What drives college students to use AI for L2 learning? Modeling the roles of self-efficacy, anxiety, and attitude based on an extended technology acceptance model
Acta Psychologica,
Год журнала:
2024,
Номер
249, С. 104442 - 104442
Опубликована: Авг. 6, 2024
Prior
research
highlights
the
critical
role
of
AI
in
enhancing
second
language
(L2)
learning.
However,
factors
that
practically
affect
L2
learners
to
engage
with
resources
are
still
underexplored.
Given
widespread
availability
digital
devices
among
college
students,
they
particularly
poised
benefit
from
AI-assisted
As
such,
this
study,
grounded
an
extended
Technology
Acceptance
Model
(TAM),
investigates
predictors
learners'
actual
use
tools,
focusing
on
self-efficacy,
AI-related
anxiety,
and
their
overall
attitude
toward
AI.
Data
was
gathered
429
at
Chinese
universities
via
online
questionnaire,
utilizing
four
established
scales.
Through
structural
equation
modeling
(SEM)
AMOS
24,
results
indicate
self-efficacy
could
negatively
positively
influence
both
tools.
Besides,
anxiety
predicted
Moreover,
a
positive
predictor
through
reducing
AI,
or
combination
both.
This
study
also
discusses
theoretical
pedagogical
implications
suggests
directions
for
future
research.
Язык: Английский
Developing and Validating a Scale of Artificial Intelligence Anxiety Among Chinese EFL Teachers
European Journal of Education,
Год журнала:
2025,
Номер
60(1)
Опубликована: Янв. 7, 2025
ABSTRACT
As
artificial
intelligence
(AI)
technology
continues
to
advance,
its
influences
across
various
industries
have
grown,
leading
increasing
levels
of
anxiety,
including
that
in
education.
Nonetheless,
terms
current
knowledge,
the
literature
lacks
a
valid
scale
measure
AI
anxiety
among
EFL
teachers,
particularly
university
teachers.
Moreover,
underlying
dimensions
this
construct
yet
be
clarified.
Against
these
gaps,
study
aims
develop
and
validate
assess
teachers
China.
We
used
qualitative
interviews
quantitative
surveys
combined
identify
key
In
so
doing,
251
Chinese
completed
newly
designed
scale.
The
result
exploratory
factor
analyses
indicated
five
21
items
questionnaire.
Five
were
identified:
technical
proficiency,
job
displacement,
technological
support,
student
experience
research
development.
Next,
another
415
participated
validating
confirmatory
analysis
demonstrated
strong
reliability,
validity
an
acceptable
model
fit.
This
new
provides
useful
tool
for
assessing
highlights
unique
challenges
they
face
adapting
AI,
offering
basis
future
targeted
support.
Язык: Английский
Modelling College Students' Acceptance to Use Generative Artificial Intelligence for Second Language Learning: A Theory of Planned Behaviour Perspective
European Journal of Education,
Год журнала:
2025,
Номер
60(1)
Опубликована: Янв. 17, 2025
ABSTRACT
The
benefits
of
Generative
Artificial
Intelligence
(GenAI)
in
enhancing
second
language
(L2)
learning
are
well
established.
However,
these
advantages
can
only
be
realised
if
learners
willing
to
adopt
the
technology.
This
study,
grounded
Theory
Planned
Behaviour
(TPB),
investigated
factors
influencing
behavioural
intention
use
GenAI
among
337
Chinese
college
L2
using
five
validated
scales.
A
Structural
Equation
Modelling
(SEM)
approach
with
Amos
24
yielded
several
key
findings.
Notably,
demographic
encompassing
gender
and
age
did
not
significantly
affect
TPB
components.
Subjective
norm
attitude
were
found
have
a
positive
significant
impact
on
intention,
while
perceived
control
demonstrate
effect.
Furthermore,
literacy
emerged
as
predictor
both
directly
indirectly
through
its
influence
attitude.
Collectively,
variables
accounted
for
51.6%
variance
intention.
study
also
discusses
theoretical
pedagogical
implications
offers
suggestions
future
research.
Язык: Английский
A meta-analysis examining AI-assisted L2 learning
IRAL - International Review of Applied Linguistics in Language Teaching,
Год журнала:
2025,
Номер
unknown
Опубликована: Март 17, 2025
Abstract
Numerous
quantitative
studies
have
investigated
how
artificial
intelligence
(AI)
impacts
the
development
of
second
language
(L2).
While
individual
delve
into
effects
AI
interventions
on
L2
learning,
a
meta-analysis
provides
comprehensive
evaluation
AI’s
effectiveness
in
acquisition
(SLA).
Despite
growing
body
meta-analytical
research
AI-assisted
several
potential
moderators
not
been
thoroughly
previous
meta-analyses.
This
examines
learning
and
analyzes
factors
that
can
influence
effectiveness.
The
analysis
included
15
involved
total
2,156
participants
generated
53
effect
sizes.
After
correcting
for
measurement
sampling
error,
demonstrated
positive
large
with
d
=
1.167.
Q
statistic
suggested
true
sizes
varied
significantly
across
studies,
which
warranted
conducting
theory-based
moderator
analysis.
results
revealed
type
interactions
was
significant
affecting
learning;
more
beneficial
developing
receptive
skills
than
productive
skills;
technologies
excelled
at
building
learners’
vocabulary
compared
to
other
higher
an
in-class
context
out-of-class
context;
IMALL
impactful
ICALL;
there
no
difference
technology
intervention
between
K-12
college
learners.
Язык: Английский
Giving Away the Immersive L2 Learning Experiences in GenAI‐Mediated Contexts: The Contributions of Cognitive and Affective Factors
European Journal of Education,
Год журнала:
2025,
Номер
60(2)
Опубликована: Март 23, 2025
ABSTRACT
Immersive
learning
plays
a
crucial
role
in
effective
second
language
(L2)
acquisition,
but
many
learners
face
limited
opportunities
to
interact
with
native
speakers.
While
existing
research
highlights
the
importance
of
immersion
L2
learning,
there
is
still
gap
understanding
how
Generative
AI
(GenAI)
can
provide
greater
access
such
immersive
environments.
This
study
aims
address
this
by
exploring
factors
influencing
GenAI‐mediated
learning.
Drawing
upon
cognitive‐affective
model
control‐value
theory,
and
technology
acceptance
model,
examined
impact
cognitive
(e.g.,
perceived
ease
use
usefulness)
affective
enjoyment
boredom)
on
immersion,
using
sample
460
Chinese
college
learners.
Structural
equation
modelling
Amos
24
was
applied
analyse
data,
yielding
several
key
findings.
(i)
Perceived
positively
predicted
usefulness
had
no
direct
effect
or
boredom.
(ii)
influenced
while
negatively
affecting
(iii)
Enjoyment
positive
predictor
whereas
boredom
significant
effect.
(iv)
Mediation
analysis
revealed
that
indirectly
through
not
combination
usefulness.
The
concludes
implications
for
practice
suggestions
future
research.
Язык: Английский
The Realisation Path of Human-Computer Collaborative Learning in College English Teaching Based on Blended Learning Model
Applied Mathematics and Nonlinear Sciences,
Год журнала:
2024,
Номер
9(1)
Опубликована: Янв. 1, 2024
Abstract
Reforming
and
innovating
the
teaching
mode
of
university
English
program
is
crucial
for
cultivating
students’
literacy
skills.
This
paper
utilizes
theory
multiple
intelligences
other
relevant
theories,
along
with
fundamental
requirements
college
in
blended
learning
mode,
to
guide
design
an
intelligent
platform-based
human-computer
collaborative
path.
Subsequently,
we
conducted
experiments
explored
changes
attitudes
aspects
through
a
questionnaire
after
conducting
reliability
test.
It
was
found
that
there
significant
difference
between
experimental
class’s
post-test
scores
on
those
control
class,
p-value
0.029<0.05
test
total
scores.
Also,
toward
have
been
significantly
improved,
which
different
from
class
(p<0.05)
supports
effectiveness
implementing
HC
pathway.
paper’s
implementation
path
can
enhance
courses
better
cater
needs
interests
innovative,
methods.
Язык: Английский