES on infant vocabulary size.
... These interactions are sources of whatever the children need to learn, as they provide opportunities for them to recognize, internalize, store, and use the words they hear. Nevertheless, in learning the words, preschool-aged children also learn how to correctly use them according to the grammar of the language they are exposed to (Davis-Kean et al., 2016;Tabors et al., 2001;Weisleder & Fernald, 2014). Participating in such interactions, preschool-aged children start to use specific registers and adapt their voice and intonation according to the role they played in the interactions. ...
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Language ability develops greatly during preschool age. Triggered by the high curiosity that goes hand in hand with the exposures to others around them, preschool-aged children show great efforts to create a collection of vocabulary to help them learn and use language in real contexts. This research aims to identify the thematic contents of preschool-aged children’s utterances and explain the categories of these thematic contents to shape their understanding of the surrounding world. To answer these objectives, both qualitative and quantitative data were used. The qualitative data were the utterances of preschool-aged children when participating in conversations, while the quantitative data were the frequency of occurrence of each thematic content, which is used to support the qualitative interpretation. The data were collected during classroom sessions in two preschools in Yogyakarta, Indonesia for a one-week period. The participants were 29 preschool-aged children, whose age ranges from 3 to 5 years old. Audiovisual recordings, field notes, datasheets, and ELAN 5.5. and FLEx 8 software were the instruments for data collection and analysis. The results show that there are two main thematic contents expressed by these preschool-aged children, i.e., objects and people. These thematic contents can be detailed into 9 categories of objects and 4 categories of people. These support the overall interpretation revealing the picture of the world as perceived by the children. In general, through the thematic contents of their utterances, preschool-aged children try to build a complete understanding of the world they live in and these thematic contents also serve as the media for understanding the stance of their peers and teachers in a conversation.Keywords: preschool-aged children; thematic contents; utterances
... Di erences in the quantity and quality of parents' talk with infants has been associated with children's vocabulary learning and academic success (e.g. Hart and Risley, 1995;Pan et al., 2005;Weisleder and Fernald, 2014), while di erences in children's spoken word recognition and phonological discrimination can predict early vocabulary growth (e.g. Tsao, Liu and Kuhl, 2004;Singh et al., 2012). ...
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Foundations of Academic Knowledge: This chapter assesses the acquisition of academic knowledge and skills in domains including literacy, numeracy, sciences, arts and physical education. It examines how learning trajectories arise from complex interactions between individual brain development and sociocultural environments. Teaching literacy and numeracy to all students is a goal of most school systems. While there are some fundamental skills children should grasp to succeed in these domains, the best way to support each student's learning varies depending on their individual development, language, culture and prior knowledge. Here we explore considerations for instruction and assessment in different academic domains. To accommodate the ourishing of all children, exibility must be built into education systems, which need to acknowledge the diverse ways in which children can progress through learning trajectories and demonstrate their knowledge.
... Di erences in the quantity and quality of parents' talk with infants has been associated with children's vocabulary learning and academic success (e.g. Hart and Risley, 1995;Pan et al., 2005;Weisleder and Fernald, 2014), while di erences in children's spoken word recognition and phonological discrimination can predict early vocabulary growth (e.g. Tsao, Liu and Kuhl, 2004;Singh et al., 2012). ...
The overall goal of the ISEE Assessment is to pool multi-disciplinary expertise on educational systems and reforms from a range of stakeholders in an open and inclusive manner, and to undertake a scientifically robust and evidence based assessment that can inform education policy-making at all levels and on all scales. Its aim is not to be policy prescriptive but to provide policy relevant information and recommendations to improve education systems and the way we organize learning in formal and non-formal settings. It is also meant to identify information gaps and priorities for future research in the field of education.
... Differences in the quantity and quality of parents' talk with infants has been associated with children's vocabulary learning and academic success (e.g. Hart and Risley, 1995;Pan et al., 2005;Weisleder and Fernald, 2014), while differences in children's spoken word recognition and phonological discrimination can predict early vocabulary growth (e.g. Tsao, Liu and Kuhl, 2004;Singh et al., 2012). ...
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The goal of this chapter is to assess research that can inform understandings of places and spaces of learning.The chapter assesses evidence across three types of learning spaces: built spaces, digital spaces, and natural spaces. It looks at the role of these different kinds of spaces for learning, attainment, interpersonal relationships, skills development, wellbeing and behaviours ‒ across four pillars of learning to know, to be, to do and to live together. The chapter also explores how learning spaces can be actively shaped, felt and understood through practices and policies that occur within and around them.
... Differences in the quantity and quality of parents' talk with infants has been associated with children's vocabulary learning and academic success (e.g. Hart and Risley, 1995;Pan et al., 2005;Weisleder and Fernald, 2014), while differences in children's spoken word recognition and phonological discrimination can predict early vocabulary growth (e.g. Tsao, Liu and Kuhl, 2004;Singh et al., 2012). ...
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This chapter assesses ways to identify and support children with learning disabilities. Learning disabilities affect many students and are seldom attributable to a single cause. They arise through complex interactions between biological and environmental factors within individual developmental trajectories. Early identification of children at risk for learning disabilities as well as adequate identification of children with learning disabilities are important for ensuring that children have access to the supports they need in order to reach their full potential. Here, we discuss identifying children’s learning needs and providing educational support. Although many school systems recognize the need to provide inclusive education to support all learners, more work is needed to raise awareness and enable adequate evidence-based early identification of children with learning disabilities and support their learning trajectories and instructional needs inside and outside of the classroom. It is also fundamental to acknowledge the importance of research on diverse populations that could inform identification and support in various countries and socio-cultural contexts.
... does not necessarily represent reliable information about quantity of exposure, as studies have shown that adults vary enormously in the amount of speech they produce when interacting with children (de Houwer, 2014;Weisleder & Fernald;. What is more, it must be considered that not all input becomes intake, that is, in order for children to actually learn from their input, this must be child-directed speech rather than mere exposure to the language (Carroll, 2007). ...
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ABSTRACT Studies assessing the grammatical knowledge of speakers of Spanish as a heritage language have largely focused on the Spanish subjunctive mood and have concluded, almost unanimously, that heritage speakers’ knowledge of the Spanish subjunctive is non-native-like and subject to incomplete acquisition. However, there is also evidence that while different, heritage speakers’ linguistic knowledge is by no means deficient. The goal of the present dissertation is to achieve a holistic understanding of the nature of grammars of heritage speakers and to contribute to a theory of processing in heritage language contexts that has greater explanatory adequacy. To this end, this dissertation examines knowledge of the Spanish subjunctive in heritage speakers who live in a long-standing bilingual community in Albuquerque, New Mexico, in comparison to a group of Spanish-dominant bilinguals born in Mexico. The dissertation sets out to provide (1) an evidence-based characterization of heritage speakers by using a sociolinguistic questionnaire which, along with PCA, examined the language-experience related factors that best explain the variability in the processing of the subjunctive mood in this population; and (2) an examination of heritage speakers’ and Spanish-dominant bilinguals’ processing of the Spanish subjunctive during online comprehension and production by means of psycholinguistic experiments that integrated corpus data into their design. Results indicated that, both in comprehension and production, the current group of heritage speakers was sensitive to the lexical and structural conditioning of mood selection, and that the performance of heritage speakers and Spanish-dominant bilinguals converged on the same results and trends. All participants showed nuanced knowledge of the morphosyntactic factors that modulate the conditioning of mood selection, as suggested by the fact that linguistic factors such as frequency and proficiency also modulated their sensitivity. In addition, based on the PCA conducted, the role of three sociolinguistic variables was examined: use of the heritage language, language entropy, and identification with the heritage language. As predicted, results indicated that sensitivity to the lexical and structural conditioning of mood selection was greater for heritage speakers who: (1) used the heritage language more often on average, (2) used the heritage language in more diverse contexts, and (3) felt more identified with the heritage language. The findings highlight that factors such as the community examined and the ecological validity of the materials used are crucial. In addition, they underscore the importance of triangulating both comprehension and production experimental data, and employing multiple explanatory variables for a more comprehensive approach to complex and highly variable systems such as heritage grammars.
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The "looking-while-listening" methodology uses real-time measures of the time course of young children's gaze patterns in response to speech. This procedure is low in task demands and does not require automated eye-tracking technology, similar to "preferential looking" procedures. However, the looking-while-listening methodology differs critically from preferential-looking procedures in the methods used for data reduction and analysis, yielding high-resolution measures of speech processing from moment to moment, rather than relying on summary measures of looking preference. Because children's gaze patterns are time-locked to the speech signal and coded frame-by-frame, response latencies can be coded with millisecond precision on multiple trials over multiple items, based on data from thousands of frames in each experiment. The meticulous procedures required in the collection, reduction, and multiple levels of analysis of such detailed data are demanding, but well worth the effort, revealing a dynamic and nuanced picture of young children's developing skill in finding meaning in spoken language. On-line methods in children's language processing, John Benjamins: Amsterdam (pp. 97-135.).
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How do children infer the meanings of their first words? Even in infant-directed speech, object nouns are often used in complex contexts with many possible referents and in sentences with many other words. Previous work has argued that children can learn word meanings via cross-situational observation of correlations between words and their referents. While cross-situational associations can sometimes be informative, social cues to what a speaker is talking about can provide a powerful shortcut to word meaning. The current study takes steps toward quantifying the informativeness of cues that signal speakers' chosen referent, including their eye-gaze, the position of their hands, and the referents of their previous utterances. We present results based on a hand-annotated corpus of 24 videos of child-caregiver play sessions with children from 6 to 18 months old, which we make available to researchers interested in similar issues. Our analyses suggest that although they can be more useful than cross-situational information in some contexts, social and discourse information must also be combined probabilistically to be effective in determining reference.
Without words, children can't talk about people, places, things, actions, relations, or states, and they have no grammatical rules. Without words, there would be no sound structure, no word structure, and no syntax. The lexicon is central in language, and in language acquisition. Eve Clark argues for this centrality and for the general principles of conventionality and contrast at the core of language acquisition. She looks at the hypotheses children draw on about possible word meanings, and how they map their meanings on to forms. The book is unusual in dealing with data from a wide variety of languages, in its emphasis on the general principles children rely on as they analyse complex word forms, and in the broad perspective it takes on lexical acquisition.
Abstract— Most studies on parental sensitivity are based on Western samples, and the cross‐cultural applicability of this construct has been subject to debate. This article reports on a systematic literature review on observational studies of parental sensitivity in ethnic minority families with young children. It shows that parental sensitivity is generally lower in ethnic minority families than in majority families. The evidence suggests that the main cause for this difference is family stress due to socioeconomic disadvantage. The review found little evidence for cultural explanations. Most importantly, the review shows that parental sensitivity is related to positive child development in ethnic minority families. Interventions attempting to improve ethnic minority children’s well‐being should focus on both reducing family stress and enhancing parental sensitivity.