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ARTICLE
Sensitivity to syntactic dependency formation in
child second language processing: a study of
numeral quantifiers in Korean
Hyunwoo Kim
1
, Kitaek Kim
2
, Kyuhee Jo
3
and Haerim Hwang
4
1
Department of English Language and Literature, Yonsei University, Seoul, South Korea;
2
Department of
English Language Education, Seoul National University, Seoul, South Korea;
3
Department of English
Language Education, Gyeongin National University of Education, Incheon, South Korea;
4
Department of
English, The Chinese University of Hong Kong, Hong Kong, China
Corresponding author: Haerim Hwang; Email: haerimhwang@cuhk.edu.hk
(Received 13 January 2023; Revised 17 March 2023; Accepted 25 April 2023)
Abstract
This study investigates whether child second language (L2) learners can use syntactic
information during the processing of sentences involving unbounded dependencies and
how their processing patterns compare to those of child monolinguals and adult L2 learners.
Through a self-paced reading experiment involving the numeral quantifier
(NQ) construction in Korean, we tested participants’sensitivity to agreement violations
between a noun phrase (NP) and an NQ in local and nonlocal conditions. The results showed
that a subset of child L2 learners who demonstrated target-like knowledge of NP-NQ
agreement in an offline task spent a longer processing time in the NP-NQ mismatch than
in the NP-NQ match condition, in both local and nonlocal contexts. These child L2 learners’
processing patterns were comparable to those observed in child monolinguals and adult L2
learners. These findings suggest that child and adult L2 learners rely on the same system of
syntactic representations and processing mechanisms that guide first language processing.
Keywords: Child L2 processing; numeral quantifier; syntactic dependency; self-paced reading
1. Introduction
One critical question raised in the field of second language (L2) research is to what
extent nonnative speakers can achieve native-like processing. Researchers have
provided different explanations as to how L2 processing compares to first language
(L1) processing, particularly in using (morpho)syntactic information (see Juffs &
Rodriguez, 2014, for a review). Regarding this issue, the role of maturational
constraints on L2 acquisition and processing has been a topic of considerable
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Language and Cognition (2023), 1–23
doi:10.1017/langcog.2023.16
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theoretical debate (Slabakova, 2016). One view keeps with the critical period hypoth-
esis for L2 acquisition (Birdsong, 2014a), which posits that there exists a qualitative
difference in linguistic competence between L1 speakers and adult L2 learners.
Conversely, other researchers contend that L1 and L2 competence and processing
mechanisms are not qualitatively distinct from each other. Processing models
that support this view include the Full Transfer/Full Access/Full Parse model
(Dekydtspotter et al., 2006) and Fundamental Similarity Hypothesis (e.g., Hopp,
2007). These models place greater emphasis on language use experience and memory
capacity, rather than on maturational constraints, in guiding L2 processing, predict-
ing that adult L2 learners can attain native-like processing with increased levels of
proficiency and/or language experience.
Although the issue of fundamental difference or similarity between L1 and L2
processing remains unresolved, Schwartz (2004, p. 64) proposed that the “L1 child–
L2 child–L2 adult comparison”helps identify the “age-dependent difference in L2
ultimate attainment,”by comparing proficiency-matched child and adult L2 learners
with the same L1. Following this idea, several studies have compared child L2 learners
with adult L2 learners and child L1 speakers, and yet they have primarily focused on
offline comprehension (Kim & Schwartz, 2022; Unsworth, 2005). Although some
studies have presented evidence of comparable processing capabilities between L1
and L2 children (e.g., Marinis, 2007; van Dijk et al., 2022), few studies have
specifically investigated whether child L2 learners are fundamentally different from
adult L2 learners and/or child L1 speakers in the domain of syntactic processing.
To address this gap, the current study investigates whether L2-Korean learners
aged 10–12, who acquired their L2 before puberty, can draw on structural cues to
compute local and nonlocal dependencies in Korean sentences. Specifically, the study
compares processing behaviors between child L1 speakers and child L2 learners, as
well as between child L2 and adult L2 learners, in their computation of agreement in
Korean numeral quantifier (NQ) constructions. Given the inconclusive evidence
regarding the availability of grammatical information in child L2 processing, com-
paring child L2 learners with child L1 speakers and adult L2 learners in terms of their
processing of Korean NQs provides an interesting test case for the issue of whether
syntactic processing in L2 children is guided by the same systems operative in L1
and/or adult L2 processing.
2. Literature review
2.1. Models of L2 sentence processing
The literature has produced mixed findings regarding the ability of L2 learners to
utilize structural cues during online sentence comprehension in a manner compar-
able to native speakers. Previous research has diverged on whether L2 learners
can construct detailed syntactic structures as efficiently as native speakers during
processing.
Some researchers propose fundamental differences between L1 and L2 processing,
such as Clahsen and Felser’s(2006,2018) Shallow Structure Hypothesis (SSH).
According to the SSH, adult L2 learners are more limited than L1 speakers in their
ability to use fully specified structural information during online processing and tend
to rely more heavily on semantic and pragmatic cues (Clahsen & Felser, 2006; Marinis
et al., 2005). This hypothesis makes different predictions depending on the onset age
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of L2 acquisition, attributing adult L2 learners’shallow parsing to neurocognitive
factors, such as age of acquisition. However, the SSH also posits that structure-based,
native-like processing is possible if L2 acquisition takes place before substantial
maturational changes (Birdsong, 2014b; Birdsong & Vanhoeve, 2016).
Recent studies have explored the onset age effect exclusively in the domain of
morphological processing. For example, Bosch et al. (2019) found that L2 onset age
significantly affected the speed of L2 speakers’morphological processing in a target
language. In their study, adult Russian-German bilinguals were asked to make lexical
decisions on German target verbs that were visually represented on a computer
screen immediately after being exposed to German prime verbs. The primes and
targets formed morphologically related pairs, one with an unmarked stem (the
infinitive form, e.g., sterben ‘to die’) and the other with a marked stem (the third-
person singular present-tense form, e.g., stirbt). The results showed that the facilita-
tion of the priming effect gradually diminished as L2 onset age increased from 0 to
11, beyond which the effect remained stable. Similar findings have been reported by
other studies, which have proposed critical periods for acquiring L2 morphosyntactic
information (e.g., Hartshorne et al., 2018; but see Stepanov et al., 2020, which
indicated that child L2 learners only exhibit native-like processing for the target
construction that is similar to their L1 counterpart). It should be noted, however, that
these studies have mainly focused on morphological processing. As Clahsen and
Felser (2006) noted, the SSH has the potential to apply to various processing domains,
which highlights the need for systematic investigations of the onset age effect in areas
beyond morphological processing.
Some researchers propose that L2 learners can use structural cues as efficiently as L1
speakers in real-time processing, attributing L2 learners’processing difficulties to their
limited memory resources, rather than neurocognitive factors (e.g., Hopp, 2014,2017;
Omaki & Schulz, 2011; Witzel et al., 2012). Proponents of this “fundamental similarity”
position assume that L1 and L2 processing operate on the same structural architecture,
and divergent L2 processing stems from processing-related challenges. For example,
some studies indicate that L2 learners with high working-memory capacity are reported
to approximate native processing (e.g., Dussias & Piñar, 2009; Frenck-Mestre, 2002;
Hopp, 2014). Other research suggests that high proficiency in an L2 enables learners to
converge on native-like processing of various types of structural information (e.g.,
Fernandez et al., 2018; Frenck-Mestre, 2002;Witzeletal.,2012).
In summary, some approaches argue for fundamental differences between L1 and
L2 processing that arise from maturational factors, such as onset age for L2 acqui-
sition, whereas others adopt the fundamental identity position and maintain that
divergent L2 processing patterns can be attributed to processing-related variables,
such as working memory and proficiency. However, despite their potential to
account for both adult and child L2 processing, these theoretical positions have
not been extensively examined in the context of child L2 processing. To address this
problem, the current study investigates child L2 learners’use of structural cues during
online processing and compares their processing behavior with that of child L1
speakers and adult L2 learners.
2.2. Numeral quantifier constructions in Korean
In classifier languages like Korean and Japanese, numeral information in a noun
phrase (NP) is signaled via a combination of a number and a quantifier (or classifier),
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for example, haksayng sey-myeng (student three-NQ, ‘three students’). One crucial
grammatical condition for the formulation of the NQ construction is agreement
between an NQ and its host NP: The NQ must be matched with the associated NP in
terms of inherent semantic properties of the NP (e.g., shape, function, animacy; Lee,
2000). Similar to lexical gender assignment in Spanish and Italian, the type of NQ is
determined by the NP’s lexical properties. In the Korean sentence (1a), for example,
the human NP haksayng ‘student’is modified by the quantifier myeng, which denotes
a human entity; the co-occurrence of haksayng ‘student’with kay, a quantifier
denoting a non-human, non-animate entity, would yield an agreement violation.
In contrast, the non-human entity sakwa ‘apple’in (1b) can only be modified by kay;
it cannot co-occur with myeng.
(1) a. Na-nun haksayng-ul sey-myeng/*kay pwa-ss-ta.
1
I-TOP student-ACC three-NQ
human
/NQ
object
see-PST-DECL
‘I saw three students.’
b. Na-nun sakwa-lul sey-kay/*myeng sa-ss-ta.
I-TOP apple-ACC three-NQ
object
/NQ
human
buy-PST-DECL
‘I bought three apples.’
While local NP-NQ agreement is determined by concordance between NQ types and
individual nouns’membership, the relationship is also captured by a syntactic
constraint; that is, the two elements must be sisters dominated by the same node
in the base-generated position (Miyagawa, 1989). One of the most compelling
testaments to the operation of this constraint is the floating NQ phenomenon,
whereby an NQ is stranded as a result of an NP undergoing syntactic movement,
for example via scrambling. The Korean sentences in (2) illustrate this point.
(2) a. Haksayng-i sicang-eyse [sakwa-lul sey-kay/*myeng]
student-NOM market-LOC apple-ACC three-NQ
object
/NQ
human
sa-ss-ta.
buy-PST-DECL
‘Students bought three apples at the market.’
b. Sakwa-lul
i
haksayng-i sicang-eyse [t
i
sey-kay/*myeng]
apple-ACC student-NOM market-LOC three-NQ
object
/NQ
human
sa-ss-ta.
buy-PST-DECL
‘Students bought three apples at the market.’
From a generative perspective, the relationship between a moved NP and its NQ is
explained as an unbounded syntactic dependency (Ko, 2007; Lee, 2000). In (2a), for
example, the NQ phrase sey-kay ‘three-NQ
object
’modifies the object NP sakwa ‘apple’
in the post-nominal position, forming a local syntactic constituent. In (2b), however,
the NQ is stranded in the base-generated position while the object NP undergoes
movement to the sentence-initial position. In this case, the fronted NP must fulfill the
1
Abbreviations: ACC = accusative marker; DECL = declarative marker; NQ = numeral quantifier;
LOC = locative marker; NOM = nominative marker; PST = past tense marker; Q = question marker;
TOP = topic marker
4 Kim et al.
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locality requirement by leaving a trace within the NQ phrase so as to create a long-
distance dependency (Miyagawa, 1989; Sportiche, 1988). Consequently, the NQ is
associated exclusively with the fronted object NP sakwa ‘apple’although it is linearly
closer to the subject NP haksayng ‘student’. This floating NQ phenomenon is well-
attested in several languages with a rich case-marking system, such as Korean and
Japanese (Miyagawa, 1989; Park & Sohn, 1993; Sohn, 2001), but is precluded in
languages without case-marking, such as Chinese, and does not occur in some
languages that do have case-marking, such as Russian (Bondarenko & Davis, 2021;
Fitzpatrick, 2006; Madariaga, 2005; Pesetsky, 1982; Stepanov & Stateva, 2018).
2.3. Previous studies on L2 acquisition and processing of numeral quantifier
constructions
The floating NQ phenomenon in Korean and Japanese has attracted considerable
attention in L1 and L2 acquisition research, with a particular focus on testing adult
speakers’knowledge of semantic and structural constraints imposed on floating NQs.
Because the literature on native speakers’acquisition and use of the NQ construction
is extensive and beyond the scope of this paper, we focus on studies that have
investigated nonnative speakers’acquisition of floating NQs (see Fukuda, 2017, for
an overview of L1 acquisition studies). Relevant to the present study’s focus, we
mention one L1 study that examined early acquisition of NQ floating in Japanese.
Using a picture-selection task, Suzuki and Yoshinaga (2013) found that five-year-old
children successfully interpreted floating NQs in both SOV and OSV structures,
whereas four-year-old children showed some variation in their interpretations. Based
on this finding, we expect Korean L1 children in our study, aged between 10 and
12 years, to have little difficulty understanding NQ floating in SOV and OSV
sentences.
In the L2 literature, only a few studies have investigated the nonnative acquisition
of floating NQs, with most focusing on adult learner performance in judgment tasks.
One of the early studies was conducted by Sorace and Shomura (2001), who tested the
knowledge of the structural constraint underlying Japanese floating NQs among
adult English speakers. The study employed two types of intransitive sentences,
unergatives and unaccusatives, as illustrated in (3) and (4). The distinct structural
properties of the two constructions, namely that the subject of unergatives is base-
generated in the external argument position while the subject of unaccusatives is
initially projected in the internal argument position (Burzio, 1986), allowed the
researchers to test whether L2 learners would show sensitivity to floating NQ
violations in these sentences. Because the Japanese unergative verb (e.g., oyoi-da
‘swam’) selects a subject NP (e.g., shoonen ‘boy’) as an external argument, the NQ can
only license the subject NP in the adjacent position (3a), while the displacement of the
two elements gives rise to a locality violation (3b). In contrast, the subject NP of an
unaccusative verb (e.g., sat-ta ‘left’) is an internal argument, and the NQ can license
the subject NP in both the nonlocal (4b) and local (4a) domains.
(3) Unergative
a. Shoonen-ga san-nin umi-de oyoi-da.
boy-NOM 3-NQ sea-in swim-PST
‘Three boys swam in the sea.’
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b. *Shoonen-ga umi-de san-nin oyoi-da.
boy-NOM sea-in 3-NQ swim-PST
‘Three boys swam in the sea.’(Sorace & Shomura, 2001, p. 263 (20a–b))
(4) Unaccusative
a. Kyaku-ga futari kaijyou-kara sat-ta.
guest-NOM 2NQ event hall-from leave-PST
‘Two guests left the event hall.’
b. Kyaku-ga kaijyou-kara futari sat-ta.
guest-NOM event hall-from 2NQ leave-PST
‘Two guests left the event hall.’(Sorace & Shomura, 2001, p. 263 (21a–b))
In a timed acceptability judgment task, Sorace and Shomura (2001) found that
beginner-level learners with classroom instruction failed to show sensitivity to the
violation of NQ floating in unergatives (e.g., (3b)), whereas intermediate-level
learners who had resided in Japan for nine months showed judgment patterns similar
to, but not the same as, a native speaker control group. These results led the
researchers to the conclusion that the intermediate-level learners, but not the
beginner-level learners, had some knowledge of the interaction of verbs’lexical-
semantic features and the syntactic operations of Japanese NQs. Sorace and Shomura
pointed out that their findings alone could not show whether L2 learners can fully
acquire the necessary knowledge because the intermediate-level learners showed
weaker sensitivity with some verb types, and they suggested that future work should
involve advanced and near-native learners.
Part of this issue was addressed by Lee (2011), who investigated advanced heritage
Korean speakers’judgment of floating NQs in Korean. Using the unergative-
unaccusative contrast in Korean, which is similar to the Japanese counterpart, she
tested two groups of adult bilinguals: early bilinguals who were born and grew up in
the USA, and late bilinguals who arrived in the USA between the ages of 4 and 14. In a
written acceptability judgment task, the early bilinguals did not distinguish between
unergatives and unaccusatives in their judgments of floating NQs in Korean, unlike
the late bilinguals and a control group of Korean speakers. Furthermore, even the late
bilinguals were more reluctant than the native speakers to accept NQ floating in
unaccusatives. Lee concluded that even advanced heritage speakers can have incom-
plete representations of NQ floating in Korean.
Extending these earlier studies’findings, Fukuda (2017) tested knowledge of
Japanese NQ floating with L2 Japanese learners who had taken second- or third-
year Japanese classes in the USA, as well as heritage Japanese speakers who were born
in the USA or immigrated to the USA at an early age. When asked to rate the
acceptability of sentences involving floating and non-floating NQs in unergatives and
unaccusatives, the heritage speakers performed at the same level as Japanese native
speakers, indicating target-like knowledge of the structural constraint underlying NQ
floating. In contrast, the L2 classroom-learners did not show target-like judgment
patterns. Fukuda interpreted these results as showing evidence of native-like repre-
sentations in the heritage speakers but not in the L2 learners.
Fukuda’s(2017) findings for heritage speakers are at odds with Lee’s(2011)
findings for early bilinguals, who showed nontarget-like performance. However, as
both authors acknowledged, their samples (13 early and 14 late bilinguals in Lee’s
6 Kim et al.
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study; 6 heritage and 10 L2 learners in Fukuda’s) were too small to yield results that
could be easily generalized. Moreover, neither of the studies tested advanced (non-
heritage) L2 learners’knowledge of floating NQs, and they employed offline judg-
ments rather than investigating online processing. Another problem with these
studies is that information other than the unergative-unaccusative contrast may also
affect participants’judgment patterns. For example, Fukuda found that the partici-
pants’acceptability judgments of NP-NQ agreement varied depending on the
animacy status of subjects in the unaccusative sentences and the telicity of events
in the unergative sentences. Such confounding factors render it difficult to draw a
firm conclusion regarding L2 learners’use of structural information in their pro-
cessing of NP-NQ agreement.
Kim (2018) addressed these issues by examining both the knowledge and
processing of floating NQs in Korean with a larger sample of advanced late learners
of Korean (L1-Mandarin Chinese, n=32)andbyemployingSOVandOSV
sentences instead of unergative and unaccusative structures. In an acceptability
judgment task where NP-NQ agreement was presented in local and nonlocal
domains, as in (2), the L2 learners displayed native-like judgment patterns, reject-
ing infelicitous sentences where an object NP (e.g., apples) was incorrectly paired
with an NQ in terms of an animacy feature (e.g., apples-ACC students-NOM
market-LOC three-kay/*myeng bought ‘Students bought three apples at the mar-
ket’). The learners also exhibited sensitivity, albeit delayed compared to native
speakers, to the NP-NQ mismatch during real-time self-paced reading, spending
longer times on sentences with an NP-NQ agreement violation than on the
grammatical counterparts in both local and nonlocal domains. Based on these
findings, Kim (2018) concluded that these advanced learners not only possessed
native-like knowledge of the floating NQ construction but were able to apply that
knowledgeduringonlineprocessing.
Collectively, these previous L2 studies suggest that while the structural constraint
underlying floating NQs presents difficulty for some heritage speakers with early
exposure to the majority language and L2 learners with intermediate proficiency, it is
still acquirable and can even be processed in a native-like way by highly advanced
learners. However, given that all of these studies targeted adult learners, a question
arises as to whether such native-like attainment and processing can be achieved by
child L2 learners. It is conceivable that child L2 learners would fail to converge on
native-like processing of floating NQs because agreement computations between
non-adjacent items require considerable processing resources (Cunnings, 2017), of
which children have less than adults. Alternatively, it is possible that child learners
would have little difficulty with the floating NQ construction if they had sufficient L2
proficiency and had acquired the L2 before puberty.
3. The present study
This study examines whether child L2 learners can exploit structural cues to detect
NP-NQ agreement violations during the online processing of the Korean NQ
construction. Two specific research questions (RQs) are posed, as follows:
RQ1. Do child L2 learners show structural sensitivity to Korean NQ and NP
agreement to the same extent as child L1 speakers?
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RQ2. How do child L2 learners’processing patterns compare to those of adult
L2 learners?
To address these questions, we conducted a self-paced reading experiment that
involved Korean sentences in canonical and scrambled word orders in which an
NQ modifies its associated NP in a local or nonlocal domain. We also administered a
picture-based interpretation task to screen L2 children for adequate levels of target
knowledge. Only those learners who achieved an accuracy level above the threshold
(50% for both local and nonlocal agreement conditions) were included in the self-
paced reading task.
4. Methods
4.1. Participants
The study involved 78 children (47 girls and 31 boys) aged 10–12 (M= 10.7, SD = 0.7),
including 52 L2 learners as an experimental group (cL2 group) and 26 native speakers
of Korean as a control group (cL1 group). The cL2 group consisted of participants
from immigrant families in South Korea, who had various L1 backgrounds, mostly
Mandarin Chinese (n= 30) or Russian (n= 19), with one L1-speaker each of
Mongolian, Thai, and Vietnamese. We later excluded the Thai-speaking child’s data
because Thai allows floating numeral quantifiers (Jenks, 2013), in order to avoid a
potentially confounding factor from L1 influence. Although the other languages have
NP-NQ structures, none of them allows nonlocal agreement, and so we included
speakers of these languages. As a result, a total of 51 children contributed to the L2
data. According to their school records and responses to a language background
survey, the L2 children were born and raised in their home country and exclusively
spoke their native language during at least the first four to five years of their life. None
had prior exposure to Korean before they came to Korea with their parents at the
mean age of 7 (Range: 4–9.7, SD = 1.5). We therefore regard them as early L2 learners
of Korean.
The children in the cL2 group had resided in Korea for an average of 3.4 years
(Range: 1.5–8, SD = 1.3). They were fifth-grade students at a public primary school in
Korea at the time of data collection. Following the school’s system, they took a two-
year-long intensive Korean language class upon entering the school, where they
studied general courses in Korean two hours a day. After the program, they were
assigned to regular classes along with other Korean-speaking peers. The students’
teacher indicated that they were fluent in Korean and had little difficulty with
listening, speaking, reading, and writing in the language at the time of testing.
We assessed the L2 participants’Korean proficiency using two measures: (a) the
Diagnostic Assessment of Korean Language Proficiency (DAKLP, Noh et al., 2020)
and (b) self-reports. The DAKLP comprised 25 multiple-choice questions that
assessed participants’reading, vocabulary, and grammar skills in Korean. We opted
for this task because it was designed for testing children learning Korean as a second
language, and it only required receptive skills. Participants’accuracy scores on the
DAKLP ranged from 52 to 100%, indicating variability in their proficiency levels. For
self-reports, each participant rated their proficiency in four domains (reading,
writing, speaking, and listening) using a 10-point scale. The mean rating across the
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four domains was 7.3 (SD = 1.6). Each rating was significantly correlated with the
others (all rs > .7), and with the DAKLP scores (all rs > .5).
To compare the results from the cL2 group with those from adult L2 learners, we
retrieved data from Kim’s(2018) adult L2 group (aL2 group, n=32,meanage=25).
Because the current study adopted the same linguistic stimuli and experimental set-
up used in Kim’s study, it was deemed appropriate to make direct comparisons
between the child and adult learners from each study. Due to the different profi-
ciency tests administered to each group (the DAKLP to the cL2 group and a C-test
to the aL2 group), we compared the two groups’proficiency in terms of their
Korean learning experience and self-ratings. The aL2 group had spent a longer
time studying Korean than the cL2 group (t(82) = 4.338, p< 0.001, Cohen’s
d=0.975), while the cL2 group had spent a longer time residing in Korea
(t(82) = 2.981, 0.004, Cohen’sd= 0.670) and had an earlier onset age of Korean
acquisition than the aL2 group (t(82) = 40.455, p< 0.001, Cohen’sd=9.089).
The two groups’self-ratings were not significantly different (t(82) = 0.064, p=0.949,
Cohen’sd= 0.014).
Participant information is presented in Table 1.
4.2. Materials
4.2.1. Picture-based interpretation task
This task was conducted as a preliminary step for selecting participants who had
sufficient understanding of NP-NQ agreement in local and nonlocal domains.
The experimental items consisted of 16 Korean wh-questions in canonical SOV
and scrambled OSV word order, as in (5). Each sentence included the wh-phrase
myech ‘how many’followed by an NQ, asking participants to identify the number
of group members in question. The goal was to test whether the participants could
successfully choose the NP associated with the NQ in the wh-phrase in the
canonical and scrambled word-order conditions. The target NP in the canonical
SOV condition is adjacent to the NQ, while the target NP in the scrambled OSV
condition is in the sentence-initial position, constituting a long-distance depend-
ency with the NQ. Other words within the sentence were held constant across the
conditions. Two types of NQ were used: the animal-noun quantifier mali and the
human-noun quantifier myeng, both associated with animate nouns and the most
frequent classifiers in Korean (Kim & Yang, 2006). All words in the sentences,
including the NQs, appeared in Korean textbooks used at the participants’school.
Table 1. Participant information
Group Age
Years of
studying
Korean
Years in
Korea
Onset age of
Korean acquisition
Self-reported
proficiency (1–10)
cL1 (n= 26) 10.0 (0.0) –– – –
cL2 (n= 51) 11.0 (0.6) 3.4 (1.2) 3.4 (1.3) 7.1 (1.5) 6.8 (1.6)
aL2 (n= 32) 25.5 (2.3) 4.5 (2.7) 1.8 (1.4) 21.3 (1.7) 6.9 (0.8)
Note: Values in parentheses indicate standard deviations.
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(5) a. Canonical SOV condition
Phaynte-ka tongmwulwen-eyse kolilla-lul myech-mali
panda-NOM zoo-LOC gorilla-ACC how many-NQ
kentuli-ess-nayo?
touch-PST-Q
‘How many gorillas do the pandas touch at the zoo?’
b. Scrambled OSV condition
Kolilla-lul phaynte-ka tongmwulwen-eyse myech-mali
Gorilla-ACC panda-NOM zoo-LOC how many-NQ
kentuli-ess-nayo?
touch-PST-Q
‘How many gorillas do the pandas touch at the zoo?’
Each sentence was paired with a picture showing two groups of characters in
different numbers, either animals or humans, as illustrated in Fig. 1. The names of the
characters were printed in Korean below each image. The position of the target image
was counterbalanced across items.
The experimental items were counterbalanced across two lists using a Latin-
square design (8 items per condition), and each participant encountered only one
condition of a given item. The experimental sentences were intermixed with 16 dis-
tractor items. Because the NQ was always associated with the object NP in the
experimental sentences, distractor items included sentences with an NQ modifying
the subject NP (e.g., rabbit-NOM wood-in deer-by how many-NQ be chased ‘How
many rabbits are chased by the deer in the wood?’). The experimental and distractor
items were pseudo-randomized such that items in the same condition or of the same
type never appeared in a row.
4.2.2. Self-paced reading task
The materials for the self-paced reading task were adopted from Kim’s(2018) study.
They consisted of 24 sets of Korean sentences with NP-NQ match and mismatch
Figure 1. Sample picture in the picture-based interpretation task.
10 Kim et al.
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conditions in canonical and scrambled word orders as in (6). All of the sentences
consisted of seven words in seven regions.
(6) a. match/mismatch conditions in the canonical word order
[Haksayng-i]
R1
[sicang-eyse]
R2
[sakwa-lul]
R3
[sey-kay/*sey-myeng]
R4
student-NOM market-LOC apple-ACC three-NQ
object
/NQ
human
[sa-se]
R5
[chinkwu-wa]
R6
[nanw-ess-ta.]
R7
buy-and friend-with share-PST-DECL
‘The students bought three apples at the market and shared them with their
friends.’
b. match/mismatch conditions in the scrambled word order
[Sakwa-lul
i
]
R1
[haksayng-i]
R2
[sicang-eyse]
R3
[sey-kay/*sey-myeng]
R4
apple-ACC student-NOM market-LOC three-NQ
object
/NQ
human
[sa-se]
R5
[chinkwu-wa]
R6
[nanw-ess-ta.]
R7
buy-and friend-with share-PST-DECL
‘The students bought three apples at the market and shared them with their
friends.’
Question
Haksayng-i sakwa-lul sa-ss-nayo?
student-NOM apple-ACC buy-PST-Q
‘Did the students buy apples?’
Two types of NQs were consistently used in the experimental sentences: the non-
animate NQ kay in the match conditions, and the human NQ myeng in the mismatch
conditions. The experimental items were distributed in a 2 × 2 Latin-square design
(agreement × word order) across four lists, and each participant was randomly
assigned to one of the lists so that s/he saw only one of the four versions of an item.
The experimental items were interleaved with 30 fillers consisting of sentences with
NQ constructions in which the NQ modifies the subject NP and transitive/intransi-
tive sentences without NQs. The fillers with NQ constructions employed one of three
types of NQs: the object-denoting NQ kay, the human-denoting NQ myeng, and the
animal-denoting NQ mali. The lexical items used in the experimental and filler
sentences were selected from the vocabulary lists for beginner to intermediate
learners of Korean provided by the International Standard Curriculum of Korean
Language (Kim et al., 2011).
4.3. Procedure
Both cL1 and cL2 groups first completed a picture-based interpretation task. The cL2
group additionally completed the DAKLP as the measure of their Korean proficiency.
Based on their performance in the interpretation task, we only included a subset of
participants who met the inclusion threshold for the self-paced reading task (see the
results section below).
4.3.1. Picture-based interpretation task
The task was implemented in a pencil-and-paper format. Participants saw pictures on
a computer screen while reading questions on a sheet and writing answers. For
Language and Cognition 11
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example, given the images in Fig. 1 and one of the questions in (5), participants were
expected to write “2”because the corresponding picture shows two gorillas. Partici-
pants were also given an additional choice of “Idon’tknow”in case they were unsure of
the answer. Prior to the task, participants received written and verbal instructions on
the task, followed by two practice items. In pre- and post-test interviews, all participants
responded that they had little difficulty understanding the task instructions. The task
took approximately 15 minutes for the cL1 group and 25 minutes for the cL2 group.
4.3.2. Self-paced reading task
The self-paced reading task was conducted about two months after the interpretation
task. The task was implemented using a noncumulative moving window display (Just
et al., 1982) via a web-based platform using the Ibex Farm 0.3.9 software
(Drummond, 2013) under the supervision of the third author. During the experi-
ment, participants read a target sentence word by word with each word comprising a
region. A series of dashes indicated the positions of the words, and participants
pressed the spacebar to reveal each word. After each sentence, a verification question
appeared, as in (6), and participants clicked on a “yes”or “no”response. The position
of the correct answer was counterbalanced across items. Before the task, participants
received oral and written instructions and worked through five practice items. All the
participants confirmed that they understood the task procedure. The task took
approximately 15 minutes for the cL1 group and 25 minutes for the cL2 group.
5. Results
5.1. Picture-based interpretation task
We first checked for the selection of the “I don’t know”option, which was chosen by
no participant. Fig. 2 presents the mean accuracy scores for the experimental
sentences in each group. As the graph indicates, the cL1 group was generally more
accurate than the cL2 group in both the canonical SOV and the scrambled OSV
conditions. Within each group, participants showed lower accuracy in the OSV than
the SOV condition, indicating the greater difficulty of resolving the nonlocal NP-NQ
dependency compared to the local NP-NQ dependency.
Given that the primary purpose of the interpretation task was to identify parti-
cipants who demonstrated a sufficient understanding of NP-NQ agreement, we
focused on individuals, rather than groups, who exhibited above-chance perform-
ance. Among the 51 participants in the cL2 group, 19 (10 L1-Chinese and
9 L1-Russian speakers) scored more than 4 in both SOV and OSV conditions. This
subset group’s mean accuracy scores were 7.1 (SD = 0.9) for the SOV condition and
5.9 (SD = 1.0) for the OSV condition. In the cL1 group, a majority of participants
(23 of 26) scored above 4 in both conditions, with average scores of 7.3 (SD = 0.9) for
the SOV condition and 6.4 (SD = 0.9) for the OSV condition.
As exploratory analyses, we investigated whether the L1 and L2 participants who
were retained after the screening task exhibited a comparable level of understanding
of the target structure. We thus compared the accuracy of the subset of native
speakers (cL1
sub
) and the subset of nonnative speakers (cL2
sub
), using mixed-effects
logistic regression (Baayen, 2008). The likelihood of a correct response was modeled
as a function of two fixed effects, group (cL1
sub
, cL2
sub
) and condition (SOV, OSV),
all coded using deviation coding (.5 assigned to cL1
sub
and OSV, and .5 assigned to
12 Kim et al.
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cL2
sub
and SOV) centered around the mean. We had initially included by-participant
and by-item random slopes for all the fixed effects (Barr et al., 2013). However, the
model with the maximal random-effects structure failed to converge, and we ended
up omitting the by-participant random slope for group and the by-item random slope
for condition (e.g., Barr et al., 2013); and the resulting model formula was Accuracy
Group * Condition + (1 + Condition | Participant) + (1 + Group | Item). The
modeling was conducted using the glmer function in the lme4 package (Bates et al.,
2015) in R version 3.6.3 (R Core Team, 2019). All dataset and R codes that were used
in this study are available at the Open Science Framework: https://osf.io/38jm5/. The
model only showed a robust effect of condition (β=1.07, SE = 0.26, p< 0.001), with
higher scores for the SOV than the OSV condition, indicating that both groups
performed comparably on the task.
We also investigated how this subset group of L2 children, who showed target-like
performance in the interpretation task, differed from the remaining L2 participants in
terms of Korean learning experience and proficiency. Independent sample t-tests
revealed that the cL2
sub
group had spent a longer time in Korea (t(50) = 2.286,
p= 0.027, Cohen’sd= 0.666), had higher average self-ratings (t(50) = 2.164, p= 0.035,
Cohen’sd= 0.631), and had higher scores on the DAKLP (t(50) = 3.114, p= 0.003,
Cohen’sd= 0.908) than the remaining L2 participants. These results suggest that the
high performance of the cL2
sub
group comparable to the cL1 group can be attributed
to their increased experience with Korean and their higher proficiency in the target
language.
Based on the results of the interpretation task, we included these subsets of
participants (19 cL2, 23 cL1) in the following self-paced reading experiment. When
we compared the subset of child L2 participants with the adult L2 learners from Kim
(2018), the two groups did not differ in their years of studying Korean (t(49) = 0.313,
p= 0.756), but the cL2 group had spent a longer time in Korea (t(49) = 5.536, p< 0.001,
Cohen’sd= 1.603), had an earlier onset age of Korean acquisition (t(49) = 30.338,
p<0.001,Cohen’sd=8.786), and had higher self-ratings (t(49) = 4.042, p< 0.001,
Cohen’sd= 1.171) than the aL2 group. Information of the two groupsis summarized in
Table 2.
Figure 2. Mean accuracy of the picture-based interpretation task. Error bars indicate standard errors.
Language and Cognition 13
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5.2. Self-paced reading task
Three L1-Korean speakers were excluded from further analyses because they did not
complete the self-paced reading task, leaving 20 in the cL1 group. Also removed were
two participants in the aL2 group who scored less than 60% on accuracy on the
verification questions. The mean accuracy rates for the verification questions were
84.7% (SD = 8.2) in the cL1, 79.5% (SD = 13.1) in the cL2, and 91.1% in the aL2 group.
The aL2 group’s accuracy scores were significantly higher than those of the cL1 group
(p= 0.027) and the cL2 group (p< 0.001). There was no significant difference between
the cL1 and cL2 groups’scores (p= 0.142). Items for which participants provided
incorrect responses on the verification questions were removed, affecting 10.6% of
the data in the cL1 group, 12.1% in the cL2 group, and 6.1% in the aL2 group.
Following Kim (2018), the reading time (RT) data were trimmed by eliminating
outlying values exceeding 5,000 ms (2.6% in the cL1 group, 1.1% in the cL2 group,
and 0.5% in the aL2 group) and those beyond 2 standard deviations from each
participant’s mean RT (1.9% in the cL1 group, 2.4% in the cL2 group, and 6.4% in the
aL2 group). Figs. 3–5show RT profiles of the three groups (mean RTs and standard
deviations for each region are provided in the Supplementary Material). We focused
on the NQ phrase as the critical region (R4, e.g., sey-kay/*myeng ‘three-NQ
object
/
NQ
human
’in (6)) because it is the earliest point where agreement checking potentially
takes place. The subsequent two regions, R5 (e.g., sa-se ‘buy-and’in (6)) and R6 (e.g.,
chinkwu-wa ‘friend-with’in (6)), were also included in data analyses as spillover
regions.
To compare the three groups’RT patterns in detail, we ran linear mixed-effects
regression. For statistical analyses, the RTs were log-transformed for normal distri-
bution (Ratcliff, 1993). We then residualized them to adjust for variability in
individuals’reading speed and the length of words across items (Trueswell et al.,
1994). The residual RTs were derived by subtracting the estimated RTs, obtained
from a linear model that included the number of characters as a fixed effect and
participant as a random effect (formula: log-transformed RT ~ number of characters
+ (1 | Participant)), from the actual log-transformed RTs. Three regression models
were fit to the residual RTs in the critical and spillover regions, each including fixed
effects of group (cL1, cL2, aL2), agreement (match, mismatch), and word order (SOV,
OSV), along with random effects of participant and item. The group factor was coded
using Helmert contrasts, with the first contrast being between L1 and L2 groups (cL1
versus cL2 and aL2) and the second contrast being between the two L2 groups (cL2
versus aL2). The agreement and word order factors were centered around the mean
and coded using deviation coding, with .5 assigned to match and OSV, and .5 to
mismatch and SOV conditions. We initially constructed the model with the maximal
random-effects structure, and then simplified the model by removing the
Table 2. Information of child and adult L2 learners
Group Age
Years of
studying
Korean
Years in
Korea
Onset age of
Korean acquisition
Self-reported
proficiency (1–10)
cL2 (n= 19) 11.9 (0.6) 4.2 (1.7) 4.2 (1.7) 7.5 (1.4) 8.1 (1.5)
aL2 (n= 32) 25.5 (2.3) 4.5 (2.7) 1.8 (1.4) 21.3 (1.7) 6.9 (0.8)
Note: Values in parentheses indicate standard deviations.
14 Kim et al.
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by-participant random slope for group and the by-item random slopes for agreement
and for word order (e.g., Barr et al., 2013). The model outputs are presented in
Table 3.
The only effects that reached significance in the model for the critical region
(R4) were the main effect of group between L1 and L2 groups and the main effect of
Figure 3. Child L1 speakers’reading time profile.Error bars indicate standard errors.
Figure 4. Child L2 speakers’reading time profile. Error bars indicate standard errors.
Language and Cognition 15
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group between cL2 and aL2 groups. There was no main effect associated with
agreement or word order, and no interaction between factors. These results indicate
that all three groups did not show sensitivity to the NP-NQ agreement violation at
this region.
In the model for the first spillover region (R5), there was a main effect of
agreement, with longer RTs in the mismatch than the match condition. We also
found a two-way interaction between group (cL2 versus aL2) and agreement and a
three-way interaction among group (cL2 versus aL2), agreement, and word order.
These interactions suggest that the cL2 and aL2 groups showed different processing
patterns depending on the agreement and word-order conditions. To inspect these
interactions in detail, we conducted by-group analyses using linear mixed-effects
regression, with agreement and word order as fixed effects (centered), and participant
and item as random effects. The fixed factors were coded using deviation coding
(match and OSV: .5, mismatch and SOV: .5). Although we initially generated the
maximal random-effects structure permitted by the design, we simplified the struc-
ture by only including the by-participant random slope for agreement when the
models failed to achieve convergence. Model outcomes for each group at R5 are
presented in Table 4.
The model for the cL1 group revealed a main effect of agreement, with longer
reading times for the mismatch than for the match condition. There was no main
effect of word order and no interaction between agreement and word order. Likewise,
the model for the cL2 group only showed a main effect of agreement, with no main
effect of word order and no interaction of word order and agreement. These findings
provide evidence that both cL1 and cL2 groups showed sensitivity to the agreement
violation in the first spillover region. For the aL2 group, we also found a main effect of
agreement, and yet this effect interacted with word order. To examine this interaction
in detail, we conducted post-hoc comparisons using the emmeans package with
Tukey’s HSD (Lenth, 2019) in R. Results showed that the effect of agreement was
Figure 5. Adult L2 speakers’reading time profile. Error bars indicate standard errors.
16 Kim et al.
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significant only in the SOV condition (p< 0.001), but not in the OSV condition
(p= 0.203). These results indicate that only the child L1 and L2 learners, but not the
adult L2 learners, showed sensitivity to agreement violations in both the local and the
nonlocal conditions in the first spillover region.
In the second spillover region (R6), we only found a main effect of agreement,
induced by longer RTs in the mismatch than in the match condition (see Table 3).
The single effect of agreement without an interaction with group indicates that all
three groups showed sensitivity to the agreement violation. This result was confirmed
by separate by-group analyses, which were conducted using mixed-effects regression
in the same manner as in the analysis of the first spillover region. Model outcomes for
each group at R6 are presented in Table 5.
Table 3. Model outcomes for the critical and spillover regions
βSE p
Region 4 (critical) Intercept 0.035 0.015 0.017*
Group (L1 vs. L2) 0.071 0.031 0.023*
Group (cL2 vs. aL2) 0.206 0.035 <0.001***
Agreement 0.013 0.018 0.465
Word order 0.015 0.019 0.429
Group (L1 vs. L2) × Agreement 0.020 0.040 0.622
Group (cL2 vs. aL2) × Agreement 0.021 0.043 0.631
Group (L1 vs. L2) × Word order 0.015 0.041 0.714
Group (cL2 vs. aL2) × Word order 0.005 0.043 0.909
Agreement × Word order 0.062 0.038 0.106
Group (L1 vs. L2) × Agreement × Word order 0.086 0.084 0.309
Group (cL2 vs. aL2) × Agreement × Word order 0.074 0.089 0.408
Region 5 (spillover) Intercept 0.036 0.016 0.030*
Group (L1 vs. L2) 0.010 0.030 0.747
Group (cL2 vs. aL2) 0.034 0.037 0.371
Agreement 0.102 0.020 <0.001***
Word order 0.018 0.019 0.356
Group (L1 vs. L2) × Agreement 0.040 0.043 0.358
Group (cL2 vs. aL2) × Agreement 0.118 0.046 0.012*
Group (L1 vs. L2) × Word order 0.063 0.043 0.141
Group (cL2 vs. aL2) × Word order 0.058 0.045 0.198
Agreement × Word order 0.058 0.038 0.127
Group (L1 vs. L2) × Agreement × Word order 0.014 0.084 0.869
Group (cL2 vs. aL2) × Agreement × Word order 0.191 0.089 0.033*
Region 6 (spillover) Intercept 0.096 0.017 <0.001***
Group (L1 vs. L2) 0.035 0.028 0.261
Group (cL2 vs. aL2) 0.006 0.039 0.875
Agreement 0.062 0.018 0.001**
Word order 0.001 0.016 0.955
Group (L1 vs. L2) × Agreement 0.022 0.041 0.588
Group (cL2 vs. aL2) × Agreement 0.014 0.043 0.750
Group (L1 vs. L2) × Word order 0.026 0.036 0.475
Group (cL2 vs. aL2) × Word order 0.028 0.039 0.475
Agreement × Word order 0.022 0.033 0.515
Group (L1 vs. L2) × Agreement × Word order 0.027 0.074 0.714
Group (cL2 vs. aL2) × Agreement × Word order 0.064 0.078 0.416
Note: Formula: Residual RT Group * Agreement * Word order + (1 + Agreement * Word order | Participant) + (1 + Group |
Item).
***p< .001;
**p< .01;
*p< .05
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The models showed a single effect of agreement, but no interaction of agreement
with word order, for the cL1 and for the aL2 groups, and the model for the cL2 group
showed a marginal effect of agreement. These results indicate that all three groups
spent longer times for the sentences in the mismatch condition than for those in the
match condition in the second spillover region.
In summary, the analyses of the three groups’processing patterns confirmed that
all groups showed online sensitivity to the NP-NQ agreement violations; yet in the
nonlocal condition, the effect emerged earlier for the cL1 and cL2 groups (at the first
spillover region) than for the aL2 group (at the second spillover region).
6. Discussion
The primary goal of this study was to test the extent to which young L2 learners use
syntactic information to detect agreement violations during the online processing of
Table 5. Outcomes of by-group analyses in the second spillover region
Group Factor βSE p
cL1 Intercept 0.105 0.017 <0.001***
Agreement 0.062 0.027 0.021*
Word order 0.024 0.027 0.373
Agreement × Word order 0.003 0.053 0.959
cL2 Intercept 0.073 0.023 0.005**
Agreement 0.048 0.027 0.070
Word order 0.017 0.039 0.662
Agreement × Word order 0.004 0.053 0.933
aL2 Intercept 0.111 0.038 0.007**
Agreement 0.077 0.027 0.005**
Word order 0.004 0.027 0.877
Agreement × Word order 0.063 0.054 0.245
Note: Formula: Residual RT Agreement * Word order + (1 + Agreement | Participant) + (1 | Item).
***p< .001;
**p< .01;
*p< .05
Table 4. Outcomes of by-group analyses in the first spillover region
Group Factor βSE p
cL1 Intercept 0.056 0.016 0.002**
Agreement 0.056 0.027 0.037*
Word order 0.010 0.027 0.715
Agreement × Word order 0.033 0.054 0.545
cL2 Intercept 0.029 0.018 0.131
Agreement 0.075 0.029 0.009**
Word order 0.025 0.032 0.444
Agreement × Word order 0.049 0.057 0.394
aL2 Intercept 0.022 0.036 0.538
Agreement 0.173 0.034 <0.001***
Word order 0.068 0.035 0.050
Agreement × Word order 0.158 0.067 0.019*
Note: Formula: Residual RT Agreement * Word order + (1 + Agreement | Participant) + (1 | Item).
***p< .001;
**p< .01;
*p< .05
18 Kim et al.
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the NQ construction in Korean. To this end, we conducted a picture-based inter-
pretation task and a self-paced reading task. In this section, we discuss how our
findings address the RQs of this study.
6.1. Processing patterns of child L1 and L2 speakers
Our first research question concerned whether child L2 learners exhibit similar
processing patterns as child L1 speakers. The age-matched L1 and L2 children in
this study, who possessed knowledge of NP-NQ agreement, patterned alike in their
detection of the agreement violations in both local and nonlocal conditions. This
finding is in line with previous studies demonstrating comparable processing abilities
between L1 and L2 children (e.g., Marinis, 2007). These results suggest qualitatively
identical structure-building routines in child L1 and L2 processing.
The target-like processing of the L2 children in this study may be attributed to at
least two factors: the children’s early onset of L2 acquisition and their extensive
experience with Korean. All the L2 children in this study acquired the L2 before 10, an
age range that lies within a period showing superior neural plasticity. However, it is
difficult to convincingly argue for the decisive role of the maturational effect
associated with the onset age of L2 acquisition to explain our L2 children’s processing
performance, because early L2 acquisition is often confounded with more L2 expos-
ure. Indeed, our L2 children had substantial experience with the L2 through the
intensive Korean program at their school as well as linguistic immersion in diverse
social contexts. Crucially, despite the early onset age of L2 acquisition in all of the
child participants, only the subset of children who had more extensive experience
with Korean displayed a sufficient understanding of NP-NQ agreement in the
picture-based interpretation task.
More compelling evidence for the stronger role of language experience would be
obtained by comparing the child L2 learners’processing patterns with those of the
adult learners. It is reasonable to assume that comparable processing patterns
between the child and adult L2 learners would counter the idea that the onset age
of L2 acquisition is determinant of native-like L2 attainment and processing. To
address this issue, we now turn to our second research question, discussing the
comparison of processing patterns between the child and adult L2 learners.
6.2. Processing patterns of child L2 and adult L2 learners
The comparison of the L2 children’s results with the adult learner data revealed the
two groups’largely comparable processing patterns. Although the NP-NQ agreement
effect emerged earlier for the child than the adult learners, delayed processing does
not necessarily indicate a reduced ability to use target information (Jackson &
Dussias, 2009). Rather, the group difference lies in the quantitative domain
(i.e., the timing of the computation of syntactic structures).
Note that the child L2 group had earlier exposure to Korean and had spent a longer
time in Korea than the adult group, while both groups had a similar amount of time
studying Korean and were currently immersed in a Korean-speaking environment.
Their quantitatively distinct processing behaviors are unlikely to be due to differences
in their cognitive abilities. We assume the adult, college-educated learners to be
cognitively more mature than the L2 children in the current study. Nevertheless, in
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the adult group, the expected agreement effect emerged only in the local condition in
the first spillover region, and the effect in the nonlocal condition was delayed to the
second spillover region. This delayed effect may be associated with the complexity of
the NQ construction, which may have placed considerable demands on the learners’
cognitive resources (for similar findings in the context of unbounded dependencies,
see Dekydtspotter et al., 2006). In contrast, the child L2 learners showed faster
detection of the agreement violations, despite their presumably limited working-
memory capacity and greater difficulty managing their processing resources com-
pared to adults (e.g., Kharitonova et al., 2015). It appears that the challenges of
maintaining and retrieving relevant information for the children were offset by their
early and extensive exposure to Korean, allowing them to employ the target syntactic
information in a rapid and efficient manner.
An alternative account for the differences between the child and adult L2 groups
may be related to different degrees of knowledge regarding the target structure.
Note that for the self-paced reading task in the current study, we selected the subset
of child L2 learners who showed sufficient knowledge in the picture-based inter-
pretation task, whereas no such screening had been implemented for the adult
comparison group, the participants in Kim’s(2018) study. Although the adult
learner group in the earlier study showed acceptability judgment patterns compar-
able to those from a native control group, this group performance does not reflect
individuals’knowledge of the target structure. As a reviewer pointed out, it is
therefore possible that some of the learners from the adult L2 group did not have
native-like knowledge of NP-NQ agreement, leading to their deferred integration of
the information. This possibility calls for a future study that administers the same
screening task to child and adult participants for a precise comparison of their
processing behaviors.
As noted earlier, however, the timing difference between the child and adult
learners is a characteristic of a quantitative difference, and we found little evidence of
qualitative differences between the two learner groups. Both groups showed a target-
like sensitivity to the NP-NQ violations, which indicates the same structure-building
routines underlying child L2 and adult L2 processing. Considering that both L2
groups had extensive L2 learning experience in an immersive environment, our
findings suggest that L2 experience is a crucial factor that leads to native-like
processing, consistent with previous studies highlighting naturalistic exposure as a
necessary condition for learners’ability to process syntactic dependencies (Pliatsikas
& Marinis, 2013).
7. Conclusions
The current study investigated the extent to which child L2 processing differs from
child L1 and adult L2 processing. As far as qualitative differences are concerned, the
child L2 and adult L2 groups showed fundamentally similar processing patterns.
These findings suggest that child and adult L2 learners employ the same system of
syntactic representations and processing mechanisms operative in L1 processing, at
least when the learners have achieved high levels of L2 proficiency through extensive
L2 experience. These results support the position that argues for fundamental
similarity between L1 processing and L2 processing (e.g., Cunnings, 2017; Fernandez
et al., 2018; Hopp, 2014,2017). Future research should investigate whether the effects
20 Kim et al.
https://doi.org/10.1017/langcog.2023.16 Published online by Cambridge University Press
found in this study can be generalized to other learner populations and linguistic
phenomena by testing learners with diverse L1 backgrounds and L2 learning experi-
ences on their processing of a broader set of syntactic dependencies.
Supplementary material. The supplementary material for this article can be found at http://doi.org/
10.1017/langcog.2023.16.
Data availability statement. All dataset and R codes that were used in this study are available at the Open
Science Framework: https://osf.io/38jm5/.
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Cite this article: Kim, H., Kim, K., Jo, K. & Hwang, H. (2023). Sensitivity to syntactic dependency formation
in child second language processing: a study of numeral quantifiers in Korean Language and Cognition,
1–23. https://doi.org/10.1017/langcog.2023.16
Language and Cognition 23
https://doi.org/10.1017/langcog.2023.16 Published online by Cambridge University Press
