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. Author manuscript; available in PMC: 2017 Sep 1.
Published in final edited form as: Child Dev. 2016 May 25;87(5):1529–1537. doi: 10.1111/cdev.12553

Preschoolers’ preference for syntactic complexity varies by socioeconomic status

Kathleen H Corriveau 1, Katelyn Kurkul 1, Sudha Arunachalam 1
PMCID: PMC5042811  NIHMSID: NIHMS777303  PMID: 27223584

Abstract

Two experiments investigated whether 4- and 5-year-old children choose to learn from informants who use more complex syntax (passive voice) over informants using more simple syntax (active voice). In Experiment 1 (N=30), children viewed one informant who consistently used the passive voice, and another who used active voice. When learning novel words from the two informants, children were more likely to endorse information from the passive informant. Experiment 2 (N=32) explored whether preference for the passive informant varied by socioeconomic status (SES; eligibility for free/reduced lunch). Whereas higher-SES children selectively preferred the passive informant, lower-SES children preferred the active informant. Explanations are discussed for why socioeconomic status might moderate children’s sensitivity to syntactic complexity when choosing from whom to learn.

Research on children’s learning suggests that by the time children reach preschool, they rely on two kinds of cues to determine from whom to learn. First, preschoolers monitor an informant’s previous accuracy, selectively preferring to learn from accurate over inaccurate sources (e.g., Birch et al., 2008; Corriveau & Harris, 2009a,b; Corriveau, Meints & Harris, 2009; Jaswal & Neely, 2006; Koenig, Clement & Harris, 2004; Koenig & Harris, 2005; Pasquini, Corriveau, Koenig & Harris, 2007; Sobel & Macris, 2012). Second, preschoolers monitor social group affiliation, preferring to learn from members of their cultural in-group (Corriveau & Harris, 2009a; Corriveau et al., 2009; Harris & Corriveau, 2011; Kinzler, Corriveau & Harris, 2011; see Harris, 2012 for review). When children have information about both cues, prior accuracy trumps social characteristics such as age (Jaswal & Neely, 2006), familiarity (Corriveau & Harris, 2009a), and accent (Corriveau, Kinzler, & Harris, 2013; although see Reyes-Jacquez & Echols, 2013).

We propose that children selectively learn from accurate informants because they view accuracy as a marker of competence (Harris & Corriveau, 2011; Sobel & Kushnir, 2012). That is, children expect accurate informants to be more competent in similar domains than inaccurate informants. Research requiring children to make inferences across domains supports this hypothesis (e.g., labels to game rules, Rakoczy et al., 2009; labels to functions, Koenig & Harris, 2005; object properties to labels, Sobel & Corriveau, 2010). However, we do not know what other informant properties children view as markers of competence. Children are unlikely to encounter opportunities to learn from accurate over inaccurate informants, but rather, may be faced with several accurate informants who vary in other properties signaling different levels of competence. Here, we ask if children track markers of informant competence beyond accuracy.

Specifically, we ask whether children show a preference between an individual who uses more complex syntax (passive voice) and one who uses less complex syntax (active voice). We investigate syntactic complexity as a potential indicator of informant competence because passive voice is a feature of academic language, and may thus be viewed as more sophisticated than active voice (Berman, 2004; Snow & Uccelli, 2009; Vasilyeva et al., 2006). Further, 4-year-olds comprehend and produce passive syntax (e.g., Bencini & Valian, 2008; Brooks & Tomasello, 1999; Crain, Thornton, & Murasugi, 2009; Harris & Flora, 1982; Messenger et al., 2012).

We anticipated one of three outcomes. First, if children only attend to accuracy, whether an accurate informant uses active or passive voice should have no effect. Second, if children view syntactically complex language as another marker of competence, they may prefer to learn from an informant who uses the more complex passive voice. Third, children may be sensitive to speakers’ use of active and passive, but prefer to learn from an informant who uses active voice because it is what they hear and use themselves—that is, they use active vs. passive use to mark social group membership, or they find the informant who uses active voice less effortful to attend to (see Bernard, Proust, & Clément, 2014 for evidence that children selectively learn from intelligible over less intelligible informants).

We also asked if children’s informant preferences were related to socioeconomic status (SES). In Experiment 2, we compared selective learning preferences of lower-SES children (as indicated by a policy-relevant indicator of poverty status: eligibility for school free/reduced lunch, i.e., household family income < 185% of the federal poverty level in the prior year) and higher-SES children (not eligible for free/reduced lunch). SES affects children’s linguistic environments (e.g., Hart & Risley, 1995; Hoff, 2003; Huttenlocher et al., 2007; Rowe, 2008; Tizard, Hughes, Carmichael & Pinkerton, 1983; Snow, 1991), and in turn, language outcomes (e.g., Huttenlocher, Vasilyeva, Cymerman & Levine, 2002; Huttenlocher, Vasilyeva, & Shimpi, 2004). Parents rarely use passive voice in everyday talk, irrespective of SES (Gordon & Chafetz, 1990). However, higher-SES children engage in more literacy activities, particularly book-reading (Payne, Whitehurst & Angell, 1994; Scarborough & Dobrich, 1994), which uses more syntactically complex language (Cameron-Faulkner & Noble, 2013).

Indeed, SES differences in academic performance may partly stem from differential exposure to academic language (Bernstein, 1971; Hoff-Ginsberg, 1991; Lacroix, Pommerleau, & Malcuit, 2002; Landry, Smith, Swank, & Miller-Loncar, 2000). One obvious mechanism underlying this exposure-related performance gap is that children have difficulty understanding academic language. Here, we pursue a different possibility, grounded in the selective learning literature. Even if children understand the passive—we administer a test to ensure they do—less exposure may decrease their willingness to learn from an informant who uses it. If true, this would point to cascading effects of SES-related differences that extend beyond children’s syntactic competence to their trust of academic language users.

Method

Participants

Participants were 4- and 5-year-old children. In Experiment 1, 30 children (M = 5;3, 18 female, range: 4;0-6;0) were recruited from preschools in the Greater Boston area that primarily serve middle- to upper-class families. Sixty-three percent of participating children were Caucasian, 27% African-American, and the remaining 10% East Asian. In Experiment 2, 32 children (M = 5;3, 18 female, range: 4;0-6;2) were recruited from 4 classrooms in a preschool in Somerville, MA. Half of the children (N = 16; Mage = 5;0; range: 4;0-6;2) were eligible to receive free/reduced lunch as indicated by school administrators (henceforth lower-SES group; household family income < 185% of the federal poverty level; in 2014-15, 64% of children of all ages in Somerville were enrolled (Kids Count Data Center)). The other half (N = 16; Mage = 5;1; range: 4;0-6;0) were not eligible (henceforth higher-SES group). Forty-four percent were Caucasian, 44% African-American, 9% Hispanic, and 3% did not report race/ethnicity. Data were collected from September 2012-April 2013.

In both Experiments, teachers indicated which children spoke English as their first language. Those families received consent forms through written communication with their teacher in a one-time recruitment process, and most consented. No financial incentive was provided; children received a sticker as a thank-you.

Materials

Two English-speaking females served as informants across several video clips. In each clip, the informants sat at a table with an object or picture between them. During passive training videos (4 in total), one informant described a picture using passive voice, whereas the other used active voice (Table 1). Note that in Experiment 2, we controlled for subtle differences between the active and passive sentences (Table 1, lower panel). Because the passive sentences were longer than the actives, we added a word to the active condition—the particle ‘up’—that conveyed little meaning. Also, because the passive condition involved the past participle, we used the past tense in the active condition so that both presented the same form (“was picked” / “picked”). During novel label testing videos (4), the same informants offered different novel labels for an unfamiliar object. During novel morphology testing (4; adapted from Corriveau, Pickard & Harris, 2011), the informants offered different (both plausible) irregular past tense forms for a novel action depicted in a picture (selected from Berko’s (1958) wug test). The past tense forms were chosen from class V and VI verbs (Bybee & Slobin, 1982). In all phases, the order in which informants spoke and the descriptions or labels they provided were counterbalanced across children.

Table 1.

Sample Descriptions Used in Training in Experiments 1 and 2

Event Passive Voice Description Active Voice Description
Experiment 1
Girl with Flower The flower is picked by the girl. The girl is picking the flower.
Boy with Dog The dog is washed by the boy. The boy is washing the dog.
Experiment 2
Girl with Flower The flower was picked by the girl The little girl picked up the flower.
Boy with Dog The dog was washed by the boy. The boy washed up his pet dog.
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Procedure

There were 6 phases in Experiment 1, and 7 phases in Experiment 2: (1) Peabody Picture Vocabulary Test (PPVT; Dunn & Dunn, 1997); (1a) picture description task (Experiment 2 only); (2) passive training; (3) novel label testing; (4) novel morphology testing; (5) explicit judgment; and (6) passive-voice comprehension. These occurred in a fixed order, except for novel label and novel morphology testing, whose order was counterbalanced across children.

The PPVT, in which children match a spoken word to one of four pictures, assesses receptive vocabulary. All children scored above 1 SD below the average standard score (<85).

In Experiment 2, we included a picture description task to ensure that children spontaneously produce active sentences (and therefore, view the active-voice informant as a member of their linguistic in-group). We expected children to use the active. Thus, subsequent preference for the passive informant would require inhibiting the primed response. The experimenter elicited children’s descriptions of four pictures (e.g., a child washing a dog) by asking, “What’s going on in this picture?”

We then administered 4 passive-voice training trials. To introduce the task, the experimenter pointed to a still frame of the two informants and said, “This one is wearing a blue shirt and this one is wearing an orange shirt. They are going tell you about what some people in some pictures are doing.” On each trial, a picture of a child performing an action was between the informants. One informant described the picture using passive voice (e.g., “The flower is being picked by the girl”), while the other used active voice (e.g., “The girl is picking the flower”). The experimenter repeated the informants’ descriptions, and asked children how they would describe the scenario (e.g., “The girl wearing the blue shirt said that the girl is picking the flower, and the girl in the orange shirt said that the flower is being picked by the girl. What would you say?”). Verbal and nonverbal (e.g., pointing) responses were recorded.

On 4 novel label test trials, the experimenter said, “Now these girls are going to name some things that you have never seen before.” On each trial, the experimenter presented a picture of a novel object and pointed to a still frame of the informants who had the same object, saying, “I wonder what this object is called.” Each informant labeled the object differently. The experimenter asked, e.g., “The girl wearing the blue shirt said it’s a dax and the girl wearing the orange shirt said it’s a wug. What would you say?”

On 4 novel morphology test trials, the experimenter said, “Now these girls are going to tell you about what someone is doing,” then labeled a picture of an action with a novel verb (e.g., “Here is a picture of a man who is glinging.”), and pointed to a still frame of the informants with the same picture, saying: “I wonder what he did yesterday.” Each informant produced a plausible irregular past tense form (e.g., “Yesterday he glang,” or “Yesterday he glung.”). The experimenter asked, e.g., “The girl wearing the blue shirt said yesterday he glang and the girl wearing the orange shirt said yesterday he glung. What would you say?”

This procedure, of introducing informants with particular characteristics and measuring children’s subsequent inclination to learn from each, is common in selective learning studies (e.g., Koenig & Harris, 2005).

Next, the experimenter elicited an explicit judgment: “Do you remember when they (pointing to the informants) were talking about pictures of little girls and boys just like you? Which girl was better at talking about those things?”

Finally, we assessed passive-voice comprehension. On three trials, children saw two pictures of reversible actions (e.g., cat chasing a dog, dog chasing a cat). For another three trials the pairs were non-reversible (e.g., girl catching a ball, girl next to a ball). The experimenter provided a passive-voice description (e.g., “Point to the picture of the cat being chased by the dog”).

Results

Experiment 1

Preliminary analyses indicated no age or gender effects on children’s selective preference for the informants (Fs < 1). Therefore we combined age groups and genders.

Training

Scores on Training Trials represent the number of trials (max = 4) on which children endorsed the sentence provided by the passive-voice informant. Endorsements did not differ from 50% chance levels (M = 1.93, SD = .94, t(29) = .38, n.s.).

Novel Labels and Novel Morphology

Preliminary analyses indicated no effect of task order (labels first, morphology first) on children’s preferences (F(1,28) = 2.28, n.s.); thus, scores were combined across order. Scores on each task indicates the number of trials (max = 4) on which children endorsed the label/morphology from the informant who previously used passive voice. Children selectively endorsed novel labels (M = 2.80, SD = .81, t(29) = 5.42, p < .001, d = .99) and novel morphology (M = 2.67, SD = .99, t(29) = 3.67, p < .001, d = .68) from the passive informant.

To examine the relationship between children’s selectivity on the two tasks, we conducted a repeated-measures ANOVA on the number of trials children selectively preferred the label endorsed by the passive informant with trial type (labels, morphology) as the within-subjects variable. There was no significant effect of task (F(1,29) = .54, n.s.).

Explicit Judgment

Children received a point if they identified the passive informant as ‘better’ at talking about the pictures; 60% of children did so (χ2(1) = 1.2, n.s.). Recall that both informants accurately described the picture; thus, chance-level performance should not be taken as unsystematic.

To determine if preference for the passive informant on test trials was related to children’s relative judgment of her as ‘better’ (see Koenig & Harris, 2005 for this relationship with informant accuracy) we repeated the ANOVA, including Trial Type (training, labels, morphology) as a within-subjects variable and Explicit Judgment (passive better, active better) as a between-subjects variable. We found a main effect of Explicit Judgment (F(1,28) = 8.12, p < .01, η2p = .25); children who judged the passive informant as ‘better’ preferred her compared to children who judged the active informant as ‘better.’ No other main effects or interactions were found.

Figure 1 displays the proportion of trials where children chose the passive informant by Trial Type (novel labels, novel morphology) and explicit judgment. Whereas children who judged the passive informant as ‘better’ selectively preferred her on novel label and morphology trials (labels: t(17) = 6.97, p < .001, d = 1.64; morphology: t(17) = 7.01, p < .001, d = 1.63), children who judged the active informant as ‘better’ displayed no preference (labels: t(11) = 1.48, n.s.; morphology: t(11) = .25, n.s.).

Figure 1.

Figure 1

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The proportion of trials where children chose the passive informant by Trial Type (novel labels, novel morphology) and explicit judgment.

Passive-Voice Comprehension and PPVT

On the passive-voice comprehension task, children received a point for choosing the picture that corresponded to the sentence. For both non-reversible and reversible sentences (max = 3), children scored significantly above chance (Non-Reversible: M = 2.76, SD = .43, t(29) = 16.12, p < .001, d = 2.93, Reversible: M = 2.53, SD = .62, t(29) = 9.00, p < .001, d = 1.66). To assess whether passive comprehension or receptive vocabulary was related to choice of informant at test, we re-ran the ANOVA including passive comprehension (max = 6) and PPVT scores as covariates. We again found a main effect of explicit judgment (F(1,26) = 15.69, p < .001, η2par = .38), but no other main effects or interactions, suggesting that vocabulary and passive comprehension were unrelated to children’s endorsement of the passive-voice informant.

Experiment 2

Preliminary analyses indicated no age or gender effects (Fs < 1). Remaining analyses collapse across age and gender.

Picture Descriptions

With the exception of one description from one higher-SES child, all pictures (127 of 128) were described with active voice.

Training

Like children in Experiment 1, higher-SES children were at chance in endorsing sentences provided by the passive over the active informant (M = 2.38, SD = .96, t(15) = 1.57, n.s.). Lower-SES children, however, endorsed the active informant (M = 1.31, SD = 1.01, t(15) = −2.71, p < .05, d = .68).

Novel Labels and Novel Morphology

Preliminary analyses indicated no effect of task order (labels first, morphology first) on children’s selectivity (Fs < 1, n.s.); thus, scores were combined across order. Higher-SES children endorsed novel labels (M = 2.94, SD = .77, t(15) = 4.86, p < .001, d = 1.22) and novel verb morphology (M = 2.56, SD = .81, t(15) = 2.76, p < .05, d = .69) from the informant who previously used passive voice. Lower-SES children, however, endorsed the informant who had used active voice (labels: M = 1.37, SD = .72, t(15) = −3.48, p < .01, d = .88; morphology: M = 1.31, SD = .87, t(15) = −3.15, p < .01, d = .79).

To explore the relationship between SES and performance, we conducted a repeated-measures ANOVA with Trial Type (training, labels, morphology) as within-subjects variable. This yielded a main effect of SES (F(1,30) = 40.15, p < .001, η2p = .57) and no other main effects or interactions. Figure 2 displays the proportion of total choices that children directed at the passive informant by SES. Higher-SES children preferred to learn from the passive-voice informant as compared to lower-SES children.

Figure 2.

Figure 2

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The proportion of total choices that children directed at the passive informant by SES.

Explicit judgment

Of higher-SES children, 57% designated the passive informant as ‘better’ than the active informant (χ2(1) = .25, n.s.). Of lower-SES children, only 25% did (χ2(1) = 4.00, p < .05).

As in Experiment 1, we asked whether children’s explicit judgment of the relative accuracy of the informants related to their preference for the passive informant on novel label and morphology trials. A repeated-measures ANOVA with trial type (labels, morphology) as a within-subjects variable and explicit judgment (passive better, active better) and SES (higher-SES, lower-SES) as between-subjects variables yielded main effects of SES (F(1,28) = 28.71, p < .001, η2p = .51) and explicit judgment (F(1,28) = 4.14, p = .05, η2p = .13). Children who judged the passive informant as ‘better’ preferred her compared to children who judged the active informant as ‘better.’ No other main effects or interactions obtained.

Passive-voice Comprehension and PPVT

Children in both SES groups scored significantly above chance on the comprehension task (Non-Reversible: higher-SES: M = 2.81, SD = .54, t(15) = 9.65, p < .001, d= 2.42; lower-SES: M = 2.87, SD = .34, t(15) = 16.10, p < .001, d = 4.02; Reversible: higher-SES: M = 2.50, SD = .63, t(15) = 6.32, d= 1.58; lower-SES: M = 2.43, SD = .72, t(15) = 5.15, p < .001, d = 1.34). Performance did not vary by SES (Non-Reversible: t(30) = .38, n.s., Reversible: t(30) = .26, n.s.).

Although the standardized PPVT scores for lower-SES children were slightly lower (M = 98.19, SD = 5.5) than higher-SES (M = 103.00, SD = 9.36), this difference was not significant, t(30) = 1.76, n.s.

To assess whether total passive-voice comprehension or PPVT score related to performance at test, we re-ran the ANOVA including these scores as covariates. We found a main effect of SES (F(1,26) = 22.63, p < .001, η2p = .46), and a trend for an effect of explicit judgment preference (F(1,26) = 3.40, p = .08, η2p = .12), but no other main effects or interactions, suggesting that receptive vocabulary and passive comprehension were unrelated to selective learning preferences.

Discussion

Taken together, these results document that preschoolers track markers of informant competence beyond accuracy. Faced with two accurate informants, preschoolers attend to the syntactic complexity of their utterances to determine from whom to learn. In Experiment 1, children preferred to learn from an informant who used more complex syntax (passive voice). Notably, this preference was not evident during training; it was only when they inferred who was a competent informant in a novel scenario that children selectively preferred the passive-voice informant. This preference extended across novel label and morphology tasks, and was related to children’s explicit judgment of the passive informant as ‘better.’

In Experiment 2, preference varied by SES. Higher-SES children (as measured by eligibility for free/reduced lunch) like children in Experiment 1, demonstrated no preference for either informant during training, but endorsed information provided by the passive informant during subsequent learning tasks. Lower-SES children preferred the active informant across training and test. This SES difference remained after controlling for receptive vocabulary and passive comprehension. Moreover, children in both groups labeled their preferred informant as ‘better,’ suggesting that they made an inference about informant competence based on the training (although this inference varied by SES).

We initially posed three hypotheses for how variability in syntactic complexity might influence learning preferences. Results from Experiment 1 and the higher-SES data from Experiment 2 are consistent with our second hypothesis: children’s preference to learn from a speaker who uses passive voice, despite that most child-directed speech uses active voice (Gordon & Chafetz, 1990), indicates that these children use passive voice as a marker of informant competence. However, results from lower-SES children in Experiment 2 indicate that preference varies by family background.

This SES difference cannot be due to failure to comprehend the passive; both SES groups performed similarly well on the passive comprehension task (see also Craig & Washington, 2002). We hypothesize that frequency and context of passive exposure are responsible. Children from higher-SES families experience more literacy activities (Payne, Whitehurst & Angell, 1994; Scarborough & Dobrich, 1994). Although the passive is rare in spontaneous speech, exposure to books might be one mechanism by which children associate passive syntax with competence. Indeed, children privilege text-based sources over oral informants (e.g., Corriveau, Einav, Robinson & Harris, 2014; Robinson, Einav & Fox, 2013). Additionally, lower-SES parents use more directive child-directed speech (e.g., ‘go sit down’) than higher-SES parents, who use more democratic speech (e.g., ‘where do you think you should be right now?’) (Heath, 1983). Thus, higher-SES child-directed speech may include more syntactically complex features (Huttenlocher et al., 2002), perhaps causing children to privilege them in learning.

In future work we will design a reading intervention to expose children to storybooks that primarily use passive voice. Vasilyeva et al. (2006) found that listening to such storybooks increased passive production and comprehension; we will further examine whether this exposure increases children’s preference to learn from informants who use passive voice. If successful, this intervention would suggest that exposure to academic language during book-reading may increase learning in academic settings more generally. Increasing book-reading in the home will likely have even stronger effects; Hoff-Ginsberg (1991) found that lower-SES mothers used more complex syntax during book-reading than other activities—even when only considering spontaneous speech, and not the language they read from the book. Increased exposure to book-reading may thus bring children into the academic language ‘in-group.’

Future work should also explore what other correlates of family income are related to learning. Here, we only use eligibility for free/reduced lunch as a marker of SES, but a more robust design would include measures of caregiver education and other characteristics of the home environment (such as access to books in the home; Snow, Barnes, Chandler, Goodman, & Hemphill, 1991).

Just as SES is a complex construct, passive voice is just one of many markers of academic competence. For example, young school-aged children recognize non-circular, cogent arguments as more intelligent than circular, repetitive arguments (Baum, Danovitch, & Keil, 2008; Corriveau & Kurkul, 2014; Mercier, Bernard & Clément, 2014). Children may choose to learn from individuals who use this more academic form of speaking. We expect that children consider a wide range of competencies, but also that what factors they weigh will vary by age and personality factors.

In summary, this is the first study demonstrating that children use syntactic complexity to determine informant competence. Importantly, we found SES differences, with lower-SES children less likely to learn from an informant who used passive voice. The findings have implications for our understanding of SES differences in academic success.

Acknowledgements

This work was supported by an APA Early Career grant to KHC and NIH K01 DC013306 to SA.

References

  1. Baum LA, Danovitch & Keil FK. Children’s sensitivity to circular explanations. Journal of Experimental Child Psychology. 2008;100:146–155. doi: 10.1016/j.jecp.2007.10.007. doi:10.1016/j.jecp.2007.10.007. [DOI] [PMC free article] [PubMed] [Google Scholar]
  2. Bencini Guilia M. L., Valian Virginia V. Abstract sentence representations in 3-year-olds: Evidence from language production and comprehension. Journal of Memory and Language. 2008;59(1):97–113. doi: 10.1016/j.jml.2007.12.007. [Google Scholar]
  3. Berko J. The child's learning of English morphology. Word. 1958;14:150–177. [Google Scholar]
  4. Berman R, editor. Language development across childhood and adolescence. John Benjamins; New York: 2004. [Google Scholar]
  5. Birch SA, Vauthier SA, Bloom P. Three and four-year-olds spontaneously use others’ past performance to guide their learning. Cognition. 2008;107:1018–1034. doi: 10.1016/j.cognition.2007.12.008. doi:10.1016/j.cognition.2007.12.008. [DOI] [PubMed] [Google Scholar]
  6. Brooks PJ, Tomasello M. Young children learn to produce passives with nonce verbs. Developmental Psychology. 1999;35(1):29. doi: 10.1037//0012-1649.35.1.29. doi:10.1037/0012-1649.35.1.29. [DOI] [PubMed] [Google Scholar]
  7. Bybee JL, Slobin DI. Rules and schemas in the development and use of the English past tense. Language. 1982;58:265–289. [Google Scholar]
  8. Cameron-Faulkner T, Noble C. A comparison of book text and child directed speech. First Language. 2013;33:268–279. doi: 10.1177/0142723713487613. [Google Scholar]
  9. Clément F, Koenig M, Harris PL. The ontogenesis of trust. Mind & Language. 2004;19:360–379. doi: 10.1111/j.0268-1064.2004.00263.x. [Google Scholar]
  10. Corriveau K, Harris PL. Choosing your informant: weighing familiarity and recent accuracy. Developmental Science. 2009a;12:426–437. doi: 10.1111/j.1467-7687.2008.00792.x. doi: 10.1111/j.1467-7687.2008.00763.x. [DOI] [PubMed] [Google Scholar]
  11. Corriveau K, Harris PL. Preschoolers continue to trust a more accurate informant 1 week after exposure to accuracy information. Developmental Science. 2009b;12:188–193. doi: 10.1111/j.1467-7687.2008.00763.x. doi: 10.1348/2044-835X.002009. [DOI] [PubMed] [Google Scholar]
  12. Corriveau KH, Harris PL, Meins E, Fernyhough C, Arnott B, Elliott L, Hearn A, Vittorini L, De Rosnay M. Young children’s trust in their mother’s claims: Longitudinal links with attachment security in infancy. Child development. 2009;80(3):750–761. doi: 10.1111/j.1467-8624.2009.01295.x. [DOI] [PubMed] [Google Scholar]
  13. Corriveau KH, Kinzler KD, Harris PL. Accuracy trumps accent in children's endorsement of object labels. Developmental Psychology. 2013;49(3):470–479. doi: 10.1037/a0030604. doi: 10.1037/a0030604. [DOI] [PubMed] [Google Scholar]
  14. Corriveau KH, Kurkul KE. “Why Does Rain Fall?”: Children Prefer to Learn From an Informant Who Uses Noncircular Explanations. Child development. 2014 doi: 10.1111/cdev.12240. Advance online publication. doi: 10.1111/cdev.12240. [DOI] [PubMed] [Google Scholar]
  15. Corriveau KH, Meints K, Harris PL. Early tracking of informant accuracy and inaccuracy by young children. British Journal of Developmental Psychology. 2009;27:331–342. doi: 10.1348/026151008x310229. doi: 10.1348/026151008X310229. [DOI] [PubMed] [Google Scholar]
  16. Corriveau K, Pickard K, Harris PL. Preschoolers trust particular informants when learning new names and new morphological forms. British Journal of Developmental Psychology. 2011;29:46–63. doi: 10.1348/2044-835X.002009. doi: 10.1348/2044-835X.002009. [DOI] [PubMed] [Google Scholar]
  17. Corriveau KH, Einav S, Robinson EJ, Harris PL. To the letter: Early readers trust print?based over oral instructions to guide their actions. British Journal of Developmental Psychology. 2014 doi: 10.1111/bjdp.12046. doi: 10.1111/bjdp.12046. [DOI] [PubMed] [Google Scholar]
  18. Craig HK, Washington JA. Oral language expectations for African American preschoolers and kindergartners. American Journal of Speech-Language Pathology. 2002;11(1):59–70. doi: 10.1044/1058-0360(2005/013). doi: 10.1044/1058-0360(2002/007) [DOI] [PubMed] [Google Scholar]
  19. Crain S, Thornton R, Murasugi K. Capturing the evasive passive. Language Acquisition. 2009;16(2):123–133. doi: 10.1080/10489220902769234. [Google Scholar]
  20. Dunn LM, Dunn LM. Examiner's manual for the PPVT-III peabody picture vocabulary test: Form IIIA and Form IIIB. AGS; 1997. [Google Scholar]
  21. Fusaro M, Corriveau KH, Harris PL. The good, the strong, and the accurate: Preschoolers’ evaluations of informant attributes. Journal of Experimental Child Psychology. 2011;110(4):561–574. doi: 10.1016/j.jecp.2011.06.008. doi: 10.1016/j.jecp.2011.06.008. [DOI] [PubMed] [Google Scholar]
  22. Gordon P, Chafetz J. Verb-based versus class-based accounts of actionality effects in children's comprehension of passives. Cognition. 1990;36(3):227–254. doi: 10.1016/0010-0277(90)90058-r. doi: 10.1016/0010-0277(90)90058-R. [DOI] [PubMed] [Google Scholar]
  23. Harris FN, Flora JA. Children's use of get passives. Journal of Psycholinguistic Research. 1982;11(4):297–311. doi: 10.1007/BF01067584. [Google Scholar]
  24. Harris PL. Trust. Developmental Science. 2007;10:135–138. doi: 10.1111/j.1467-7687.2007.00575.x. [DOI] [PubMed] [Google Scholar]
  25. Harris PL, Corriveau KH. Young children’s selective trust in informants. Philosophical Transactions of the Royal Society. 2011;366(1567):1179–1187. doi: 10.1098/rstb.2010.0321. doi: 10.1098/rstb.2010.0321. [DOI] [PMC free article] [PubMed] [Google Scholar]
  26. Harris PL, Kruithof A, Terwogt MM, Visser T. Children’s detection and awareness of textual anomaly. Journal of Experimental Child Psychology. 1981;31:212–230. doi: 10.1016/0022-0965(81)90013-8. [Google Scholar]
  27. Hart B, Risley TR. Meaningful differences in the everyday experience of young American children. Paul H. Brookes Publishing; 1995. [Google Scholar]
  28. Heath SB. Ways with words: Language, life and work in communities and classrooms. Cambridge University Press; 1983. [Google Scholar]
  29. Hoff E, Tian C. Socioeconomic status and cultural influences on language. Journal of Communication Disorders. 2005;38(4):271–278. doi: 10.1016/j.jcomdis.2005.02.003. doi: 10.1016/j.jcomdis.2005.02.003. [DOI] [PubMed] [Google Scholar]
  30. Hoff-Ginsberg E. Mother-child conversation in different social classes and communicative settings. Child Development. 1991;62:782–796. doi: 10.1111/j.1467-8624.1991.tb01569.x. doi: 10.1111/j.1467-8624.1991.tb01569.x. [DOI] [PubMed] [Google Scholar]
  31. Huttenlocher J, Vasilyeva M, Waterfall HR, Vevea JL, Hedges LV. The varieties of speech to young children. Developmental Psychology. 2007:1062–1083. doi: 10.1037/0012-1649.43.5.1062. doi: 10.1037/0012-1649.43.5.1062. [DOI] [PubMed] [Google Scholar]
  32. Huttenlocher J, Vasilyeva M, Shimpi P. Syntactic priming in young children. Journal of Memory and Language. 2004;50:182–195. doi: 10.1016/j.jml.2003.09.003. [Google Scholar]
  33. Huttenlocher J, Vasilyeva M, Cymerman E, Levine S. Language input and child syntax. Cognitive Psychology. 2002;45:337–374. doi: 10.1016/s0010-0285(02)00500-5. doi: 10.1016/S0010-0285(02)00500-5. [DOI] [PubMed] [Google Scholar]
  34. Jaswal VK, Neely LA. Adults don’t always know best: preschoolers use of past reliability over age when learning new words. Psychological Science. 2006;17:757–758. doi: 10.1111/j.1467-9280.2006.01778.x. doi: 10.1111/j.1467-9280.2006.01778.x. [DOI] [PubMed] [Google Scholar]
  35. Kids Count Data Center Free and reduced price lunch enrollment rates by school district. 2015 [Data file]. Available from datacenter.kidscount.org.
  36. Kinzler KD, Corriveau KH, Harris PL. Children’s selective trust in native accented speakers. Developmental Science. 2011;14:106–111. doi: 10.1111/j.1467-7687.2010.00965.x. doi: 10.1111/j.1467-7687.2010.00965.x. [DOI] [PubMed] [Google Scholar]
  37. Koenig M, Harris PL. Preschoolers mistrust ignorant and inaccurate speakers. Child Development. 2005;76:1261–1277. doi: 10.1111/j.1467-8624.2005.00849.x. doi: 10.1111/j.1467-8624.2005.00849.x. [DOI] [PubMed] [Google Scholar]
  38. Koenig MA, Jaswal VK. Characterizing children’s expectations about expertise and incompetence: Halo or pitchfork effects? Child Development. 2011;82(5):1634–1647. doi: 10.1111/j.1467-8624.2011.01618.x. doi: 10.1111/j.1467-8624.2011.01618.x. [DOI] [PubMed] [Google Scholar]
  39. Mercier H, Bernard S, Clément F. Early sensitivity to arguments: How preschoolers weight circular arguments. Journal of experimental child psychology. 2014;125:102–109. doi: 10.1016/j.jecp.2013.11.011. doi: 10.1016/j.jecp.2013.11.011. [DOI] [PubMed] [Google Scholar]
  40. Messenger K, Branigan HP, McLean JF, Sorace A. Is young children's passive syntax semantically constrained? Evidence from syntactic priming. Journal of Memory and Language. 2012;66(4):568–587. [Google Scholar]
  41. Pasquini E, Corriveau KH, Koenig M, Harris PL. Preschoolers monitor the relative accuracy of informants. Developmental Psychology. 2007;43:1216–1226. doi: 10.1037/0012-1649.43.5.1216. doi: 10.1037/0012-1649.43.5.1216. [DOI] [PubMed] [Google Scholar]
  42. Payne AC, Whitehurst GJ, Angell AL. The role of home literacy environment in the development of language ability in preschool children from low-income families. Early Childhood Research Quarterly. 1994;9(3):427–440. doi: 10.1016/0885-2006(94)90018-3. [Google Scholar]
  43. Rakoczy H, Warneken F, Tomasello M. Young children's selective learning of rule games from reliable and unreliable models. Cognitive Development. 2009;24(1):61–69. doi: 10.1016/j.cogdev.2008.07.004. [Google Scholar]
  44. Robinson EJ, Einav S, Fox A. Reading to learn: prereaders' and early readers' trust in text as a source of knowledge. Developmental psychology. 2013;49(3):505. doi: 10.1037/a0029494. doi: 10.1037/a0029494. [DOI] [PubMed] [Google Scholar]
  45. Scarborough HS, Dobrich W. On the efficacy of reading to preschoolers. Developmental Review. 1994;14(3):245–302. doi: 10.1006/drev.1994.1010. [Google Scholar]
  46. Snow CE. The theoretical basis for relationships between language and literacy in development. Journal of Research in Childhood Education. 1991;6(1):5–10. doi: 10.1080/02568549109594817. [Google Scholar]
  47. Snow CE, Barnes WS, Chandler J, Goodman IF, Hemphill L. Unfulfilled expectations: Home and school influences on literacy. Harvard University Press; 1991. [Google Scholar]
  48. Snow CE, Uccelli P. The challenge of academic language. The Cambridge handbook of literacy. 2009:112–133. [Google Scholar]
  49. Sobel DM, Corriveau KH. Children monitor individuals’ expertise for word learning. Child Development. 2010;81(2):669–679. doi: 10.1111/j.1467-8624.2009.01422.x. doi: 10.1111/j.1467-8624.2009.01422.x. [DOI] [PubMed] [Google Scholar]
  50. Sobel DM, Macris DM. Children's understanding of speaker reliability between lexical and syntactic knowledge. Developmental Psychology. 2013;49(3):523–532. doi: 10.1037/a0029658. doi: 10.1037/a0029658. [DOI] [PubMed] [Google Scholar]
  51. Sobel DM, Sedivy J, Buchanan DW, Hennessy R. Speaker reliability in preschoolers' inferences about the meanings of novel words. Journal of Child Language. 2012;39(1):90–104. doi: 10.1017/S0305000911000018. doi: 10.1017/S0305000911000018. [DOI] [PubMed] [Google Scholar]
  52. Tizard B, Hughes M, Carmichael H, Pinkerton G. Language and social class: Is verbal deprivation a myth? Journal of Child Psychology and Psychiatry. 1983;24(4):533–542. doi: 10.1111/j.1469-7610.1983.tb00130.x. doi: 10.1111/j.1469-7610.1983.tb00130.x. [DOI] [PubMed] [Google Scholar]
  53. Vasilyeva M, Huttenlcoher J, Waterfall H. Effects of Language Intervention on Syntactic Skill Levels in Preschoolers. Developmental Psychology. 2006;42:164–174. doi: 10.1037/0012-1649.42.1.164. doi: 10.1037/0012-1649.42.1.164. [DOI] [PubMed] [Google Scholar]

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