International Journal Of Literature And Languages
83
https://theusajournals.com/index.php/ijll
VOLUME
Vol.05 Issue06 2025
PAGE NO.
83-85
10.37547/ijll/Volume05Issue06-24
Cognitive Processes In Second Language Learning: A
Psycholinguistic Perspective
Madirimova Gulmira
ESL teacher at Renessans Educational University, Uzbekistan
Received:
12 April 2025;
Accepted:
08 May 2025;
Published:
19 June 2025
Abstract:
This article examines the constellation of cognitive processes that underlie second-language (L2)
learning, drawing on contemporary psycholinguistic theory and empirical evidence. The study integrates models
of working memory, attentional control, implicit
–
explicit knowledge interaction, and lexical access to explore how
learners internalise and retrieve a new linguistic system. A mixed-methods design combined eye-tracking with
stimulated-recall protocols during an intensive twelve-week instructional programme for Uzbek-Russian bilingual
adults acquiring English. Quantitative analyses of gaze duration and reaction-time measures were triangulated
with qualitative thematic coding of verbal reports to trace the dynamics of noticing, chunking, form
–
meaning
mapping, and automatisation. Results show that high phonological working-memory span and efficient executive
control predict faster consolidation of morphosyntactic sequences, while implicit statistical learning mechanisms
dominate the acquisition of low-salience grammatical cues. The discussion situates these findings within usage-
based and declarative/procedural frameworks, arguing that successful L2 learning emerges from the synergy of
domain-general and language-specific cognitive resources modulated by task design. Pedagogical implications
point to adaptive scaffolding that targets the shifting locus of cognitive load across proficiency levels.
Keywords: -
Second-language acquisition, psycholinguistics, working memory, attentional control, implicit
learning, eye-tracking, bilingualism.
Introduction:
The quest to unravel how humans
acquire a new language after early childhood has long
engaged linguists, psychologists, and educators. Classic
hypotheses
—from Krashen’s input
-driven monitor
model to Ellis’s usage
-based emergentism
—
highlight
the pivotal role of cognition in mediating exposure to
linguistic input. Despite substantial progress, the field
lacks an integrative account that reconciles
mechanism-oriented
laboratory
findings
with
classroom-based evidence. Recent advances in
cognitive neuroscience, particularly the precision of
eye-tracking and the temporal resolution of
electroencephalography,
create
unprecedented
opportunities to observe language processing in situ.
Psycholinguistics views language as a set of mental
representations manipulated by specialised and
general-purpose cognitive systems. During L2
acquisition, learners must segment the speech stream,
map novel forms to existing conceptual schemas, and
restructure attentional routines forged by the first
language (L1). Working memory supplies a buffer for
holding verbal material; attentional control regulates
the allocation of limited resources; implicit learning
tallies distributional regularities; and metalinguistic
awareness enables hypothesis testing. These processes
do not operate in isolation but converge dynamically,
conditioned by proficiency, task demands, and
affective variables.
Research with Uzbek-Russian bilinguals presents a
fertile testing ground because their L1s differ
typologically from English in morphology, syntax, and
word order. Such contrast sharpens the visibility of
transfer effects and heightens cognitive load. The
present study adopts a psycholinguistic lens to track
how specific cognitive mechanisms support or hinder
the internalisation of syntactic and lexical patterns
during an intensive instructional cycle. By triangulating
International Journal Of Literature And Languages
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International Journal Of Literature And Languages (ISSN: 2771-2834)
process-data (eye movements, reaction times) with
introspective reports, we aim to delineate the
trajectories through which declarative knowledge
becomes proceduralised and automatised.
Forty-two adult volunteers (age 19
–
31, M = 24.6, SD =
3.1) were recruited from university language centres in
Tashkent. All participants were balanced Uzbek-
Russian bilinguals with no prior sustained exposure to
English beyond secondary-school curricula. They gave
informed consent and completed background
questionnaires covering language history, socio-
economic status, and cognitive health.
Learners engaged in a twelve-week, five-day-per-week
intensive course (total 180 contact hours) following a
communicative-grammar
syllabus.
Instruction
incorporated
audiovisual
input,
corpus-based
frequency lists, and task-based interaction.
Phonological working memory was assessed with an
automated reading-span task adapted to Uzbek
phonotactics. Attentional control was indexed via the
colour
–
word Stroop and n-back tasks. Implicit
statistical learning aptitude was measured using a
visual artificial-grammar paradigm. Pre- and post-tests
of English proficiency employed the Oxford Quick
Placement Test.
During weeks four, eight, and twelve, participants
completed focus-on-form tasks while wearing a Tobii
Pro X3-120 eye-tracker (sampling rate 120 Hz). Stimuli
consisted of controlled narrative texts embedding
target structures (e.g., third-person -s, participial
adjectives). Gaze duration on regions of interest served
as a proxy for cognitive effort. Immediately afterwards,
stimulated-recall interviews captured on-line noticing
and metacognitive reflections. Reaction times for
grammaticality-judgement tasks were recorded
through E-Prime.
Eye-movement metrics (first-pass duration, total
reading time) and reaction times were log-transformed
to correct skewness. Mixed-effects linear models
predicted processing speed and accuracy from
cognitive-aptitude scores, time, and task type, with
random intercepts for participants and items.
Qualitative data underwent inductive thematic analysis
supported by NVivo 14, generating coding categories
such as noticing lexical chunks, hypothesis testing, and
automatized retrieval. Validity was enhanced through
inter-rater agreement
(κ = 0.81).
Quantitative modelling revealed that phonological
working-memory span significantly predicted shorter
first-
pass durations on morphosyntactic target zones (β
= −0.34, p < .001), indicating more efficient initial
parsing. Attentional-control performance accounted
for incremental gains in grammaticality-judgement
accuracy across sessions (β = 0.27, p = .004). Implicit
statistical-learning
aptitude
uniquely
explained
variance in the post-test acquisition of low-salience
inflections such as third-person -
s (β = 0.22, p = .012)
after controlling for explicit aptitude.
Reaction-time distributions showed a progressive shift
from controlled to automatic processing. Median
response latency decreased from 1430 ms (SD = 312
ms) at week four to 885 ms (SD = 198 ms) at week
twelve. Eye-tracking corroborated this temporal
pattern: total reading time on grammatical targets
dropped by 38 %, while regressions to preceding
context declined by 41 %.
Qualitative analysis illuminated how learners allocated
attention. In the early phase, participants reported
conscious monitoring of verb endings and reliance on
native-language
translation
equivalents.
Mid-
programme narratives highlighted the emergence of
chunk-based processing, with learners citing formulaic
sequences
such as I don’t think or at the same time as
anchors for sentence planning. By the final phase, many
described an “intuitive grasp” of tense–
aspect marking,
reflecting a transition from declarative to procedural
control.
The findings substantiate a multicomponent model of
L2 learning in which domain-general cognitive faculties
interface with language-specific mechanisms. High
working-memory capacity facilitates the temporary
maintenance of novel forms, enabling deeper syntactic
integration. This aligns with
Baddeley’s multi
-store
model and subsequent SLA adaptations that posit a
phonological loop sensitive to articulatory rehearsal.
Efficient attentional control enhances selective
processing, allowing learners to filter irrelevant cues
and prioritise diagnostically rich input, echoing theories
of input enhancement.
Crucially, implicit statistical learning emerged as the
principal driver for mastering forms that receive limited
classroom explanation. The success of learners with
strong
aptitude
scores
supports
the
declarative/procedural
distinction
advanced
by
Ullman, where rule-like patterns become encoded in
procedural memory networks through repeated
exposure,
without
conscious
mediation.
The
convergence of gaze-based indices and verbal reports
indicates that noticing and implicit abstraction coexist:
initial focal attention to salient forms seeds implicit
pattern extraction, which gradually automatizes
performance.
These
dynamics
resonate
with
usage-based
perspectives that attribute grammatical development
to
the
frequency-driven
entrenchment
of
constructions. Yet the predictive power of individual-
International Journal Of Literature And Languages
85
https://theusajournals.com/index.php/ijll
International Journal Of Literature And Languages (ISSN: 2771-2834)
difference variables underscores that frequency effects
are
filtered
through
cognitive
constraints.
Pedagogically, this calls for adaptive task sequencing:
beginner instruction may exploit high-salience input
with overt feedback to cultivate noticing, thereafter
shifting toward rich exposure that leverages implicit
learning. Additionally, training executive attention
—
through task-switching or mindfulness exercises
—
m
ight boost learners’ capacity to manage L1
interference and inhibit premature lexical retrieval.
Second-language learning is a cognitively intensive
endeavour orchestrated by the interplay of working
memory, attentional control, and implicit statistical
learning. The present study demonstrates that these
mechanisms collectively shape the trajectory from
initial noticing to automatized production, and their
relative contributions fluctuate with proficiency and
structural salience. By harnessing multimodal process-
tracing, we provide nuanced evidence that successful
instruction must tailor interventions to learners’
evolving cognitive profiles, enriching exposure while
scaffold¬ing attentional focus. Future research should
employ longitudinal neuroimaging to chart neural
reorganisation during L2 acquisition and explore how
affective factors modulate cognitive resource
allocation.
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