Clinical Linguistics & Phonetics, Early Online, 2011, 1–18
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Cognitive state verbs and complement clauses in children
with SLI and their typically developing peers
AMANDA J. OWEN VAN HORNE & SHANJU LIN
Department of Communication Sciences & Disorders, University of Iowa, Iowa City, IA, USA
(Received 16 September 2010; Accepted 14 April 2011)
Abstract
This study investigated the use of cognitive state verbs (CSVs) and complement clauses in children with
specific language impairment (SLI) and their typically developing (TD) peers. In Study 1,
conversational samples from 23 children with SLI (M ¼ 6;2), 24 age-matched TD children
(M ¼ 6;2) and 21 vocabulary-matched TD children (M ¼ 4;9) were analysed for the proportional
use of CSVs, verb types, co-occurrence with complement clauses and syntactic frame types. Children in
all three groups had similar performance in all measures. Study 2 compared a subset of children on CSV
use in conversational and narrative/expository samples. Conversation elicited more high-frequency
verbs, whereas narrative/expository samples elicited more low-frequency verbs. Children with SLI
used fewer different verbs and were less likely to combine low-frequency verbs with a complement
clause than their TD peers. We conclude that these observed deficits can be attributed to limitations in
lexical knowledge rather than a syntactic deficit.
Keywords: specific language impairment, syntax, verb frequency, cognitive state verbs, complement
clauses
Introduction
The hallmark characteristic of language use by English-speaking children with specific
language impairment (SLI) is a deficit in the use of verb morphology. Children with SLI
have also documented deficits in verb semantics (Fletcher and Peters, 1984; Watkins, Rice,
and Moltz, 1993; Kelly, 1997; Leonard, Miller, and Gerber, 1999; Hansson and Bruce,
2002). Researchers have attempted to determine whether these observed deficits are attributable to the semantic or syntactic properties of verbs by investigating control of different verb
subclasses. For instance, Kelly (1997) investigated the use of motion and change of state
verbs through an experimental elicitation task. Whereas the children with SLI did not differ
from their typical peers with regard to the number of different verbs or the number of general
all purpose (GAP) verbs produced; they were more likely to make semantic substitutions than
their peers (e.g. substituting break for changed colour). Similar results have been observed for
Swedish (Hansson and Bruce, 2002). In an elicitation task, children with SLI were equally
Correspondence: Amanda J. Owen Van Horne, Department of Communication Sciences & Disorders, Delta Center, 250 Hawkins
Drive, 121A SHC, University of Iowa, Iowa City, IA 52242, USA. Tel: 319-335-6951. E-mail: [email protected]
ISSN 0269-9206 print/ISSN 1464-5076 online © 2011 Informa UK Ltd.
DOI: 10.3109/02699206.2011.582226
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2
A. J. Owen Van Horne & S. Lin
capable of labelling an action, but they were less proficient at producing causative alternations
(e.g. the boy rolled the ball / the ball rolled / the ball was rolled by the boy) than their typical
peers. They relied more heavily on immature strategies (verb þ adjective) rather than on the
passives and periphrastic constructions observed in age-matched children (King, Schelletter,
Sinka, Fletcher, and Ingham, 1995; Loeb, Pye, Richardson, and Redmond, 1998). Given
that part of knowing a verb is knowing in which structures it may be used (Goldberg, 1995),
the question of syntactic or semantic deficits remains.
In this article we further explore the interaction between verb semantics and syntax by
examining the use of cognitive state verbs (CSVs) and the syntactic frames associated with
these verbs in the spontaneous language of 5–8-year-old children with SLI and their age- and
vocabulary-matched typically developing (TD) peers. CSVs are of particular interest because
they are complex from both semantic and syntactic perspectives. Frequency effects and the
use of vocabulary-matched peers may allow us to differentiate the source of the deficit. In the
following, we review the properties of CSVs and the developmental trajectory of these verbs in
the language of TD children and children with SLI.
Cognitive state verbs – development and use
CSV use in children has been well studied because of its potential to shed light on cognitive,
semantic and syntactic development in different populations (e.g. Johnston, Miller, and
Tallal, 2001; de Villiers and Pyers, 2002; Miller, 2004, 2006; Lee and Rescorla, 2007).
CSVs communicate information about mental states and actions, such as thought (know,
forget), emotion (anger, enjoy), perception (see, hear) and desire (want, hope). These verbs
are difficult for a variety of reasons. They are abstract at the semantic level, generally
representing unobservable events (Gillette, Gleitman, Gleitman, and Lederer, 1999).
Appropriate use requires some rudimentary understanding of perspective taking, politeness
and/or theory of mind (Shatz, Wellman, and Silber, 1983; Johnston et al., 2001), as well as
appropriate grading of the semantic information associated with the verbs (Moore, Furrow,
Chiasson, and Patriquin, 1994).
In addition to the cognitive and semantic demands, these verbs are complex at the syntactic
level because they often co-occur with complement clauses (Gleitman, 1990; Naigles, 2000;
Nixon, 2005). Each verb is associated with one or more syntactic frames that must be learned
and linked to the target verb. Notice that want and think, two different CSVs, are not
interchangeable as far as the syntactic frames go (asterisk marks ungrammatical utterances;
e.g. I want him to go home; *I think him to go home; I think that he went home; *I want that
he went home). While want and think differ in terms of their semantics, this is not the sole
reason for the fact that they require different sentence frames. Verbs with similar meanings
may actually take different syntactic frames (e.g. say and tell : I told/*said him to go home; I
said/*told that he should go home), leading researchers to hypothesize that verb frame
information is stored in the lexicon rather than being a syntactic operation (Goldberg,
1995, 2006). These cognitive, semantic and syntactic demands make learning and using
CSVs potentially challenging for both TD children and children with SLI (Eisenberg, 2003;
Owen and Leonard, 2007).
CSVs commonly take full clauses as their direct object (also known as a complement clause
or propositional clause). TD children start producing complement clauses between 2 and 3
years of age, initially producing non-finite complements (e.g. I want to go home) followed
rapidly by finite complements (e.g. I think (that) he has a ball ; Bloom, Rispoli, Gartner, and
Hafitz, 1989; Diessel, 2004). Children initially restrict production to high-frequency (HF)
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Cognitive state verbs and complement clauses
3
complement-taking verbs used in a formulaic fashion (Bloom et al., 1989; Diessel and
Tomasello, 2001). For instance, young children may begin using phrases like I think to
indicate ‘maybe’ as in Daddy is home, I think and you know to call attention to something,
for example, You know, she is a doctor, rather than with their full propositional force. Adults
also use these common mental verbs as pragmatic markers, but are assumed to understand
the full propositional intent. Additional evidence that children have limited understanding of
the nuances of these verbs comes from Peskin and Astington (2004). Exposure to metacognitive language increased children’s use of these terms, but did not lead to measurable gains in
comprehension. Development of true propositional use in children is gradual, with onset
associated with the development of theory of mind (Diessel and Tomasello, 2001; Diessel,
2004). Development continues through high school. Astington and Olson (1990) showed
significant growth between 6th and 10th grade in a study of reading comprehension/word
replacement task with typical adolescents. Nippold, Ward-Lonergan, and Fanning (2005b)
examined the use of metacognitive terms in persuasive writing with typical 11-, 17- and
24-year-olds and found an increase in the use of CSVs with age.
Despite this protracted developmental trajectory, there is evidence that typical preschool
children do use these verbs flexibly. Nixon (2005) studied the relationship between mental
verb use and complement clauses in the spontaneous speech of 4- and 5-year-old TD
children. Following Diessel and Tomasello (2001), Nixon (2005) found that when CSVs
were used to express mental states, they were more likely to co-occur with complement
clauses than when these same verbs were used as pragmatic markers. Thus, co-occurrence
of a CSV with a complement clause may represent syntactic mastery but also indicates an
understanding of the lexical force of the verb. Kidd, Lieven, and Tomasello (2006) asked 3and 4-year-old children to imitate grammatical and ungrammatical sentences using HF and
low-frequency (LF) CSVs (e.g. I think/pretend she is riding away on the horse; I think/
pretend him running away from the dog). Children were more likely to produce correctly the
HF verb þ complement clause combinations and to correct or alter the LF combinations.
The most common changes were to change from an LF verb (e.g. pretend) to a HF verb (e.g.
think). Kidd et al. (2006) argued that the verb frequency in combination with how often
children hear that verb in the particular sentence frame was critical for accurate imitation.
However, even when children can produce sentences containing CSVs, we may overestimate their knowledge of the verb semantics. Owen and Leonard (2006) examined the
production of finite and non-finite complement clauses by children with SLI, and their ageand vocabulary-matched peers using seven verbs in an elicited production task. All seven verbs
were used in both finite and non-finite frames by all children, but children in all three groups
also frequently switched syntactic frames, changing the meaning of the sentence in the process
(e.g. producing the target Ernie decided that Elmo should wear a hat as Ernie decided to wear
a hat, changing who is the hat-wearer). Such switches were particularly frequent for less
common verbs (e.g. decide and forget). They suggest that children do not understand how
the verb and the syntactic frame interact within an utterance (Owen and Leonard, 2007).
Complex syntax, CSV and children with SLI
There is a general agreement that preschool-aged children with SLI show areas of weakness in
the use of complement-taking verbs and complex syntax, including delayed onset, greater
error rates and decreased use. For instance, Johnston et al. (2001) found that 4-year-old
children with SLI used cognitive state terms less often than mental-age-matched peers who
were close in chronological age and at a rate similar to their language-matched peers who were
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4
A. J. Owen Van Horne & S. Lin
on average 2 years younger. In the second study, utilizing children with more severe language
deficits, the children with SLI were more likely to use verbs of communication as compared to
mental verbs, whereas the mean length of utterance (MLU)-matched group used both verb
classes equally often. The authors speculated that the syntactic demands associated with
CSVs could be one reason for delayed use by the SLI group.
That said, these findings are not supported by studies of older children or studies using
alternative elicitation techniques. Norbury and Bishop (2003) asked 17 children with SLI
between 6 and 10 years of age, along with typical children and other clinical populations (high
functioning autism, pragmatic language impairment), to retell the story Frog Where Are
You? There were no group differences in evaluative references, including the use of mental
terms and references to states of mind. This set of words consisted of a broader set of words
than just CSVs (e.g. crying, naughty). Nonetheless, there was a significant correlation
between the use of such mental-state terms and overall complex syntax use. Reilly, Losh,
Bellugi, and Wulfeck (2004) also examined cognitive state term use and complex syntax
elicited via frog story narratives from 4- to 12-year-old children with SLI and a variety of other
clinical populations (focal brain lesion, Williams syndrome). They found no differences at
any age examined between TD children and children with SLI with regard to the use of CSVs.
It is not clear whether the discrepant findings across the studies are due to the age of the
children, the size of the samples or the elicitation methods.
Despite disparate findings on the rate of use of CSVs, the idea that CSV deficits might be
related to syntactic demands does seem supportable based on the studies examining the use of
complex syntax in these children. Both Norbury and Bishop (2003) and Reilly et al. (2004) do
document deficits in complex syntax at all ages for these children. Similar results have been
found in conversational samples (Eisenberg, 2003; Schuele and Wisman Weil, 2004; Schuele
and Dykes, 2005) and in sentence elicitation tasks (Eisenberg, 2004; Owen and Leonard,
2006; Owen, 2010). This is not just true for complex syntax in general, but is specifically
linked to syntactic structures associated with mental verbs. Using omission of past tense as a
measure of processing difficulty, Owen (2010) showed that 5–8-year-old children with SLI
have greater difficulty with the finite complement clauses associated with mental verbs than
with clauses that use action verbs. Interestingly, younger TD children matched on MLU and
expressive vocabulary skills were even worse than the SLI group at producing complement
clause sentences accurately, linking the problems to general language level rather than
disordered language status.
Once again, though, the differences are less clear when we turn to older children.
Marinellie (2004) found that school-age TD children (mean age: 10 years) used significantly
more complex syntax in 100-utterance conversational language samples than the children
with SLI. However, unlike previously mentioned studies (e.g. Eisenberg, 2003, 2004; Owen
and Leonard, 2006; Owen, 2010; Schuele and Wisman Weil, 2004; Schuele and Dykes,
2005), both groups performed similarly in their use of CSVs and full propositional clauses.
Returning to the role of verb frequency, three verbs accounted for 70% or more of the
contexts for complement clauses for both groups of children. This reliance on HF verbs
makes it difficult to determine whether these children are truly proficient and flexible in their
use of CSVs. It is possible that they are reliant on HF frames in such a way that masks
underlying deficits. The focus of Marinellie’s study was on syntax use and so CSV/complement clause use was not probed further. By the time children are 12–15 years of age, it is
difficult to document the differences between groups in complex syntax, even when more
formal narrative contexts are used (Wetherell, Botting, and Conti-Ramsden, 2007).
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Cognitive state verbs and complement clauses
5
Our purpose in carrying out this study was twofold. First we wished to answer a clinically
oriented question: Do children with SLI have problems with the use of CSVs as compared to
their TD peers beyond the preschool years? Previous work in the preschool age range has
demonstrated clear deficits in verb use and syntactic complexity (e.g. Johnston et al., 2001;
Schuele and Dykes, 2005). However, more general studies of older children present conflicting results, with some suggesting that these children continue to have difficulty with complement clause and cognitive state term use as they get older (King and Fletcher, 1993; Reilly
et al., 2004) and others suggesting that this may be an area that resolves (Marinellie, 2004;
Reilly et al., 2004; Wetherell et al., 2007). Our data are focused narrowly on CSVs and come
from children between 5 and 8, allowing us to examine whether children with SLI do indeed
improve relative to their peers in their use of CSVs and complement clauses as they move out
of the preschool years. Here the most relevant comparisons are with age-matched children.
Our second question is more theoretical in nature: If children with SLI have difficulty with
CSV use, can this difficulty be attributed to a syntactic or semantic deficit? To address this
question we divide the verbs into HF and LF verbs based on Child Language Data Exchange
System (CHILDES) frequency counts. If the deficits are primarily semantic in nature, we predict
that those verbs that are of HF will be used proficiently by all children, while the children with SLI
will show particular difficulty with the LF verbs, producing fewer verb types than their typical
peers, using these verbs less often than their peers and using less varied syntactic frames than their
peers. If the deficits are primarily syntactic in nature, we predict that children with SLI will show
deficits in verb use that are not frequency driven. Specifically, group differences in complement
clause use will be observable for both HF and LF verbs, suggesting that producing the grammatical form is the primary difficulty. Type-based differences across groups would also not be
expected if semantic learning is proceeding as expected for these verbs. Furthermore, by including a vocabulary-matched group in our study, we also allow for the examination of lexicon
differences. If the differences are attributable to the children’s general vocabulary knowledge, we
might expect the children with SLI to pattern similarly to their younger peers who have been
matched on expressive vocabulary. However, a syntactic deficit would likely manifest itself as
performance that is even worse than the vocabulary-matched group, given that vocabulary skills
often are better than morphosyntax in these children.
Method – Study 1
Participants
Data from 23 children with SLI (age range years; months: 5;1–8;0), 22 age-matched TD
children (AGE: 5;0–7;11) and 20 vocabulary-matched TD children (VOC: 4;0–4;11) from
Owen and Leonard (2006) and Owen (2010) were analysed for this study. These particular
children were selected from the previous two studies because they had conversational language samples of 100 or more utterances. All participants were monolingual speakers of
English, passed a hearing screening, obtained a standard score of 83 or above on the
Columbia Mental Maturity Scales (CMMS; Burgemeister, Blum, and Lorge, 1972) or
Kaufman Basic Intelligence Test – II Matrices subtest (KBIT-2; Kaufman and Kaufman,
2004) and had no history of neurological impairments or pervasive developmental disorder by
parent report. All children were administered the Expressive Vocabulary Test (EVT;
Williams, 1997).
The children with SLI from Owen and Leonard (2006) all scored below the 10th percentile
on the Structured Photographic Expressive Language Test, Second Edition (SPELT-II;
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6
A. J. Owen Van Horne & S. Lin
Werner and Kresheck, 1974) and all but one were receiving treatment for speech, language or
reading difficulties at the time of the study. The children with SLI from Owen (2010) met two
of the following four qualification criteria: (1) received speech/language/reading therapy in
the past 12 months; (2) scored below the 10th percentile on the SPELT-II; (3) obtained a
standard score less than 80 (M ¼ 100; SD ¼ 15) on the Test of Narrative Language (TNL)
(Gillam and Pearson, 2004); (4) obtained a subtest standard score less than 7 (M ¼ 10,
SD ¼ 3) on the NEPSY Nonword Repetition (NWR) Subtest (Korkman, Kirk, and Kemp,
1998). Further details about the participants and the rationale behind the subject selection
measures and subject-matching criteria can be found in Owen and Leonard (2006) and Owen
(2010). Demographic information, including average age and test scores, can be found in
Table I. MLU for each group is reported in Table II, along with additional information about
the language samples.
The TD children scored above the 15th percentile on the SPELT-II (both studies), the
TNL and the NEPSY NWR (Owen, 2010 only) and had no history of speech/language
treatment. The children in the AGE group were each matched to a child in the SLI group
within 3 months of age, t(44) ¼ 0.135, p ¼ 0.89.
The children in the VOC group each scored within 5 raw score points of one of the children
with SLI on the EVT, t(42) ¼ 0.24, p ¼ 0.81. While MLU matching is more common,
vocabulary matching was used given that we were attempting to assess the role of the lexicon
in the acquisition of CSVs. Children with SLI are known to have smaller vocabularies than
their typical age-mates. Deficits in CSVs even when matched on expressive vocabulary skills
would suggest that these abstract verbs are of particular difficulty for the SLI group.
Tasks
Conversational samples were unstructured interactions collected during the two experimental studies. To complete each 1-hour visit to the laboratory, the children played with an
examiner using age-appropriate toys that matched the child’s interests. Thus, the duration of
the samples and the elicitation contexts varied across children and children with SLI often
had more sessions because they needed more days to finish the experimental tasks. Each child
was tested individually and language samples were recorded for later transcription.
Transcription was completed using systematic analysis of language transcripts (SALT)
Table I. Descriptive data about the children who participated in the study.
Diagnostic group
2006 Cohort
2010 Cohort
Study 1 totals
Study 2 totals
AGE
SLI
VOC
AGE
SLI
VOC
AGE
SLI
VOC
AGE
SLI
VOC
N
Age
EVT (Raw)
PPVT SS
CMMS/KBIT SS
12
13
12
10
10
8
22
23
20
11
11
12
72.07 (11.47)
73.5 (11.27)
56.41 (3.46)
76.45 (10.86)
77.13 (9.18)
53.00 (2.78)
74.08 (11.18)
74.95 (10.39)
54.95 (3.44)
72.18 (12.22)
74.63 (11.08)
55.58 (3.5)
69.15 (9.05)
53.92 (10.03)
53.75 (8.52)
66.73 (13.48)
50.37 (9.64)
53.89 (11.88)
68.04 (11.10)
52.50 (9.78)
53.81 (9.77)
69.55 (9.19)
55.09 (9.62)
52.00 (8.19)
122.30 (14.82)
98.58 (6.60)
111.50 (8.08)
112.27 (13.47)
98.50 (9.64)
115.44 (11.87)
117.71 (15.13)
98.55 (7.09)
113.19 (8.93)
122.55 (14.77)
98.73 (6.9)
111.42 (8.30)
116.23 (13.43)
103.41 (8.91)
118.42 (7.50)
99.73 (11.15)
97.88 (11.41)
105.56 (9.39)
108.67 (14.79)
101.20 (10.08)
112.90 (10.50)
116.73 (14.61)
102.36 (8.52)
118.67 (7.81)
Notes: Age is given in means (standard deviation). AGE, age-matched TD children; SLI, specific language impairment; VOC, vocabulary-matched TD children; EVT, expressive vocabulary test; PPVT, Peabody picture vocabulary
test -III Form b.; CMMS, Columbia mental maturity scales; KBIT, Kaufman basic intelligence test - II, Matrices
subtest; SS= standard score.
Cognitive state verbs and complement clauses
7
Table II. Descriptive data about the language samples.
MLU in words
Utterance w/verbs
Utterance w/cognitive verbs
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Cognitive verbs w/complement clauses
AGE
SLI
VOC
5.46 (0.57)
4.85–7.52
328.95 (166.96)
105–792
110.64 (63.38)
33–293
38.59 (22.40)
15–103
4.95 (0.52)
4.13–5.78
403.7 (192.2)
130–859
131.17 (57.80)
32–229
42.48 (20.95)
10–95
5.47 (0.54)
4.81–6.81
270.45 (111.54)
116–484
95.75 (49.14)
27–201
36.15 (24.68)
8–100
Notes: AGE, age-matched TD children; SLI, specific language impairment; VOC, vocabulary-matched TD
children. Means (standard deviations) and ranges are given.
(Miller and Chapman, 2003). Transcripts were later coded for the syntactic types in the
sample following Scott and Lane (2008), which included tagging all verb complements.
Twenty per cent of the samples were recoded and reliability was above 90% on both coding
systems. Information about these samples can be found in Table II.
Analyses
To examine the use of CSVs and their co-occurrence with complement clauses, 59 CSVs
were adapted from Johnston et al. (2001) and Nixon (2005). Additional verbs were added
using Levin’s book of English verb classes (1993) as a reference. We added all verbs in the
classes associated with the original 59 verbs. A search for all instances of these 150þ verbs was
carried out and verbs that were unattested (e.g. digest) or attested only as another part of
speech (e.g. cow) were eliminated. Analyses of the remaining 87 CSVs and their co-occurrence
with verb complements were conducted. All examples of CSVs and complement clauses
extracted via SALT searches were hand-checked to verify true use as a verb and accurate
coding of the complement clause. Non-verb uses (e.g. like : the chair is like the table) were
discarded from the results. Searches for all complement clauses verified that we had an
accurate list of CSVs.
For each child, verbs that co-occurred with more than one complement clause were coded
for syntactic types, in the spirit of Thordardottir and Ellis Weismer (2002). Given our focus
on mental verbs and complement clauses, we identified unique syntactic types of embedded
and unembedded instances of the following: (1) no complement clause, (2) finite complement clause, (3) non-finite complement clause, (4) finite wh-clause, (5) non-finite wh-clause
and (6) if/whether clause. Lexical frequency was determined using corpus-based counts from
CHILDES (Li and Shirai, 2000; MacWhinney, 2000). Although these lists do not allow the
determination of whether a word is used as a noun or a verb, they are a common means in the
literature of determining the relative frequency of words. Eight CSVs had log-frequency
values greater than 3.75 (see, want, know, like, say, look, think, tell) and were classified
as HF verbs. These verbs were analysed separately from the remaining 79 LF verbs.
Results – Conversational Samples
Because the language samples varied widely in length (105–859 utterances, M ¼ 337), we
corrected for sample size differences rather than truncating samples and losing data (Richards
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A. J. Owen Van Horne & S. Lin
and Malvern, 1997). In all the verb-only analyses, the number of CSVs was divided by the total
number of utterances containing any verb in each language sample. When we examined the use
of complement clauses, the rate of co-occurrence of a CSV with a complement clause was
divided by the number of CSVs produced by that child. We did not correct for syntactic types
or verb types. Instead we considered the average number of types per verb with two or more
instances of use in the samples. We only considered verbs that occurred at least twice so that we
were not penalizing children for limited syntactic types when they had no opportunity to vary
the productions. Table III reports these values for the conversational samples used here. All
analyses were one-way ANOVAs with group (SLI, AGE, VOC) as the between-subject factor.
No group differences were observed with regard to the proportion of utterances containing
CSVs, in the number of different cognitive state terms used, the corrected number of
complement clauses and the average number of syntactic types, F(2, 62) < 1.51, p > 0.23.
Further analyses were conducted with verbs divided by frequency. In the HF verb analyses,
no differences between groups were observed for the proportion of utterances with cognitive
verbs, the number of different HF verbs used, the corrected number of complement clauses
or the average number of syntactic types used, F(2, 62) < 1.59, p > 0.21. With regard to LF
verbs, no differences in group were observed for the proportion of utterances containing LF
CSVs, for the number of different LF verbs used, the number of complement clauses or the
number of syntactic types, F(2, 62) < 1, p > 0.51.
Discussion – Study 1
Our purpose was to determine whether children with SLI have problems with CSVs by
comparing their usage to that of their TD peers. The results seem to suggest that children
with SLI are as proficient as their peers in the use of CSVs in conversational language. This
Table III. Means (standard deviations) describing the use of cognitive verbs in conversational language samples.
AGE
SLI
VOC
All verbs
Proportion of utterance w/cognitive verbs
Number of verb types
Proportion of cognitive verbs w/complements
Number of verb types w/complements
Average syntactic types per verb w/2þ instances
Average number of verbs w/2þ types
0.33 (0.06)
23.5 (7.05)
0.36 (0.08)
10.82 (3.6)
2.24 (0.33)
13.79 (5.66)
0.33 (0.09)
22.4 (6.5)
0.34 (0.10)
9.3 (3.5)
2.22 (0.33)
14.87 (5.35)
0.34 (0.07)
20.5 (4.7)
0.36 (0.11)
9.1 (3.0)
3.11(0.40)
12.24 (3.71)
8 HF verbs
Proportion of utterance w/cognitive verbs
Number of verb types
Proportion of cognitive verbs w/complements
Number of verb types w/complements
Average syntactic types per verb w/2þ instances
Average number of verbs w/2þ types
0.22 (0.05)
7.32 (0.65)
0.42 (0.10)
5.8 (1.2)
2.81 (0.67)
6.45 (1.53)
0.23 (0.06)
7.30 (1.06)
0.40 (0.12)
5.1 (1.4)
2.74 (0.54)
6.82 (1.85)
0.23 (0.07)
7.30 (0.73)
0.42 (0.14)
5.3 (1.3)
2.49 (0.61)
6.33 (1.35)
79 LF verbs
Proportion of utterance w/cognitive verbs
Number of verb types
Proportion of cognitive verbs w/complements
Number of verb types w/complements
Average syntactic types per verb w/2þ instances
Average number of verbs w/2þ types
0.12 (0.04)
16.2 (6.6)
0.22 (0.12)
5.0 (2.8)
1.74 (0.35)
8.00 (4.09)
0.10 (0.05)
15.04 (5.6)
0.21 (0.15)
4.2 (2.8)
1.77 (0.32)
8.04 (3.75)
0.12 (0.03)
13.2 (4.5)
0.24 (0.11)
4.5 (2.6)
1.73 (0.39)
5.90 (2.94)
Notes: AGE, age-matched TD children; SLI, specific language impairment; VOC, vocabulary-matched TD children; HF, high frequency; LF, low frequency.
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Cognitive state verbs and complement clauses
9
finding would be consistent with that of Marinellie (2004) and Norbury and Bishop (2003),
who found comparable rates of use of complement clauses and CSVs in conversational and
narrative samples. Given the large number of children included in this analysis, the size of the
language samples and the fact that most results were solidly non-significant, we feel that this is
a robust finding. Thus, we can answer our first question with a clear ‘no’: children with SLI
may continue to exhibit deficits in complex syntax as they move out of the preschool years
(Owen and Leonard, 2006; Owen, 2010), but these deficits are not observable in conversational language when CSVs and complement clauses are examined. The negative answer to
this first question obviates the need to directly address the second question.
However, before we abandon this line of research, we wish to consider an alternative source
of data. Emerging evidence shows that conversational samples do not elicit the best effort or the
most complex language from children or adults (Scott and Windsor, 2000; Nippold, Hesketh,
Duthie, and Mansfield, 2005a; Thordardottir, 2008; Nippold, 2009). Interview-style conversations (Evans and Craig, 1992), personal narratives or story retells (Hadley, 1998; Southwood
and Russell, 2004) and expository samples (Scott and Windsor, 2000; Nippold et al., 2005a;
Nippold, Mansfield, Billow, and Tomblin, 2008; Nippold, 2009) can lead to longer utterances,
more complex sentences and increased error rates, as compared to unstructured conversation
and free play samples. Thordardottir (2008) found that English-speaking children with SLI
produce longer utterances and make more morphological errors in expository and narrative
contexts as compared to conversation, suggesting that increased task demands may negatively
influence performance. Wetherell et al. (2007) showed that group differences in fluency and
error rates are observable when adolescents are asked to tell a story based on a book, but not
when they are asked to recount a personal narrative in a conversational style.
Furthermore, one might hypothesize that the use of CSVs with true complements might be
more likely to occur in narration to indicate the motives and thoughts of characters or in
exposition to reflect the strategic thinking required to play a game well. LF verbs may be used
at greater rates when the speaker is required to express his or her thoughts in these particular
discourse formats. The independent thought and pre-planning required may lead to
increased processing load for monologue-style genres. Given the weaker language abilities
of children with SLI, one might expect that they would be less likely to use such advanced
forms, particularly in difficult speaking situations. To that end, we ask the same questions as
previously described but instead focus on whether speaking style leads to group differences,
using a subset of children for whom we had both interactive (conversational) samples and
monologue-style (narrative and/or exposition) samples available. Does the use of CSVs change
with discourse contexts for typical children or children with SLI? Can lexical or syntactic deficits
account for any group differences that are observed?
Method – Study 2: Genre Comparisons
Participants
Data from 11 children with SLI (5;1–7;2), 11 age-matched TD children (AGE: 5;0–7;11)
and 12 vocabulary-matched TD children (VOC: 4;0–4;11) from Owen and Leonard (2006)
were analysed for this study. These children had combined narrative and expository language
samples that equalled 40 or more utterances in addition to producing conversational samples
of 100 or more utterances. Demographic information, including age and test scores, can be
found in Table I. MLU information for the samples included in this study is reported in
Table IV.
10
A. J. Owen Van Horne & S. Lin
Table IV. Descriptive data for the language samples from each diagnostic group, divided into interactive and
monologue-style language samples used in Study 2.
AGE
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MLU w
SLI
VOC
Inter
Mono
Inter
Mono
Inter
Mono
5.4 (0.38)
4.97–6.39
5.7 (0.69)
4.14–6.18
4.8 (0.44)
4.12–5.49
4.5 (0.77)
3.81–6.55
5.4 (0.64)
4.18–6.81
5.6 (0.89)
4.61–8.01
Utterance w/verbs
383.4 (168.4) 130.5 (106.9) 441.4 (218.2)
190–792
35–414
130–859
192.6 (82.3)
55–308
269.7 (123.4)
116–484
122 (51.5)
70–242
Utterance w/
cognitive verbs
121.3 (66.22)
65.5 (38.1)
96.1 (49.8)
39.6 (29.6)
Utterance w/
complement
clauses
46.6 (48.9)
136.5 (60.1)
60–293
13–181
32–216
19–145
27–201
11–126
42.8 (23.8)
13.9 (14.1)
42.3 (17.1)
21.7 (17.3)
34.3 (20.5)
11.83 (9.9)
26–103
2–51
17–73
2–64
8–72
3–38
Notes: AGE, age-matched TD children; SLI, specific language impairment; VOC, vocabulary-matched TD children; MLU, mean length of utterance.
Tasks
In addition to the conversational language samples used above, two elicitation contexts
contributed to the monologic samples analysed here. We justify combining these samples
because, to our knowledge, interactions between group and genre style have not been
observed between narrative and expository samples. For the narrative sample, children
watched the wordless video adaptation (Bresnahan, 1991) of the book Picnic (McCully,
1984) and then told the story depicted in the video using picture prompts from the book.
The story is about a small mouse that gets left behind while his family goes on a picnic. His
family realizes he is missing and looks for him. As the story concludes, the mouse has been
found, but has left his toy mouse behind. After watching the silent film, the child was asked to
tell the examiner the story, using the book, and to ‘say something about every page’. The
examiner prompted by saying ‘what next?’ ‘anything else?’ repeating the child’s previous
utterance and turning the page.
The expository sample was modelled after Nippold et al. (2005a) except that children were
restricted to a board game or card game and were encouraged to bring the game with them to
the data collection session. This modification was done to ensure that even the youngest
vocabulary-matched children could participate. Children were asked to explain to the experimenter the rules of the game and strategies to win the game. Initially, children were asked
which game they had brought and what they liked about the game. Then they were encouraged to teach the experimenter how to play the game. The experimenter supported the
explanations by asking ‘what next’ or ‘and then what’ and by generally acting naïve about
the game and its rules. Following instructions, the experimenter asked the child what would
be a good way to play if you wanted to win the game every time or wanted to get better every
time you played. By restricting analysis to utterances with verbs, the majority of the routine
utterances (e.g. your turn) were excluded. Transcription, coding and verb analyses proceeded as described previously. Reliability for transcripts in Study 1 and Study 2 was carried
out at the same time by the same research assistants and was above 90% for both syntactic and
morphological coding systems. Information about the samples is provided in Table IV.
Cognitive state verbs and complement clauses
11
Results – Study 2
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Analyses were carried out as in Study 1, with corrections for sample size used. In the analyses
of the use of CSVs, corrections were based on the number of utterances containing verbs in
the samples; in analysis of the use of complement clauses, corrections were based on the
number of CSVs. See Table V for presentation of means and SDs. All analyses were mixedmodel ANOVAs with group (SLI, AGE, VOC) as the between-subject factor and speaking
style (Interactive, Monologue) as the within-subject factor. All post-hoc comparisons
reported below used a Bonferroni correction for multiple comparisons.
Table V. Means (standard deviations) describing the use of cognitive verbs in interactive- and monologue-style
samples for the subset of children used in Study 2.
AGE
All verbs
Proportion of utterance
w/cognitive verbs
Number of verb types
Proportion of cognitive
verbs w/complements
Number of verb types
w/complements
Average syntactic types per
verb w/2þ instances
Average number of verbs
w/2þ types
8 HF verbs
Proportion of utterance
w/cognitive verbs
Number of verb types
Proportion of cognitive
verbs w/complements
Number of verb types
w/complements
Average syntactic types per
verb w/2þ instances
Average number of verbs
w/2þ types
79 LF verbs
Proportion of utterance
w/cognitive verbs
Number of verb types
Proportion of cognitive
verbs w/complements
Number of verb types
w/ complements
Average syntactic types per
verb w/ 2þ instances
Average number of verbs
w/ 2þ types
SLI
VOC
Inter
Mono
Inter
Mono
Inter
Mono
0.31 (0.06)
0.33 (0.09)
0.31 (0.08)
0.33 (0.09)
0.35 (0.06)
0.30 (0.09)
24.0 (6.2)
0.36 (0.09)
15.5 (7.1)
0.30 (0.10)
21.5 (5.8)
0.34 (0.11)
17.2 (5.8)
0.30 (0.13)
20.8 (5.1)
0.34 (0.07)
14.4 (5.2)
0.29 (0.10)
12.5 (3.3)
7.1 (4.1)
8.5 (1.9)
7.2 (2.8)
9.3 (3.1)
5.9 (3.3)
2.36 (0.41)
1.93 (0.29)
2.19 (0.35)
2.03 (0.38)
2.06 (0.43)
1.84 (0.34)
14.1 (5.13)
11.1 (6.87)
14.81 (5.63)
10.82 (5.69)
12.42 (4.12)
9.67 (5.50)
0.21 (0.04)
0.18 (0.06)
0.22 (0.07)
0.22 (0.07)
0.23 (0.06)
0.17 (0.06)
7.5 (0.52)
0.40 (0.11)
5.9 (1.6)
0.35 (0.24)
7.4 (1.2)
0.41 (0.14)
6.7 (1.3)
0.38(0.16)
7.5 (0.67)
0.41 (0.10)
6.2 (1.3)
0.34 (0.14)
6.3 (1.0)
3.4 (2.0)
5.0 (1.0)
4.2 (1.1)
5.0 (1.1)
3.3 (1.0)
2.77 (0.71)
2.01 (0.48)
2.71 (0.49)
2.20 (0.44)
2.46 (0.70)
1.95 (0.55)
7.0 (1.25)
5.4 (2.99)
7.0 (2.28)
6.7 (2.94)
6.4 (1.62)
5.3 (1.78)
0.11 (0.03)
0.15 (0.05)
0.09 (0.02)
0.12 (0.04)
0.12 (0.03)
0.13 (0.05)
16.5 (5.9)
0.28 (0.11)
9.5 (6.4)
0.25 (0.13)
14.1 (4.9)
0.18 (0.13)
10.5 (4.7)
0.16 (0.12)
13.3 (4.9)
0.23 (0.11)
8.25 (4.5)
0.21 (0.17)
6.3 (2.9)
3.6 (2.9)
3.5 (1.3)
3.0 (2.3)
4.3 (2.1)
2.7 (2.7)
1.9 (0.28)
1.9 (0.24)
1.6 (0.30)
1.6 (0.45)
1.6 (0.38)
1.7 (0.51)
7.8 (3.33)
5.7 (4.41)
7.6 (3.52)
3.9 (3.97)
6.0 (3.07)
4.3 (3.96)
Notes: AGE, age-matched TD children; SLI, specific language impairment; VOC, vocabulary-matched TD
children.
12
A. J. Owen Van Horne & S. Lin
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All verbs
As before we began by considering the use of all CSVs. Neither group nor genre differences
were observed for the proportion of utterances containing CSVs (group: F(2, 31) ¼ 0.007,
p ¼ 0.99; genre: F(1, 31) ¼ 0.03, p ¼ 0.86; group genre: F(2, 31) ¼ 1.68, p ¼ 0.20).
With regard to verb types, however, differences do emerge for both group: F(2, 31) ¼ 4.78,
p ¼ 0.02, η2 ¼ 0.23; and genre: F(1, 31) ¼ 40.40, p < 0.0001, η2 ¼ 0.57. Children used a
wider variety of verbs, given the sample size, in the monologue-style samples than in the
interactive samples. In both types of samples, children with SLI were less likely than their agemates to vary their verb choice (p ¼ 0.02). The vocabulary-matched children were comparable to the SLI group and trended toward using less varied verbs than the age-matched group
( p ¼ 0.06).
We also examined the rate of use of all CSVs with complement clauses to determine
whether children were using these verbs in a more advanced way. While there were no
main effects or interactions involving group, main effect: F(2, 31) ¼ 0.148, p ¼ 0.86; interaction: F(2, 31) ¼ 0.063, p ¼ 0.94, there were differences between the two speaking styles, F
(1, 31) ¼ 5.25, p ¼ 0.03, η2 ¼ 0.14. Children were more likely to include a complement
clause with the CSV in the interactive samples than in the monologues. We speculated that
this might be due to a reliance on shorter, more formulaic uses of the CSVs. To examine this,
we looked at the average number of syntactic types for verbs that the child used two or more
times. One child was dropped from these analyses due to not using verbs more than twice in
their sample. Although there were no differences in group, F(2, 30) ¼ 1.46, p ¼ 0.24, and no
interactions between group and genre, F(2, 30) ¼ 0.94, p ¼ 0.40, there were differences in
genre, F(1, 30) ¼ 10.78, p ¼ 0.002, η2 ¼ 0.26. The children used verbs on average with
more syntactic types in the conversational style (M ¼ 2.2), than in the monologue style
(M ¼ 1.9). Because such differences may be attributable to the choice of verbs children
used, we once again examine the role of verb frequency.
Verbs grouped by frequency
In the HF verb-only analyses, no differences between groups were observed either as main
effects, F(2, 31) ¼ 0.89, p ¼ 0.41, or as an interaction, F(2, 31) ¼ 1.53, p ¼ 0.23. Interactivestyle samples had higher rates of these eight HF verbs than did the monologue-style samples, F
(1, 31) ¼ 6.28, p ¼ 0.02, η2 ¼ 0.17, even though both samples had similar rates of overall
verbs use. However, when these verbs were considered in combination with their complements, no differences in group, F(2, 31) ¼ 0.122, p ¼ 0.88, or genre, F(1, 31) ¼ 2.59,
p ¼ 0.12, and no interactions, F(2, 31) ¼ 0.07, p ¼ 0.93, were observed suggesting that,
once the number of HF verbs present was corrected for, the rate of complement clause use
was similar. That said, the higher variety of syntactic types observed persisted in the
conversational sample, F(1, 30) ¼ 27.80, p < 0.0001, η2 ¼ 0.48, but group differences
were not observed, group: F(2, 30) ¼ 0.91, p ¼ 0.42, group genre: F(2, 30) ¼ 0.54,
p ¼ 0.59. Thus, the conversational samples use more of the HF verbs and these verbs are
used in a wider variety of contexts in this sample type.
In the LF verb analyses, children produced a higher rate of LF CSVs in the monologuestyle samples than in the interactive-style samples, F(1, 31) ¼ 9.95, p ¼ 0.003, η2 ¼ 0.24.
Although there was a numeric trend for the SLI group to produce a smaller proportion of
utterances with CSVs (M ¼ 0.10) than AGE (M ¼ 0.13) and VOC (M ¼ 0.12) groups, this
did not attain significance, F(2, 31) ¼ 2.72, p ¼ 0.08. There was no interaction between
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Cognitive state verbs and complement clauses
13
group and genre, F(2, 31) ¼ 1.19, p ¼ 0.32. The SLI group also appeared to produce a
smaller variety of cognitive verb types than either of their typical peers, but the rate of use
of LF verb types only trended toward significance when the three groups were compared, F
(2, 31) ¼ 2.55, p ¼ 0.09. There were no differences in the verb types between speaking
styles, F(1, 31) ¼ 2.26, p ¼ 0.14, and no interactions, F(2, 31) ¼ 1.84, p ¼ 0.18.
Turning to the use of the LF verbs with complements, we see that children with SLI were
less likely than their age-matched peers to combine these verbs with complement clauses,
p ¼ 0.04; F(2, 31) ¼ 3.34, p ¼ 0.048, η2 ¼ 0.18. The VOC group’s rate of use of complement clauses with CSVs (M ¼ 0.22) fell in between that of the AGE group (M ¼ 0.27;
p ¼ 0.49) and the SLI group (M ¼ 0.17; p ¼ 0.69). Use across genres did not differ,
F(1, 31) ¼ 0.58, p ¼ 0.45. No interactions were observed F(2, 31) ¼ 0.032, p ¼ 0.97.
There was also a trend toward group differences in the average number of syntactic types
used with verbs that occurred twice or more times in the samples, F(2, 30) ¼ 2.98, p ¼ 0.06,
η2 ¼ 0.16. This was primarily due to a higher rate of syntactic types used by the age-matched
group as compared to the other two groups (AGE vs. SLI, p ¼ 0.03; AGE vs. VOC, p ¼ 0.06;
SLI vs. VOC, p ¼ 0.74). There were no genre differences, F(1, 30) ¼ 0.09, p ¼ 0.76, and no
interactions, F(2, 30) ¼ 0.212, p ¼ 0.81, with regard to syntactic types.
Thus, we observe children using a higher rate of HF CSVs in conversational samples and
LF CSVs in the monologue-style samples. Given that a wider variety of syntactic types is also
observed for the HF CSVs in conversation, it is difficult to disambiguate the contribution of
discourse style and frequency. We carried out a 3(group) 2(frequency) 2(style) mixedmodel ANOVA with the average number of syntactic types as the dependent variable in an
attempt to distinguish the contributions of each factor. There were no group effects and no
interactions with group, F(2, 29) < 1.6, p > 0.21; thus we conclude that frequency and style
seem to influence all three groups of children similarly. There were, however, clear effects of
frequency such that children were more likely to use HF verbs with a variety of types, F (1,
29) ¼ 58.01, p < 0.0001, η2 ¼ 0.67. There was also an effect of style, which showed that
children were more likely to use a variety of syntactic types with conversational samples, F
(1, 29) ¼ 2.81, p < 0.001, η2 ¼ 0.29. These effects are mitigated by an interaction, F (1,
29) ¼ 3.30, p < 0.0001, η2 ¼ 0.49, between group and genre. Children were more likely to
use HF verbs than LF verbs with a variety of types in conversational samples. In contrast, in
monologue-style samples, the HF and LF verbs were equally likely to be used in varied
syntactic forms (see Table V).
Discussion
Limitations
This study is limited by its retrospective nature. Although we had nearly 70 children available
for the first analysis of conversational samples, the second analysis only had 11–12 children
per group. The children were drawn from a wide age range and the samples varied considerably in size. More children and more control of the sampling contexts would be ideal for
further exploring the possibility that task demands influence children’s productions.
Nonetheless, the pattern of differences in the second analysis in combination with overwhelming similarities across groups in the first analysis is informative with regard to the
questions posed.
14
A. J. Owen Van Horne & S. Lin
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The role of genre
While the base rate of CSV use was similar across the two discourse styles, conversational
samples appear to differ from narrative/expository contexts in several ways. Conversational
samples contained a higher rate of HF CSVs and a higher rate of CSVs with complement
clauses than the other discourse styles. Children used these HF CSVs more flexibly, that is
with a wider range of syntactic types. Because undirected conversation makes fewer requirements on the children with regard to topic and communication needs, children could rely on
common verbs that they were highly familiar with. Given this familiarity, children may have
been more facile in combining the verb with a complement clause. In fact, as was previously
observed three common verbs, want, think and know, comprised more than 66% of the
conversational uses of a cognitive verb plus a complement clause (Marinellie, 2004).
Diessel and Tomasello (2001) would suggest that co-occurrence with a finite complement is
not equal to a sophisticated use in all cases and that flexible use in a variety of contexts is critical
for documenting true productive use. It is difficult to establish clear criteria for productive/
flexible/non-formulaic use across children without longitudinal samples, thus we considered
whether a verb occurred in more than one syntactic type. It still seems that children were using
the HF verbs more flexibly and in a wider variety of contexts in the conversational-style samples
(M ¼ 2.6), suggesting that the children were more readily able to combine these familiar verbs
in a variety of novel ways than the LF verbs elicited in the same context (M ¼ 1.78) or either
verb type elicited in the monologue-style samples (HF: M ¼ 2.0; LF: M ¼ 1.8).
Even though they used them in less flexible ways, children in all three groups were more
likely to use a wider variety of verbs in the narrative/expository samples, both in terms of the
higher corrected rate of LF verbs and in terms of the higher number of verb types. The rate of
LF verb use is especially telling since many of these verbs were used once or twice by any given
child or, in some cases (e.g. hear, call, agree, imagine), only used once by a single child. No
genre-related differences in complement clause use with LF verbs were observed. Thus, while
narrative/expository samples are more likely to elicit sophisticated vocabulary, conversational
samples may yield more productions of complement clauses, albeit primarily with highly
familiar verbs. At first, this finding may appear inconsistent with data showing that narrative
and expository samples elicit more complex language. But instead it indicates that these
genres elicit different kinds of complexity. For instance, (Nippold et al., 2005a; Nippold,
Mansfield, and Billow, 2007) have found that adverbial and relative clause use is more
sensitive to age-related changes. Our own work on these samples also suggests that the rate
of finite complement clause use does not differentiate the groups, but adverbial clause use
does (Achenbaugh and Owen, 2010).
Interactions between group and genre were generally not found, making it difficult to
interpret the role of task demands. On the one hand, it does not seem that the task demands
influenced one group more than another. However, this may be one area where limited power
was particularly detrimental since increased sample size is required to reliably detect
interactions.
CSVs and frequency effects across groups
Elementary-school children with SLI use CSVs at a comparable rate as their TD age- and
vocabulary-matched peers, both overall and when the use of either HF or LF verbs is
considered, although here was a slight trend (p ¼ 0.08) in Study 2 for children with SLI to
use fewer LF verbs than their peers. We differ from the reports of Johnston et al. (2001) who
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Cognitive state verbs and complement clauses
15
found that preschool-aged children with SLI generally used CSVs and other mental-state
terms less often than TD peers. Given that the children in our study were 2–4 years older than
the children who participated in Johnston et al.’s (2001) study, this suggests that children with
SLI do eventually acquire an age-appropriate expressive vocabulary of CSVs.
Our findings are more mixed when we consider the variety of verbs and the use of verbs
with complement clauses. In the larger sample of conversational speech only, no differences
emerged on any measure. When the subset of narrative/expository samples was considered,
the children with SLI used fewer different verbs in general and were less likely to combine LF
verbs with a complement clause than their typical peers. When we examined LF verbs only,
they also trended toward fewer LF verb types and fewer syntactic types with LF verbs. Taken
together, these results suggest that children with SLI may have subtle deficits associated with
LF CSVs. One possibility is that children with SLI may know the LF verbs well enough to use
them in limited contexts (e.g. oh no, I forgot!), but not well enough to use them in truly
productive contexts. Such a hypothesis would be consistent with King and Fletcher’s (1993)
finding that 7–10-year-old children with SLI were less likely to include optional verb complements than their peers. Differences are most observable when a variety of discourse contexts
are a component of the assessment and when children are asked to use less common verbs in
sophisticated ways.
Semantic or syntactic contributions to the CSV use
We would attribute these deficits to limitations within the lexical knowledge of the verbs
rather than a syntactic deficit for a variety of reasons. First, we have clear evidence that all
children were able to produce complement clauses flexibly with the HF verbs (see Tables III
and V which show the number of HF verbs used with two or more syntactic types). Second,
careful examination of the utterances for evidence of productive use suggested that the
children were using the HF verbs in similar ways across groups, under a variety of task
demands. Finally, these same children participated in an experimental study eliciting verbs
that take both finite and non-finite complement clauses (Owen and Leonard, 2006) or
eliciting coordinated clauses, complement clauses and adverbial clauses (Owen, 2010). All
the children were able to produce finite complement clause responses using a variety of main
verbs. Thus, an appeal to deficits in the abstract knowledge of how to use the syntactic frame
seems unsupportable.
Evidence for a lexical deficit arises from the differences observed across HF and LF verbs.
Differences between age-mates and children with SLI were most readily observed in the LF
verbs combined with complement clauses, but not in the rate of use of any of the different verb
classes alone. Differences in the number of verb types are also likely to be a lexical learning
problem. Furthermore, no differences between the children with SLI and their vocabularymatched peers were observed. In fact, the groups appeared to be highly similar with most
p-values approaching 1.0, suggesting significant group overlap. Inasmuch as group matching
reflects truly similar processes (see Mervis and Robinson, 2003), this would suggest that
children with SLI have representations of LF verbs that are comparable to those of their
younger typical peers who have similar overall expressive vocabularies.
Further evidence is required to determine whether older children with SLI eventually attain
comparable levels of use with all verb types or simply increase the rate of use of complement
clauses with HF verbs making them appear comparable. Combining analyses of HF and LF
verbs may mask group differences. Unlike previous studies (e.g. Marinellie, 2004) which have
treated all CSVs the same, focusing on LF verbs may enhance group separation.
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16
A. J. Owen Van Horne & S. Lin
An outstanding question is why the use of CSVs by children with SLI resembles that of
younger children with less experience. One possibility is that the initial delay in acquiring
CSVs as lexical items (Johnston et al., 2001) cascades into a problem with syntax at older
ages, particularly if one assumes that the syntactic form must be learned item by item
(Goldberg, 1995). Another possibility is that more input is required for the child with SLI
to associate a verb with a syntactic frame or to develop robust representations of the verb. At
this older age, we observe continued low rates of complement clauses with LF verbs and a
more limited variety of types of sentences with these same verbs, suggesting immature
strategies for acquisition and use. Studies that document the process and not just the products
of development will be necessary to identify the source of the delay and the means by which it
resolves.
Acknowledgements
We thank Whitney Achenbaugh and Sarah McConnell Michels for data coding, Haley Ellis
and Keegan Koehlinger for verifying transcription and transcription reliability and Karla
McGregor and members of Grammar Acquisition Laboratory and Word Learning
Laboratory at the University of Iowa for their comments and suggestions. Data collection
of this study was completed at Purdue University and supported by NIH RO1DC00458
awarded to Laurence B. Leonard and by a Bamford–Lahey Scholarship awarded to Amanda
J. Owen. Data analysis was funded by a pre-doctoral scholarship from the Ministry of
Education, Taiwan, awarded to Shanju Lin. Portions of this article were presented at the
2010 Symposium on Research in Child Language Disorders, Madison, WI, USA.
Declaration of interest: The authors report no conflicts of interest. The authors alone are
responsible for the content and writing of this paper.
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