China’s national image in the classroom: evidence of bicultural identity integration
Current Psychology,
Год журнала:
2025,
Номер
unknown
Опубликована: Фев. 13, 2025
Язык: Английский
A deep learning-based hybrid PLS-SEM-ANN approach for predicting factors improving AI-driven decision-making proficiency for future leaders
Journal of International Education in Business,
Год журнала:
2025,
Номер
unknown
Опубликована: Март 3, 2025
Purpose
This
study
explores
the
factors
influencing
artificial
intelligence
(AI)-driven
decision-making
proficiency
(AIDP)
among
management
students,
focusing
on
foundational
AI
knowledge,
data
literacy,
problem-solving,
ethical
considerations
and
collaboration
skills.
The
research
examines
how
these
competencies
enhance
self-efficacy
engagement,
with
curriculum
design,
industry
exposure
faculty
support
as
moderating
factors.
aims
to
provide
actionable
insights
for
educational
strategies
that
prepare
students
AI-driven
business
environments.
Design/methodology/approach
adopts
a
hybrid
methodology,
integrating
partial
least
squares
structural
equation
modeling
(PLS-SEM)
neural
networks
(ANNs),
using
quantitative
collected
from
526
across
five
Indian
universities.
PLS-SEM
model
validates
linear
relationships,
while
ANN
captures
nonlinear
complexities,
complemented
by
sensitivity
analyses
deeper
insights.
Findings
results
highlight
pivotal
roles
of
literacy
problem-solving
in
fostering
self-efficacy.
Behavioral,
cognitive,
emotional
social
engagement
significantly
influence
AIDP.
Moderation
analysis
underscores
importance
design
enhancing
efficacy
constructs.
identifies
most
critical
predictors
AIDP,
respectively.
Research
limitations/implications
is
limited
central
universities
may
require
contextual
adaptation
global
applications.
Future
could
explore
longitudinal
impacts
AIDP
development
diverse
cultural
settings.
Practical
implications
findings
designers,
policymakers
educators
integrate
into
education.
Emphasis
experiential
learning,
frameworks
interdisciplinary
preparing
AI-centric
landscapes.
Social
By
equipping
future
leaders
proficiency,
this
contributes
societal
readiness
technological
disruptions,
promoting
sustainable
contexts.
Originality/value
To
author’s
best
uniquely
integrates
analyze
interplay
shaping
It
advances
theoretical
models
linking
learning
theories
practical
education
strategies,
offering
comprehensive
framework
developing
students.
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
From Excitement to Anxiety: Exploring English as a Foreign Language Learners' Emotional Experiences in the Artificial Intelligence‐Powered Classrooms
European Journal of Education,
Год журнала:
2024,
Номер
unknown
Опубликована: Дек. 31, 2024
ABSTRACT
The
use
of
artificial
intelligence
(AI)
technologies
in
second/foreign
language
education
has
recently
gained
a
bulk
attention.
However,
the
emotional
experiences
English
as
foreign
(EFL)
learners
AI‐mediated
classes
have
been
ignored.
To
fill
this
gap,
present
qualitative
study
examined
34
Chinese
EFL
students'
perceptions
AI‐induced
emotions
and
regulation
strategies.
A
semi‐structured
interview
narrative
frame
were
used
to
collect
data.
gathered
data
thematically
analysed
through
latest
version
MAXQDA
software
(v.
2023).
findings
revealed
that
students
had
mostly
experienced
positive
‘motivation’,
‘excitement’,
‘engagement’
‘confidence’.
On
negative
side,
they
reported
experiencing
‘frustration’,
‘anxiety’
‘stress’
more
frequently
their
classes.
Furthermore,
indicated
participants
six
strategies,
namely
‘seeking
help
from
others’,
‘shifting
attention’,
‘cognitive
change’,
‘persistent
practice’,
‘staying
positive’
‘suppression’
regulate
emotions.
are
discussed
implications
provided
for
educators
understand
aspect
AI
injection
into
L2
education.
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
What is the influence of psychosocial factors on artificial intelligence appropriation in college students?
BMC Psychology,
Год журнала:
2025,
Номер
13(1)
Опубликована: Янв. 4, 2025
In
recent
years,
the
adoption
of
artificial
intelligence
(AI)
has
become
increasingly
relevant
in
various
sectors,
including
higher
education.
This
study
investigates
psychosocial
factors
influencing
AI
among
Peruvian
university
students
and
uses
an
extended
UTAUT2
model
to
examine
constructs
that
may
impact
acceptance
use.
employed
a
quantitative
approach
with
survey-based
design.
A
total
482
from
public
private
universities
Peru
participated
research.
The
utilized
partial
least
squares
structural
equation
modeling
(PLS-SEM)
analyze
data
test
hypothesized
relationships
between
constructs.
findings
revealed
three
out
six
significantly
influenced
students.
Performance
expectancy
(β
=
0.274),
social
influence
0.355),
learning
self-efficacy
0.431)
were
found
have
significant
positive
effects
on
adoption.
contrast
expectations,
ethical
awareness,
perceived
playfulness,
readiness
anxiety
did
not
impacts
appropriation
this
context.
highlights
importance
practical
benefits,
context,
self-confidence
within
These
contribute
understanding
diverse
educational
settings
provide
framework
for
developing
effective
implementation
strategies
education
institutions.
results
can
guide
policymakers
creating
targeted
approaches
enhance
integration
academic
environments,
focusing
demonstrating
value
AI,
leveraging
networks,
building
students'
confidence
their
ability
learn
use
technologies.
Язык: Английский
Exploring the relationship among technology acceptance, learner engagement and critical thinking in the Chinese college-level EFL context
Yang Han,
Shixin Yang,
Song Han
и другие.
Education and Information Technologies,
Год журнала:
2025,
Номер
unknown
Опубликована: Янв. 31, 2025
Язык: Английский
Exploring the Dynamics of Artificial Intelligence Literacy on English as a Foreign Language Learners’ Willingness to Communicate: The Critical Mediating Roles of Artificial Intelligence Learning Self-Efficacy and Classroom Anxiety
Behavioral Sciences,
Год журнала:
2025,
Номер
15(4), С. 523 - 523
Опубликована: Апрель 14, 2025
The
increasing
incorporation
of
artificial
intelligence
(AI)
in
English
as
a
foreign
language
(EFL)
instruction
has
garnered
much
attention
on
the
importance
technological
elements
instruction.
However,
while
AI
education
(AIED)
is
still
its
early
development,
research
how
learners’
literacy
affects
their
learning
outcomes
insufficient.
Furthermore,
studies
examining
impact
emotional
states
within
context
AIED
are
remarkably
few.
This
study
examines
interplay
between
and
EFL
willingness
to
communicate
(WTC),
emphasizing
mediating
roles
self-efficacy
classroom
anxiety.
utilizes
structural
equation
modeling,
analyzing
data
from
517
university
students
China
construct
prediction
model
for
WTC
AI-enhanced
contexts.
findings
indicate
that
improves
diminishes
anxiety,
both
which
significant
mediators
relationship
communicate.
highlights
imperative
integrating
into
enhance
expressive
confidence
mitigate
fear.
improve
understanding
literacy,
psychological
factors,
outcomes,
offering
practical
insights
integration
education.
Язык: Английский
Latent Profile Analysis of AI Literacy and Trust in Mathematics Teachers and Their Relations with AI Dependency and 21st-Century Skills
Behavioral Sciences,
Год журнала:
2024,
Номер
14(11), С. 1008 - 1008
Опубликована: Окт. 30, 2024
Artificial
Intelligence
(AI)
technology,
particularly
generative
AI,
has
positively
impacted
education
by
enhancing
mathematics
instruction
with
personalized
learning
experiences
and
improved
data
analysis.
Nonetheless,
variations
in
AI
literacy,
trust
dependency
on
these
technologies
among
teachers
can
significantly
influence
their
development
of
21st-century
skills
such
as
self-confidence,
problem-solving,
critical
thinking,
creative
collaboration.
This
study
aims
to
identify
distinct
profiles
trust,
examines
how
correlate
the
aforementioned
skills.
Using
a
cross-sectional
research
design,
collected
from
489
China.
A
robust
three-step
latent
profile
analysis
method
was
utilized
analyze
data.
The
revealed
five
literacy
teachers:
(1)
Basic
Engagement;
(2)
Developing
Literacy,
Skeptical
AI;
(3)
Balanced
Competence;
(4)
Advanced
Integration;
(5)
Expertise
Confidence.
found
that
an
increase
directly
correlates
decrease
findings
underscore
need
for
careful
integration
educational
settings.
Excessive
reliance
lead
detrimental
dependencies,
which
may
hinder
essential
contributes
existing
literature
providing
empirical
evidence
impact
professional
teachers.
It
also
offers
practical
implications
policymakers
institutions
consider
balanced
approaches
integration,
ensuring
enhances
rather
than
replaces
thinking
problem-solving
capacities
educators.
Язык: Английский