Determinantes psicolingüísticos da compreensão de leitura em
inglês como língua estrangeira II
RESULTS
The
final sample for the study included 280 undergraduate college
students, 118 males (42.1%) and 162 females (57.9%). The mean age
for the sample 23.06 years. 105 of the participants were from the
UNAM whereas 175 of them were students at UAM. As to their field of
studies, 208 (74.3%) were from the Division of Social Sciences and
Humanities; 38 (13.6%) from the Division of Basic Sciences and
Engineering; and 34 (12.0% from the Division of Biological and
Health Sciences.
The
descriptive analysis of the main variables under study yielded the
following results: (1) Reading comprehension in English: mean score
of 19.32, equivalent to 52/100, with an standard deviation of 4.99;
(2) Reading comprehension in Spanish: mean score of 25.62 (equivalent
to 69/100) with a standard deviation of 4.75; (3) Linguistic
competence in English: mean score of 15.85 (equivalent to 31/100)
with a standard deviation of 5.87; (4) Perception of lexical
transparency between English and Spanish: mean score of 93.8 (equivalent
to 69% of correctly identified cognates within the corresponding
test) with a standard deviation of 19.46; (5) Cognitive style: mean
score of 9.55 (slightly above de median of possible scores for such
test) with a standard deviation of 4.72; (6) Locus of control: mean
score of 20.24 (slightly above the median of possible scores for the
corresponding test 20) with a standard deviation of 6.84, (7) Action
Orientation (AOF subscale): mean score of 6.57 (slightly above the
median of possible scores for the corresponding subscale of Kuhl’s
scale=6.0) with a standard deviation of 6.57.
Multiple regression analysis. The regression model originally
proposed to explain the variability of reading comprehension in
English (RCE) -Model 1- estimated from the scores of the 280
subjects included in the sample under study, yielded the following
results (Table 1): An F=25.46627 for the associated analysis of
variance, indicating a significant regression of model 1 (p<0.01), a
multiple correlation coefficient of 0.59904 (Multiple R), and a
determination coefficient of 0.35885 (R. Square), indicating that
the independent variables explained 35.88% of the variability in
discourse processing in English under Model 1.
RCE =
b0 + b1RCS + b2 LCE + b3PLT
+ b4CS + b5LC + b6AOF +
e...........(Model 1)1
However,
under Model 1 only three variables showed to be significant, namely,
reading comprehension in Spanish, linguistic competence in English
and perception of lexical transparency between L1 and L2 (p <
0.0000; 0.0000; and 0.05, respectively). Therefore, alternative
models were examined, withdrawing each of the nonsignificant
variables. Models with 5, 4 and 3 independent variables were tested.
The model with three independent variables (RCS, LCE, and PLT) was
the only one in which all explanatory variables were significant (Table
2 - “Sig T column”).
RCE =
b0 + b1RCS +b2 LCE + b3PLT+
e...............................(Model 2)
The
regression analysis for Model 2 (Table 2) yielded a multiple
correlation coefficient of 0.59652, a determination coefficient of
0.35584 (that is, RCS, LCE, and PLT explained 35.584% of RCE’s
variability under model 2, roughly equivalent to the percentage
obtained under model 1), and an F value of 50.82 indicating the
existence of a significant regression for model 2 (p<.01). Column
“B” in Table 2 presents the estimators for the b0, b1, b2 and b3
parameters, from which the following fit model was derived (Prediction
Model):
RCE =
2.5829 + .38847 RCS + .27944 LCI + .0253 PLT............Prediction
Model
Nevertheless, and given the fact that the exclusion of the
psychological variables from the original model contradicted to a
certain extent research findings in the field suggesting their
theoretical relevance, it was hypothesized that they could have not
a direct but an indirect influence on he discourse processing skills
in English. That is, it could be the case that the psychological
variables did not explain RCE in the presence of RCS, LCI and PLT
due to the fact that they could be involved in the explanation of
the variability of any of those variables. Hence, and as a first
step in such direction, it was decided to analyze the influence of
the reader’s cognitive style, locus of control and action control on
his/her text processing skills in Spanish, based on the following
considerations: (1) The knowledge of the first language is
considered to be play the role of a metamodel in the acquisition of
a foreign language (Beaugrande, 1984); (2) The analysis of
correlations among variables showed that the correlations between
text processing skills in Spanish and the psychological variables (Table
3) was stronger than that between the latter variables and
linguistic competence in English or perception of lexical
transparency between L1 and L2. Hence, it was hypothesized that the
psychological set of variables could exert a preliminary influence
on reading comprehension in the first language which, in turn, could
become a major determinant of reading comprehension in the foreign
language. Accordingly, the following model was tested:
RCS =
b0 + b1 CS + b2LC + b3AOF
+ e...................................(Model 3)
The
results in Table 4 show a significant regression for Model 3
(F=10.29472, p<0.0001) with all three independent variables (cognitive
style, locus of control and action control) significant (p<0.0256;
p<0.0005 and p<0.0002, respectively).
Furthermore, the three psychological variables explained 10.1% of
the variability of reading comprehension in Spanish as indicated by
the associated determination coefficient (R Square), with a multiple
correlation coefficient of .31723 (Multiple R). The estimators for
the model’s coefficients generated the following prediction model:
RCS =
22.0089 + .20289 EC + .15381 LC - .21925 AOF............Prediction
Model
Notice
that the weights for cognitive style (CS) and locus of control (LC)
were positive as well as the correlation coefficients between
reading comprehension in Spanish (RCS) and both, cognitive style and
locus of control (Table 5). Hence, it is suggested that these two
psychological variables are directly proportional to reading
comprehension in Spanish. On the other hand, both the coefficient of
action control in the predictive model as well as its correlation
with reading comprehension in Spanish were negative, indicating that
such variable is inversely proportional to RCS.
In
short, in can be concluded that the last three variables in Model 1
(cognitive style, locus of control and action control) are not
significant because what we actually have is a rather indirect
effect of those variables a two-phase model which is explained as
follows:
PHASE
1
Reading
comprehension in Spanish is a function of the reader’s cognitive
style, locus of control, and action control orientation. Model 3
PHASE
2
Reading
comprehension in English is a function of the reader’s level of
reader comprehension in Spanish, linguistic competence in English,
and ability to perceive lexical transparency between L1 and L2.
Model 2
DISCUSSION AND CONCLUSIONS
The main
research hypothesis of this study was that that the variation in
reading comprehension in English in Mexican university students was
a function of the interaction of both linguistic variables (text
processing strategies in L1, linguistic competence in L2 and
perception of lexical transparency between L1 and L2) and
psychological variables (cognitive style, locus of control and
action control). However, and even though the influence of the
aforementioned variables was partially validated from the series of
regression analyses performed, it became evident that the
explanation of the variability in reading comprehension in L2 was
not straightforward (i.e., one that could be accounted for on the
basis of the direct contribution of the complete set of originally
proposed variables). Rather, such variability was partially
explained on the basis of a two-stage process in which the influence
of the three linguistic variables integrated into the model showed
to be direct, whereas the influence of the three psychological
variables was indirect (Figure 2). Figure 2:
Specifically, and as originally hypothesized, the readers’ ability
to process academic written discourse in English has shown to be a
function of three major predictor variables, namely, reading
comprehension in Spanish, linguistic competence in the foreign
language, and ability to perceive lexical transparency between the
two languages. In such regard, a model has been validated that
accounts for an initial 35% of the variance of reading comprehension
in English taking as predictor variables the three linguistic
variables incorporated into the original model. On the other hand,
and even though the set of psychological variables did not show a
direct, significant contribution in the explanation of reading
comprehension in English, an alternative multiple regression
analysis, which considered the readers’ text processing strategies
in L1 as the dependent variable, revealed that the reader’s
cognitive style, locus of control and action control orientation
have a slight, though significant contribution, in the explanation
of the variability of text processing strategies in L1. Hence, given
the fact that reading comprehension in Spanish constitute in our
model the most important predictor of the variability associated
with discourse processing in English, and that the former is in
itself partially explained by the complete set of psychological
variables, a two-stage explanatory model of reading in LLL2 is
suggested from this study based on the following considerations.
First,
it has been found that the ability of the reader to process written
academic discourse in L1 is the most powerful predictor of his/her
reading comprehension in the foreign language, maybe in the form of
the metamodel of language proposed by Beaugrande (1984) paving the
way for the extrapolation of reading strategies from L1 to L2.
Second, text processing skills in English have also been explained
by the reader’s level of linguistic competence in the foreign
language, competence that would represent the linguistic knowledge
base of the reader and that would play a major role in the
successful construction of meaning from text. Third, the ability to
perceive and exploit lexical transparency between L1 and L2 has also
been found to constitute a determinant of text processing ability in
the foreign language.
Furthermore, it has been found that cognitive style, locus of
control, and action control orientation function as indirect
psychological mediators of reading comprehension in English,
exerting an indirect impact on such variable via their influence on
the reader’s discourse processing ability in the first language, the
first major predictor of L2 reading in our study. In such regard, it
may be the case that the influence of psychological variables can be
more strongly differentiated in the explanation of reading
comprehension in L1 due to the fact that the reader would have
already developed and internalized a sound spectrum of lexical,
semantic, syntactic and grammatical decoding skills, thus making it
more feasible to discriminate the differential impact of
psychological variables, in themselves more distal to the central
process under study. On the other hand, the impact of linguistic
variables in the explanation of text processing variability in L2
would be expected to be more preeminent, since the readers’ lexical,
syntactic and grammatical repertories would tend to be more limited
as a result of the limited level of linguistic competence in the
foreign language. Hence, upon constructing meaning from text the
specialized processes associated with the linguistic dimension of
analysis would constitute the strongest determinants in the
construction of meaning from text.
To
conclude, the model validated from this study provides a preliminary,
non-exhaustive explanation of an otherwise extremely complex
phenomenon: the development of academic written discourse processing
skills in a foreign language. In such regard, further research is
needed in order to broaden our explanatory framework, integrating
the analysis of the contribution of additional predictive variables
not considered in this investigation which may include vocabulary
knowledge in L2 (Nation, 1983), lexical access (Baddeley, Loggie,
Nimmo- Smith & Brereton, 1985), previous knowledge (Afferbach,
1990); and socially-related factors (Parry, 1993; Street, 1993; Au,
1998)
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1 Universidad Autónoma Metropolitana, Unidad Iztapalapa -
Área de Investigación en Lenguas y Culturas Extranjeras.
2 Universidad Nacional Autónoma de México - Facultad de
Psicología.
3 Universidad Autónoma Metropolitana - Unidad Iztapalapa -
Departamento de Matemáticas.
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