Foreign language comprehension achievement: insights from the cognate facilitation effect

Abstract

Numerous studies have shown that the native language influences foreign word recognition and that this influence is modulated by the proficiency in the non-native language. Here we explored how the degree of reliance on cross-language similarity (as measured by the cognate facilitation effect) together with other domain-general cognitive factors contribute to reading comprehension achievement in a non-native language at different stages of the learning process. We tested two groups of native speakers of Spanish learning English at elementary and intermediate levels in an academic context. A regression model approach showed that domain-general cognitive skills are good predictors of second language reading achievement independently of the level of proficiency. Critically, we found that individual differences in the degree of reliance on the native language predicted foreign language reading achievement, showing a markedly different pattern between proficiency groups. At lower levels of proficiency the cognate facilitation effect was positively related with reading achievement, while this relation became negative at intermediate levels of foreign language learning. We conclude that the link between native- and foreign-language lexical representations helps participants at initial stages of the learning process, whereas it is no longer the case at intermediate levels of proficiency, when reliance on cross-language similarity is inversely related to successful non-native reading achievement. Thus, at intermediate levels of proficiency strong and direct mappings from the non-native lexical forms to semantic concepts are needed to achieve good non-native reading comprehension, in line with the premises of current models of bilingual lexico-semantic organization.

Full text

ORIGINAL RESEARCH
published: 06 May 2015
doi: 10.3389/fpsyg.2015.00588
Edited by:
Jonathan Grainger,
Laboratoire de Psychologie
Cognitive – Centre National de la
Recherche Scientifique, France
Reviewed by:
Judith F. Kroll,
Pennsylvania State University, USA
David Peeters,
Max Planck Institute
for Psycholinguistics, Netherlands
*Correspondence:
Aina Casaponsa,
Basque Center on Cognition, Brain
and Language, Paseo Mikeletegi 69,
20009 Donostia, Spain
a.casaponsa@bcbl.eu
Specialty section:
This article was submitted to
Language Sciences,
a section of the journal
Frontiers in Psychology
Received: 06 December 2014
Accepted: 21 April 2015
Published: 06 May 2015
Citation:
Casaponsa A, Antón E, Pérez A
and Duñabeitia JA (2015) Foreign
language comprehension
achievement: insights from
the cognate facilitation effect.
Front. Psychol. 6:588.
doi: 10.3389/fpsyg.2015.00588
Foreign language comprehension
achievement: insights from the
cognate facilitation effect
Aina Casaponsa*, Eneko Antón, Alejandro Pérez and Jon A. Duñabeitia
Basque Center on Cognition, Brain and Language, Donostia, Spain
Numerous studies have shown that the native language influences foreign word
recognition and that this influence is modulated by the proficiency in the non-native
language. Here we explored how the degree of reliance on cross-language similarity (as
measured by the cognate facilitation effect) together with other domain-general cognitive
factors contribute to reading comprehension achievement in a non-native language
at different stages of the learning process. We tested two groups of native speakers
of Spanish learning English at elementary and intermediate levels in an academic
context. A regression model approach showed that domain-general cognitive skills are
good predictors of second language reading achievement independently of the level of
proficiency. Critically, we found that individual differences in the degree of reliance on the
native language predicted foreign language reading achievement, showing a markedly
different pattern between proficiency groups. At lower levels of proficiency the cognate
facilitation effect was positively related with reading achievement, while this relation
became negative at intermediate levels of foreign language learning. We conclude that
the link between native- and foreign-language lexical representations helps participants
at initial stages of the learning process, whereas it is no longer the case at intermediate
levels of proficiency, when reliance on cross-language similarity is inversely related to
successful non-native reading achievement. Thus, at intermediate levels of proficiency
strong and direct mappings from the non-native lexical forms to semantic concepts are
needed to achieve good non-native reading comprehension, in line with the premises of
current models of bilingual lexico-semantic organization.
Keywords: cognate effect, reading comprehension achievement, second language learning, formal L2 lessons,
lexical decision, foreign language acquisition
Introduction
Nowadays, most countries include a second language in their educational curricula, and English
has been, so far, the most frequently taught non-native language in formal academic contexts. The
generalized increase in second language learning has stimulated a lot of research into the cogni-
tive mechanisms underlying non-native language learning and the way in which newly acquired
sounds, words, and grammatical structures from the non-native language interact with preexisting
representations from the native language. In the current study we explored how individual differ-
ences in the degree of implicit reliance on cross-language similarity (i.e., the spontaneous sensitivity
to orthographic, phonological and semantic similarities between words from different languages)
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Casaponsa et al. Cognate effect and language learning
observed at early stages of the learning process contribute to
reading comprehension achievement in a non-native language
together with other domain-general cognitive factors.
There is extensive empirical evidence showing that word
recognition in a foreign language is influenced by the native
language (van Heuven et al., 1998;Dijkstra and van Heuven,
2002;Kroll and Dijkstra, 2002;Kroll et al., 2002;Lemhöfer and
Dijkstra, 2004; among others) and that the degree of reliance on
the native language depends upon second language proficiency.
In line with this idea, the Revised Hierarchical Model (RHM) of
bilingual lexico-semantic organization (Kroll and Stewart, 1994;
Kroll et al., 2010) predicts that semantic access during reading
comprehension is mediated by inter-lingual links at lower levels
of proficiency in the non-native language (L2) and that medi-
ation through the native language (L1) is necessary to achieve
full access to conceptual representations while reading in the
L2. Critically, the same theoretical account also implies that
direct links between L2 lexical representations and language-
independent semantic representations are created at higher levels
of the L2 proficiency, such that reliance on the L1 during L2
reading diminishes as a function of increased L2 proficiency.
The RHM is a developmental model of L2 acquisition initially
proposed to account for performance in translation production.
However, its predictions also fit the changes observed in L2 word
recognition (see Kroll et al., 2010, for a summary; but see also
Brysbaert and Duyck, 2010). One of the main assumptions of the
RHM that it is still a matter of debate is the existence of sep-
arate lexicons, an assumption mostly incompatible with neural
and computational models of bilingualism. Other models have
been put forward to overcome this issue, and the Developmental
Bilingual Interactive-Activation model (BIA-d; Grainger et al.,
2010) appears to lead the way as an alternative theoretical frame-
work. The BIA-d is a dynamic model of L2 learning that combines
the main features of the developmental changes in L2 acquisition
proposed by the RHM and the interactive-activation principles
of the Bilingual Interactive Activation model that assumes a
unified mental lexicon (BIA-model; first described by Grainger
and Dijkstra, 1992, and implemented by van Heuven et al.,
1998).
According to the BIA-d, the acquisition of L2 words requires
direct mappings with their translation equivalents in the native
language, direct mappings with language-independent seman-
tic representations, and information regarding the correspond-
ing language tag, which, in turn, is connected to L1 word
forms. These connections follow interactive-activation principles
and their strength depends on the proficiency in the L2. The
BIA-d predicts that at higher levels of L2 proficiency, the weights
of excitatory connections between L2 lexical representations and
language-independent semantic representations increase, while
the strength of links between L2 and L1 word forms (i.e., L1
mediation) decreases. Another key aspect of this model is that
the decrease of reliance on the L1 is modulated by inhibitory
connections from the L2 language tag to the L1 word forms.
Thus, as reliance on L1 translation during L2 word compre-
hension decreases as a function of increased proficiency, the
inhibitory connections between L2 and L1 words increase. This
is a critical aspect of this model since it features L2 word forms
integrated into a common lexicon, thus allowing for inhibitory
effects to emerge for both L2 and L1 lexical representations.
According to this model, newly acquired L2 words are con-
nected to their translation equivalents and to their correspond-
ing semantic representations via excitatory connections. These
connections are then strengthened as a function of increased
exposure to these words. At higher levels of proficiency, and
with the integration of the L2 words into the L1 lexicon, the
strength of the connections between L2 words and their L1
translations is reduced due to the development of inhibitory
connections. At this stage, L1 and L2 lexical representations
would be automatically activated during reading (i.e., there would
be language-independent lexical access to a single multilingual
lexicon), and lexical competition would be modulated by the rel-
ative resting activation threshold of each word form as well as
formal overlap and lexical distance between L1 and L2 represen-
tations.
Both the RHM and BIA-d models predict similar effects dur-
ing L2 reading at early stages of L2 learning, since the acquisition
and processing of L2 words is supposedly mediated by L1 transla-
tions during these early stages. Both the models also suggest that
reliance on L1 translations decreases as a function of increased L2
proficiency, given the strengthening of the direct links between
L2 lexical forms and corresponding semantic representations.
However, at higher and native-like levels of proficiency the mod-
els differ in the way L2 and L1 lexical items are represented
(i.e., in two different lexicons in the RHM and in a single lexi-
con in the BIA-d). Thus, even though the two models account
for the development of L2 acquisition, they differ substantially
as regards predictions on the degree of cross-language inter-
actions (excitatory and inhibitory) at different levels of word
processing.
Reliance on cross-language similarity is a critical factor that
has been shown to modulate not only L2 lexical access, but also
L2 word learning. Research on non-native word learning has
shown that new foreign words that follow the phonotactic or
orthotactic rules of the native language elicit stronger and ear-
lier behavioral and neural changes than new words that are at
odds with the native language phonotactic or orthotactic rules
(e.g., Mestres-Missé et al., 2007;Borovsky et al., 2010, 2012).
In a nutshell, studies exploring native and non-native vocabu-
lary acquisition show that the lexico-semantic representations of
newly acquired vocabulary are better established when these rep-
resentations overlap with the native language at form-based lin-
guistic levels (orthography and phonology), thus suggesting that
non-native cognate words (i.e., translation equivalents with over-
lapping orthographic and/or phonological representations; e.g.,
guitar for a native Spanish speaker learning English, translated as
guitarra in Spanish) are easier to learn and integrate in the lexi-
con than non-cognate words (i.e., translation equivalents without
ortho-phonological overlap; e.g., the English word house,trans-
lated as casa in Spanish; see Ellis and Beaton, 1993;Kroll et al.,
1998;Lotto and De Groot, 1998;De Groot and Keijzer, 2000;
De Groot and van Hell, 2005).
In order to better characterize the impact of cross-language
similarity during L2 reading, Lemhöfer et al. (2008) investigated
how various non-native speakers of English responded to a large
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Casaponsa et al. Cognate effect and language learning
set of English words. They tested Dutch, French, and German
learners of English in a progressive demasking task in which
participants had to identify visually presented words in their L2
(English), and tested the modulation of word identification time
by several within and between-language factors. They found that
the cognate status of words was the best cross-language perfor-
mance predictor in all the groups tested. Indeed, cognate words
were easier to recognize than non-cognate words in all three
groups of bilinguals reading in English. The cognate effect is thus
pervasive across languages and probably generalizable.
The fact that non-native cognate words are recognized
and produced faster and more accurately than non-native
non-cognate words (e.g., guitarra-guitar vs. casa-house)isa
well-documented finding (see Caramazza and Brones, 1979;
Cristoffanini et al., 1986;De Groot and Nas, 1991;Sánchez-Casas
et al., 1992;Dijkstra et al., 1998, 1999;Font, 2001;Van Hell and
Dijkstra, 2002;Kroll et al., 2002;Lemhöfer and Dijkstra, 2004;
Lemhöfer et al., 2004;Voga and Grainger, 2007;Davis et al., 2010;
Duñabeitia et al., 2010;Midgley et al., 2011;Peeters et al., 2013,
among many others). Critically, the cognate facilitation effect
has also been shown to decrease as a function of proficiency in
the non-native language (e.g., Bultena et al., 2014). The mag-
nitude of the cognate effect is larger at lower levels of second
language proficiency, suggesting a greater reliance on preexisting
native-language representations (Potter, 1979;Kroll and Stewart,
1994;Kroll and De Groot, 1997;Dijkstra and van Heuven, 2002;
Kroll and Dijkstra, 2002;Kroll et al., 2002;Grainger et al., 2010).
In contrast, at higher levels of second language proficiency, the
facilitative effects of cognate words compared to non-cognate
words are reduced, possibly indicating lower reliance on native-
language representations (e.g., Potter et al., 1984;Kroll et al.,
2010), and the potential inclusion of L2 words in an integrated
lexicon in which excitatory and inhibitory connections between
L2 and L1 representations play a critical role (Grainger et al.,
2010).
In the current study we set out to explore whether the cognate
effect, a well-known psycholinguistic effect associated with cross-
language interactions, contributes to non-native reading compre-
hension achievement in a formal academic context. Specifically,
we tested whether the cognate effect measured during the learn-
ing process can predict non-native language achievement at the
end of the academic year. Furthermore, the current study tried to
better characterize how the degree of reliance on cross-language
similarity (as measured by the cognate effect) at different lev-
els of the learning process contributes to reading comprehension
achievement.
Considering that preceding studies have consistently shown
that the cognate effect is a highly reliable psycholinguistic mea-
sure, and considering the evidence suggesting that the magnitude
of the cognate effect decreases as a function of increased pro-
ficiency in the non-native language, in the current study we
explored whether the cognate effect is a reliable measure able
to explain individual differences in second language learning.
Consistent with the literature reviewed above, we expected to find
a substantial cognate facilitation effect at initial stages of formal
second language learning and a reduction of this effect at higher
proficiency levels. Moreover, given that at initial stages of second
language learning readers tend to rely on their L1 in order to con-
solidate and integrate newly acquired words (Kroll and Stewart,
1994;Dijkstra and van Heuven, 2002;Kroll et al., 2002, 2010;
Grainger et al., 2010) reliance on cross-language similarity was
expected to positively contribute to L2 reading comprehension in
novice readers. We thus predicted that the magnitude of the cog-
nate effects would relate positively to general non-native reading
comprehension achievement in novice readers of L2. Conversely,
we predicted that reliance on cross-language similarity (as mea-
sured by the cognate effect) would relate negatively to general
L2 reading comprehension achievement at higher levels of profi-
ciency. To the best of our knowledge, this is the first study aimed
at exploring how cross-language reliance modulates general read-
ing comprehension at different stages of the L2 academic learning
process.
We tested two groups of participants attending to two different
levels of English learning according to the Common European
Framework of Reference for Languages: Learning, Teaching,
Assessment (CEFR). The low proficiency group was enrolled at
the A2 level and the intermediate proficiency group was enrolled
at the B1 level of the CEFR. All participants were tested (inde-
pendently of their level) at the beginning of the second semester
with a battery including various psychological and psycholin-
guistic measures. We then explored the contribution of these
indices to the final scores in the official reading comprehension
assessment completed at the end of the academic year. The read-
ing comprehension tests followed the CEFR guidelines for each
level and were evaluated by qualified professors from the Public
Language School at the end of the scholar term following CEFR
standards.
Experiment 1: Low Proficient Learners
of English (Level A2)
Methods
Participants
Sixty two native Spanish speakers (45 Females) attending English
lessons (level A2 of the CEFR) at the Public Language School
in Donostia took part in the experiment. Their mean age was
43.16 years (range: 19–68; SD: 12.44). Participants’ self-ratings of
proficiency in English are listed in Table 1. None of them reported
history of neuropsychological disorder and all had normal or
corrected-to-normal vision. All participants gave their written
TABLE 1 | Means (and SD) of participants language report in Experiment 1.
Item Mean (SD)
Age of English acquisition 25.56 (18.37)
Self-ratings
English Spoken 3.11 (1.64)
English Written 3.53 (1.59)
English Understand 3.53 (2.04)
General level of English 3.52 (1.55)
General level of Spanish 8.81 (0.87)
Self-ratings were given on a scale from 1 (low) to 10 (high).
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Casaponsa et al. Cognate effect and language learning
informed consent in accordance with guidelines approved by
the Ethics and Research Committees of the Basque Center on
Cognition, Brain and Language. The study was also performed
in accordance with the ethical standards set in the Declaration of
Helsinki.
Materials and Procedure
The initial assessment of the participants was carried out at the
end of the first school term (February), 4 months before they were
tested in the official exams of the Public Language School (June).
Every participant completed a battery consisting of three tasks
during class time. They volunteered to leave their regular classes
in groups of 10 for a 30-min session held in the multimedia room
of the Public Language School. After receiving basic information
about the aims of the study and the tasks they had to complete,
participants completed a series of questionnaires on their lin-
guistic and socio-demographic background. The three main tasks
that participants completed were (1) an English lexical decision
task (used to estimate students’ cognate effect; see Table 2 and
below), (2) a working memory test using the forward number
retention task from the Wechsler Adult Intelligence Scale-Fourth
Edition (WAIS-IV; Wechsler, 2008), and (3) an abridged ver-
sion of the Kaufman Brief Intelligence Test (KBIT; Kaufman,
1990;Kaufman and Kaufman, 2004)tohaveanestimatemea-
sure of their non-verbal intelligence. The working memory test
(WAIS-IV) included eight sequences of numbers read aloud by
the experimenters at the pace of one digit per second. Participants
had to write the digits in the same order they heard them once
they received the command from the experimenters (right after
giving the last digit of each sequence). The number of consecu-
tive correct responses was used as a rating of working memory
(WM). The sequences followed a progressively increasing level
of difficulty, ranging from 2 to 9 digits per sequence. Non-verbal
IQ was assessed with an abridged version of the matrices subtest
from the KBIT test. Participants had to respond to as many matri-
ces as they could during a 6-min interval. The total amount of
correct answers during this period was used as a measure of fluid
intelligence. The results of all tasks included in the experimental
session are summarized in Table 3.
A set of 200 English nouns were selected from the N-Watch
database (Davis and Perea, 2005) for the lexical decision task.
Half of the words were Spanish-English cognates (e.g., MINUTE,
minuto in Spanish), and the other half were non-cognates
(e.g., SUMMER, verano in Spanish). Orthographic overlap was
assessed following the same methodology used in Duñabeitia
et al. (2013;seealso,Schepens et al., 2011). According to a 0-to-1
continuum of cognate status1(with higher values corresponding
to greater overlap across languages), cognate words ranged from
1Corrected Levensthein distance was used to calculate the cognate status of words
between English and Spanish, ranging from 0 (non-cognates) to 1 (fully cognates).
TABLE 2 | Mean values and SD for the stimuli used in the experiment.
Frequency Length Number of
neighbors
Imageability
Cognates 56.04 (63.08) 6.71 (1.67) 1.41 (2.87) 4.50 (1.1)
Non-cognates 54.06 (54.27) 6.66 (1.40) 1.69 (2.63) 4.63 (1.07)
TABLE 3 | Scores obtained for the tasks in Experiment 1 and scores
obtained at the end of the learning process for A2 group of English
learners.
Task Mean (SD)
Cognate effect (in ms) 60.94 (80.26)
Cognate effect (% of errors) 16.70 (10.76)
WM estimate 4.22 (0.88)
IQ estimate 18.99 (4.03)
Reading comprehension 16.19 (3.05)
Reading comprehension scores ranged from 0 to 20 assessed using the criteria
set on by the CEFR.
0.7 to 1 (mean =0.82, SD =0.09) and non-cognate words
ranged from 0 to 0.3 (mean =0.11, SD =0.10). Cognate and
non-cognate words were matched for frequency, length, num-
ber of orthographic neighbors and imageability (see Tab l e 2 ).
A set of 200 non-words following English orthotactic rules
(e.g., ENCHORY) was generated using Wuggy (Keuleers and
Brysbaert, 2010). Each trial consisted of the presentation of a
fixation cross (“+”) in the middle of the screenfor 500 ms, imme-
diately followed by the presentation of a letter string that could be
either a real English word or not. Participants were instructed to
press the “L” button of the keyboard for real words and the “S”
button for non-words. Letter strings remained on the screen for
2500 ms or until a response was given. Prior to the presentation
of the experimental trials in a random order generated for each
participant, six practice trials were presented in order to famil-
iarize participants with the task. The lexical decision experiment
lasted for ∼10 min and was created using Experiment Builder.
Results from questionnaires and from the three experimen-
tal tests were then used to predict participants’ outcome in
the official assessment for reading comprehension skills by the
Public Language School following the standard methods used
in Common European Framework of Reference for Languages
(20112) at the end of the academic year (4 months after comple-
tion of the experimental session). Grades in the official examina-
tion ranged from 0 to 20, 12 being the minimum score required
to obtain a pass for the A2 level. The criteria used to assess read-
ing comprehension included the understanding of short, simple
texts on familiar matters of a concrete type which consist of high
frequency everyday or job-related language. Furthermore, it also
included the understanding of basic types of standard routine let-
ters and faxes (enquiries, orders, letters of confirmation, etc.) on
familiar topics, the understanding of short simple personal letters,
and the understanding of everyday signs and notices.
Results and Discussion
First, trials from the lexical decision task associated with erro-
neous responses and responses latencies that were above or below
2 SD from the participant-based means in each condition were
excluded from the RT analysis (5.67% of the data). Second,
ANOVAs on the RTs and percentage of errors were conducted
in order to test for an overall cognate effect in the test group
(i.e., comparing latencies and accuracy data between cognate and
non-cognate words). Third, a regression analysis was carried out
2http://www.coe.int/t/dg4/linguistic/cadre1_en.asp
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Casaponsa et al. Cognate effect and language learning
using participants’ scores in reading comprehension at the end
of the academic year as the dependent variable, together with
the following list of predictor variables: the cognate effect (in ms;
obtained by subtracting RTs to cognate words from RTs to non-
cognate words), the general self-rating of English proficiency (on
a scale from 1 to 10), participants’ age of acquisition of English
and their chronological age (both in years), and the results from
the WM and IQ tests (raw scores).
ANOVAs aimed at confirming the existence of a cognate
effect in the lexical decision task showed a significant main
effect of Cognate status on RTs [F1(1,61) =35.74, p<0.001;
F2(1,99) =7671.90, p<0.001] and accuracy [F1(1,61) =40.83,
p<0.001; F2(1,99) =72.97, p<0.001], such that cognate words
were recognized faster and more accurately than non-cognate
words (see Figure 1A).
Next, the mean cognate effect was entered into a regression
model (backward multiple regression) together with the age of
the participants, their self-perceived English level, their age of
acquisition of English, and their scores in the WM and IQ tests in
order to investigate the relative contribution of each factor for the
final scores obtained in the official examinations from the Public
Language School. The simplest model accounting for most of the
variance included three out of the six initial predictors and was
reached in three steps. Age of acquisition (as measured by age
of first contact with English) was first dropped from the most
complex model without losing explanatory capacity [βs=0.11,
t(61) =0.68, p=0.49], then the chronological age of the partici-
pants was also dropped from the model in a later step [βs=0.15,
t(61) =1.11, p=0.27] and finally the WM was also dropped
from the final model [βs=0.15, t(61) =1.26, p=0.21; see
Tab l e 4 ].
The model was statistically significant [F(4,58) =7.46,
p<0.001] and accounted for approximately 25% of the vari-
ance of reading comprehension (R2=0.28, Adjusted R2=0.24).
The resulting regression weights, tvalues, significance levels,
structured coefficients, squared partial correlations and their
correlations with reading comprehension are summarized in
Tab l e 5 . Higher scores in reading comprehension as assessed
by official examinations were significantly predicted by higher
cognate effects, higher levels of self-rating perception of English
proficiency, and higher scores in IQ. β-weights revealed that all
predictors received similar credit in the regression equation (see
Tab l e 5 ), and a closer inspection of the structure coefficients
suggested that cognate effect contributed most to the variance
explained (R2) with the largest absolute value for both the β-value
and the structure coefficient (β=0.36, rs=0.74, r2
s=54%), fol-
lowed by IQ (β=0.25, rs=0.60, r2
s=36%) and self-rating of
perceived proficiency (β=.28, rs=0.18, r2
s=11%). Interestingly,
the cognate effect measuredat the end of the first termturned out
to be a good predictor of future reading comprehension level at
the end of the academic year. That is, non-native language read-
ing achievement is highly influenced by the magnitude of the
cognate effect at initial stages of the learning process.
Experiment 2: Intermediate proficient
learners of English (Level B1)
Methods
Participants
One hundred and five native Spanish speakers (65 Females) took
part in this study. All of them were attending English lessons
(level B1 of CEFR) at the Public Language School in Donostia,
Spain. Their mean age was 38.76 (range: 19–69; SD: 13.05).
Participants’ self-ratings of proficiency in English are listed in
Tab l e 6 . None of them reported a history of neuropsychological
disorder and all had normal or corrected-to-normal vision.
Materials and Procedure
These were the same as in Experiment 1. The criteria used
to assess reading comprehension for the B1 level included the
understanding of texts of high frequency everyday or job-related
language, and the understanding of events, feelings and whishes
FIGURE 1 | (A) Mean latencies and error rates for cognate and non-cognate words in Experiment 1. Error bars represent 95% confidence intervals. (B) Correlation
between individuals’ cognate effects and reading comprehension scores for A2 group of English learners.
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Casaponsa et al. Cognate effect and language learning
TABLE 4 | Model Summary for the backward multiple regression analysis
with reading comprehension as a dependent variable in Experiment 1.
Model RR
2Adjusted
R2
Change statistics
R2change Fchange pchange
10.57
a0.32 0.25 0.32 4.29 0.01
20.56
b0.31 0.25 −0.01 0.46 0.50
30.55
c0.30 0.25 −0.02 1.24 0.27
40.53
d0.28 0.24 −0.02 1.59 0.21
aPredictors: cognate effect, WM estimate, IQ estimate, level English, age, AoA
English.
bPredictors: cognate effect, WM estimate, IQ estimate, level English, age.
cPredictors: cognate effect, WM estimate, IQ estimate, level English.
dPredictors: cognate effect, IQ estimate, level English.
TABLE 5 | Results of the multiple regression model using the backward
method in Experiment 1.
Predictor βtp rsr2rsr2
s
Cognate
effect
0.36 3.30 0.002 0.39 0.14 0.74 0.54
Self-rating
of English
proficiency
0.28 2.45 0.02 0.18 0.07 0.34 0.11
IQ estimate 0.25 2.17 0.03 0.32 0.06 0.60 0.36
r, Pearson correlation; sr2, squared semi-partial correlation; rs, structure coeffi-
cient =r/R. r2
s, squared structure coefficient =r2\R2.
TABLE 6 | Mean (and SD) of participants language report.
Item Mean (SD)
Age of English acquisition 19.90 (16.30)
Self-ratings
English Spoken 4.15 (1.32)
English Written 4.93 (1.47)
English Understand 4.44 (1.62)
General level of English 4.67 (1.29)
General level of Spanish
Self-ratings were given on a scale from 1 (low) to 10 (high).
in personal letters. Furthermore, it also included the understand-
ing of longer texts requiring students to be able to locate and
gather desired information from different parts of a text, as well
as to recognize significant aspects in straightforward newspaper
articles on familiar subjects.
Results and Discussion
Data analyses were carried out following the same criteria as in
Experiment 1. Trials associated with erroneous responses and
responses latencies that were above or below 2 SD from the
participant-based means in each condition were excluded from
the RT analysis (2.99% of the data). The same factors used in
Experiment 1 were included in a backward multiple regression
model using the final scores of reading comprehension as a
dependent variable. Descriptive results can be found in Table 7.
Analyses of variance (ANOVAs) aimed at confirming the exis-
tence of a cognate effect in the lexical decision task showed
TABLE 7 | Scores obtained for the tasks in Experiment 2 and scores
obtained at the end of the learning process for B1 group of English
learners.
Task Mean (SD)
Cognate Effect (in ms) 47.45 (48.43)
Cognate Effect (% of errors) 10.12 (6.84)
WM Estimate 4.65 (1.03)
IQ Estimate 20.55 (3.76)
Reading Comprehension 15.32 (3.35)
Reading comprehension ranged from 0 to 20 assessed using the criteria set on by
the CEFR.
a significant main effect of Cognate status in the RT data
[F1(1,104) =100.78, p<0.001; F2(1,99) =4896.89, p<0.001]
and in the accuracy data [F1(1,104) =106.17, p<0.001;
F2(1,99) =99.35, p<0.001], demonstrating that cognate words
were recognized faster and more accurately than non-cognate
words (see Figure 2A).
The mean cognate effect along with the same predictors used
in Experiment 1 were entered into a backward multiple regression
model with the final scores obtained in the official examina-
tions from the Public Language School as a dependent variable
(see Table 8). The simplest model accounting for most of the
variance included four out of the six initial predictors and was
reached in three steps. Self-perceived English proficiency was first
dropped from the most complex model without losing explana-
tory capacity [βs<0.005, t(104) =−0.03, p>0.95], and the
chronological age of the participants was also dropped from the
model in a later step (βs<0.07, t(104) =0.45, p>0.65; see
Tab l e 9 ).
The model was statistically significant [F(4,104) =6.80,
p<0.001] and accounted for ∼20%ofthevarianceofreading
comprehension (R2=0.22, Adjusted R2=0.18). The result-
ing regression weights, tvalues, significance levels, structured
coefficients, squared partial correlations and their correlations
with reading comprehension are summarized in Table 5 .Higher
scores in reading comprehension as assessed by official exam-
inations were significantly predicted by lower cognate effects,
lower age of acquisition of English, and higher WM and IQ.
β-weights revealed that all predictors received similar credit in
the regression equation (see Table 5 ), and a closer inspection
of the structure coefficients suggested that IQ contributed most
to the variance explained (R2) with the largest absolute value
for both the β-value and the structure coefficient (β=0.22,
rs=0.73, r2
s=54%), followed by the cognate effect and age
of acquisition (β=0.20, rs=0.53, r2
s=28% and β=0.19,
rs=0.61, r2
s=37%) and WM (β=0.21, rs=0.36, r2
s=13%).
Interestingly for the purposes of the current study, the cognate
effect measured at the end of the first term turns out to be
a good predictor of future reading comprehension level at the
end of the academic year. That is, non-native language read-
ing achievement was highly influenced by the magnitude of the
cognate effect at earlier stages of the learning process. However,
the direction of this effect was the opposite of that found in
Experiment 1. In Experiment 1 larger cognate effects significantly
predicted better reading achievement, but in Experiment 2 the
Frontiers in Psychology | www.frontiersin.org 6May 2015 | Volume 6 | Article 588

Casaponsa et al. Cognate effect and language learning
FIGURE 2 | (A) Mean latencies and error rates for cognate and non-cognate words in Experiment 2. Error bars represent 95% confidence intervals. (B) Correlation
between individuals’ cognate effects and reading comprehension scores for B1 group of English learners.
TABLE 8 | Model summary for the backward multiple regression analysis
with written comprehension as a dependent variable.
Model RR
2Adjusted
R2
Change statistics
R2Change Fchange Pchange
10.47
a0.22 0.17 0.22 4.51 0.01
20.47
b0.22 0.18 0.01 0.01 0.98
30.47
c0.22 0.18 −0.01 0.20 0.67
aPredictors: cognate effect, WM estimate, IQ estimate, AoA English, age, level
English.
bPredictors: cognate effect, WM estimate, IQ estimate, AoA English, age.
cPredictors: cognate effect, WM estimate, IQ estimate, AoA English.
TABLE 9 | Results of the multiple regression model using backward
method.
Predictor βtprsr2rsr2
s
Cognate effect −0.20 −2.25 0.03 −0.25 0.04 0.53 0.28
Age of acquisition −0.19 −1.87 0.06 −0.28 0.04 0.61 0.36
IQ estimate 0.22 2.24 0.03 0.34 0.04 0.73 0.53
WM estimate 0.21 2.34 0.02 0.17 0.03 0.36 0.13
r, Pearson correlation; sr2, squared semi-partial correlation; rs=structure coefi-
cient =r/R. r2
s, squared structure coefficient =r2\R2.
magnitude of these effects were negatively related to reading com-
prehension achievement, so that learners with smaller cognate
effects scored better in official examinations (see Figure 2B).
Moreover, the cognate effect was not correlated with any other
general performance factor such as participants’ scores in the
WM and IQ tests (both rs<0.15; ps>0.05), suggesting a
neat link between cognate effect and reading comprehension
achievement.
General Discussion
The main goal of the present study was to investigate relations
between the cognate effect and non-native language acquisition
and to explore the extent to which reliance on cross-language
similarity contributes to further reading achievement in a formal
academic context at different levels of proficiency. We aimed at
characterizing how the degree of reliance on cross-language sim-
ilarity contributes to reading comprehension achievement at dif-
ferent levels of L2 proficiency. To do so, we first tested the cognate
effect in two groups of native Spanish speakers who were learning
English at a Public Language School, corresponding to the lev-
els A2 (low-proficiency level) and B1 (intermediate-proficiency
level) of CEFR. Participants were also assessed for WM and fluid
intelligence, as domain-general cognitive factors have already
been proven to have an effect on reading acquisition (Papagno
and Vallar, 1995;Kempe et al., 2010;Lopez-Barroso et al., 2011).
We then investigated the contribution of these factors (together
with other socio-demographic and linguistic factors) on the final
reading comprehension scores obtained 4 months afterward at
the end of the school year (assessed using the criteria set on by
the CEFR).
As expected, we found a significant cognate effect in a single-
word presentation lexical decision task in the non-native lan-
guage, showing that cognate words were processed faster and
more accurately than non-cognate words in both our participant
groups3, in line with previous literature (Dijkstra et al., 1998,
1999, 2010;Font, 2001;Van Hell and Dijkstra, 2002;Lemhöfer
and Dijkstra, 2004;Lemhöfer et al., 2004;Duñabeitia et al., 2010;
Midgley et al., 2011;Peeters et al., 2013).
These results are in line with the RHM (Kroll and Stewart,
1994; Kroll et al., 2010) that suggests that semantic access for L2
words is highly mediated by the activation of their corresponding
L1 translation equivalents. As a consequence, L2 words that
highly overlap with their L1 translations at the orthographic
3In general, the cognate effect was larger for the low proficient group (mean RT
effect =61; SD =80; mean accuracy effect =7.84%, SD =9.67) than for the
intermediate proficient group (mean RT effect =47; SD =48; mean accuracy
effect =5.47%, SD =5.44). A combined analysis on the latency and accuracy data
including the factor Group showed that the cognate effect was larger in the group
with lower proficiency. This difference was statistically significant in the analysis
on the accuracy data [F1(1,165) =4.13, p=0.04; F2(1,198) =3.63, p=0.05], and
marginal in the RT analysis, in whi ch only the by-item analysis showed a significant
difference [F1(1,165) =1.84, p=0.17; F2(1,198) =13.86, p<0.001].
Frontiers in Psychology | www.frontiersin.org 7May 2015 | Volume 6 | Article 588

Casaponsa et al. Cognate effect and language learning
level (i.e., cognates) would be recognized faster and more accu-
rately than non-cognates, since L1-mediation would be facil-
itated as a consequence of the high similarity. Furthermore,
according to the RHM, a substantial increase of L2 profi-
ciency would boost the creation and strengthening of direct
links from L2 words to their corresponding semantic represen-
tations, yielding reduction of the strength of pre-existing links
between L2 and L1 lexical representations. Within this frame-
work, greater cognate effects are expected for lower proficiency
stages of L2 learning due to the greater involvement of L1
mediation.
In a similar vein, the different cognate effects reported for
the two groups of participants fit well with the BIA-d model
(Grainger et al., 2010), which also predicts faster reaction times
and greater accuracy rates for cognate words over non-cognates
given that the orthographic, lexical and semantic representations
activated by L2 cognate words overlap with those from their L1
translation equivalents. Besides, this model suggests that cognate
words also present higher relative frequency of use than non-
cognates, thus speeding up their recognition. At low levels of
L2 proficiency the BIA-d predicts similar results than those pre-
dicted by the RHM. Newly acquired L2 words highly rely on
interconnections with their L1 translations as well as with the
corresponding semantic representations, leading to greater cog-
nate effects than at higher levels of L2 proficiency. However, when
the L2 proficiency increases and L2 words are integrated into
the L1 lexicon (note that the BIA-d model assumes a single inte-
grated lexicon), the interconnections with their L1 translations
decrease as a result of the inhibition coming from the L2 language
nodes, and hence the diminished cognate effects at higher levels
of L2 proficiency. Therefore, the BIA-d model correctly accounts
for the different magnitudes of cognate effects observed in the
B1 and A2 groups. While the theoretical source of the cognate
effects is not a critical issue under debate in the current study,
we acknowledge that both theoretical frameworks (i.e., RHM and
BIA-d model) can account for the reported differences in the
cognate effects.
More importantly and directly related to the issue at stake
in the current study, the results from the multiple regression
analyses show that the magnitude of the cognate effect mea-
sured at the end of the first term is a reliable predictor of
non-native reading comprehension achievement at the end of
the academic year for both groups of second language learn-
ers. Interestingly, in Experiment 1 we found that individual
differences in the cognate effect were positively related with
the reading comprehension scores at the end of the academic
year at lower proficiency levels (A2). That is, those L2 learners
who showed larger cognate facilitation effects at the end of the
first academic term (February) obtained higher reading compre-
hension scores at the end of the academic year. These results
suggest a positive relationship between the degree of reliance on
cross-language similarity (as measured by the cognate effect) and
foreign reading comprehension achievement at low levels of for-
mal non-native language learning. In contrast, in Experiment 2
we found that individual differences in the magnitude of the cog-
nate effect were negatively related with the final scores in the
reading comprehension assessment at intermediate proficiency
levels (B1). Those intermediate L2 learners who achieved bet-
ter reading comprehension scores at the end of the academic
year were the ones who relied less on cross-language similari-
ties when reading words in L2 at the end of the first academic
term.
More specifically, results from the multiple regression model
in the low-proficiency group (Experiment 1) showed that final
reading comprehension scores were best explained by higher
cognate effects, higher self-ratings of self-perceived proficiency,
and higher scores in the non-verbal intelligence test. The model
explained ∼25% of the variance in reading comprehension and
included only the three factors mentioned above. In contrast,
the resulting regression model for the intermediate-proficiency
group (Experiment 2), which approximately explained 20% of
the variance in reading comprehension scores, included four
variables as significant predictors: the cognate effect, partici-
pants’ age of acquisition of the non-native language, WM skills
and an estimate of non-verbal intelligence. Results from this
group showed that better reading comprehension achievement
was primarily predicted by lower cognate effects (i.e., smaller
RT differences between the recognition of cognates and non-
cognates) and by lower age of non-native language acquisition
(i.e., earlier contact with English as a non-native language),
and by higher scores in the WM and non-verbal intelligence
tests.
Taken together the results from both groups of participants
suggest that the link between native- and foreign-language lexical
representations helps participants at initial stages of the learning
process,whilethisisnotthecaseatintermediatelevelsofpro-
ficiency. Thus, at intermediate levels of proficiency strong and
direct mappings from the non-native lexical forms to semantic
concepts seem needed to achieve good non-native reading com-
prehension scores. Theseresults are in line with the predictions of
both the RHM (Kroll and Stewart, 1994) and the BIA-d (Grainger
et al., 2010) even though the rationale and mechanisms impli-
cated are not the same. Both theoretical accounts suggest that at
initial stages of L2 learning the lexico-semantic organization of
L2 words are mostly mediated by L1 translations, and therefore
the process of acquiring new L2 vocabulary is highly sensitive to
the overlap at the orthographic and/or phonological and seman-
tic levels with the L1. In contrast, strong mappings between
L2 lexical representations and concepts are needed in order to
achieve good reading comprehension at intermediate levels of
proficiency. Therefore, at intermediate levels of proficiency the
degree of reliance on cross-language similarity is inversely related
with reading comprehension achievement, suggesting that those
L2 learners who at the end of the first academic term presented
a decrease on the strength of L1 reliance in favor of the direct
links between L2 lexical representations and semantic concepts
(as measured by a decrease in the cognate effect) had better prog-
nostic at achieving good reading comprehension scores at the end
of the academic year.
These results also demonstrate a close relationship between
general cognitive skills and individual differences in (non-native)
language learning. The estimate of non-verbal intelligence signif-
icantly explained part of the variance of the subsequent reading
language comprehension in both groups (Experiments 1 and
Frontiers in Psychology | www.frontiersin.org 8May 2015 | Volume 6 | Article 588

Casaponsa et al. Cognate effect and language learning
2), in line with preceding studies (Papagno and Vallar, 1995;
Kempe et al., 2010;Lopez-Barroso et al., 2011). Higher non-
verbal intelligence scores provided a better prognostic of reading
comprehension. It is well known that fluid intelligence is closely
related with executive functions (Carpenter et al., 1990;Miyake
et al., 2001;Salthouse et al., 2003;Colom et al., 2006) and reason-
ing abilities (Duncan et al., 1995, 1996). Furthermore, IQ has been
found to be a good predictor of general academic performance
(Murray and Lamb, 1994;Gottfredson, 2004;Coyle and Pillow,
2008;Herrnstein and Murray, 2010). Our results add to a growing
body of evidence showing a link between non-verbal intelligence
and academic performance in a non-native language-learning
context (see Pishghadam and Khajavy, 2013).
Similarly, and in line with preceding evidence, results from
Experiment 2 showed that WM capacity is also related to non-
native language achievement, at least at intermediate levels of
proficiency. It has been previously shown that WM capac-
ity is highly correlated not just with general reading compre-
hension, but with general reasoning abilities (Daneman and
Carpenter, 1980;Turner and Engle, 1989;Kyllonen and Christal,
1990), mathematical processing (Ashcraft, 1995;Gathercole and
Pickering, 2000;Lee and Kang, 2002;Kyttälä and Lehto, 2008)
and attentional control, among other cognitive skills (Barrett
et al., 2004;Wright et al., 2014). In that sense, WM capacity was
also positively related with good reading achievement at inter-
mediate levels of proficiency, but not at lower levels, suggesting
that this factor could play a different role at different stages of
language learning. In general, it seems that both factors (IQ and
WM) contribute significantly to the general learning processes,
and it is not surprising that similar effects are also found in
experimental contexts aimed at exploring non-native language
learning processes.
One question that remains open is whether the two groups
differ in their general cognitive abilities. Kroll et al. (2002)inves-
tigated the role of WM (as measured with an L1 reading span
task) at different levels of L2 achievement in a series of L1/L2
word naming and explicit translation tasks. They found that L2
learners displayed a generally lower reading span than highly
proficient bilinguals. Interestingly, we found a similar pattern of
results. The more proficient group had a greater memory span
than the low proficient group [t(165) =2.81; p=0.005]. In addi-
tion, the more proficient learners also had a significantly higher
IQ [t(165) =2.48; p=0.01], even though we had no expectation
that general cognitive factors would differ between participants
at different levels of proficiency. Certainly, deciphering whether
these differences are a consequence or a cause of non-native lan-
guage proficiency in the present study is not possible, and it goes
beyond the scope of this manuscript. Nonetheless, we believe that
this is a suggestive finding that is worth mentioning.
More directly related with the main goal of this study, Kroll
et al. (2002) showed that the cognate effect was inversely related
with WM scores. They showed that at lower levels of proficiency,
the group with higher memory span showed reduced cognate
effects compared to the group with lower memory span. In partial
contrast with these results, we found that the performance in the
WM and intelligence tests were not related to the cognate effect.
Even though there was a marginal positive relationship between
the magnitudes of the cognate effect and IQ estimates in the A2
group (r=0.23; p=0.07), such a relationship was not found for
the WM estimates (r=0.05; p=0.69). For the more proficient
B1 group none of these estimates showed a significant correlation
with the cognate effect (IQ: r=−0.15; p=0.14; WM: r=0.08;
p=0.45). Nonetheless, it should be kept in mind that the read-
ing span task used by Kroll et al. (2002) is a more complex task
than the forward number retention task used in the current study
to estimate WM (see Daneman and Carpenter, 1980,foradirect
comparison between both tasks and different reading tests). In
addition, it should be noted that the translation naming task
used by Kroll et al. (2002) require a deeper lexical search and an
involvement of WM should probably be more anticipated in that
task than in the lexical decision task used in the current study.
Interestingly, our results also showed that the chronologi-
cal age of participants (which varied from 19 to 69 years) did
not account for individual differences in reading comprehension
achievement in either group. In contrast to the common view
that non-native language achievement is hampered by age, these
results demonstrate that the non-native second language acquisi-
tion age is more relevant for language attainment than the actual
age of the learners (see Dowens et al., 2010, for a similar con-
clusion) at intermediate levels of proficiency. Furthermore, while
these two variables show a high degree of cross-correlation due
to the relatively recent structural changes in the educational poli-
cies in Spain leading to the inclusion of English in the formal
academic curriculum, chronological age, but not age of English
acquisition, was dropped from both models resulting in a negli-
gible change in the predictive capacity of the general regression
models.
Previous studies have shown that learning a foreign language
is positively influenced by previous experience with other lan-
guages (Sanz, 2000;Cenoz, 2003, 2013;Errasti, 2003;Pilar and
Jordà, 2003;Safont, 2005;Kassaian and Esmae’li, 2011;Zare
and Mobarakeh, 2013; among others). All participants tested
in our study were native Spanish speakers living in a bilin-
gual region (the Basque Country). Hence, all of them had some
knowledge of Basque, the co-official language in this region
(self-ratings of Basque proficiency of the participants in A1
level according to a 1-to-10 scale: mean =5.53, SD =2.84;
level B1: mean =6.52, SD =2.58). To investigate the poten-
tial impact of knowledge and exposure to Basque on English
learning, we reanalyzed the models by adding the participants’
self-ratings of Basque proficiency as a factor. The inclusion
of this factor did not significantly improved the predictability
of second language achievement for the low proficiency group
[Adjusted R2=0.23; F-change(1,57) =0.63; p=0.43]. In
other words, the variability associated with the prior knowl-
edge of another language did not modulate foreign language
comprehension achievement at lower levels of formal lessons
[βs=0.09, t(61) =0.79, p>0.40]. However, inclusion of
Basque proficiency into the model improved the predictability
of English comprehension achievement of intermediate learn-
ers of English at the end of the scholar year, even though the
effect was marginal [Adjusted R2=0.21; F-change(1,99) =3.68;
p=0.06]. Participants with higher knowledge of Basque showed
a marginal advantage at achieving better scores in English
Frontiers in Psychology | www.frontiersin.org 9May 2015 | Volume 6 | Article 588

Casaponsa et al. Cognate effect and language learning
reading comprehension [βs=0.19, t(104) =1.92, p=0.06]. This
suggests that knowing another language different from the native
language facilitates learning a foreign language, even though this
positive impact of bilingualism only appeared for intermediate
levels of language acquisition and was not very robust.
Overall, the results suggest that the cognate facilitation effect,
a purely psycholinguistic measure that has been found to be a
good predictor of word identification across different language
combinations (Lemhöfer et al., 2008) and that is highly influ-
enced by the degree of proficiency in the non-native language
(Bultena et al., 2014), predicts reading comprehension skills in
non-native language learners at the end of the academic year.
More specifically, our results indicate that higher achievement in
reading comprehension is predicted by lower cognate facilitation
effects assessed several months before the exam at intermedi-
ate levels of proficiency (Experiment 2), and that higher cognate
effects predict higher reading comprehension achievement at ini-
tial levels of foreign language learning (Experiment 1). These
findings fit well with previous evidence from studies testing bilin-
gual reading comprehension showing an inverse relationship
between the magnitude of the cognate effect and the level of pro-
ficiency in a given non-native language. The cognate effect was
a good predictor of reading comprehension achievement at the
end of the school year, showing a positive relationship between
cognate effects and reading comprehension at lower levels of
proficiency, and an inverse correlation between cognate effects
and reading comprehension at intermediate levels of proficiency
(see Figures 1B and 2B). As discussed above, at the theoretical
level these results fit well with models suggesting that during the
course of non-native language learning, bilinguals move from
a non-native word recognition process that mainly relies on
the pre-existing native-language representations (the L1-lexical
mediation hypothesis), to a direct conceptual access that is mainly
dependent on the non-native linguistic representations (Potter
et al., 1984;De Groot and Nas, 1991;De Groot, 1992;De Groot
et al., 1994;Kroll and Stewart, 1994;Kroll and De Groot, 1997;
Perea et al., 2008;Kroll et al., 2010). The current results confirm
these hypotheses and further demonstrate that a greater reliance
on native-language lexical mediation strategies goes hand in hand
with impoverished non-native reading comprehension skills at
intermediate levels of proficiency.
To conclude, these results suggest that individual differences
in non-native reading comprehension achievement are highly
influenced by general cognitive and linguistic factors, and criti-
cally, by the extent to which learners rely on their native language
during the non-native language learning process.
Acknowledgments
The authors are grateful to Brendan Costello, Guillaume Thierry
and the two reviewers for their helpful comments on ear-
lier drafts and to the member of the Public Language School
for their disposal and collaboration during the data collection.
This research has been partially funded by grant PSI2012-32123
from the Spanish Government, ERC-AdG-295362 grant from the
European Research Council, and by the AThEME project funded
by the European Union Seventh Framework Programme (grant
number 613465).
Supplementary Material
The Supplementary Material for this article can be found
online at: http://journal.frontiersin.org/article/10.3389/fpsyg.
2015.00588/abstract
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Conflict of Interest Statement: The authors declare that the research was con-
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