International Journal of Academic Research in Business and Social Sciences,
Год журнала:
2024,
Номер
14(1)
Опубликована: Янв. 5, 2024
Artificial
Intelligence
(AI)
has
gained
significant
attention
in
recent
years,
permeating
various
sectors
and
transforming
the
way
tasks
are
performed.
In
field
of
education,
AI
potential
to
revolutionize
traditional
teaching
learning
methodologies,
particularly
context
English
as
a
Second
Language
(ESL)
classrooms.
This
systematic
literature
review
aims
provide
comprehensive
overview
current
state
research
on
implementation,
challenges,
impacts
ESL
classrooms
based
different
countries.
For
this
purpose,
been
carried
out
ERIC,
WOS
Scopus
databases.
After
applying
inclusion
exclusion
criteria,
sample
was
set
at
25
articles.
The
findings
reveal
that
technologies
offer
promising
opportunities
enhance
instruction.
Despite
benefits,
also
uncovers
several
challenges
limitations
associated
with
implementation
Furthermore,
identifies
need
for
further
empirical
measure
long-term
effects
AI.
conclusion,
provides
valuable
insights
into
landscape
It
highlights
language
instruction,
while
acknowledging
be
addressed.
can
guide
educators,
policymakers,
researchers
making
informed
decisions
about
integration
classrooms,
fostering
effective
inclusive
environments
digital
era
besides
require
analysis
Malaysian
classroom
context.
Languages,
Год журнала:
2023,
Номер
8(4), С. 238 - 238
Опубликована: Окт. 18, 2023
ChatGPT
is
a
state-of-the-art
generative
artificial
intelligence
(AI)
chatbot
released
by
OpenAI
in
2022.
It
simulates
human
conversation
and
has
the
capability
to
generate
different
texts
at
various
levels
of
sophistication
near
real
time
depending
upon
user’s
skill
creating
prompts.
While
concerns
have
been
raised
about
academic
dishonesty
cheating
among
students,
significant
potential
for
education,
particularly
field
language
learning.
This
research
explores
supporting
empowering
Chinese
learners
(CLLs)
whose
first
English
enhance
their
writing
skills,
mainly
focusing
on
question:
Is
there
functional
relation
between
from
low‐income
families
using
after
school
twice
week
improvements
writing?
Four
participants
with
varying
proficiency
were
recruited,
data
analyzed
an
ABA
design.
Over
three
weeks,
they
utilized
approximately
20
min
each
school.
The
students’
scores,
samples,
learning
reflections
used
triangulate
data’s
trustworthiness.
findings
indicate
that
(1)
participant
made
noticeable
improvement
scores
during
intervention
reversal
phases;
(2)
played
crucial
role
correcting
errors
facilitating
development
complete
sentence
structures;
(3)
students
expressed
sense
empowerment
through
interactions
ChatGPT.
These
highlight
shows
promise
as
supportive
tool
CLLs
low-income
families,
reducing
educational
inequality
promoting
equitable
access
opportunities.
International Journal of Human-Computer Interaction,
Год журнала:
2024,
Номер
unknown, С. 1 - 22
Опубликована: Июнь 7, 2024
Artificial
intelligence
generates
vibrant
characters,
encompassing
teachers,
peer
students,
and
advisors
within
diverse
educational
media.
However,
the
impact
of
perceived
embodiment
such
characters
in
language
learning
videos
on
students'
technology
acceptance
adoption
is
unclear.
Integrating
structural
equation
modeling
into
thematic
analysis,
this
study
analyzes
1042
valid
responses
from
higher
education
students
to
bridge
research
gap.
Our
reveals
that
four
subdimensions
(human-likeness,
credibility,
facilitation,
engagement)
significantly
positively
predict
higher-education
ease
use
usefulness
artificial
intelligence-generated
virtual
teachers
videos.
Notably,
an
exception
arises,
as
human-likeness
does
not
our
context.
Students'
systemic
interactivity
process
emerge
pivotal
mediators.
The
qualitative
analysis
identifies
concerns
about
classroom
administration,
developmental
support,
technical
issues,
deprived
interpersonal
collaboration,
liberal
attainment
cultivation
with
teacher
presence.
This
can
illuminate
designs
applications
education.
Heliyon,
Год журнала:
2024,
Номер
10(10), С. e31053 - e31053
Опубликована: Май 1, 2024
Integrating
Artificial
Intelligence
(AI)
applications
into
language
learning
and
teaching
is
currently
a
growing
trend
in
higher
education.
Literature
reviews
have
demonstrated
the
effectiveness
of
AI
improving
English
as
foreign
(EFL)
second
(ESL)
learners'
receptive
productive
skills,
vocabulary
knowledge,
intercultural
competencies.
However,
systematic
investigating
usefulness
technologies
education
to
enhance
EFL
affective
factors
are
scarce.
This
study
review
that
investigates
integrating
motivation,
engagement,
attitude,
reduce
their
anxiety.
Articles
from
reputable
journal
databases
such
IEEE,
Wiley,
Web
Science,
Sage,
ProQuest,
Springer,
Science
Direct
were
screened
by
examining
titles
abstracts,
irrelevant
articles
excluded
search.
Of
64
analyzed
only
21
published
between
2017
2023
determined
be
relevant
research
topic.
The
findings
suggest
implementation
contexts
its
early
stages,
further
required
establish
impact
AI-integrated
classes
on
factors.
also
identifies
gaps
literature
recommends
avenues
for
future
this
novel
area.
Artificial intelligence,
Год журнала:
2024,
Номер
unknown
Опубликована: Апрель 3, 2024
This
conceptual
chapter
discusses
how
requirements
for
teacher
educator
professionalism
may
be
impacted
by
the
integration
of
Artificial
Intelligence
(AI)
in
education.
With
aim
to
continuously
facilitate
high-quality
education,
education
institutions
must
evolve
alignment
with
rapidly
changing
landscape
AI
and
respective
shifting
educational
needs.
Amidst
this
evolution,
we
argue
that
profound
Literacy
AI-related
ethical
knowledge
constitute
two
additional
inextricably
intertwined
facets
essential
an
effective
into
teaching
practices
–
thus
crucial
high
quality
The
paper
explores
avenues
through
which
these
professional
competence
can
fostered
on
micro,
meso
macro
levels
institutional
By
consolidating
specific
a
framework
age
AI,
highlight
necessity
continuous
adaptation
institutions,
ongoing
multidisciplinary
collaboration,
provision
periodic
development
educators.
Finally,
presents
concrete
practical
example
future
research
directions
contribute
advancement
era.
The
integration
of
artificial
intelligence
(AI)
in
language
teaching
has
emerged
as
a
transformative
approach,
particularly
the
realms
English
Second
Language
(ESL)
and
Chinese
Foreign
(CFL).
This
article
explores
potential
AI
chatbots
effective
tools
for
enhancing
acquisition.
By
examining
current
landscape
education,
we
identify
unique
benefits
that
bring
to
learning
process,
including
personalized
interaction,
immediate
feedback,
continuous
engagement.
delves
into
design
implementation
chatbot
systems
tailored
ESL
CFL
contexts,
highlighting
their
role
vocabulary
development,
grammar
practice,
conversational
skills.
Furthermore,
it
addresses
challenges
limitations
using
teaching,
proposing
strategies
overcoming
these
obstacles.
Through
case
studies
empirical
data,
demonstrates
how
can
be
harnessed
create
dynamic
interactive
environment
caters
diverse
needs
learners.
Ultimately,
this
work
advocates
thoughtful
complement
traditional
methods,
thereby
paving
way
more
accessible
education
IEEE Transactions on Learning Technologies,
Год журнала:
2024,
Номер
17, С. 1762 - 1776
Опубликована: Янв. 1, 2024
Reading
comprehension
is
a
widely
adopted
method
for
learning
English,
involving
reading
articles
and
answering
related
questions.
However,
the
training
typically
focuses
on
skill
level
required
standardized
stage,
without
considering
impact
of
individual
differences
in
linguistic
competence.
This
paper
presents
personalized
support
system
comprehension,
named
ChatPRCS,
based
Zone
Proximal
Development
(ZPD)
theory.
It
leverages
advanced
capabilities
large
language
models
(LLMs),
exemplified
by
ChatGPT
(Chat
Generative
Pre-trained
Transformer).
ChatPRCS
employs
methods
including
prediction,
question
generation,
automatic
evaluation,
to
enhance
instruction.
Firstly,
ZPD-based
algorithm
developed
predict
students'
skills.
analyzes
historical
data
generate
questions
with
appropriate
difficulty.
Second,
series
prompt
patterns
proposed
address
two
key
aspects
objectives:
automated
evaluation.
These
further
improve
quality
generated
Finally,
integrating
prediction
patterns,
validated
through
experiments.
Empirical
results
demonstrate
that
it
provides
learners
high-quality
are
broadly
aligned
expert-crafted
at
statistical
level.
Furthermore,
this
study
investigates
effect
achievement,
motivation
cognitive
load,
providing
evidence
its
effectiveness
instructing
English
comprehension.
Journal of Educational Computing Research,
Год журнала:
2024,
Номер
unknown
Опубликована: Авг. 31, 2024
This
study
investigates
the
impact
of
AI-assisted
language
learning
(AIAL)
strategies
on
cognitive
load
and
outcomes
in
context
acquisition.
Specifically,
explores
three
distinct
AIAL
strategies:
personalized
feedback
adaptive
learning,
interactive
exercises
with
speech
recognition,
intelligent
tutoring
data-driven
insights.
The
research
employs
a
pretest-posttest
random
assignment
experimental
design,
utilizing
groups
control
group,
total
484
EFL
students
specializing
teaching
English
as
foreign
participating
study.
Data
collection
involves
pre-
post-tests,
questionnaires,
interviews
to
assess
influence
outcomes.
Cognitive
is
measured
using
Load
Scale,
while
assessments
evaluate
efficacy
interventions
across
various
skills.
These
results
contribute
existing
body
by
offering
empirical
evidence
for
effectiveness
specific
optimizing
experiences.
implications
this
extend
educators,
researchers,
developers
field
AIAL,
emphasizing
potential
enhance
acquisition
processes
inform
instructional
design
practices.
