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Clinical Linguistics & Phonetics
ISSN: 0269-9206 (Print) 1464-5076 (Online) Journal homepage: http://www.tandfonline.com/loi/iclp20
Noun and verb knowledge in monolingual
preschool children across 17 languages: Data from
cross-linguistic lexical tasks (LITMUS-CLT)
Ewa Haman, Magdalena Łuniewska, Pernille Hansen, Hanne Gram
Simonsen, Shula Chiat, Jovana Bjekić, Agnė Blažienė, Katarzyna Chyl, Ineta
Dabašinskienė, Pascale Engel de Abreu, Natalia Gagarina, Anna Gavarró,
Gisela Håkansson, Efrat Harel, Elisabeth Holm, Svetlana Kapalková, Sari
Kunnari, Chiara Levorato, Josefin Lindgren, Karolina Mieszkowska, Laia
Montes Salarich, Anneke Potgieter, Ingeborg Ribu, Natalia Ringblom,
Tanja Rinker, Maja Roch, Daniela Slančová, Frenette Southwood, Roberta
Tedeschi, Aylin Müge Tuncer, Özlem Ünal-Logacev, Jasmina Vuksanović &
Sharon Armon-Lotem
To cite this article: Ewa Haman, Magdalena Łuniewska, Pernille Hansen, Hanne Gram Simonsen,
Shula Chiat, Jovana Bjekić, Agnė Blažienė, Katarzyna Chyl, Ineta Dabašinskienė, Pascale Engel
de Abreu, Natalia Gagarina, Anna Gavarró, Gisela Håkansson, Efrat Harel, Elisabeth Holm,
Svetlana Kapalková, Sari Kunnari, Chiara Levorato, Josefin Lindgren, Karolina Mieszkowska,
Laia Montes Salarich, Anneke Potgieter, Ingeborg Ribu, Natalia Ringblom, Tanja Rinker, Maja
Roch, Daniela Slančová, Frenette Southwood, Roberta Tedeschi, Aylin Müge Tuncer, Özlem
Ünal-Logacev, Jasmina Vuksanović & Sharon Armon-Lotem (2017): Noun and verb knowledge
in monolingual preschool children across 17 languages: Data from cross-linguistic lexical tasks
(LITMUS-CLT), Clinical Linguistics & Phonetics, DOI: 10.1080/02699206.2017.1308553
To link to this article: http://dx.doi.org/10.1080/02699206.2017.1308553
Published with license by Taylor & Francis.©
Ewa Haman, Magdalena Łuniewska,
Pernille Hansen, Hanne Gram Simonsen,
Shula Chiat, Jovana Bjekić, Agnė Blažienė,
Katarzyna Chyl, Ineta Dabašinskienė,
Pascale Engel de Abreu, Natalia Gagarina,
Anna Gavarró, Gisela Håkansson, Efrat
Harel, Elisabeth Holm, Svetlana Kapalková,
Sari Kunnari, Chiara Levorato, Josefin
Lindgren, Karolina Mieszkowska, Laia
Montes Salarich, Anneke Potgieter, Ingeborg
Ribu, Natalia Ringblom, Tanja Rinker,
Maja Roch, Daniela Slančová, Frenette
Southwood, Roberta Tedeschi, Aylin Müge
Tuncer, Özlem Ünal-Logacev, Jasmina
Vuksanović, and Sharon Armon-Lotem.
Published online: 25 Apr 2017.
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Noun and verb knowledge in monolingual preschool children
across 17 languages: Data from cross-linguistic lexical tasks
(LITMUS-CLT)
Ewa Haman
a
,MagdalenaŁuniewska
a
,PernilleHansen
b
, Hanne Gram Simonsen
b
,
Shula Chiat
c
,JovanaBjekić
d
,AgnėBlažienė
e
, Katarzyna Chyl
a
,InetaDabašinskienė
e
,
Pascale Engel de Abreu
f
, Natalia Gagarina
g
, Anna Gavarró
h
, Gisela Håkansson
i
,
Efrat Harel
j
, Elisabeth Holm
b
, Svetlana Kapalková
k
,SariKunnari
l
, Chiara Levorato
m
,
JosefinLindgren
n
, Karolina Mieszkowska
a
, Laia Montes Salarich
h
,
Anneke Potgieter
o
,IngeborgRibu
b
, Natalia Ringblom
p
, Tanja Rinker
q
,MajaRoch
m
,
Daniela Slančová
r
, Frenette Southwood
o
,RobertaTedeschi
a
, Aylin Müge Tuncer
s
,
Özlem Ünal-Logacev
t
, Jasmina Vuksanović
d
and Sharon Armon-Lotem
u
a
Faculty of Psychology, University of Warsaw, Warsaw, Poland;
b
MultiLing, University of Oslo, Oslo, Norway;
c
City
University London, London, UK;
d
Institute for Medical Research, University of Belgrade, Serbia;
e
Vytautas Magnus
University, Kaunas, Lithuania;
f
Language and Cognitive Development Group, University of Luxembourg, Luxembourg;
g
Research Area Language Development and Multilingualism (FB II), Leibniz-ZAS Berlin, Berlin, Germany;
h
Universitat
Autònoma de Barcelona, Barcelona, Catalonia, Spain;
i
Lund University, Lund, Sweden;
j
Kibbutzim College of
Education, Technology and Arts, Tel-Aviv, Israel;
k
Comenius University in Bratislava, Bratislava, Slovakia;
l
Research Unit
of Logopedics, University of Oulu, Oulu, Finland;
m
University of Padua, Padua, Italy;
n
Uppsala University, Uppsala,
Sweden;
o
Department of General Linguistics, Stellenbosch University, Stellenbosch, South Africa;
p
Stockholm
University, Stockholm, Sweden;
q
Department of Linguistics, University of Konstanz, Konstanz, Germany;
r
Faculty of
Arts, Prešov University, Prešov, Slovakia;
s
Health Sciences Faculty, Health Sciences Faculty, Anadolu University,
Eskişehir, Turkey;
t
School of Health Science, Istanbul Medipol University, Istanbul, Turkey;
u
Bar-Ilan University, Ramat-
Gan, Israel
ABSTRACT
This article investigates the cross-linguistic comparability of the newly
developed lexical assessment tool Cross-linguistic Lexical Tasks
(LITMUS-CLT). LITMUS-CLT is a part the Language Impairment Testing
in Multilingual Settings (LITMUS) battery (Armon-Lotem, de Jong & Meir,
2015). Here we analyse results on receptive and expressive word knowl-
edge tasks for nouns and verbs across 17 languages from eight different
language families: Baltic (Lithuanian), Bantu (isiXhosa), Finnic (Finnish),
Germanic (Afrikaans, British English, South African English, German,
Luxembourgish, Norwegian, Swedish), Romance (Catalan, Italian),
Semitic (Hebrew), Slavic (Polish, Serbian, Slovak) and Turkic (Turkish).
The participants were 639 monolingual children aged 3;0–6;11 living in
15 different countries. Differences in vocabulary size were small
between 16 of the languages; but isiXhosa-speaking children knew
significantly fewer words than speakers of the other languages. There
was a robust effect of word class: accuracy was higher for nouns than
verbs. Furthermore, comprehension was more advanced than produc-
tion. Results are discussed in the context of cross-linguistic comparisons
of lexical development in monolingual and bilingual populations.
ARTICLE HISTORY
Received 30 July 2015
Revised 25 April 2016
Accepted 26 June 2016
KEYWORDS
Lexical development;
cross-linguistic comparison;
basic word classes; word
comprehension; word
production
CONTACT Ewa Haman ewa.haman@psych.uw.edu.pl Faculty of Psychology, University of Warsaw, Stawki 5/7,
00-183 Warsaw, Poland.
CLINICAL LINGUISTICS & PHONETICS
http://dx.doi.org/10.1080/02699206.2017.1308553
© Ewa Haman, Magdalena Łuniewska, Pernille Hansen, Hanne Gram Simonsen, Shula Chiat, Jovana Bjekić,AgnėBlažienė, Katarzyna Chyl, Ineta
Dabašinskienė, Pascale Engel de Abreu, Natalia Gagarina, Anna Gavarró, Gisela Håkansson, Efrat Harel, Elisabeth Holm, Svetlana Kapalková, Sari
Kunnari, Chiara Levorato, Josefin Lindgren, Karolina Mieszkowska, Laia Montes Salarich, Anneke Potgieter, Ingeborg Ribu, Natalia Ringblom, Tanja
Rinker, Maja Roch, Daniela Slančová, Frenette Southwood, Roberta Tedeschi, Aylin Müge Tuncer, Özlem Ünal-Logacev, Jasmina Vuksanović,and
Sharon Armon-Lotem. Published with license by Taylor & Francis.
This is an Open Access article distributed under the terms of the Creative Commons Attribution-NonCommercial-NoDerivatives License (http://
creativecommons.org/licenses/by-nc-nd/4.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the
original work is properly cited, and is not altered, transformed, or built upon in any way.
Most research on bi- and multilingual children’s lexical development rests on an implicit
assumption that vocabulary development is similar across languages. However, it is not
clear to what extent this assumption is valid. Cross-linguistic data collected from mono-
lingual children who were tested on lexical tasks designed to be uniform across languages
could be useful in suggesting what differences may be expected across languages, inde-
pendently of the bi- or multilingual status of the speakers. The novel assessment tool
Cross-linguistic Lexical Tasks (LITMUS-CLT, henceforth CLT; Haman, Łuniewska, &
Pomiechowska, 2015) was designed within COST Action IS0804 as a response to the
need for cross-linguistically and cross-culturally comparable lexical assessment tools for
children. CLT is a part of the Language Impairment Testing in Multilingual Settings
(LITMUS) battery (Armon-Lotem et al., 2015).
This article presents a large-scale cross-linguistic study of expressive and receptive word
knowledge in monolingual children assessed using this new tool. The goal of this study
was twofold: (1) to compare lexical development across languages and cultures and (2) to
evaluate the assessment tool itself.
Importantly, analyses of cross-linguistic data from monolingual children may contri-
bute crucial information for the cross-linguistic assessment of bilinguals, who should be
assessed in both of their languages (Bedore & Peña, 2008). If the timing and pace of
monolingual language development is not the same across languages due to the factors
intrinsic to linguistic or culture characteristics, then it should not be expected that the
languages of a bilingual child will develop in a fully balanced way, even if input and other
external factors are levelled out. Thus, any cross-linguistic differences found with regard to
the timing and pace of lexical development could be used, for instance, to inform clinical
practice about whether similar levels of lexical knowledge should be expected in the
different languages of bilingual children who are diagnosed with a language disorder.
In this article, we analyse data from monolingual preschool children across 17 lan-
guages. These analyses provide a background for the other studies presented in this issue
that refer to specific languages, language pairs or language problems (Altman, Goldstein &
Armon-Lotem, this issue; Gatt, Attard, Łuniewska & Haman, this issue; Hansen,
Simonsen, Łuniewska & Haman, this issue; Kapalková & Slančová, this issue; Khoury
Aouad Saliby, dos Santos, Kouba-Hreich & Messarra, this issue) as well as the recently
published (Potgieter & Southwood 2016). Furthermore, we investigate similarities in
measurements of children’s lexical knowledge across languages. We explore whether the
assumptions underlying CLT affect the scores, as well as to what extent our results
correspond to previous cross-linguistic research on the lexical skills of children.
Why do we need cross-linguistic lexical tasks?
Many studies on the lexicons of bilingual children have analysed word knowledge by
considering language scores from only one of the children’s languages (e.g. Bialystok, Luk,
Peets, & Yang, 2010; Pearson, 2010; Umbel, Pearson, Fernández, & Oller, 1992). Studies
analysing both languages of bilingual children have typically focused on one of a limited
number of specific language pairs. The most commonly investigated language pair is
Spanish and English, and in most of the studies, English was the children’s second
language (L2). A comprehensive list of previously studied language pairs is presented in
Appendix 1.
2E. HAMAN ET AL.
Several studies of young children below the age of 3 years (Armon-Lotem & Ohana,
2017; Conboy & Thal, 2006; De Houwer, Bornstein & Putnick, 2014; Gatt, 2017;Miękisz
et al., 2017;O’Toole & Hickey, 2017;O’Toole et al., 2017) have combined two language
adaptations of MacArthur-Bates Communicative Development Inventories (MB-CDI) to
assess children’s lexical development across their languages. This has been possible due to
the large number of available adaptations for this inventory: 61 language versions were
mentioned in a review by Dale and Penfold (2011), and this number is increasing as new
language versions are developed (e.g. Baal & Bentzen, 2014; Dar, Anwaar, Vihman, &
Keren-Portnoy, 2015). Although MB-CDI is potentially a useful tool for providing a
comparable assessment of both languages spoken by young bilingual children (Law &
Roy, 2008), this instrument was originally developed for a monolingual context.
Therefore, MB-CDIs need to be used with caution in clinical practice or research in
multilingual contexts (Gatt, O’Toole, & Haman, 2015). Furthermore, MB-CDIs are
designed for children aged 8–30 months (or in some cases up to 36 months) and do
not cover the full preschool age range.
Instruments designed for bilingual children older than 3 years are scarce and have
typically been developed for one specific population only, such as the Bilingual English
Spanish Assessment (BESA) for Spanish–English-speaking Americans (Peña, Gutierrez-
Clellen, Iglesias, Goldstein, & Bedore, 2014), Sprachstandstest Russisch für mehrsprachige
Kinder [Russian language proficiency test for multilingual children] for Russian–German
children (Gagarina, Klassert, & Topaj, 2010), the Prawf Geirfa Cymraeg [Welsh
Vocabulary Test] for bilingual Welsh–English children with different home-language
backgrounds (Gathercole, Thomas, & Hughes, 2008), and the Bilingual Verbal Ability
Test for children acquiring American English along with one of 17 minority languages
(Muñoz-Sandoval, Cummins, Alvarado, & Ruef, 2005). Going beyond specific language
pairs with preschool children has been a challenge due to the lack of comparable
measures. Given the variety of language combinations in bilingual and multilingual
populations within Europe, Working Group 3 of the recent COST Action IS0804 (Bi-
SLI; http://bi-sli.org/) aimed to construct a set of quasi-universal lexical tasks that could be
freely paired within an extensive list of languages. The CLT is thus a first attempt to design
such a uniform tool across languages. CLT is in the process of being normed on mono-
and bilingual children, and will subsequently be applied in individual diagnosis. Preparing
a normed instrument for clinical practice is a lengthy and expensive process that should be
preceded by extensive research on the tool’s characteristics. Here we present one of the
initial steps in research on designing a tool to assess word knowledge.
Cross-linguistic comparisons of monolingual development
Cross-linguistic comparisons of monolingual children’s lexical development are important
for two reasons. First, such a comparison could shed light on the tool’s cross-linguistic
comparability. If the CLT reveals similar results across languages for monolinguals of
equal age and socio-economic background (SES), we could assume that the CLT is cross-
linguistically comparable not only in terms of design, but also in terms of its relative
difficulty. As a consequence, we could assume that bilingual children who scored equally
in both of their languages are balanced bilinguals in terms of their lexical knowledge. If the
CLT is not directly cross-linguistically comparable (does not reveal similar difficulty across
CLINICAL LINGUISTICS & PHONETICS 3
languages), the tool may still be useful, but analyses across languages would then need to
rely on comparisons with language-specific norms. In any case, before the CLT is used in
diagnosis of both monolingual and bilingual children, norming studies for specific popu-
lations are needed.
Second, cross-linguistic comparisons of monolingual children’s lexical development can
be used to investigate cross-linguistic variation per se. There is strikingly little research on
cross-linguistic differences in lexical development in terms of first-words onset, word-
learning rate or vocabulary size. We need cross-linguistic tools to assess potential cross-
linguistic variability in lexical development. However, any variability found between
languages using such tools could come from either cross-linguistic variability or inherent
differences in the tools. The present study contributes to a deeper understanding of these
issues.
Lexical development attracts the most research attention at its earliest stages: i.e. from
the first words uttered or comprehended (Bergelson & Swingley, 2012; Fenson, Dale,
Reznick, & Thal, 1993). A few publications have aimed to analyse cross-linguistic simila-
rities and differences in the composition of early lexicons across several languages
(Bornstein et al., 2004; Caselli et al., 1995; Conboy & Thal, 2006; Mayor & Plunkett,
2014). However, none of these studies have directly addressed the issue of cross-linguistic
differences in the exact age of use of first words. The exception is the meta-analysis by
Bleses et al. (2008) involving a comparison of the use of words and vocabulary size in 18
languages assessed using MB-CDIs.
Regarding age of the use of first words, a longitudinal multi-case study of spontaneous
speech from English, French, Japanese and Swedish infants (N= 20) showed that Japanese
children (N= 5) produced their first word and reached the 4 and 25 word milestones
about 2 months later than the other infants (de Boysson-Bardies & Vihman, 1991), while
the onset times for English, French and Swedish were very similar to each other.
Results by Bornstein et al. (2004) suggest that although the composition of the
vocabularies of 20-month-old children was similar across seven languages (two
Germanic: Dutch, English; three Romance: French, Italian, and Spanish; and two from
other families: Hebrew and Korean) in terms of the prevalence of nouns over other word
classes, vocabulary size varied across the languages, although the researchers did not
directly comment on this. The data they provided regarding the average scores on ELI,
an earlier version of MB-CDI (Borstein et al., 2004, Table 2, page 1124), showed that
Korean children had the smallest vocabularies and the smallest variation between parti-
cipants, while Hebrew children had the largest vocabularies. There were no significant
differences among speakers of the Romance and Germanic languages. It seems that
differences are more pronounced between language families than within a family. Note
that the study by Bornstein et al. involved a significantly larger sample than de Boysson-
Bardies and Vihman’s(1991) study (N= 269, ranging from N= 28 to 51 per language).
The only large cross-linguistic study tapping directly into data on the age of use of first
words and vocabulary size in early language development was carried out by Bleses et al.
(2008); it involved 14 languages,
1
based on data from over 26,000 children (with a median
1
Existing MB-CDI data were compared for Basque, Mandarin Chinese, Croatian, Danish, Dutch, American
English, British English, Finnish, French, Galician, German, Hebrew, Icelandic, Italian, European
Spanish, Mexican Spanish and Swedish.
4E. HAMAN ET AL.
sample size of 864 children per language, and sample sizes ranging from 30 children for
Chinese to 6112 for Danish). The study showed that Danish children in the age span 8–30
months knew fewer words than children acquiring most of the other languages. Bleses
et al. (2008) argue that this relative lag for Danish speakers is caused by specific phono-
logical features (phonological reductions as compared to the closely related languages
Norwegian and Swedish), which renders Danish words less phonologically transparent
and harder to perceive. Similarly, de Boysson-Bardies and Vihman (1991) argued that the
reason for the delay in Japanese vocabulary acquisition was related to specific features of
word onsets that affected the articulatory process.
One piece of research that could shed light on potential cross-linguistic differences in
lexical development is Bornstein and Hendricks (2012), which assessed children’s lan-
guage comprehension and production in 16 countries.
2
This study used extremely short
parental reports (two simple yes/no questions about whether the child could understand
talk directed to her/him and whether he/she could speak at all), which was filled in by the
parents of over 100,000 children aged 2–9 years. Scores for rates of production by children
aged 2–5 years varied from .84 (for Sierra Leone) to .99 (for Uzbekistan). The two
countries with the lowest scores also have the lowest ratings on the Human
Development Index (HDI), an indicator of life chances that –according to the authors
–may influence language development. However, the study did not gather any detailed
information on what language(s) the children had acquired; most of the countries were
multilingual, and those with the lowest HDI were highly multilingual.
So far, we have considered studies that discuss cross-linguistic similarities and differ-
ences in vocabulary size or the pace of vocabulary acquisition in monolingual children.
Studies like Bleses et al. (2008) have not yet been replicated with older children (above the
age of 3 years), at least partly because of the lack of adequate tools. No instrument exists to
directly measure lexical knowledge in a comparable way for older children across a similar
range of languages. The development of the CLT was intended to fill this gap, tapping
directly into both expressive and receptive vocabulary knowledge in children above the
age of 3 years.
CLT –construction and design
The CLT consists of picture-identification and picture-naming tasks aimed at assessing the
comprehension and production of nouns and verbs via four subtasks, each consisting of
32 items. Each CLT language version was developed according to the same set of criteria.
Target words were selected from a common set of 299 candidate words comprised of 158
nouns and 141 verbs. The list of candidate words was drawn up on the basis of a cross-
linguistic picture-naming study conducted in 34 languages with adult native speakers
(Haman et al., 2015). For a word to be included in the candidate set its meaning had to be
shared in most of the 34 languages. The target word selection process takes into con-
sideration two main factors which are assumed to contribute to the difficulty of word
learning and processing for children and adults: the age of acquisition of the words (AoA)
(D’Amico, Devescovi, & Bates, 2001; Ellis & Morrison, 1998; Juhasz, 2005) and a
2
Albania, Bangladesh, Belize, Bosnia and Herzegovina, Central African Republic, Ghana, Iraq, Jamaica,
Macedonia, Mongolia, Montenegro, Serbia, Sierra Leone, Thailand, Uzbekistan and Yemen.
CLINICAL LINGUISTICS & PHONETICS 5
complexity index (CI) which mainly takes into account the phonological (Morrison, Ellis,
& Quinlan, 1992) and morphological (Baayen, Feldman, & Schreuder, 2006) character-
istics of the target words. The AoA ratings for the words were obtained through a separate
study (Łuniewska & et al., 2015).
3
The CI is based on a set of linguistic features: the
number of phonemes in the word, morphological features (the number of roots for
compound words, whether it is a derived word, plus the number of suffixes and prefixes),
phonological features (the presence of initial fricatives, an initial consonant cluster or an
internal consonant cluster), whether it is a recent loanword and the subjective frequency
of exposure to the word, all as judged by linguists (one expert per language), who filled in
a multipart form which contained questions about all the features for individual words.
The exact formula used for calculating the CI can be found in Haman et al. (2015). In the
construction of the CLT for each language, for both AoA and CI two-level categories were
used (for AoA: early and late; for CI: low and high).
The production subtasks contain one picture for each target word. Each item in the
comprehension subtask consists of a four-picture board containing one picture for the target
word and three distractor pictures; one distractor was a picture used in the production task,
while the other two were selected from words that matched the comprehension targets in
AoA and CI. The target words for the two subtasks were different but had been carefully
matched for their AoA and CI. Thus, across the four subtasks, children were presented with
pictures of the comprehension targets only once. However, pictures of the production
targets were presented twice: once in the production subtask and once in the comprehension
subtask (as distractors).
4
The other distractor pictures never occur twice within the tasks.
All pictures were designed exclusively for the CLT. Some appeared in several versions
to take into account cultural differences. In particular, pictures for actions involving
people depicted different races and genders.
Although both the AoA and CI indices reflect word characteristics which were assumed
to have an effect on word learning and processing, their impact on the accuracy of
performance on the CLT tasks has not previously been directly assessed. This study is
the first to analyse the interaction of the AoA and CI indices in 17 languages with the
scores obtained by monolingual children; Hansen at al. (this issue) do this in more detail
using the same set of monolingual data for Polish and Norwegian, alongside bilingual
Polish–Norwegian data. Similar analysis for Hebrew using monolingual Hebrew and
bilingual Russian–Hebrew data can be found in Altman et al. (this issue).
Target word selection for the CLT followed the same principles across languages, but the
final list of 128 target words was specific for each language version. None of the 299 candidate
words was selected as a target (either for the production or comprehension subtask) in more
than 14 of the 17 languages, and there were no candidate words that were never used as a
target. Figure 1 shows the number of times each candidate word occurred as a target across the
3
Norwegian AoA ratings were obtained through a connected but distinct study, as described and
discussed in Lind, Simonsen, Hansen, Holm, and Mevik (2015).
4
Note that pictures for the production subtasks are never named by the researcher during the testing
procedure. Pictures for the comprehension target words are named by the researcher once in a
comprehension prompt (see next section). This asymmetry was inevitable in the construction of the
CLT due to the limited number of candidate words. A total of 128 pictures/words were needed in
each language, chosen from a set of 299, with strict matching criteria for distractors, which made the
selection quite challenging.
6E. HAMAN ET AL.
17 languages. This distribution is close to what we would expect if the selection of target words
was random. Thus, all 299 words proved useful for this range of languages, which is
important, as no constraints were imposed on the semantics of candidate words during the
selection process. However, the AoA study conducted on the same word list showed that all
these words are on average acquired between the ages of 2 and 8 years in the 25 languages
studied (see Łuniewska et al., 2015). According to the estimated AoA, most of the CLT
candidate words can be assumed to be acquired before the age of five, and only a few after
the age of six. Thus, the CLT may be assumed to be a sensitive measure of lexical development
in children within the age range involved in this study (i.e. 3–6 years), as it potentially contains
target words that vary in difficulty for this age range.
The current study
In this study, we address the issue of potential word-learning differences by children in
terms of vocabulary size, lexicon composition (proportion of nouns and verbs) and
receptive vs. expressive word knowledge across 17 languages from 8 language families:
Baltic (Lithuanian), Bantu (isiXhosa), Finnic (Finnish), Germanic (Afrikaans, British
English, South African English, German, Luxembourgish, Norwegian, Swedish),
Romance (Catalan, Italian), Semitic (Hebrew), Slavic (Polish, Serbian, Slovak) and
Turkic (Turkish). In view of previously published research findings, we expected partici-
pants to achieve higher accuracy on the lexical tasks for nouns than for verbs (Gentner,
1982; Gentner & Boroditsky, 2001; Tomasello & Merriman, 1995) and higher accuracy for
comprehension than production (Bates & Goodman, 1999; Benedict, 1979; Clark, 2009;
Fenson et al., 1994, Goldfield, 2000; Harris, Yeeles, Chasin, & Oakley, 1995; Reznick &
Goldfield, 1992) across all languages studied. We also expected that the assessment would
be sensitive to the participants’age, showing an increase in accuracy with age. To
investigate the comparability of the different CLT versions, we also examined the potential
impact on results of the language-specific background variables used in constructing the
CLT, namely the AoA and CI.
Figure 1. Distribution of frequency of word choice across 17 CLT language versions.
CLINICAL LINGUISTICS & PHONETICS 7
We did not formulate specific hypotheses regarding overall differences in vocabulary
size among the languages, since previous studies present ambiguous and incomplete
results about this issue. Thus, cross-linguistic analyses concerning vocabulary size are
exploratory in nature here.
The sample of languages shows some imbalance. Indo-European languages dominate
the sample (13 out of the 17 languages), with half of the Indo-European group
consisting of Germanic languages. Only four languages (Hebrew, Finnish, Turkish
and isiXhosa) represent non-Indo-European language families. This reflects the fact
that our data are drawn from the networking programme of COST Action IS0804,
which focuses on languages of the European Union, rather than from a systematically
constructed research project. It was only possible to add languages spoken in non-EU
countries when COST awarded the country special status to be included in the Action.
Additionally, although the CLT is now available for 25 languages (http://psychologia.pl/
clts/), as can be seen in other articles in this issue, collecting monolingual data for some
of them was not possible since there are no monolingual speakers of these languages
(e.g. for Maltese, Gatt et al., this issue; and Lebanese, Khoury Aouad Saliby et al., this
issue). Thus, for this study we analysed data from monolingual children speaking one
of 15 mostly European languages.
Method
Participants
The participants consisted of 639 monolingual children (52% female) within an age range
of 3;0–6;11 years. The distribution of participants was not equal across age groups (given
in one-year intervals): the largest age group comprised 5-year-olds (46% of all children),
followed by 4-year-olds (23%) and 6-year-olds (21%). Table 1 presents the number of
participants by average age for each language group. Participants were recruited through
preschools and schools, under the inclusion criteria that they were typically developing
children with no previous diagnosis of language or cognitive problems. For 11 of the
Table 1. Number of participants per age and language group.
Language\age group 3 4 5 6 Total per language Mean age per language
Afrikaans 1 20 –– 21 4;5
Catalan 20 20 20 –60 4;7
English (British) ––8 9 17 5;11
English (South African) –10 18 1 29 5;2
Finnish 11 10 15 11 47 5;0
German ––33 3 36 5;6
Hebrew ––11 4 15 5;8
IsiXhosa –10 –– 10 4;6
Italian ––10 15 25 6;2
Lithuanian 3 9 14 16 42 5;6
Luxembourgish –17 38 34 89 5;8
Norwegian 6 9 11 –26 4;8
Polish –11 38 15 64 5;6
Serbian –1 13 6 20 5;10
Slovak 18 18 22 15 73 5;0
Swedish –7 24 1 32 5;4
Turkish –7 20 6 33 5;5
Total 59 149 295 136 639 5;4
8E. HAMAN ET AL.
languages (Afrikaans, British English, South African English, Finnish, Hebrew, isiXhosa,
Norwegian, Polish, Serbian, Slovak, Swedish), participants’basic SES data were available,
which confirmed that most of the participants came from a mid-to-high SES. The
exceptions were participants from South Africa, for which the SES was carefully ascer-
tained and used in separate analyses (Potgieter & Southwood, 2016); half of the speakers of
Afrikaans and South African English, and all the speakers of isiXhosa, came from a low
SES background. For the remaining six languages (Catalan, German, Italian, Lithuanian,
Luxemburgish and Turkish), no SES data were available for the individual child partici-
pants; however, their place of recruitment (e.g. school and type of neighbourhood)
reflected a mid-to-high SES environment.
Procedure
To assess children’slexical knowledge, we used the CLT in their respective languages. The
children were assessed in their preschools or schools in a quiet setting (such as a separate
room). They were acquainted with the experimenter prior to testing. For most of the languages
tested, paper CLT versions were used: for the comprehension subtasks, one target picture and
three distractors were presented per page, printed in colour in A4 format (landscape). The
production subtasks contained a single-coloured picture per page, printed in A5 format (land-
scape). This ensured that the pictures were of a similar size across the subtasks. For three of the
languages (Norwegian, Polish and Slovak), e-versions of the task were used, with the pictures
presented on a computer touch-screen, and the prompts for target words were pre-recorded.
For German, a PowerPoint version was used, with pictures presented on the computer screen
and pre-recorded prompts, but without the automatic saving of responses (no touch-screen was
available). Otherwise, the procedure was as similaraspossibletothepaperversiondescribed
above. The differences in task delivery reflected specific research goals of the various language
teams which went beyond the aims of the current analyses.
5
We consider the various versions of
theCLTstobeequivalent,sincetheadministrationprocedurewasthesame,withthe
introductory instructions always provided by the experimenter; the only difference was whether
or not item prompts (questions) were pre-recorded. In both cases, children were asked to point
to or name the picture which corresponded to the prompt. Considering the rapidly rising access
of very young children in the mid-to-high SES groups to electronic and mobile devices which
mostly use touch-screens (Holloway, Green, & Livingstone, 2013), we did not expect that the
difference in picture presentation would affect the results of our study.
At the beginning of the assessment, the children were told, using simple wording, that
they were going to view a series of pictures, and that the researcher would ask them about
the pictures. They were informed that there would be one question per page, and that
pointing to one picture or giving a one-word answer would be sufficient. The original
introductory instructions were written in English and subsequently translated into the
other languages, with the recommendation that the wording should be natural and play-
like, using simple vocabulary appropriate for young children. The form of the prompts in
the comprehension subtasks were: ‘Where is the [x, target noun]?’(e.g. squirrel), ‘Who is
5
Specifically, the teams using e-versions were interested in word-processing speed for the two word
classes assessed in the comprehension and production tasks. Reaction time measurement was not
possible with the printed version.
CLINICAL LINGUISTICS & PHONETICS 9
[x-ing, target verb]?’(for agentive verbs, e.g. singing) and ‘Where is it [x-ing, target verb]?’
(for stative verbs, e.g. raining). The form of the prompts in the production subtasks were:
‘What/who is this?’for nouns, ‘What is he/she doing?’for agentive verbs and ‘What is
happening here?’for stative verbs (e.g. boiling).
The order for administering the four subtasks was balanced so that nearly equal
numbers of participants received each of the four possible orders, as shown in Table 2.
A short break could be taken between the subtasks if needed. Once all the subtasks were
completed, the children were thanked for their participation.
Results
Preliminary data analysis
Items removed from analysis
As mentioned above, there were 32 items in each subtask of the CLT for all language
versions. The complete set of items is analysed here for 14 of the 17 languages. For three
language versions, some items were removed from the analysis.
For British English, we have used results from the pilot version of the CLT. In the
analysis here, we only include items that were used in both the pilot version and the final
version of the tasks (28 items for both noun production and comprehension; 26 items for
verb production; 25 items for verb comprehension).
Due to an error in constructing the Afrikaans version, two items were repeated in the
production and comprehension tasks (helikopter in the noun subtasks, and brei ‘to knit’in
the verb subtasks). We dealt with this by counting helikopter as a target word for
comprehension but not for production, and brei as a target word for production but
not for comprehension; these are the subtasks where these items occur in the final
corrected version of the Afrikaans CLT. Thus, for Afrikaans we have analysed 31 items
for noun production and verb comprehension, and 32 items for the two other subtasks.
For isiXhosa, an error in constructing this version of the CLT led to most items in the
verb comprehension subtask not being the right ones. As only six items were correct, we
omit the isiXhosa verb comprehension subtask in the analysis.
Item and subtask difficulty
In order to assess the influence of AoA and CI, the language-specific variables used in
constructing the CLTs, we analysed the effects of these factors on item difficulty, as
measured by the percentage of children who responded correctly to a particular item in
a given language. We calculated the Spearman ρcorrelations for AoA and CI with item
difficulty in each subtask for each language version.
Table 2. Order of CLT delivery.
First subtask Second subtask Third subtask Forth subtask
ORDER 1 Verb comp Noun comp Verb prod Noun prod
ORDER 2 Noun comp Verb comp Noun prod Verb prod
ORDER 3 Noun prod Verb prod Noun comp Verb comp
ORDER 4 Verb prod Noun prod Verb comp Noun comp
10 E. HAMAN ET AL.
To analyse the accuracy of the monolingual children’s performance on the CLTs, we
calculated the mean percentage of correct responses for each of the four subtasks in each
language. The percentage score was used instead of raw scores, as some items were
excluded from the analyses, as discussed above.
Below, we report first on results concerning the evaluation of the CLT background
variables, and then proceed to analyses that are linked to our expectations regarding higher
accuracy for older participants, for nouns vs. verbs, and for comprehension vs. production,
including also exploratory analyses regarding potential differences across languages.
Effects of AoA and CI on item difficulty
For the AoA, we found a pattern of significant moderate-to-strong negative correlations
with item difficulty (Table 3) in over 72% of cases (all the subtasks in all languages). The
number of languages in which significant correlations were found differed across subtasks:
10 for noun comprehension, 11 for noun production, 12 for verb comprehension and 16
for verb production. The average Spearman ρof all significant coefficients for a subtask
ranged from –.49 for noun comprehension to –.59 for noun production. In general, the
correlation was stronger for verbs than for nouns.
This pattern of correlations was not repeated for the CI, where significant low-to-
moderate negative correlations were found for only 13% of the subtasks, mostly verb
production (Table 4). In 10 languages there was no effect of the CI at all.
Accuracy
The mean accuracy rating for each subtask in each of the 17 languages is given in Figure 2.
Accuracy ranged from 72% to 100% for noun comprehension (Mdn = 98%); from 80% to
98% for verb comprehension (Mdn = 92%), from 41% to 93% for noun production (Mdn
= 82%), and from 28% to 85% for verb production (Mdn = 66%).
Table 3. Correlations between item difficulty and AoA in 17 languages (Spearman ρcoefficients).
Comprehension Production
Language/task Nouns Verbs Nouns Verbs nRange: years Range
Afrikaans −0.41* −0.61** ns −0.68*** 21 0.98 3;11–4;11
Catalan −0.45** −0.53*** −0.46** −0.49** 60 2.59 3;4–5;11
English (British) NA ns ns −0.53*** 17 1.58 5;2–6;9
English (South African) −0.65*** −0.62*** −0.56** −0.65*** 29 2.18 4;0–6;2
Finnish ns −0.67*** −0.60*** −0.43* 47 3.92 3;0–6;11
German ns −0.49** ns −0.42* 36 1.22 5;0–6;3
Hebrew −0.49*** −0.56*** ns –0.67*** 15 1.29 5;0–6;3
IsiXhosa −0.63*** NA −0.79*** −0.42* 10 0.75 4;0–4;10
Italian ns ns −0.46** −0.70*** 25 1.65 5;3–6;11
Lithuanian ns −0.64** ns ns 42 3.5 3;5–6;11
Luxembourgish −0.47** −0.74*** −0.65*** −0.58*** 89 2.18 4;7–6;10
Norwegian −0.56** −0.36* −0.58*** −0.69*** 26 2.42 3;6–5;11
Polish −0.42* −0.56** −0.68*** −0.64*** 64 2.81 4;1–6;11
Serbian −0.30* ns ns −0.53** 20 1.59 4;11–6;6
Slovak ns −0.70*** −0.72*** −0.55** 73 3.66 3;4–6;11
Swedish −0.48** ns −0.53** −0.36* 32 1.63 4;4–6;0
Turkish ns −0.42* −0.44** −0.59*** 33 2.63 4;1–6;10
Note. English noun comprehension: no variance. *** means significance at p ≤0.001; ** means significance at p ≤0.01; *
means significance at p ≤0.05; ns means non-significant result.
CLINICAL LINGUISTICS & PHONETICS 11
Participants’age
Analysis of the results for each of the 639 participants showed a significant positive
correlation between overall accuracy (percentage of correct answers in all subtasks for
each child) and the participants’age (in months) for the languages taken together (ρ= .61;
p< .001), as well as for 11 individual languages (see Table 5). The Spearman ρcoefficients
for the subtasks ranged from .26 (noun comprehension in Polish) to .82 (verb production
in Norwegian) and, in eight of the 17 languages, the correlation was significant for at least
three of the four subtasks.
Language, subtask and word class
We first ran a multivariate analysis of variance (MANOVA) to explore the differences
between the results in isiXhosa and the other languages. The dependent variables were the
Table 4. Correlations between item difficulty and CI in 17 languages (Spearman ρcoefficients).
Comprehension Production
Language /task Nouns Verbs Nouns Verbs nRange: years Range
Afrikaans ns ns ns −0,44* 21 0,98 3;11–4;11
Catalan ns ns ns ns 60 2,59 3;4–5;11
English NA ns ns ns 17 1,58 5;2–6;9
English (South African) −0,37* ns −0,50** ns 29 2,18 4;0–6;2
Finnish ns ns −0,38* −0,42* 47 3.92 3;0–6;11
German ns ns ns ns 36 1,22 5;0–6;3
Hebrew ns ns ns ns 15 1,29 5;0–6;3
IsiXhosa ns NA ns ns 10 0,75 4;0–4;10
Italian ns ns ns ns 25 1,65 5;3–6;11
Lithuanian ns −0,38* ns ns 42 3,5 3;5–6;11
Luxembourgish ns ns ns ns 89 2,18 4;7–6;10
Norwegian ns ns ns ns 26 2,42 3;6–5;11
Polish ns ns −0,41* ns 64 2,81 4;1–6;11
Serbian ns ns ns −0,39* 20 1,59 4;11–6;6
Slovak ns ns ns ns 73 3,66 3;4–6;11
Swedish ns ns ns ns 32 1,63 4;4–6;0
Turkish ns ns ns −0,53** 33 2,63 4;1–6;10
Note. English noun comprehension: no variance. *** means significance at p ≤0.001; ** means significance at p ≤0.01; *
means significance at p ≤0.05; ns means non-significant result.
Figure 2. CLT accuracy across 17 languages.
Note. Verb comprehension data in isiXhosa were not included in the analysis. Error bars represent 1/2 SD.
Tables –Noun and verb knowledge in monolingual preschool children across 17 languages: Data from
Cross-linguistic Lexical Tasks (CLTs)
12 E. HAMAN ET AL.
scores on the three subtasks for which isiXhosa data were available (noun comprehension,
noun production, verb production), and the independent variable was language. There
was a significant effect of language (F(48,1866) = 15.2, p<.001). We then ran a Dunett t
post-hoc test to determine whether the isiXhosa results differed from those in the other
languages. All pairwise comparisons were significant (p<.001 in all 48 cases), revealing
that the isiXhosa results were lower than results in all the other languages for all three
subtasks. Because of this, the isiXhosa data were omitted from further analyses of the
effects of language, subtask and word class.
We ran a repeated-measure ANCOVA using within-subject factors (type of task:
comprehension vs production; and word class: noun vs. verb), a between-subject factor
(language), and a covariate (age). This analysis revealed significant main effects of lan-
guage, participants’age, subtask and word class (see Table 6). As the main effect of
language was weak (partial η
2
= .16) and the main effects of subtask (partial η
2
= .28)
and word category (partial η
2
= .25) were stronger, we ran partial comparisons of
estimated marginal means for the latter two factors.
Table 5. Correlations of the CLTs results with the participants’age (Spearman ρcoefficients).
Comprehension Production
Language/task Nouns Verbs Nouns Verbs Total nAge range
Total 0.49*** 0.50*** 0.52*** 0.51*** 0.61*** 639 3;0–6;11
Afrikaans ns ns ns ns ns 21 3;11–4;11
Catalan 0.52*** 0.75*** 0.61*** 0.73*** 0.81*** 60 3;4–5;11
English NA ns ns ns ns 17 5;2–6;9
English (South African) 0.59** 0.62*** 0.67*** 0.72*** 0.66*** 29 4;0–6;2
Finnish 0.57*** 0.69*** 0.66*** 0.68*** 0.73*** 47 3;0–6;11
German ns ns ns ns ns 36 5;0–6;3
Hebrew ns 0.55* ns ns ns 15 5;0–6;3
IsiXhosa ns NA 0.73* ns ns 10 4;0–4;10
Italian ns ns ns 0.40* 0.46* 25 5;3–6;11
Lithuanian 0.49** 0.47** 0.43** 0.62*** 0.61*** 42 3;5–6;11
Luxembourgish 0.36*** ns 0.31** ns 0.25* 89 4;7–6;10
Norwegian ns 0.68*** 0.74*** 0.82*** 0.80*** 26 3;6–5;11
Polish 0.26* 0.36** 0.38** 0.48*** 0.50*** 64 4;1–6;11
Serbian ns ns ns 0.71** 0.57** 20 4;11–6;6
Slovak 0.39* 0.67*** 0.47*** 0.52*** 0.64*** 73 3;4–6;11
Swedish 0.53** 0.36* 0.46* 0.51** 0.58** 32 4;4–6;0
Turkish ns 0.39** ns ns 0.40* 33 4;1–6;10
Note. There was no variance for the comprehension of nouns in the British English.
Verb comprehension data in isiXhosa were not included in the analysis.
***, ** and * indicate significance levels at p≤0.001, p≤0.01 and p≤0.05, respectively; ns –non-significant result.
Table 6. Within-subject and between-subject effects in the ANCOVA.
df FpPartial η
2
Between-subject Intercept 1 859.42 <0.001 0.58
Age 1 260.84 <0.001 0.30
Language 15 7.78 <0.001 0.16
Error df 612
Within-subject Subtask 1 234.42 <0.001 0.28
Subtask * age 1 56.75 <0.001 0.09
Subtask * language 15 5.20 <0.001 0.11
Word category 1 204.30 <0.001 0.25
Word category * age 1 82.52 <0.001 0.12
Word category * language 15 22.11 <0.001 0.35
Task * word category 1 0.78 0.38 0.00
CLINICAL LINGUISTICS & PHONETICS 13
Subtask
A comparison of the marginal means with a Bonferroni correction for confidence
intervals showed significant effects of subtask for all 16 languages: there were higher
scores for the comprehension tasks than for the production tasks across all languages
(Table 7).
Word class
A comparison of the marginal means with a Bonferroni correction for confidence
intervals showed significant effectsforwordclassin13ofthe16languages,the
exceptions being Afrikaans, Norwegian and Swedish. In those 13 languages, the
scores were higher for the noun tasks than for the verb tasks. For the other three
languages, the direction of difference was the same but was not significant. Table 8
presents the exact values of marginal means for all the languages.
Table 7. Marginal means of the subtask results across languages, with a Bonferroni correction for the
confidence intervals.
Language Subtask Mean SE
95% Confidence interval
Lower bound Upper bound
Afrikaans*** Comprehension 0.89 0.01 0.86 0.92
Production 0.73 0.02 0.69 0.77
Catalan*** Comprehension 0.91 0.01 0.90 0.93
Production 0.72 0.01 0.70 0.74
English (British)*** Comprehension 0.96 0.02 0.93 0.99
Production 0.79 0.02 0.75 0.83
English (South African)*** Comprehension 0.90 0.01 0.87 0.92
Production 0.75 0.02 0.71 0.78
Finnish*** Comprehension 0.95 0.01 0.93 0.97
Production 0.74 0.01 0.71 0.76
German*** Comprehension 0.95 0.01 0.93 0.97
Production 0.83 0.01 0.80 0.86
Hebrew*** Comprehension 0.92 0.02 0.89 0.95
Production 0.71 0.02 0.66 0.75
Italian*** Comprehension 0.93 0.01 0.90 0.95
Production 0.71 0.02 0.67 0.74
Lithuanian*** Comprehension 0.95 0.01 0.93 0.97
Production 0.78 0.01 0.76 0.81
Luxembourgish*** Comprehension 0.91 0.01 0.91 0.93
Production 0.73 0.01 0.71 0.75
Norwegian*** Comprehension 0.96 0.01 0.93 0.98
Production 0.73 0.02 0.69 0.76
Polish*** Comprehension 0.95 0.01 0.93 0.97
Production 0.77 0.01 0.75 0.79
Serbian** Comprehension 0.95 0.02 0.92 0.98
Production 0.85 0.02 0.81 0.89
Slovak*** Comprehension 0.91 0.01 0.89 0.92
Production 0.74 0.01 0.72 0.76
Swedish*** Comprehension 0.96 0.01 0.94 0.99
Production 0.78 0.02 0.75 0.81
Turkish*** Comprehension 0.98 0.01 0.96 1.00
Production 0.81 0.01 0.78 0.84
Note. *** and ** indicate significance levels at p≤0.001 and p≤0.01, respectively.
14 E. HAMAN ET AL.
Discussion
The impact of background variables on CLT results
First, we evaluated the impact of the two background variables that were used to select
target words for the assessment tasks –AoA and CI. As expected, for AoA, the correla-
tions were negative for all languages (the higher a word’s AoA value, i.e. the later a word is
acquired, the lower its item accuracy). For 12 of the languages, correlations were sig-
nificant for at least three of the four subtasks (Table 3). For British English, German,
Italian and Lithuanian, the lack of significant correlations for noun subtasks can be
attributed to a ceiling effect in the CLT results. It is harder to explain the lack of a
significant correlation for Serbian noun production and Lithuanian verb production, the
latter being the only non-significant result among all the verb production subtasks.
The second factor used for target word selection was the CI. Contrary to our predic-
tions, there was no significant correlation between the CI and item accuracy for most
languages and subtasks (Table 4). This may be due to the compositionality of the CI,
which was meant to account for various word characteristics: phonological, morphologi-
cal, whether it is a loanword, and children’s exposure to the object or action depicted by
Table 8. Marginal means of the word categories results across languages, with a Bonferroni correction
for the confidence intervals.
Language Subtask Mean SE
95% Confidence interval
Lower bound Upper bound
Afrikaans
ns
Nouns 0.82 0.01 0.80 0.85
Verbs 0.80 0.02 0.76 0.84
Catalan*** Nouns 0.92 0.01 0.90 0.93
Verbs 0.72 0.01 0.70 0.74
English (British)* Nouns 0.92 0.01 0.89 0.95
Verbs 0.83 0.02 0.79 0.87
English (South African)*** Nouns 0.89 0.01 0.87 0.91
Verbs 0.75 0.02 0.72 0.78
Finnish*** Nouns 0.90 0.01 0.88 0.91
Verbs 0.79 0.01 0.77 0.82
German*** Nouns 0.93 0.01 0.91 0.95
Verbs 0.85 0.01 0.82 0.88
Hebrew*** Nouns 0.89 0.02 0.86 0.92
Verbs 0.74 0.02 0.69 0.78
Italian*** Nouns 0.90 0.01 0.87 0.92
Verbs 0.74 0.02 0.70 0.77
Lithuanian** Nouns 0.90 0.01 0.88 0.92
Verbs 0.84 0.01 0.81 0.86
Luxembourgish*** Nouns 0.88 0.01 0.87 0.90
Verbs 0.76 0.01 0.74 0.78
Norwegian
ns
Nouns 0.87 0.01 0.85 0.89
Verbs 0.81 0.02 0.78 0.85
Polish*** Nouns 0.90 0.01 0.89 0.92
Verbs 0.82 0.01 0.80 0.84
Serbian* Nouns 0.94 0.01 0.91 0.97
Verbs 0.86 0.02 0.82 0.90
Slovak*** Nouns 0.89 0.01 0.87 0.90
Verbs 0.76 0.01 0.74 0.78
Swedish
ns
Nouns 0.88 0.01 0.86 0.90
Verbs 0.86 0.02 0.83 0.89
Turkish** Nouns 0.93 0.01 0.91 0.95
Verbs 0.86 0.02 0.83 0.88
Note. ***, ** and * indicate significance levels at p≤0.001, p≤0.01 and p≤0.05, respectively; ns –non-significant result.
CLINICAL LINGUISTICS & PHONETICS 15
the word (Haman et al., 2015). Hansen et al. (this issue) discuss possible reasons under-
lying the absence of correlation between the CI and item accuracy. They suggest that
including characteristics from several different domains in one composite score may lead
to an inconsistent measure, as particular components may give contradictory values. Thus,
the resulting average score (a word’s CI) may fail to reflect the actual difficulty of each
component. However, when these word characteristics were analysed separately, the only
component that had some impact was exposure (whether children had frequent and easy
access to the object or action depicted by the word). The expected correlation with
phonology, morphology or borrowings was not found. It is not clear, however, whether
the target words used in the Polish and Norwegian versions of the CLT presented enough
variability in each of these domains to reveal significant effects, as target word selection for
these CLTs was based on only two levels of the composite CI score: low and high (i.e.
under or above the mean for each language). Another possibility is that the complexity
measures used for the different domains did not capture actual word complexity for all
languages. It is also possible that word complexity has more influence on word learning at
earlier ages, while participants in this study were mostly 4–6-year olds. Phonology has
indeed been shown to have an influence on word learning in several cross-linguistic
comparison tasks for children below the age of 3 years, as discussed in Hansen et al.
(this issue). It is possible that once the phonological system of a language is mastered,
phonology exerts less influence on lexical development, at least as long as the words
comply with the phonological characteristics of the language.
It is also possible that word complexity in terms of phonology and morphology
influences word learning in different ways in each language. Calculating the CI in the
same way for every language might thus be inadequate. For example, languages differ
when it comes to typical word length (Garmann, Hansen, Simonsen, & Kristoffersen, in
press). This suggests that the relationship between word length and word difficulty is not
linear but depends on which phonological patterns are typical in the language. For
instance, English and Danish children tend to prefer monosyllabic words in their produc-
tion (Garmann et al., in press), while children acquiring Italian produce very few mono-
syllables and tend to acquire di- and polysyllabic words first (Caselli et al., 1995). When it
comes to morphology, both inflectional and derivational morphology are mastered earlier
in morphologically rich languages than in morphologically poor ones (Clark, 2001), and
thus morphology might not have an impact on word difficulty for children of the age
range under scrutiny in this study. Thus, the CI requires much more detailed investigation
for individual languages, using new data possibly from younger children, before the
hypothesis that it plays a role in word learning is rejected.
Effect of participants’age
Next, we evaluated the CLT’sability to reflect the expected increase in vocabulary size with
age. We found strong significant positive correlations between overall CLT scores and the
participants’age across all samples. This result holds for all four subtasks, and for 11 out
of 17 languages (see Table 5).
No age effect was found for four languages (Afrikaans, British English, Hebrew and
isiXhosa). This may be due to the small sample sizes (N≤21) and narrow age ranges
(< 1.58 years; see Table 1).ForGerman,thesamplesizewasmoderate(N=36),but
16 E. HAMAN ET AL.
the age range was low (1.22), and as the participants were all at or above the age of 5;0,
there were ceiling effects in the CLT results (especially for noun comprehension, where
there was no variation at all, see Figure 2). This meant that there was a lower
correlationwithagefortheGermangroup.Whenthesamplesizeandagerange
were adequate, the CLT was sensitive to participants’age, which confirms that the
measure reflects expected developmental changes in vocabulary size for children over
the age of three.
IsiXhosa as an exception
In the overall analysis of CLT performance, we found that one language was an outlier in
comparison to all the other languages. The scores for the isiXhosa CLT were significantly
lower than for all the other languages on all three subtasks analysed for isiXhosa. This
could be due to the small sample size (N= 10) and relatively low age of the isiXhosa
participants (average age 4;6), but there is some evidence that this finding may reflect real
differences in lexical development. First, Potgieter and Southwood (2016) report that the
isiXhosa vocabulary size of monolingual isiXhosa-speaking children (the group which is
reported on here) does not differ from that of South African trilinguals. They also state
that monolingual isiXhosa children came from a low SES. This was unavoidable, as in the
South African society, parents with a higher socio-economic status who speak isiXhosa
have a strong tendency to raise their children bilingually, perceiving the ability to speak
South African English as providing an opportunity for social advancement. Second, in the
study of subjective age of acquisition in 25 languages carried out by Łuniewska et al.
(2015), adult native speakers of isiXhosa generally rated the words as being acquired at a
later age than speakers of other languages did. Note that isiXhosa, the only example of a
Bantu language in our sample, is a seriously understudied language in terms of language
acquisition. It is thus possible that the rate of isiXhosa lexical acquisition does indeed
differ significantly from that of the other languages included here, but it is not clear
whether this is due to linguistic properties of isiXhosa, the social status of isiXhosa
speakers in South African society, or other factors.
Word class
Our results confirmed that overall nouns are learned earlier than verbs across all languages
apart from Afrikaans, Swedish and Norwegian. The lack of a word class effect for these
three languages was due to high variability in accuracy on the verb tasks (Table 8),
although the difference was in the expected direction (see Figure 2).
For the 14 other languages, there was a consistent pattern of better performance on the
noun subtasks, which supports claims that nouns take precedence in lexical development
(Black & Chiat, 2003; Bornstein et al., 2004; Gentner, 2006). Our findings may reflect a
greater conceptual saliency of nouns over verbs, and a greater reliance of verbs on
linguistic structure (Gentner & Boroditsky, 2001). It is, however, important to note that
the fact that the CLT is based on pictures may in itself give an advantage to nouns, as the
picture prompts for nouns are perceptually simpler than those for verbs. The nouns are
typically represented by single objects or people, whereas most of the verbs are depicted by
human characters performing an action. In many cases, the pictures for verbs include
CLINICAL LINGUISTICS & PHONETICS 17
instruments required for carrying out the actions or clues about the environment in which
the action is typically performed. For example, a picture prompt for a saw only requires
the object itself, while a picture prompt for the verb ‘to saw’requires an agent and an
instrument. This difference was unavoidable and is also discussed in previous studies
comparing noun and verb production through picture tasks (Bello et al., 2012; Kauschke,
Lee, & Pae, 2007; Masterson, Druks, & Gallienne, 2008; Mätzig, Druks, Masterson, &
Vigliocco, 2009). However, this effect (better performance on nouns than verbs) also holds
across a wide variety of languages when other measures are used, e.g. in studies using MB-
CDI or similar parental checklists (Bornstein et al., 2004; Caselli et al., 1995).
Comprehension vs. production
As predicted, lexical comprehension was more advanced than production for participants
from each of the languages studied (Table 7). Findings showing the primacy of compre-
hension over production (Benedict, 1979; Bornstein & Hendricks, 2012; Clark, 2012;
Goldfield, 2000; Goldin-Meadow, Seligman, & Gelman, 1976; Harris et al., 1995;
Reznick & Goldfield, 1992) are robust, and our data add to this body of research.
Production is claimed to be more demanding in terms of long-term memory and lexical
access. Clark (1993,2009) suggests that children have separate word representations for
comprehension and production, and that this allows them to operate on word meanings
before mastering their articulatory form and actually enables them to come up with the
adult form by comparing the non-mastered child form with the adult version, which is
represented initially only at a comprehension level. According to Clark, the discrepancy
between comprehension and production holds from early childhood to adulthood.
It should also be noted that in our study, this effect in part reflects the specificity of
each subtask. For the comprehension tasks, there were only four possible answers, as the
child was asked to choose among four pictures. In contrast, the production task required
selecting a word from an open set limited only by the child’s overall lexical repertoire
(Markman, 1989; Quine, 1960). Although children may overcome this problem either by
applying constraints in selecting possible meanings for a word (Clark, 1995; Markman,
1991) or by using more general conceptual strategies (Bloom, 2000), they may still provide
a variety of adequate labels for a picture in a naming task. For this article, the only
production responses considered to be correct were those involving the target word
(allowing only for mispronunciations or unexpected inflections, as long as the target
word stem was present), as discussed by Kapalková and Slančová (this issue). This is
because the AoA and CI, which underlie the development of the tasks, were available only
for target words and not for other potential answers children may provide). When CLT is
used to investigate differences between groups, synonyms typically count as correct
responses, according to guidelines agreed upon in the Bi-SLI Working Group 3, which
is discussed in detail by Kapalková and Slančová (this issue).
Cross-linguistic differences
Overall, we found only a small effect (partial η
2
= .16) of language on the CLT results
when the outlier isiXhosa was removed. Thus, there were only small differences in
vocabulary size, as measured by CLT, between the 16 other languages. However, as
18 E. HAMAN ET AL.
there were differences in the age range of the participants for the languages, we cannot
draw any strong inferences about this factor. To gain a deeper insight into potential cross-
linguistic differences in word learning, we need to systematically assess younger children
in order to bypass ceiling effects which were evident in many of the languages for nouns
and sometimes even for verbs. The current results obtained from monolingual children
suggest, however, that for this age range the CLT may be an adequate screening tool for
assessing lexical knowledge, as it is sensitive to the participants’age and differentiates well
between comprehension and production, as well as between nouns and verbs, in line with
previous research. Thus, we could expect that the CLT will also adequately assess word
knowledge in bilingual and multilingual children. This has already been partially demon-
strated for a limited number of language pairs: Polish–Norwegian (Hansen et al., this
issue); Maltese–English (Gatt et al., this issue), and one trilingual configuration: South
African English, Afrikaans and isiXhosa (Potgieter & Southwood, 2016). Further studies
should confirm whether the CLT may also be used in assessing the severity of specific
language impairment (SLI) in the lexical domain or for establishing the type of SLI
(Friedmann & Novogrodsky, 2008). To date, a study of monolingual Slovak children
has shown the CLT’s sensitivity at the group level in differentiating between children
with language impairment and their typically developing peers. The same study provided
insights into different error patterns on naming subtasks between impaired children and
typically developing peers who were matched on comprehension results (Kapalková &
Slančová, this issue). Similarly, a study of bilingual children acquiring Lebanese as one of
their languages showed differences in the Lebanese vocabulary size (as assessed by CLT)
between children with and without a language impairment (Khoury Aouad Saliby et al.,
this issue).
Limitations of this study
One limitation of this study is that it does not account in detail for potential differences in
vocabulary caused by the socio-economic status of participants. The influence of this
factor on children’s lexical knowledge is now well attested (Hart & Risley, 1995;Hoff,
2003). The fact that isiXhosa was the only outlier language in our study may at least
partially be explained by these participants’low socio-economic status, as discussed in
more depth in Potgieter and Southwood (2016).
Although our overall sample is quite large, it should be noted that some language
subsamples had only a small number of participants. It is also clear that the CLT has limits
to its sensitivity in discerning age differences. In particular, a ceiling effect for noun
comprehension, observable for some languages, indicates that for typical populations the
CLT may not be sensitive enough above the age of 5–6 years. However, this does not
exclude its usefulness as a potential screening tool for children who are suspected of
having a language disorder or who have limited language input (e.g. successive bilinguals)
at the age of 6 years or even beyond.
More studies need to be conducted using the CLT, and directed specifically at the problems
highlighted above, before any claims can be made about its ability to account for e.g. socio-
economically-driven differences in children’s lexical knowledge. In addition, more research on
impaired populations is needed to confirm the CLT’s validity in assessing vocabulary devel-
opment in a clinical context. At this point, we assume that the CLT is a sensitive measure of
CLINICAL LINGUISTICS & PHONETICS 19
children’s receptive and expressive lexicon, suitable for use with typically developing mono-
lingual children above the age of 3 years, with the potential for it to become a wider
assessment tool when new data (or norming studies) become available for particular languages
or language pairs for specific populations (e.g. monolingual or bilingual children).
CLT: Future directions
This article, along with the other articles in this issue, present a first cross-linguistic
comparison of results obtained using the CLT for word knowledge in preschool children.
We are still at the initial stages of applying the CLT for diagnostic and clinical purposes.
To render the CLT useful in clinical settings, norming studies are needed, controlling for
participants’SES (Hart & Risley, 1995; Roy & Chiat, 2012), as well as quantifying language
input for bilingual and multilingual populations (Gathercole et al., 2008).
Revisions to the CLT should also be considered, particularly if it is meant to be used as
an effective diagnostic tool. In the current study, all the participants took part in a
relatively long testing session –they performed all subtasks on all items. Once more
data are available, important modifications to the procedure can be envisaged, namely
adaptive testing: adjusting the test difficulty to the child’s performance during testing.
However, implementation of adaptive testing would only be possible with fully computer-
ized versions of the CLT, which is another potential future direction for the development of
the CLT. Fully computerized versions would also enable inclusion of additional variables, such
as processing speed, which may prove to be of importance for clinical assessment, since
children with SLI are sometimes claimed to have lower processing abilities when compared to
typically developing children (Lahey & Edwards, 1996;Lahey,Edwards,&Munson,2001).
For future studies, the CLT is freely available to all interested researchers (http://
psychologia.pl/clts/). New language versions are under development (e.g. American
English, Armenian and Malay), and new collaborators who are willing to develop the
CLT for other languages are welcome.
Acknowledgments
This study is a result of collaboration that took place within the COST Action IS0804 ‘Language
Impairment in a Multilingual Society: Linguistics Patterns and the Road to Assessment’(www.bi-sli.org).
We would like to express our gratitude to all children who participated in the study as well as
their parents and teachers. Our appreciation for help in data collection goes to Rachel Haas (British
English), Eeva-Maria Kovalainen, Suvi Sirviö, Heta Toivola and Marika Pirnes (Finnish), and
Annegret Klassert, Vanessa Borchers, Sabrina Klostermeier and Henriette Stoll (German).
Declaration of interest
The authors report no conflict of interest.
Funding
The research presented here was partially supported by Berliner Senate and Bundesministerium für
Bildung und Forschung (BMBF), Germany [grant number 01UG1411]; the Research Council of
Norway through its Centres of Excellence funding scheme [grant number 223265]; the National
20 E. HAMAN ET AL.
Science Centre, Poland [grant number 809/N-COST/2010/0]; Polish Ministry of Science and Higher
Education [grant number 0046/DIA/2013/42]; Faculty of Psychology, University of Warsaw [grant
number BST2015-1744/4]; Ministry for Education, Science and Technological Development of
Republic of Serbia [grant number 175012]; the Slovak Research and Development Agency [grant
number APVV-0410-11]; Harry Crossley Foundation and National Research Foundation of South
Africa [grant number 88631]; Ministerio de Economía y Competitividad, Spain [grant number FFI2014-
56968-C4-1-P]; and Åke Wiberg Foundation [grant number H14-0104], Birgit and Gad Rausing
Foundation (Sweden) [grant number S14-14]. We also acknowledge support from International
Visegrad Fund partially enhancing collaboration reported in this article [grant number 21420015]. All
pictures used for CLTs are subject of copyright of University of Warsaw (Poland).
ORCID
Pernille Hansen http://orcid.org/0000-0003-3785-0132
References
Allman, B. (2005). Vocabulary size and accuracy of monolingual and bilingual preschool children.
In J. Cohen, K. T. McAlister, K. Rolstad, & J. MacSwan (Eds.), Proceedings of the 4th
International Symposium on Bilingualism (vol. 5, pp. 58–77). Somerville, MA: Cascadilla Press.
Altman, C., Goldstein, T. & Armon-Lotem, S. (this issue). Quantitative and qualitative differences in
the lexical knowledge of monolingual and bilingual children on the LITMUS-CLT task. Clinical
Linguistics and Phonetics.
Armon-Lotem, S., de Jong, J., & Meir, N. (Eds.). (2015). Assessing multilingual children.
Disentangling bilingualism from language impairment. Bristol: Multilingual Matters.
Armon-Lotem, S., & Ohana, O. (2017). A CDI study of bilingual english-hebrew children –
frequency of exposure as a major source of variation. International Journal of Bilingual
Education and Bilingualism,20 (2), 201–217.
Baal, B. A., & Bentzen, K. (2014, August 16–18). Adapting the MacArthur-Bates CDI to North Sámi
–minority language issues. Paper presented at NorPhlex final seminar, Tromsø, Norway.
Baayen, R. H., Feldman, L. B., & Schreuder, R. (2006). Morphological influences on the recognition
of monosyllabic monomorphemic words. Journal of Memory and Language,55 (2), 290–313.
Barnett, W. S., & Lamy, C. (2006). Estimated impacts of number of years of preschool attendance
on vocabulary, literacy and math skills at kindergarten entry. New Brunswick, NJ: National
Institute for Early Education Research.
Bates, E., Goodman, J. C. (1999). On the emergence of grammar from the lexicon. In B.
MacWhinney (Ed.). The emergence of language (pp. 29–79). Mahwah, NJ: Erlbaum.
Bedore, L., & Peña, E. D. (2008). Assessment of bilingual children for identification of language
impairment: Current findings and implications for practice. International Journal of Bilingual
Education and Bilingualism,11 (1), 1–29.
Bello, A., Giannantoni, P., Pettenati, P., Stefanini, S., & Caselli, M. C. (2012). Assessing lexicon:
Validation and developmental data of the Picture Naming Game (PiNG), a new picture naming
task for toddlers. International Journal of Language & Communication Disorders,47 (5), 589–602.
Benedict, H. (1979). Early lexical development: Comprehension and production. Journal of Child
Language,6(02), 183–200.
Bergelson, E., & Swingley, D. (2012). At 6–9 months, human infants know the meanings of many
common nouns. Proceedings of the National Academy of Sciences,109 (9), 3253–3258.
Bialystok, E., Luk, G., Peets, K. F., & Yang, S. (2010). Receptive vocabulary differences in mono-
lingual and bilingual children. Bilingualism: Language and Cognition,13 (04), 525–531.
Black, M., & Chiat, S. (2003). Noun-verb dissociations: a multi-faceted phenomenon. Journal of
Neurolinguistics,16 (2–3), 231–250.
CLINICAL LINGUISTICS & PHONETICS 21
Bleses, D., Vach, W., Slott, M., Wehberg, S., Thomsen, P., Madsen, T. O., & Basbøll, H. (2008). Early
vocabulary development in Danish and other languages: A CDI-based comparison. Journal of
Child Language,35 (03), 619–650.
Bloom, P. (2000). How children learn the meanings of words. Cambridge, MA: The MIT Press.
Bohman, T. M., Bedore, L. M., Pena, E. D., Mendez-Perez, A., & Gillam, R. B. (2010). What you
hear and what you say: Language performance in Spanish English bilinguals. International
Journal of Bilingual Education and Bilingualism,13 (3), 325–344.
Bornstein, M. H., & Hendricks, C. (2012). Basic language comprehension and production in >100,000
young children from sixteen developing nations. Journal of Child Language,39 (4), 899–918.
Bornstein,M.H.,Cote,L.R.,Maital,S.,Painter,K.,Park,S.Y.,Pascual,L.,Pêcheux,M.G.,Ruel,J.,Venuti,
P., & Vyt, A. (2004). Cross-linguistic analysis of vocabulary in young children: Spanish, Dutch, French,
Hebrew,Italian,Korean,andAmericanEnglish.Child Development,75 (4), 1115–1139.
Caselli, C., Bates, E., Casadio, P., Fenson, J., Fenson, L., Sanderl, L., & Weir, J. (1995). A cross-
linguistic study of early lexical development. Cognitive Development,10 (2), 159–200.
Chiang, P. Y., & Rvachew, S. (2007). English-French bilingual children’s phonological awareness
and vocabulary skills. Canadian Journal of Applied Linguistics (CJAL)/Revue canadienne de
linguistique appliquée (RCLA),10 (3), 293–308.
Clark, E. V. (1993). The lexicon in acquisition. Cambridge: Cambridge University Press.
Clark, E. V. (1995). Language acquisition: The lexicon and syntax. In J. L. Miller & P. D. Eimas
(Eds.), Speech, language and communication (vol. 11, pp. 303–337). San Diego: Academic Press.
Clark, E. V. (2001). Morphology in Language Acquisition. In A. Spencer & A. M. Zwicky (Eds.), The
Handbook of Morphology. Blackwell. Reference Online. 28 December 2007.
Clark, E. V. (2009). First language acquisition (2nd. ed.). Cambridge: Cambridge University Press.
Clark, E. V. (2012). First Language Vocabulary Acquisition. In C. A. Chapelle (Ed.), The
Encyclopaedia of Applied Linguistics. Oxford: Blackwell Publishers.
Conboy, B. T., & Thal, D. J. (2006). Ties Between the lexicon and grammar: Cross-sectional and
longitudinal studies of bilingual toddlers. Child Development,77 (3), 712–735.
Dale, P. S., & Penfold, M. (2011). Adaptations of the MacArthur-bates CDI into non-U.S. English languages.
Retrieved from http://www.sci.sdsu.edu/cdi/documents/AdaptationsSurvey7-5-11Web.pdf
D’Amico, S., Devescovi, A., & Bates, E. (2001). Picture naming and lexical access in Italian children
and adults. Journal of Cognition and Development,2(1), 71–105.
Dar, M., Anwaar, H., Vihman, M. & Keren-Portnoy, T. (2015). Developing an Urdu CDI for early
language acquisition in Pakistan. York Papers in Linguistics, Series 2(14), 1–14.
de Boysson-Bardies, B., & Vihman, M. M. (1991). Adaptation to language: Evidence from babbling
and first words in four languages. Language,67 (2), 297–319.
De Houwer, A., Bornstein, M. H., & Putnick, D. L. (2014). A bilingual–monolingual comparison of
young children’s vocabulary size: Evidence from comprehension and production. Applied
Psycholinguistics,35 (06), 1189–1211.
Dixon, L. Q. (2011). The role of home and school factors in predicting English vocabulary among
bilingual kindergarten children in Singapore. Applied Psycholinguistics,32 (01), 141–168.
Duursma, E., Romero-Contreras, S., Szuber, A., Proctor, P., Snow, C., August, D., & Calderon, M.
(2007). The role of home literacy and language environment on bilinguals’English and Spanish
vocabulary development. Applied Psycholinguistics,28 (01), 171–190.
Ellis, A. W., & Morrison, C. M. (1998). Real age-of-acquisition effects in lexical retrieval. Journal of
Experimental Psychology: Learning, Memory, and Cognition,24 (2), 515–523.
Engel de Abreu, P. M. J., Baldassi, M., Puglisi, M. L., & Befi-Lopes, D. M. (2013). Cross-linguistic and
cross-cultural effects on verbal working memory and vocabulary: Testing language-minority children
with an immigrant background. Journal of Speech, Language, and Hearing Research,56(2), 630–642.
Engel de Abreu, P. M. J., Cruz-Santos, A., & Puglisi, M. L. (2014). Specific language impairment in
language-minority children from low-income families. International Journal of Language &
Communication Disorders,49 (6), 736–747.
Engel de Abreu, P. M. J., & Gathercole, S. E. (2012). Executive and phonological processes in
second-language acquisition. Journal of Educational Psychology,104 (4), 974.
22 E. HAMAN ET AL.
Fenson, L., Dale, P. S., Reznick, J. S., & Thal, D. (1993). The MacArthur-Bates Communicative
Development Inventories (CDI I): Words and Gestures. Baltimore, MD: Paul Brookes Publishing.
Friedmann, N., & Novogrodsky, R. (2008). Subtypes of SLI: SySLI, PhoSLI, LeSLI and PraSLI. W A.
Gavarró & M. J. Freitas (Eds.), Language acquisition and development (pp. 205–217). Newcastle:
Cambridge Scholars Publishing.
Gagarina, N. V., Klassert, A., & Topaj, N. (2010). Sprachstandstest Russisch für mehrsprachige
Kinder [Russian language proficiency test for multilingual children]. ZAS Papers in Linguistics,
54, Berlin: ZAS.
Garmann, N. G., Hansen, P., Simonsen, H. G., & Kristoffersen, K. E. (in press). Phonological
characteristics of children’sfirst words. In F. Gayraud, S. Kern & F. Chenu (Eds.). Proceedings
from the ELA 2012 conference. Cambridge Scholar Publishing.
Gathercole, V. C. M., Thomas, E. M., & Hughes, E. (2008). Designing a normed receptive
vocabulary test for bilingual populations: A model from Welsh. International Journal of
Bilingual Education and Bilingualism,11 (6), 678–720.
Gatt, D. (2017). Bilingual vocabulary production in young children receiving Maltese-dominant
exposure: individual differences and the influence of demographic and language exposure factors.
International Journal of Bilingual Education and Bilingualism,20 (2), 163–182.
Gatt, D., Attard, D., Łuniewska, M., Haman, E. (this issue). The effects of bilingual status on lexical
comprehension and production in Maltese five-year-old children: a LITMUS-CLT study. Clinical
Linguistics and Phonetics
Gatt, D., O’Toole, C., & Haman, E. (2015). Using parental report to assess early lexical production
in children exposed to more than one language. In S. Armon-Lotem, J. de Jong, & N. Meir (Eds.),
Assessing multilingual children: Disentangling bilingualism from language impairment (pp. 151–
195). Bristol: Multilingual Matters.
Gentner, D. (1982). Why nouns are learned before verbs: Linguistic relativity versus natural parti-
tioning (Technical Report No. 257). Cambridge, MA: Bolt Beranek and Newman Inc. Retrieved
from http://files.eric.ed.gov/fulltext/ED219724.pdf
Gentner, D. (2006). Why verbs are hard to learn. In K. Hirsh-Pasek & R. M. Golinkoff(Eds.), Action
meets word: How children learn verbs (pp. 544–564). Oxford: Oxford University Press.
Gentner, D., & Boroditsky, L. (2001). Individuation, relativity, and early word learning. In M.
Bowerman & S. C. Levinson (Eds.), Language acquisition and conceptual development (pp. 215–
256). Cambridge: Cambridge University Press.
Goldfield, B. A. (2000). Nouns before verbs in comprehension vs. production: the view from
pragmatics. Journal of Child Language,27 (03), 501–520.
Goldin-Meadow, S., Seligman, M. E. P., & Gelman, R. (1976). Language in the 2-year-old.
Cognition,5,189–202.
Gorman, B. K. (2012). Relationships between vocabulary size, working memory, and phonological
awareness in Spanish-speaking English language learners. American Journal of Speech-Language
Pathology,21 (2), 109–123.
Haman, E., Łuniewska, M. & Pomiechowska, B. (2015). Designing cross-linguistic lexical tasks
(CLTs) for bilingual preschool children. In Armon-Lotem, S., Jong, J. d. & Meir, N. (Eds.),
Assessing multilingual children: Disentangling bilingualism from Language Impairment (pp. 196–
240). Bristol, UK: Multilingual Matters.
Hammer, C. S., Komaroff, E., Rodriguez, B. L., Lopez, L. M., Scarpino, S. E., & Goldstein, B. (2012).
Predicting Spanish-English bilingual children’s language abilities. Journal of Speech, Language
and Hearing Research,55 (5), 1251–1264.
Hansen, P., Simonsen, H. G., Łuniewska, M., Haman, E. (this issue). Validating the psycholinguistic
aspects of LITMUS-CLT: Evidence from Polish and Norwegian. Clinical Linguistics and
Phonetics.
Harris, M., Yeeles, C., Chasin, J., & Oakley, Y. (1995). Symmetries and asymmetries in early lexical
comprehension and production. Journal of Child Language,22 (01), 1–18.
Hart, B., & Risley, T. R. (1995). Meaningful differences in the everyday experience of young American
children. Chicago: Paul H Brookes Publishing.
CLINICAL LINGUISTICS & PHONETICS 23
Hemsley, G., Holm, A., & Dodd, B. (2013). Conceptual distance and word learning: Patterns of
acquisition in Samoan–English bilingual children. Journal of Child Language,40 (04), 799–820.
Hoff, E. (2003). The specificity of environmental influence: Socioeconomic status affects early
vocabulary development via maternal speech. Child Development,74 (5), 1368–1378.
Holloway, D., Green, L., & Livingstone, S. (2013). Zero to eight: Young children and their internet
use. LSE, London: EU Kids Online.
Juhasz, B. J. (2005). Age-of-acquisition effects in word and picture identification. Psychological
Bulletin,131 (05), 684–712.
Kan, P. F., & Kohnert, K. (2005). Preschoolers learning Hmong and English lexical-semantic skills
in L1 and L2. Journal of Speech, Language, and Hearing Research,48 (02), 372–383.
Kapalková. S., and Slančová, D. (this issue). The vocabulary profile of Slovak children with primary
language impairment compared to typically developing Slovak children measured by LITMUS-
CLT. Clinical Linguistics and Phonetics.
Kauschke, C., Lee, H. W., & Pae, S. (2007). Similarities and variation in noun and verb acquisition:
A cross-linguistic study of children learning German, Korean, and Turkish. Language and
Cognitive Processes,22 (7), 1045–1072.
Khoury Aouad Saliby, C., dosSantos, C., Kouba-Hreich, E., Messarra, C. (this issue). Assessing
Lebanese bilingual children: the use of Cross-Linguistic Lexical Tasks in Lebanese Arabic
language. Clinical Linguistics and Phonetics.
Klassert, A., Gagarina, N., & Kauschke, C. (2014). Object and action naming in Russian- and
German-speaking monolingual and bilingual children. Bilingualism: Language and Cognition,17
(01), 73–88.
Kohnert, K. J., Bates, E., & Hernandez, A. E. (1999). Balancing bilinguals: Lexical-semantic
production and cognitive processing in children learning Spanish and English. Journal of
Speech, Language, and Hearing Research,42 (6), 1400–1412.
Kohnert, K., Kan, P. F., & Conboy, B. T. (2010). Lexical and grammatical associations in sequential
bilingual preschoolers. Journal of Speech, Language, and Hearing Research,53 (3), 684–698.
Lahey, M., & Edwards, J. (1996). Why do children with specific language impairment name pictures
more slowly than their peers? Journal of Speech, Language and Hearing Research,39 (5), 1081–
1098.
Lahey, M., Edwards, J., & Munson, B. (2001). Is processing speed related to severity of language
impairment? Journal of Speech, Language, and Hearing Research,44 (6), 1354–1361.
Law, J., & Roy, P. (2008). Parental report of infant language skills: A review of the development and
application of the Communicative Development Inventories. Child and Adolescent Mental
Health,13 (4), 198–206.
Lind, M., Simonsen, H. G., Hansen, P., Holm, E., & Mevik, B.-H. (2015). Norwegian Words: A
lexical database for clinicians and researchers. Clinical Linguistics & Phonetics,29 (4), 276–290.
Loizou, M., & Stuart, M. (2003). Phonological awareness in monolingual and bilingual English and
Greek five-year-olds. Journal of Research in Reading,26 (1), 3–18.
Łuniewska, M., Haman, E., Armon-Lotem, S., Etenkowski, B., Southwood, F., Anđelković, D., . . . &
Ünal-Logacev, Ö. (2016). Ratings of age of acquisition of 299 words across 25 languages: Is there
a cross-linguistic order of words? Behavior Research Methods,48(3), 1154–1177.
Mancilla-Martinez, J., & Lesaux, N. K. (2011). Early home language use and later vocabulary
development. Journal of educational psychology,103 (3), 535–546.
Markman, E. M. (1989). Categorization and naming in children: Problems of induction. Cambridge,
MA: The MIT Press.
Markman, E. M. (1991). The whole-object, taxonomic, and mutual exclusivity assumptions as
initial constraints on word meanings. In S. A. Gelman & J. P. Byrnes (Eds.), Perspectives on
language and thought: Interrelations in development (pp. 72–106). Cambridge: Cambridge
University Press.
Masterson, J., Druks, J., & Gallienne, D. (2008). Object and action picture naming in three- and
five-year-old children. Journal of Child Language,35 (02), 373–402.
Mätzig, S., Druks, J., Masterson, J., & Vigliocco, G. (2009). Noun and verb differences in picture
naming: Past studies and new evidence. Cortex,45 (6), 738–758.
24 E. HAMAN ET AL.
Mayor, J., & Plunkett, K. (2014). Shared understanding and idiosyncratic expression in early
vocabularies. Developmental Science,17 (3), 412–423.
Messer, M. H. (2010). Verbal short-term memory and vocabulary development in monolingual Dutch
and bilingual Turkish-Dutch preschoolers (Unpublished PhD dissertation). Utrecht University.
Miękisz, A., Haman, E., Łuniewska, M., Kuś,K.,O’Toole, C. & Katsos, N. (2017). Impact of first generation
immigrant environment on the heritage language: Productive vocabulary of polish toddlers living in the
UK and Ireland. International Journal of Bilingual Education and Bilingualism,20 (2), 183–200.
Morrison, C. M., Ellis, A. W., & Quinlan, P. T. (1992). Age of acquisition, not word frequency,
affects object naming, not object recognition. Memory & Cognition,20 (6), 705–714.
Muñoz-Sandoval, A. F., Cummins, J., Alvarado, C. G., & Ruef, M. L. (2005). Bilingual verbal ability
tests. Normative update. Boston, MA: Houghton Mifflin Harcourt.
O’Toole, C., & Fletcher, P. (2010). Validity of a parent report instrument for Irish-speaking
toddlers. First language,30 (2), 199–217.
O’Toole, C. & Hickey, T.M. (2017). Bilingual language acquisition in a minority context: Using the
Irish-English Communicative Development Inventory to track acquisition of an endangered
language. International Journal of Bilingual Education and Bilingualism,20 (2), 146–162.
O’Toole, C., Gatt, D., Hickey, T.M., Miękisz, A., Haman, E., Armon-Lotem, S., Rinker, T., Ohana,
O., dos Santos, C., & Kern, S. (2017). Parent report of early lexical production in bilingual
children across varied contexts: A CDI study. International Journal of Bilingual Education and
Bilingualism,20 (2), 124–145.
Pearson, B. Z. (2010). We can no longer afford a monolingual norm. Applied Psycholinguistics,31
(02), 339–343.
Peña, E. D., Bedore, L., & Kester, E. S. (2015). Discriminant accuracy of a semantics measure with
Latino English-speaking, Spanish-speaking, and English–Spanish bilingual children. Journal of
Communication Disorders,53,30–41.
Peña, E. D., Gutierrez-Clellen, V., Iglesias, A., Goldstein, B., & Bedore, L. (2014). Bilingual English-
Spanish assessment. San Rafael, CA: AR-Clinical Publications.
Pham, G., & Kohnert, K. J. (2014). A longitudinal study of lexical development in children learning
Vietnamese and English. Child Development,85 (2), 767–782.
Potgieter, A., and Southwood, F. (2016). A comparison of proficiency levels in four-year-old
monolingual and trilingual speakers of Afrikaans, isiXhosa and South African English across
SES boundaries, using LITMUS-CLTs. Clinical Linguistics & Phonetics,30 (2), 87–100.
Quine, W. V. O. (1960). Word and object. Cambridge, MA: The MIT Press.
Reznick, J. S., & Goldfield, B. A. (1992). Rapid change in lexical development in comprehension and
production. Developmental Psychology,28 (3), 406–413.
Rinker, T., Budde-Spengler, N., & Sachse, S. (2017). The relationship between L1 and L2 lexical
development in young Turkish-German children. International Journal of Bilingual Education
and Bilingualism,20 (2), 218–233.
Roy, P., & Chiat, S. (2012). Teasing apart disadvantage from disorder. In C. R. Marshall (Ed.),
Current issues in developmental disorders (pp. 125–150). New York: Psychology Press.
Scheele, A. (2010). Home language and mono- and bilingual children’s emergent academic language.
A longitudinal study of Dutch,Moroccan-Dutch, and Turkish-Dutch 3- to 6-olds (Unpublished
PhD dissertation). Utrecht University.
Thordardottir, E. (2011). The relationship between bilingual exposure and vocabulary development.
International Journal of Bilingualism,15 (4), 426–445.
Tomasello, M., Merriman, W. (1995). Beyond names for things: Young children’s acquisition of verbs.
Mahwah, NJ: Erlbaum.
Uchikoshi, Y. (2006). English vocabulary development in bilingual kindergarteners: What are the
best predictors? Bilingualism, Language and Cognition,9(1), 33–49.
Umbel, V. M., Pearson, B. Z., Fernández, M. C., & Oller, D. K. (1992). Measuring bilingual
children’s receptive vocabularies. Child Development,63 (4), 1012–1020.
Van Tuijl, C., Leseman, P. P. M., & Rispens, J. (2001). Efficacy of an intensive home-based
educational intervention programme for 4-to 6-year-old ethnic minority children in the
Netherlands. International Journal of Behavioral Development,25(2), 148–159.
CLINICAL LINGUISTICS & PHONETICS 25
Appendix 1. Studies analysing bilingual lexical development in various
language pairs
Language pairs Tasks used References
English–Spanish CDI Conboy and Thal (2006)
Comprehension (PPVT, TVIP), naming (Expressive One
Word Picture Vocabulary Test, EOWPVT –Spanish and
English)
Allman (2005)
Comprehension (PPVT + TVIP) Barnett and Lamy (2006)
BESOS Bohman, Bedore, Peña, Mendez-Perez and
Gillam (2010) and Peña, Bedore, and Kester
(2015)
Woodcock Language Proficiency Battery –Revised for
English and Spanish
Duursma et al. (2007) and Mancilla-
Martinez and Lesaux (2011)
Woodcock Language Proficiency Battery –Revised for
English and Spanish + PPVT+TVIP
Uchikoshi (2006)
Naming (modified Receptive One-Word Picture
Vocabulary Test)
Gorman (2012)
Comprehension (PPVT + TVIP), naming (TELD-3 + PLS-3) Hammer et al. (2012)
Naming task prepared for this study Kohnert, Bates, and Hernandez (1999)
English–French Comprehension (PPVT + EVIP), naming (EOWPVT +
French version of EOWPVT)
Chiang and Rvachew (2007)
Comprehension (PPVT + EVIP –Canadian French PPVT),
naming (Expressive Vocabulary subtest of CELF,
expression-vocabuilare subtest of N-EEL)
Thordardottir (2011)
English–Greek Comprehension & naming (Wechlser Preschool Primary
Scale of Intelligence - Revised)
Loizou and Stuart (2003)
English–Hebrew CDI Armon-Lotem and Ohana (2017)
English–Hmong Receptive + picture naming tasks developed for this
study
Kan and Kohnert (2005) and Kohnert, Kan
and Conboy (2010)
English–Irish CDI O’Toole and Fletcher (2010) and O’Toole
and Hickey (2017)
English–Maltese CDI Gatt (2017)
English–
Mandarin
PPVT translated from English Dixon (2011)
English–Polish CDI Miękisz et al. (2017)
English–
Vietnamese
ROWPVT + EOWPVT translated from English Pham and Kohnert (2014)
English–Samoan Receptive + picture naming tasks developed for this
study
Hemsley, Holm and Dodd (2013)
Dutch–Arabic
and Dutch–
Turkish
Part of the Test for Bilingualism (Toets Tweetaligheid)
(Verhoeven, Narain, Extra, Konak, & Zerrouk, 1995)
Messer (2010)
Comprehension (Diagnostic Test of Bilingualism) +
instrument specifically developed for research with
bilingual immigrant children
Scheele (2010)
Comprehension + naming (parts of the Diagnostic Test
of Bilingual Development)
Van Tuijl, Leseman, and Rispens (2001)
Dutch–French CDI De Houwer et al. (2014)
German–Turkish CDI Rinker, Budde-Spengler, and Sachse (2017)
Luxembourgish–
Portuguese
EOWPVT and BPVS translated from English Engel de Abreu, Baldassi, Puglisi and Befi-
Lopes (2013)
EOWPVT and PPVT translated from English Engel de Abreu, Cruz-Santos and Puglisi
(2014)
Luxembourgish–
German–
French
EOWPVT translated from English Engel de Abreu and Gathercole (2012)
Russian–German Picture-naming
task comprising pictures of objects and actions
Klassert, Gagarina, and Kauschke (2014)
26 E. HAMAN ET AL.
