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Hoff&Naigles Lexicon Acquisition
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How Children Use Input to Acquire a LexiconAuthor(s): Erika Hoff and Letitia NaiglesSource: Child Development, Vol. 73, No. 2 (Mar. - Apr., 2002), pp. 418-433Published by: Blackwell Publishing on behalf of the Society for Research in ChildDevelopmentStable URL: http://www.jstor.org/stable/3696366Accessed: 22/12/2008 17:45
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Child Development, March/April 2002, Volume 73, Number 2, Pages 418-433
How Children Use Input to Acquire a Lexicon
Erika Hoff and Letitia Naigles
The contributions of social processes and computational processes to early lexical development were evalu- ated. A re-analysis and review of previous research cast doubt on the sufficiency of social approaches to word learning. An empirical investigation of the relation of social-pragmatic and data-providing features of input to the productive vocabulary of sixty-three 2-year-old children revealed benefits of data provided in mother- child conversation, but no effects of social aspects of those conversations. The findings further revealed that the properties of data that benefit lexical development in 2-year-olds are quantity, lexical richness, and syntac- tic complexity. The nature of the computational mechanisms implied by these findings is discussed. An inte- grated account of the roles of social and computational processes to lexical development is proposed.
INTRODUCTION
The process of acquiring a lexicon is clearly a process of learning from experience, and the relevant experi- ence must be conversational interaction, because that is the context in which exposure to language occurs. It is not yet clear, however, just how word-learning ben- efits from participating in or overhearing conversa- tions. What do children find in conversation that is useful to word learning, and what is the nature of the
word-learning mechanism that makes those particu- lar things useful?
Two types of answers have been proposed. The first focuses on the social-pragmatic aspects of conversa- tion and the social-cognitive abilities of children. Ac-
cording to this view children figure out the meaning of the words they hear to a substantial degree by in-
ferring the speaker's attentional focus and communi- cative intent (Akhtar & Tomasello, 2000; Baldwin, 2000). The routinized and jointly engaged nature of the conversations that children experience support this process by making the speaker's communicative intentions transparent (Bruner, 1974/1975; Pinker, 1984; Tomasello, 1990, 2001). The second answer fo- cuses on the data-providing aspects of conversation, arguing that the lexical content and syntactic struc- ture of the utterances themselves, along with the ac-
companying nonlinguistic context, provide consider- able information that children use in figuring out word meaning (Carey, 1978; Gillette, Gleitman, Gleit- man, & Lederer, 1999; Gleitman, 1990; Siskind, 1996).
These two proposals are not mutually exclusive. Recent work acknowledges that multiple sources of information must contribute to word learning and seeks to build an integrative account of how word
learning occurs (e.g., Akhtar & Tomasello, 2000; L. Bloom, 1993, 2000; P. Bloom, 2000; Hollich, Hirsh- Pasek, & Golinkoff, 2000). The purpose of this study was to add to this effort by evaluating the roles of
social-pragmatic and data-providing functions of con- versation on both the theoretical and empirical levels.
The Social-Pragmatic View of the Role of Input
Early formulations of the social-pragmatic pro- posal argued that the recurrent social interactions be- tween mother and child establish each participant's intentions throughout a given routinized activity, al-
lowing the child to predict "where the adult's atten- tion is currently focused and where it is likely to be focused next. Therefore, any language the adult may use in such a context is likely to be immediately meaningful to the child" (Tomasello & Todd, 1983, p. 199). Additionally, if, in nonroutinized interaction, mothers talk about the aspect(s) of the activity that the child is focused on, then the meaning(s) the child is harboring should be consistently expressed, with the result that "mothers who follow their children's leads in determining the topics of conversation may help their children's language learning by increasing the likelihood that their children will be able to con- struct semantic representations of the sentences they hear" (Hoff-Ginsberg, 1987, p. 147). Thus, the social-
pragmatic argument is that by virtue of either routin- ization or maternal attentiveness, children often know what their mothers are saying without under-
standing the language, and they can use that nonlin-
guistically acquired knowledge to figure out the
meaning of the language they hear. More recently, the social-pragmatic proposal has
focused on the social-cognitive abilities and inclina- tions of children (Akhtar & Tomasello, 2000; Baldwin, 2000; P. Bloom, 2000). There is evidence that children are not at the mercy of adults' following their atten- tional focus for word meaning to be made transparent
? 2002 by the Society for Research in Child Development, Inc. All rights reserved. 0009-3920/2002/7302-0006
Hoff and Naigles 419
because children have the ability to discern their mothers' communicative intentions. According to this view, word learning begins once children understand others as intentional agents, assume that there is some communicative intention behind the vocalizations others make, and successfully figure out what those communicative intentions are. In both social-pragmatic accounts, mutual engagement or joint attention pro- vides support for word learning, but in the early for- mulation the social-pragmatic skill resides in the minds of the adults who structure the learning envi- ronment, whereas in the more recent formulation the
social-pragmatic skill that contributes to word learn-
ing is located in the minds of the children who do the
learning. Empirical support for the notion that word learning
is aided when the learner and speaker are mutually engaged is plentiful. Thirteen-month-old infants whose mothers are more verbally responsive during toy play demonstrate earlier onset of their first word and of their first 50 words in both comprehension and production, and this benefit of verbal respon- siveness is specific to language development (Tamis- LeMonda, Bornstein, Baumwell, & Damast, 1996; Tamis-LeMonda, Bornstein, Kahana-Kalman, Baum- well, & Cyphers, 1998). That is, maternal responsive- ness to child vocalizations predicts child language outcomes, and responsiveness to play predicts mea- sures of children's play (Tamis-LeMonda et al., 1996). There is evidence of even more specific links between mother-child interaction and subsequent word learn-
ing. For example, children who are part of mother- child dyads that engage in greater amounts of joint interaction have larger production vocabularies be- tween 12 and 18 months of age than children who
engage in less joint interaction with their mothers (Tomasello & Todd, 1983). Mothers of normally devel-
oping children more frequently make reference to ob-
jects currently in their children's focus of attention than do mothers of children who are developing lan-
guage slowly (Harris, Jones, Brookes, & Grant, 1986). Children whose mothers engage in more directives that specifically follow their children's focus of atten- tion (as opposed to lead it, or just describe it) when the children are 13 months old have production vo- cabularies that include more nouns and more words at 22 months (Akhtar, Dunham, & Dunham, 1991). Twelve-month-olds whose interactions with their mothers include more joint engagement and maternal follow-in subsequently manifest larger comprehen- sion vocabularies at 15 months of age (Carpenter, Nagell, & Tomasello, 1998). Fifteen- to 21-month-olds whose joint attention episodes with their mothers in- clude considerable maternal verbal follow-ins also
are the ones who have the larger production vocabu- laries, assessed via a checklist (Tomasello & Farrar, 1986). In an experimental setting in which the match between input and children's attention was manipu- lated, 17-month-olds were more likely to learn words that label their current focus of attention than words that label something they are not attending to (Tomasello & Farrar, 1986). In sum, it is clear from a substantial body of naturalistic evidence and one ex-
perimental demonstration that when mothers struc- ture children's experiences so that input is responsive to the children's verbalizations and matches children's attentional focus, vocabulary development benefits.
There is also evidence that children contribute to
establishing the joint engagement that benefits word
learning. There are direct relations between 14-month- old children's joint attentional behaviors and their mothers' sensitivity (Laakso, Poikkeus, Katajamaki, & Lyytinen, 1999); and individual differences in 14- month-olds' abilities to follow another into a joint at- tentional state predict later language development (Laakso et al., 1999; Mundy & Gomes, 1998). These re- lations between very young children's joint atten- tional skills and subsequent language development are most likely mediated by the effects of children's skill on the mutual engagement they achieve.
Other experimental evidence suggests that after 18 months, children have social-cognitive abilities that make them less dependent on such mutual engage- ment. At 18 months, children seem to know that if the
speaker and listener are not attending to the same
thing, the speaker is more likely to be talking about what the speaker is attending to than about what the listener is attending to, and children use that informa- tion to guide word learning (Baldwin, 1993; Hollich et al., 2000). Children at 24 months of age have dem- onstrated even more powerful abilities to use clues to
speakers' communicative intentions as sources of in- formation about word meaning. For example, Toma- sello and Barton (1994) found that telling 2-year-old children "I'm going to hoist Big Bird," and then doing something but saying "Woops," resulted in the chil- dren not taking "hoist" as a label for the action dem- onstrated. Presented with the same sequence of events, but with "There" replacing "Woops," children took "hoist" as the label for the action. There have been similar effects of speakers' indications of their intentions on object label learning (see also Golinkoff, Hirsh-Pasek, & Hollich, 1999; Tomasello, 2001; Wood- ward & Markman, 1999).
This evidence leaves no doubt that children as
young as 12 months have social skills that enable them to participate in mutually engaged social inter- actions (Akhtar et al., 1991; Carpenter et al., 1998;
420 Child Development
Tomasello & Todd, 1983), that by 18 months children can discern speakers' intentions even in the absence of mutual engagement (e.g., Baldwin, 1993; Toma- sello & Barton, 1994), and that these abilities support word learning. Even the strongest social-pragmatic view allows that social information alone is insuffi- cient to account for word learning (e.g, Akhtar & To- masello, 2000), however, thus raising the question of what other sources of information children use. A
complete account of lexical development requires specifying just what contribution social-pragmatic information makes to word learning, when in the course of development these contributions are made, and where else in their experience children find infor- mation about the meaning of the words they hear. In the next sections we begin to explore the parameters of the role of social-pragmatic information in word
learning in three ways: (1) we reconsider the implica- tions of previous findings of correlations between in- dices of mutual engagement and children's vocabu-
lary development, (2) we analyze the task of word
learning for the potential contribution of social-prag- matic information, and (3) we consider evidence re-
garding the degree to which children's conversations are actually characterized by mutual understanding.
The Correlational Findings, Reconsidered
Not all positive relations between social-pragmatic support and language development are necessarily evidence that children find information about word
meaning by being provided with or by figuring out the communicative intentions of their conversational
partner. The most general positive correlations may merely reflect that social-pragmatic support is an in- dex of supportive parenting and vocabulary growth is an index of healthy development. After all, Monnot (1999) found that the degree to which mothers used characteristics of infant-directed speech in talk to their 3- to 4-month-old infants was positively corre- lated with infant weight gain, yet no one would argue that infants find calories in the fundamental frequency of their mothers' speech. Other correlations, such as those observed by Tamis-LeMonda et al. (1996) and Bornstein, Haynes, and Painter (1998) may reflect the fact that mothers who are responsive to their children's verbalizations benefit language development in gen- eral by encouraging further verbal interaction, and the
greater information provided by this greater amount of interaction is what benefits lexical development.
The findings of benefits of maternal follow-in that are specific to the learning of particular words could
simply be benefits of the temporal contiguity of words and children's attention, rather than a reflec-
tion of any socially based process in the mind of the child. Finally, the correlations between maternal social-
pragmatic support and lexical development rely fre-
quently on mother-generated checklists or diaries as the measure of infant vocabulary size or growth. It is
likely that these are correlated for reasons other than
language development: those mothers who are good at establishing and following their children's joint at- tention may be better at assessing their children's vo-
cabulary, whereas mothers who are less responsive overall may also be less good at such an assessment. In sum, responsive mothering might be statistically associated with indicators of more rapid language development for reasons that have nothing to do with the role of social-pragmatic understandings in word learning.
The Word-Learning Task, Divided into Three Parts
A consideration of what the task of word learning consists of suggests that social-pragmatic informa- tion must be supplemented by other types and sources of information. Current research and theory suggest that the process of word learning consists of at least the following three components: word seg- mentation; an initial fast mapping of the new word onto a referent; and a longer, extended process of
completing the lexical entry. There is no evidence, nor indeed any proposals, that social understandings contribute to word segmentation. In contrast, there is evidence that several physical properties of input do contribute, including stress patterns, prosody, and
repetition of words in combination with a variety of different words (see references in Aslin, Saffran, &
Newport, 1999; Morgan & Demuth, 1996). Not only are social understandings and communicative inten- tions irrelevant to this process, anything to do with utterance or word meaning also appears to be irrele- vant. Although a theory is not expected to account for
everything, it is worth noting that despite strong claims that language acquisition is a social process (e.g., Carpenter et al., 1998), there are components of
language acquisition that social-process accounts have not addressed.
In addition to isolating the sound sequences that constitute words, children must map those sound se-
quences onto meanings. The social-pragmatic ap- proach argues that children's socially based under-
standings of speakers' intentions aid in this latter task: Children know what their interlocutors are re-
ferring to because utterances follow children's atten- tional focus or because the children can infer their in- terlocutors' communicative intentions. Thus, children are guided to the referents of new words by their in-
Hoff and Naigles 421
terlocutors' skill in following children's attentional focus and / or by their own understandings of their in- terlocutors' intentions. Indeed, the evidence suggests that social-pragmatic information is useful in the iden- tification of referents, at least in experimental settings.
Word learning is not complete once the initial map- ping of word onto referent has been accomplished, however. Although children's ability to make a map- ping on the basis of as little as one presentation of a word is an impressive feat and important to word
learning, it is not the case that children learn the en-
tirety of a given word's meanings on the basis of a sin-
gle or very few hearings. The initial fast mapping of a word results in only a partial lexical entry and is fol- lowed by a process in which the lexical entry is "com-
pleted slowly as the child encounters the word again and contrasts it with other words" (Carey, 1978, p. 292). Indeed, many accounts describe the protracted nature of word learning (e.g., L. Bloom, 1993; P. Bloom, 2000; Gropen, Pinker, Hollander, & Goldberg, 1991; Naigles, 2000a; Rice, 1990). Thus, even if social understand-
ings are responsible for fast mappings, they do not
fully explain lexical development. There must be other sources of information as well.
The Degree of Mutual Understanding in Adult-Child Conversations
The third reason to look for additional sources of information that children might use in word learning comes from a consideration of how frequently social interaction in joint attention actually occurs for most children and how able children actually are to divine their mothers' meanings during mother-child inter- actions. Some studies provided data that allowed for the calculation of the percent of time that mothers and children spent in joint attention, which yielded esti- mates of 11.6% (Carpenter et al., 1998) and 20% (Toma- sello & Todd, 1983) for children under 18 months, and 29% for children aged 2 years (Hoff-Ginsberg, 1998). It appears that episodes of joint attention did not
comprise much of the time these dyads spent interact-
ing. Tomasello and Farrar (1986) provided no raw data with which to make such calculations, but they reported that their dyads, taped for 15 min during toy play at home, spent two thirds of their time in joint at- tention episodes. Potential sources of the variability in the proportion of time spent in joint attention are both the setting and the age of the child. Higher esti- mates come from studies of older children, although studies of younger children have produced the find-
ings that variability in time spent in joint attention predicts vocabulary development (Laakso et al., 1999; Mundy & Gomes, 1998).
Another indicator of mutual engagement is the de-
gree to which topics are continued across conversa- tional turns. The social-pragmatic account might be construed to predict that such continuations are com- mon, both on the parents' side (i.e., parents frequently understanding their children and continuing their
topics) and on the children's side. The data suggest otherwise, however. The percent of maternal utter- ances that follow children's topics has been reported as 18.7% (Hoff-Ginsberg, 1987), 21.6% (Akhtar et al., 1991), 32.2% (Hoff-Ginsberg, 1987), and 36.3% (Car- penter et al., 1998). Again, these different estimates come from different settings and children of different
ages-in general, there is more topic following with older children. Additionally, there are findings that 45% of parental responses are nonsequiturs (Brown & Hanlon, 1970) and that 10% to 20% of maternal turns and 20% to 30% of paternal turns reflect communica- tive breakdowns (Tomasello, Conti-Ramsden, & Ewert, 1990). Moreover, only 31% of the signals that prever- bal infants produce lead to immediately successful comprehension on their mothers' parts (Golinkoff, 1986). When topic continuations are calculated from the children's point of view, it appears that only half of children's speech receives a topic-related response, and these responses most often simply acknowledge, repeat, or clarify, rather than build on what the chil- dren said (Bloom, Margulis, Tinker, & Fujita, 1996). Furthermore, children appear to be no more engaged with mothers than mothers are with children. The
percent of all child utterances that continue the topic of a prior maternal prior utterance has been estimated as 21% for children at 20 months of age (Bloom, Rocis- sano, & Hood, 1976), 33% for children with a mean
age of 24 months (Hoff-Ginsberg, 1998), and 47% for children at 36 months (Bloom et al., 1976).
It is possible that despite being a small percentage of children's time in conversation, the time that is
spent in mutual engagement is when word learning occurs. This argument, however, requires children to
ignore more than half of their linguistic input (be- cause some input is being provided when mutual en-
gagement is not occurring). Moreover, there is evi- dence that children do learn aspects of their language outside of episodes of mutual engagement; in partic- ular, from overhearing speech among others. In both
experimental and naturalistic research (Oshima-Takane, 1988; Oshima-Takane, Goodz, & Derevensky, 1996) found that children acquire aspects of the personal pronoun system from overheard speech. Abundant anecdotal evidence that children go through a stage during which they call their parents by their given names, against the family convention of variants of "Mom" and "Dad," also implies that they learn from
422 Child Development
speech that is not addressed to them (Naigles, 2000b). In sum, evidence that mutual engagement is neces-
sary for word learning is weak and, in many cases, observed benefits of mutual engagement to word
learning may be attributed to general effects of posi- tive interaction on child development. Moreover, the
social-pragmatic account does not address the seg- mentation or the lexical entry completion aspects of word learning.
The Data-Providing View of Input
An alternative to the view that conversation is a so- cial experience and language development is a social process is the view that language acquisition is a data-
crunching process and conversation is a delivery mechanism whose value lies, to a substantial degree, in the nature of the data that it delivers. This view of the contribution of conversation to language develop- ment has previously been proposed with respect to syntactic development (Hoff-Ginsberg, 1986, 1990, 1999). We propose it in this article with respect to lex- ical development. Although the data-providing ac- count of the role of conversational experience in lexical
development has not, to our knowledge, been previ- ously labeled as such, there are several lines of re- search that support the notion. The relevant and po- tentially helpful properties of the speech signal for the word segmentation component of word learning were mentioned earlier and have been explored in de- tail in work in Morgan and Demuth (1996; see also Aslin et al., 1999). With respect to the initial referent
mapping and subsequent lexical entry completion components, the conversation-as-data argument is that children can use their (sometimes partial) under-
standing of the other words and the structure of the utterance in which an unknown word is placed to make conjectures about the referent of that novel word.
Evidence for the potential usefulness and actual use of the rest of the utterance for learning a new word comes from computational and human simula- tions of word learning and from experimental and naturalistic studies of young children's word learn- ing. Computer simulations have demonstrated that the use of partial linguistic knowledge to constrain hypotheses, combined with the ability to extract com- monalties across different situations of use, can result in lexical acquisition by a system that has no access to speaker intentions at all (Siskind, 1996). To illustrate, knowledge of what the word ball means, combined with knowledge about what kinds of entities do what kinds of things, indicates to the learning device that if the word ball is in the utterance, then the unknown word in that utterance is more likely to mean roll than
eat. Evidence that humans can similarly make infer- ences about word meaning from information in the utterance containing a novel word comes from Gillette et al.'s (1999) simulation of word learning with human (adult) participants. The learners in this case were shown a series of silent videoclips of real mother- child interactions during which a specific verb had been spoken by the mother. The participants were provided with various "clues" to the identity of the verb, including (1) just the videoclips; (2) the video- clips plus the nouns in the mother's utterance; (3) just the nouns in the utterance; (4) just the sentence frames in which the verb was placed; (5) the sentence frames plus the nouns; or (6) the videoclips, the sentence frames, and the nouns. With only the videoclip infor- mation, the participants made correct identifications of the target verbs only 7.7% of the time. Each addi- tional bit of information raised this level of accuracy significantly, until those with complete information, that is, condition 6, made correct identifications 90.4% of the time.
The relevance of these simulations to understand- ing how children actually acquire a lexicon is sup- ported by experimental studies that have demon- strated that children can also use the rest of the sentence as a source of information about word reference and
meaning. Two- and three-year-old children are better able to identify the referent of "Susie" if they are told "Susie is painting Jill" than if they are told "Susie is in this picture," and their choice of a referent for "Susie" is different depending on whether they hear "Susie is painting Jill" or "Susie and Jill are painting," thus
demonstrating that they use information in the struc- ture of the sentence to figure out who, in a picture that
they are presented, is "Susie" (Prasada & Choy, 1998; see also Goodman, McDonough, & Brown, 1998). Children's ability to use information in the structure of sentences as clues to novel word meaning has been
amply demonstrated with respect to nouns, verbs, and adjectives (e.g., Naigles, 1990; and see P. Bloom, 1996; Woodward & Markman, 1998 for summaries). Furthermore, Naigles and Hoff-Ginsberg (1998) found that the use of syntax was part of children's conven- tional word-learning process, in that the diversity of
syntactic frames in which 25 verbs appeared in mater- nal input predicted the subsequent order of acquisi- tion of those verbs. A more general suggestion that the syntax of input is a source of information that con- tributes to lexical development comes from findings that maternal mean length of utterance (MLU) is pos- itively related to the size of 1.5-year-old children's
comprehension and production vocabularies as as- sessed with a checklist (Bornstein et al., 1998).
Another relevant feature of input, in addition to
Hoff and Naigles 423
lexical and structural clues to meaning, is its sheer amount. One naturalistic source of evidence that amount of input matters is the finding that the rela- tive sizes of the Spanish and English vocabularies of
bilingually developing 1- to 2-year-olds in South Flor- ida are related to the relative amount of input they re- ceive in each language (Pearson, Fernandez, Lewedeg, & Oiler, 1997). In addition, children's overall rates of
vocabulary growth are related to the amount of speech they hear (Hart & Risley, 1995; Huttenlocher, Haight, Bryk, Seltzer, & Lyons, 1991). Amount of input is, of course, related to the frequency with which each word is presented and there is substantial evidence that frequency affects word learning. Children's first uses of a word are likely to match the most frequently occurring use of that word by the children's mothers (Harris, Barrett, Jones, & Brookes, 1988), and the or- der in which words appear in children's vocabularies is predicted by their frequency in input (Huttenlocher et al., 1991; Naigles & Hoff-Ginsberg, 1998). There are
complementary experimental demonstrations that
frequency in input is positively related to word learn-
ing (Schwartz & Terrell, 1983; Smith, 1999). One reason that frequent presentations may bene-
fit word learning is that multiple presentations are
likely to vary in the accompanying nonlinguistic and
linguistic contexts; thus, each presentation provides somewhat new information about word meaning. With respect to what types of variety matter, several researchers have argued that children require cross- situational information (Fisher, Hall, Rakowitz, & Gleitman, 1994; Pinker, 1989) because this reveals more aspects of a given word's meaning. In a direct assessment of the value of cross-situational informa- tion, Akhtar and Montague (1999) gave 2-, 3-, and
4-year-old children the sentence, "This is the modi one," paired with three different objects selected from a visible array of nine objects. Across all three age groups, the children were able to identify the com- mon attribute of those three objects and use it as a ba- sis for extending the new term, modi, to novel objects. For similar reasons, hearing words (particularly verbs) in a variety of syntactic environments should also be useful because each syntactic frame in which a verb
appears supports additional conjectures about the se- mantics of that verb (Gleitman, 1990; Naigles, 1996; Naigles & Hoff-Ginsberg, 1998; see also Waxman & Markow, 1998, for similar findings with adjectives). The finding that the syntactic diversity of the context in which verbs appeared in mothers' speech uniquely accounted for variance in both the frequency and the
syntactic diversity of the children's use of those verbs is consistent with that argument (Naigles & Hoff-
Ginsberg, 1998).
Other data suggest that children who hear a greater number of different words produce a greater number of different words. The number of word types in their mothers' speech has been found to be positively re- lated to the size of children's comprehension and pro- duction vocabularies (Bornstein et al., 1998). Cross- linguistic comparison shows that when mothers pro- duce more verb types (i.e., Chinese mothers who
speak Mandarin), children's spontaneous speech con- tains more verb types and tokens, and when mothers'
speech contains more or equal numbers of noun types (i.e., mothers who speak English and mothers who
speak Italian), children's speech includes more noun
types and tokens (Tardif, Shatz, & Naigles, 1997; see also Choi & Gopnik, 1995). In these data, the differ- ence in the relative usage of verbs and nouns was
only in types, not in tokens; therefore the data only provide evidence that the number of types has a
unique effect on children's vocabularies. That is an
important finding, however, because within a lan-
guage, the number of types and number of tokens tend to be highly correlated (e.g., Hart & Risley, 1992, 1995; Weizman & Snow, 2001). Thus, any relations be- tween the amount of input provided to children and children's vocabulary size that is found in naturalistic data could be either effects of word frequency, effects of the number of different words modeled, or some combination of the two.
In sum, the results of both experimental and natu- ralistic studies suggest that not only can children use the data-providing aspects of their conversational
input, but also that the availability of data in input affects children's lexical development. Taken to-
gether, these findings suggest that three different
data-providing properties of input are related to chil- dren's vocabulary development: sheer frequency of
presentation, number of different words, and rich- ness and variety of linguistic environments in which the words are placed.
Summary and Prospectus
Research findings suggest that the degree to which mother and child are mutually engaged in their con- versations as well as the data provided in the utter- ances that mothers produce in conversation are re- lated to children's lexical development. Integrating the accounts of how these two sources of information are used into a single theory of the process by which children use input to acquire a lexicon has been ham-
pered by the fact that little research has investigated the influence of both sources of support within a sin-
gle study. The present study was designed to do just that by looking for correlations between properties of
424 Child Development
the input that children hear and the size of their sub-
sequent vocabularies, focusing on both properties of
input that plausibly index the extent to which social
engagement makes meaning transparent and proper- ties of input that index the amount of nonsocial infor- mation in the utterances that children hear. The goal was to investigate the unique and combined contri- butions of these properties of input to children's vo-
cabulary growth.
METHOD
Participants
Participants were 63 children who resided in the midwestern United States and were between the ages of 18 and 29 months at the start of the study (age: M = 21.3 months, SD = 3.05). Thirty-three of the children came from high-SES families in which both parents were college educated, and 30 of the children came from mid-SES families in which both parents were
high school educated. Within the high-SES sample there were 9 firstborn boys, 7 firstborn girls, 7 later- born boys, and 10 laterborn girls; within the mid-SES
sample there were 8 firstborn boys, 8 firstborn girls, 8 laterborn boys, and 6 laterborn girls. All the families were White. All the mothers were native speakers of
English, were the primary caretakers for their chil- dren, and were not employed outside of the home for more than 15 hours per week.
The children were selected to be comparable in terms of their level of productive language use, and were all at the point at which they were just begin- ning to combine words. Each child was heard to pro- duce at least three different two-word combinations
during a preliminary screening visit, but no more than 50% of any child's utterances were multiword constructions, as assessed on the basis of the first
speech sample. The average MLU for the children was 1.27 (SD = .12). The age of the children was not a selection criterion. The sample is more fully described in Hoff-Ginsberg (1991).
Procedure
Children were videotaped in dyadic interaction with their mother at two time points, 10 weeks apart. The recordings were made in the participants' homes
during a mealtime, as the mothers were getting the children dressed for the day, and during toy play with
experimenter-provided toys. The durations of the mealtime and dressing interactions were allowed to
vary naturally and were taped in their entirety. The
toy play was taped for no more than 25 min. The av-
erage duration of the Time 1 tapings was 42.4 minutes (SD = 8.4). The interactions were transcribed by trained research assistants into the format required by the Systematic Analysis of Language Transcripts (SALT) software (Miller & Chapman, 1985). The mea- sures of input were based on the transcripts of the first visit (Time 1). The measures of child language were assessed from transcripts of both visits (Time 1 and Time 2).
Measures
Input measures. The measures of the data-providing properties of maternal speech included the total num- ber of utterances produced, the number of word to- kens (i.e., the total number of words) in the input samples, the number of word types (i.e, the number of different words), and the MLU. This latter measure indicates the degree of syntactic complexity in the ut- terances, and as such may be considered an index of the richness of the linguistic environment. In count-
ing word types, different forms of the same root were treated as the same word. Thus, for example, walk, walked, and walking were counted as one word type, as were table and tables. For the measures of the num- ber of utterances, word types, and tokens, no correc- tion was made for the individual differences in the duration of interaction, because these reflect real dif- ferences in the children's conversational experiences (see Hoff-Ginsberg, 1992, for a more complete argu- ment to this effect). The number of word tokens, the number of word types, and the MLU in morphemes were calculated using SALT.
Two measures were selected to index the degree to which maternal speech was likely to be referentially transparent by virtue of the social engagement of mother and child. The first was the number of mater- nal utterances produced during episodes of joint at- tention. Joint attention was coded only for the toy play interaction, because judging attentional focus can require eye gaze information, and only the toy play interaction was recorded in a manner that en- sured that both the mother's and child's faces were visible. Joint attention was defined following Toma- sello and Farrar (1986) and Tomasello and Todd (1983) as periods lasting at least 3 s during which the mother and child were both focused on the same ob-
ject or activity. All coding of joint attention was done
by the same research assistant. Reliability was as- sessed by comparing the research assistant's ratings on this measure with those produced by a second re- search assistant who independently coded 6 of the 63
play sessions. The two coders were always within 8
percentage points of each other in their estimates of
Hoff and Naigles 425
the total percent of utterances in joint attention; the correlation between the two coders' estimates was r(4) = .98.
The second measure of social engagement was the number of maternal utterances that were topic- continuing replies to child speech, as an index of the
contingency of maternal speech on child speech. To be coded as a topic continuing reply, a maternal utter- ance had to follow a child's utterance immediately and continue the topic of the child's utterance. Utter- ances were coded as topic continuing if they met one of the following conditions: the utterance (1) referred to any entity or event mentioned in the child's utter- ance, (2) was an answer to a question, (3) continued some patterned speech such as reciting the alphabet or a nursery rhyme, (4) commented on objects or events referred to in the prior utterance, or (5) was a
paraphrase of the prior utterance. The category of
topic-continuing replies was one of several in the scheme for coding the topic relations in mother-child conversation described in Hoff-Ginsberg (1987). In the present study, interrater agreement for this code was 87%, with a Cohen's K of .80, calculated on 220 ut- terances from excerpted portions of the mealtime and
toy play interactions in two different transcripts. Lastly, two other measures of the social-pragmatic
aspects of interaction were calculated: (1) the number of maternal utterances judged to be behavior direc- tives, and (2) the number of maternal utterances
judged to be intended as conversation-eliciting ques- tions. Behavior directives directed either the child's attention or behavior. Conversation-eliciting ques- tions were utterances intended to elicit verbal replies, including several categories of questions and prompts to answer questions. It has been argued that these measures are also related to the hypothesis that mu- tual social engagement is the basis for language learn-
ing because the relative frequency of directives and
conversation-eliciting questions that mothers use in- dicates the degree to which their purpose in interact-
ing with their child is to control behavior or engage in conversation (Hoff-Ginsberg, 1991; McDonald & Pien, 1982). Furthermore, Hoff-Ginsberg (1990), in an- other sample of mothers and children, found that children respond to conversation-eliciting questions more than they respond to other types of maternal ut- terances. Thus, a higher frequency of conversation-
eliciting questions would appear to be a good index of interaction that involves more mutual engagement. Interrater reliability for this code calculated between the coder and the first author yielded 82% agreement and a Cohen's K of .80, based on 201 coded utterances in excerpted portions of the mealtime and dressing segments of two transcripts. This assessment of reli-
ability was done at a different time and on different
transcripts than the assessment of reliability for topic continuity. Coders were blind to participants' SES.
Child language measure. To assess differences among the children with regard to the size of the vocabular- ies they used in spontaneous speech, all of the chil- dren's transcripts were truncated to the size of the shortest transcript so that the estimates would not be contaminated by differences among the children in the amount of their verbal output (see Hoff-Ginsberg, 1992; Richards, 1987). This procedure resulted in tran-
scripts for each child that were 90 utterances in length and were selected in approximately equivalent pro- portions from the mealtime, dressing, and toy play in- structions. On the basis of these speech samples, the total number of word types produced by each child was calculated using SALT. This count of word types in a speech sample does not provide an estimate of the size of the children's total vocabularies, but it does
provide estimates of the variety of vocabulary that children use. Therefore, we investigated how social-
pragmatic properties of mother-child conversation and the data-providing properties of the maternal ut- terances produced in these conversations compare in terms of predicting children's vocabulary diversity within a given fixed sample, not their entire vocabu-
lary size. These same 90-utterance samples were also used to calculate the MLU in morphemes, again using SALT.
RESULTS
Descriptive statistics for the child vocabulary data are
presented in Table 1; Table 2 presents descriptive sta- tistics for the input measures hypothesized to explain the child vocabulary data.
Correlations were calculated between the input measures based on the Time 1 language samples and the child vocabulary measures based on the Time 2
language samples, removing the variance attribut- able to variance in the children at Time 1. Such par- tialing was necessary to avoid obtaining correlations between input at Time 1 and child language measures at Time 2 that are only reflections of the effect of the
Table 1 Means and Standard Deviations for Child Vocabulary Measure
Time 1 Time 2
M SD M SD
Total word types 36.06 8.07 48.40 12.98
Note: Word counts are based on 90-utterance speech samples.
426 Child Development
Table 2 Means and Standard Deviations for Measured Proper- ties of Input (Time 1)
Input Property M SD
Data-providing properties Number of utterances 614 232 Number of word tokens 1,882 763 Number of word types 298 82 Mean length of utterance 3.56 .43
Social-pragmatic properties Number of utterances in joint attentiona 101 59 Number of topic-continuing replies 130 58 Number of behavior directives 120 60 Number of conversation-eliciting questions 193 90
a Coded for toy play session only.
children's language levels at Time 1 on both their in-
put and their future language levels (Newport, Gleit- man, & Gleitman, 1977). This procedure, however, is a
very conservative approach that will "underestimate parent effects on the child in cases where these effects have already manifested themselves by the time of the first observation" (Huttenlocher et al., 1991, p. 240).
Three of the four measures of the data-providing properties of input were found to predict children's vocabulary: the number of word tokens, the number of word types, and the MLU were all positively re- lated to subsequent lexical growth. Of the data-
providing measures, only the total frequency of utter- ances bore no relation to vocabulary development. No measure of the social-pragmatic features of inter- action predicted vocabulary. The values of the partial rs obtained are presented in Table 3.
The next step in data analysis was to pursue the
Table 3 Partial Correlations between Input Properties at Time 1 and Child Vocabulary at Time 2
Number of Word
Types in
Input Measure Child Speech
Data-providing features Number of utterances .05 Number of word tokens .21* Number of word types .22* Mean length of utterance .55***
Social-pragmatic features Number of utterances in joint attention .02 Number of topic-continuing replies .18 Number of behavior directives -.05 Number of conversation-eliciting questions -.03
Note: Variance attributable to the number of word types in child
speech at Time 1 was removed.
*p < .05 (one-tailed); ***p < .001. (one-tailed).
significant findings to ask how the predictive data-
providing properties of input operated together to ac- count for variance in children's vocabularies. Analy- sis of the intercorrelations among these predictive properties of input revealed that the number of word tokens and the number of word types in input were so highly correlated as to make their effects statisti- cally unseparable, r(61) = .89, p < .001. For further use in the tests of predictive relations, one measure- the number of different word types-was selected. The MLU of input was also significantly related to the number of word types in input, but that correlation was more moderate, r(61) = .48, p < .001, and both of those variables were retained as separate predictors.
The reduced set of predictors-input MLU and number of word types in input-were entered into a hierarchical regression analysis with the child vocab-
ulary measure at Time 2 as the outcome. Child vo-
cabulary at Time 1 was entered first, analogous to the
previous partialing procedure; number of words types in input was entered second; and input MLU was en- tered last. Input MLU was entered last because the
positive correlation between the MLU and child vo-
cabulary was not specifically predicted by any hy- pothesized mechanism of word learning, although it had been observed once before (Bornstein et al., 1998). We wanted to remove from the MLU any predictive power carried by properties of input that were pre- dicted by hypothesized mechanisms of learning. The results, presented in Table 4, confirmed that the num- ber of word types in input was a significant predictor of child vocabulary when analyzed alone, but the MLU accounted for more variance. Furthermore, in the final model with both word types and MLU as
predictors, only the MLU was a significant predictor. One last analysis was conducted to ensure that the
observed relation between the MLU of input and child vocabulary was not spurious. It is possible that children who hear longer utterances also produce longer utterances, and thus use a greater number of different words in a 90-utterance speech sample not because their vocabularies are bigger, but because the number of word tokens in the speech sample is
Table 4 Hierarchical Regression Predicting Time-2 Word Types in Child Speech
Adjusted Predictors R2 R2 AR2 Final 3
Child word types (Time 1) .20 .18 .20*** .31**
Input word types .24 .21 .04* -.02
Input mean length of utterance .44 .42 .20*** .53***
*p < .05; **p < .01; ***p < .001 (one-tailed).
Hoff and Naigles 427
Table 5 Hierarchical Regression Predicting Time-2 Word Types in Child Speech, Removing Variance Attributable to Child Mean Length of Utterance (MLU)
Predictors R2 AdjustedR2 AR2 Final P
Child word types (Time 1) .20 .19 .20*** .31** Child MLU (Time 2) .61 .59 .41*** .53***
Input word types .62 .60 .01 .03
Input MLU .65 .63 .03* .24**
*p < .05; **p < .01; ***p < .001 (one-tailed).
greater. To test this possibility, the regression analysis in Table 4 was rerun with variance in children's MLU at Time 2 removed before the input predictors were entered. As Table 5 shows, the outcome of this analy- sis was that input MLU remained a significant predic- tor of child vocabulary.
DISCUSSION
The foregoing analyses of the relation between prop- erties of input and children's subsequent vocabulary use provide a snapshot of children around the age of 24 months as they use language experience to build their productive vocabularies. The observed patterns of correlation suggest that at this point in develop- ment, variation in the extent to which mothers and children are mutually engaged in their conversations has little influence on the richness of the vocabulary that children will come to use. In contrast, variation in the lexical richness and syntactic complexity of the ut- terances that mothers produce in those conversations does account for variation among children with re-
gard to their subsequent production vocabularies. These findings are consistent with the theoretical
arguments of the present study that the process of lexical development can be understood only by con-
sidering the data-providing function of children's conversational experience in addition to the social
support for language development that conversation
may provide.
The Social-Pragmatic Basis of Lexical Development
Previous findings that have been interpreted as ev- idence for the social-pragmatic basis of lexical devel-
opment have, in large part, come from either correla- tional studies that found that differences in the degree to which children experience joint attention predicted subsequent vocabulary, or experimental demonstra- tions that showed that children have the ability to use
social-pragmatic cues to a speaker's communicative intentions. The correlational studies primarily used
maternal checklists or diaries as the basis for their es- timates of child vocabulary size, whereas the pres- ent study used a fixed-size sample of spontaneous speech. Maternal checklists have not been subjected to the usual criteria of inter- and intrarater reliability (L. Bloom, 1993). One possibility, as discussed earlier, is that the observed child differences in vocabulary size assessed by checklist can be attributed to mater- nal differences in sensitivity to child language, be- cause, after all, mothers fill out checklists based on the interactions that they have had with their child. To be sure, these interactions are more extensive than those recorded by experimenters; however, they are also more likely to be selectively filtered. For example, Carpenter et al. (1998) found correlations of joint en-
gagement and maternal following with children's
subsequent word comprehension (assessed via the MacArthur Communicative Developer Inventory [CDI] checklist), but not production (also assessed via the CDI). At such a young age (12-15 months), mothers' estimates of their children's levels of word compre- hension are extremely likely to be differentially influ- enced by maternal sensitivity.
The foregoing arguments suggest, then, that some of the correlations between mutual engagement and child vocabulary previously observed in naturalistic data are spurious. We do not make that claim with
respect to all the previously observed correlations, however. Some correlations, not involving maternal
report measures of child language, are quite probably real, but it is worth noting that (1) they involved chil- dren who were younger than the participants in the
present study, and (2) they involved maternally guided rather than child-guided mutual engagement. Thus, previous findings that maternal responsive- ness, contingency, and follow-in behavior benefit vo-
cabulary development may reflect the fact that these
pragmatic features of maternal language are particu- larly important when children are too young to have the skills to discern maternal intentions and are not
sufficiently linguistically advanced to use lexical and
syntactic cues to meaning. At this early stage- between 9 and 18 months-the relevant property of interaction may be how well the mother structures the interaction so that children hear the labels of the
things that they are already attending to. The only thing social about this support for word learning is the social skill of the mother in following her child's attentional focus and timing her words to match. From the child's point of view, the benefit is that of
temporal contiguity between attention and input. Similarly, the finding that individual differences
among children under 18 months with regard to their
joint attention skills predict subsequent language de-
428 Child Development
velopment (Laakso et al., 1999; Mundy & Gomes, 1998) may merely reflect the fact that being in joint attention makes temporal contiguity of the child's at- tention and the word presented more likely. That is, the benefit is real and depends on a social skill-this time the child's-but is not the social skill of reading others' intentions. By the age of 24 months, develop- mental differences in these skills among children are likely to have evened out, and all children may have a sufficient level of skill such that any remain-
ing differences have little consequence for language development.
The last type of finding that is used to argue for the social-pragmatic view of lexical development is the experimental finding that children can read speaker intentions and use them as clues to word meaning (Baldwin, 1993; Golinkoff et al., 1999; Tomasello & Barton, 1994). This ability, however, has been demon- strated only in children over 18 months of age, and thus it could not be part of the early social basis of word learning. In principle, children over 18 months could use this ability to learn words, but in the
present study no evidence of this ability was found in naturalistic data. The present study investigated the role of the child's reading of speaker communicative intention only indirectly. We reasoned that if children found significant information in reading the commu- nicative intentions of their conversational partners, then children whose mothers more often expressed readable communicative intentions-indexed by ut- terances spoken in joint attention and by the related- ness of the topics of maternal speech to prior child
speech-should be advantaged in vocabulary devel-
opment. No such advantage was found, however. It is always difficult to interpret a null result. It is
possible that more direct measures of intention read-
ing and/or other measures of vocabulary (e.g., com-
prehension) would have produced positive results. It is also possible that the pattern of positive findings for data-providing properties and null findings for
social-pragmatic properties of conversation reflects that the data-providing properties of input can be more reliably assessed from a limited sample of inter- action than can the social-pragmatic properties. This concern may particularly pertain to the measure of
language use in joint attention because it was assessed
only for the toy play interaction. We cannot, and do not, conclude from the current findings that there is no effect of mutual engagement on language devel-
opment at this stage. Some degree of mutual engage- ment is necessary, if only to sustain the interactions that provide the child with input. On the other hand, the present database for assessing social-pragmatic features was as large or larger than that used in most
previous studies that have found effects at younger ages, and toy play is the most widely used interactive
setting in both naturalistic and experimental studies. Thus, the present findings deserve interpretation.
The findings of the present study suggest a devel-
opmental progression in which social-pragmatic properties of conversation-which result primarily from maternal effort-produce information that is used by children at the very earliest stages of word
learning but apparently is not used at later stages (around 24 months of age). This account has points that both agree and disagree with other recently pro- posed accounts. For example, Hollich et al. (2000) asked children aged 12, 20, and 24 months to learn novel words for objects, and compared the usefulness of perceptual and pragmatic information for making the correct object-word mapping at each age. Hollich et al. found that the youngest children did not use ex-
perimenter eye gaze (i.e., child-guided joint atten- tion) as a source of information about the referent of the novel word; however, the older children (20 months and older) did. Their findings with the young- est group led them to conjecture that very young chil- dren's initial learning of words is not based on their
reading of the communicative intents of others. Our
understanding of the data from naturalistic studies is in line with this view: the usefulness of social-
pragmatic bases of information for child word learn- ers around 10 to 15 months of age is due to maternal
sensitivity, not children's social-cognitive abilities. The findings in this study, however, do not converge with those of Hollich et al. (see also Baldwin, 1993) with respect to word learning in children over 18 months. That is, their experiments found that chil- dren 18 months and older can read adults' communi- cative intents en route to learning novel words. In contrast, the present study's data indicate that chil- dren are apparently not using this ability as they go about the process of actually learning words of En-
glish. That is, even though children over 18 months of
age can use speaker intent, it appears not to be a par- ticularly important source of information for actual word learning. Thus, the question of what children can use in word learning, which experiments address, and what children actually do use, which naturalistic data address, are two different questions. Moreover, the current findings suggest that these two questions have different answers for 24-month-old word learn- ers. A similar suggestion has been made by Carpenter et al. (1998), who allowed that the relations between
joint attentional engagement and children's language development that they observed may be true during only the earliest stages of language development. Later, children can and do use more complex sources
Hoff and Naigles 429
of information. One final possibility that only can be considered at this point is that the toddlers' newfound
ability to read intentions beginning at 18 months may mean that the usual measures of social-pragmatic en-
gagement (joint attention, maternal topic following) are no longer the right ones; what becomes needed- and what no one has yet analyzed in this vein-is a direct assessment of children's discernment of their mothers' communicative intents in naturalistic interaction.
In sum, the previous findings, in conjunction with the findings of the present study, suggest that the
social-pragmatic features of mother-child conversa- tion matter most to vocabulary development early in the second year of life. The particular social-pragmatic features that appear to matter-maternal responsiv- ity, contingency, and following of the child's atten- tional focus-are all things that mothers do to maxi- mize the match between the child's attentional focus and the speech the child hears and to reinforce the child for participating in communicative interaction. This may indeed be a crucial social-pragmatic foun- dation for language development. The child contrib- utes to these interactions the capacity to be engaged, but the social-pragmatic work that benefits vocabu-
lary development in particular is done by the mother. The child's social abilities and inclinations are a pre- condition for learning, but they are not part of the ex-
planation, at that early stage, of how children figure out the meaning of the new words they hear. After 18 months, children do have the ability to read others' intentions, but this has been demonstrated only in ex-
perimental settings. Thus far, there has been no em-
pirical demonstration that the exercise of children's
experimentally demonstrated ability to read inten- tions and use them as clues to word meaning plays a
significant role in accounting for conventional vocab-
ulary development. This may be because, as was ar-
gued in the Introduction, naturalistic interaction sim-
ply does not provide the carefully constructed cues that experiments have provided, or because other sources of information prove more important.
The Data-Analytic Basis of Lexical Development
The analyses of correlations between properties of
input and children's subsequent vocabularies identi- fied three data-providing features of input as positive predictors: the number of words produced, the lexical richness of the vocabulary used (i.e., the number of different words), and utterance length. The number of utterances in input was unrelated to vocabulary growth. This latter finding is consistent with the null
findings with respect to the social-pragmatic mea-
sures of engagement. Whether or not the mother talks to the child is essentially a measure of engagement. The present findings argue that it is not the fact that mothers talk to their children, but rather the lexical and syntactic properties of what they say, that is rele- vant for vocabulary development. These findings are consistent with Huttenlocher et al.'s (1991) finding that the amount of input predicts vocabulary growth, because in that study amount was measured in terms of number of words, not number of utterances. In the
present data, number of words (i.e., tokens) was sim-
ilarly a significant predictor of child vocabulary, but it was also highly correlated with the number of differ- ent words (i.e., types). Of these two highly correlated measures, only the number of types was retained in further analyses. The observed benefit of lexical rich- ness, however, must be interpreted as a benefit of not
only lexically varied input but also of a large amount of such input. Although it is an interesting intellectual exercise to consider how the amount and lexical vari-
ety of input might independently benefit lexical de-
velopment, the present data show that in naturally occurring maternal speech, the two properties are too
highly correlated to be able to separate their effects. This finding is consistent with those of Hart and Ris-
ley (1992, 1995) and Weizman and Snow (2001) who found that mothers who produced more words when
talking to their children also produced a greater num- ber of different words. Relatedly, Huttenlocher et al. (1991) found that more talkative mothers did not use more word types in equivalent-sized samples of
speech. Nonetheless, the by-product of talking more
appears to be using a bigger vocabulary. Multiple regression analyses further revealed that
this benefit of lexically rich input was not indepen- dent of the benefit of syntactic complexity. It is a prop- erty of speech to children, perhaps of speech in gen- eral, that use of a more varied vocabulary is associated with production of longer utterances. The positive correlation between the lexical richness of input and child vocabulary is carried by the effect of the MLU. Maternal MLU uniquely accounted for a significant portion of the variance in children's vocabularies. These findings are consistent with other findings in the literature that the amount of input, the lexical richness of input, and maternal MLU are positively associated with children's vocabulary sizes (Born- stein et al., 1998; Hart & Risley, 1995; Huttenlocher et al., 1991). The present findings suggest, for the first time, that among these correlated predictors, the MLU accounts for the greatest portion of the variance in child vocabulary sizes.
What does the observed benefit of large amounts of lexically rich and, in particular, syntactically com-
430 Child Development
plex input suggest about how children use input to build a lexicon? Large amounts of input provide re-
peated exposure to the same word, which is likely to be useful for several reasons. First, as Huttenlocher et al. (1991) argued, repeated exposures function as
multiple learning trials. Second, words presented fre-
quently are likely to be presented in a variety of situ- ations and syntactic frames, allowing for both cross- situational learning and syntactic bootstrapping. Frequency may be particularly relevant when the out- come measure is production based, because frequent presentations of a word in input may not only help build a lexical entry by providing more opportunities to obtain information about word meaning, but also
may also have a separate effect on the ease with which children can retrieve a word in the course of
talking. One benefit of lexical richness seems obvious: the more words a child hears, the more words the child can potentially learn. Additionally, to the extent that children know-even partially-the meaning of the other words presented with a new word, that in- formation constrains the possible interpretation of the new word. This finding is wholly consistent with the results of simulations that demonstrate a benefit of complex input to a variety of language-learning tasks (Gillette et al., 1999; Plaut & Kello, 1999; Siskind, 1996). What is interesting is that this contradicts the notion that simple input is better with regard to chil- dren's language acquisition.
The benefit of longer MLU also contradicts the
simpler-is-better notion, but it is consistent with evi- dence about potential sources of clues to word mean-
ing. Other known words in the utterance, as well as the structure of the utterance in which a new word
appears, provide clues to the meaning of that new word. Longer utterances may provide more of these sources of information than do shorter utterances- at least for children old enough to take advantage of the information and within the range of utterance
length to be found in maternal child-directed speech. Longer utterances may also be long because they con- tain explicit information about new word meaning (Clark, 1999; Koenig & Naigles, 1996). For example, hearing a new word, bat, in a sentence such as "That's a bat," is less useful for building a new lexical entry than hearing bat in the sentence, "Bats have big wings and they live in caves." Such additional information
may not only contribute to completing a lexical entry, but also may result in deeper processing of that new word, with all the benefits of depth-of-processing to
memory.1 This explanation is consistent with Della Corte, Benedict, and Klein's (1983) finding that chil-
1 The authors are grateful to Tom Sawallis for this suggestion.
dren's noun vocabularies are related to the amount of de-
scription their mothers provide, and not to the amount of task-oriented, child-oriented, or context-oriented talk. It
suggests that building a vocabulary depends not only on
hearing words, but also on finding information about word meaning in the speech that one hears.
Summary and Conclusions
Acquiring a vocabulary consists of learning map- pings between sound sequences and meanings. An obvious prerequisite to this process is development of the conceptual understandings that sound sequences express (L. Bloom, 1993). Also necessary is a process for figuring out which meanings are being expressed by which sound sequences-the part of the process of lexical development addressed here. The combined results of this and previous studies suggest that the
process of word learning makes use of both the hu- man child's social interest in and ability to interact with others and the child's computational ability to extract information from the speech presented in those interactions. Evidence that babies as young as 7 months can learn distributional regularities in input (Saffran, Aslin, & Newport, 1996) and have actually learned some of the distributional regularities that constitute the phonotactics of their language (Jus- czyk, 1997) suggests that the computational mecha- nism starts working early on. The fact that some se-
verely asocial individuals, such as some individuals with autism, can acquire aspects of language suggests that the computational mechanisms alone may be sufficient for the acquisition of linguistic competence, if not communicative competence.
On the other hand, the rich body of evidence on children's capacities for joint attention and the evi- dence that time spent in joint attention predicts lan-
guage development suggest that in the normal course of events, language acquisition is very much a social
process. A critical look at the data, however, suggests that the nature and extent of the social contribution
may be less than sometimes has been claimed. The so- cial nature of humans and human interaction appear to do two things for language acquisition. One, social interaction provides the motivation and occasion for
language use and thus brings the child into the con- text in which language-advancing data are provided. Second, children's social cognitive capacities to infer the intentions of others may actually provide data about word reference that is used by the computa- tional mechanism. Just how significant a source this information is in word learning remains to be demon- strated. It depends on how often the mutual under-
standing it requires actually occurs and on the rela-
Hoff and Naigles 431
tive value of that source of information over other information also available in the environment.
Although both social and data-analytic processes contribute to lexical development, their relative im-
portance changes over the course of development. When joint attention skills begin to develop, there are
developmental differences among children that will result in individual differences in the rate of language development. Similarly, differences among mothers in the extent to which they respond to these emerging abilities will affect language development. Thus, at this point-between 9 and 18 months-variability in the experience of joint attention may be the greatest source of variability affecting lexical development. As children mature, early developmental differences in the capacity for engagement recede as even the slower developing children acquire this capacity. As all children become competent at staying engaged and following their mother's focus, individual dif- ferences in maternal responsivity and contingency lessen in importance. Instead, what comes to matter is how much data is available and how informative are those data. The particular qualities that appear to make data useful suggest that the child's armamen- tarium of computational devices includes mecha- nisms for extracting information from the nonlinguistic context and from the content and structure of utter- ances, a mechanism for accruing that extracted infor- mation across multiple presentations, and a mecha- nism for inducing what is common among those accrued instances. The richer the information, the faster the process occurs.
The present argument does not deny the necessity of the social nature of humans nor the significance of the experience of social interaction to language devel- opment. It merely asserts that the explanation of how
language develops as a result of experiencing social interaction cannot be written solely in the vocabulary of social processes. In those social interactions, children obtain data regarding the form of language and there are computational mechanisms that children bring to bear on those data to produce linguistic knowledge. Thus, a full account of language development must be written in both the vocabulary of social processes and the vocabulary of computational mechanisms.
ACKNOWLEDGMENTS
Data collection was supported by the National Insti- tute of Child Health and Human Development, grant # HD20936, and by a Spencer Foundation grant to the first author. Portions of this research were presented at the 23rd Boston University Conference on Lan-
guage Development, Boston, 1998; and the VIIlth In-
ternational Congress for the Study of Child Lan-
guage, San Sebastian-Donostia, Spain, 1999. The authors thank Carol Fowler, Janellen Huttenlocher, Alan Kersten, Brett Laursen, and the anonymous re- viewers for conversations on this topic and for com- ments on earlier versions of this article.
ADDRESSES AND AFFILIATIONS
Corresponding author: Erika Hoff, Department of
Psychology, Florida Atlantic University, 2912 College Avenue, Ft. Lauderdale, FL 33314; e-mail: ehoff@ fau.edu. Letitia Naigles is at the University of Con- necticut in Storrs.
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