Interactive Learning Environments,
Journal Year:
2024,
Volume and Issue:
unknown, P. 1 - 25
Published: Dec. 17, 2024
In
actual
blended
learning
environments,
the
quality
and
depth
of
peer
interaction
still
face
many
challenges.
The
current
research
on
factors
influencing
is
not
comprehensive,
particularly
lacking
systematic
analysis
how
to
improve
level
interaction.
Based
Social
Learning
Theory
Community
Inquiry
(CoI)
framework,
this
study
constructs
a
hypothetical
model
explore
key
affecting
university
students'
Structural
Equation
Modeling
(SEM)
was
used
analyze
300
questionnaire
samples,
indicating
that
motivation,
personality
traits,
diverse
tasks,
grouping
methods,
teacher
support
significantly
influence
effectiveness.
Complementary
Artificial
Neural
Networks
shows
methods
most
important
factor
in
predicting
interaction,
followed
by
environment,
motivation.
these
findings,
proposes
several
strategies
enhance
levels,
including
self-paced
based
micro-videos,
collaborative
heterogeneous
grouping,
teacher-student
assistance
Blended
Environment,
review
self-reflection.
This
provides
valuable
insights
into
optimizing
learning,
contributing
development
more
effective
educational
practices.
Research Square (Research Square),
Journal Year:
2024,
Volume and Issue:
unknown
Published: May 28, 2024
Abstract
This
study
investigates
the
performance
of
generative
artificial
intelligence
(AI)
in
evaluating
acceptance
AI
technologies
within
higher
education
guidelines,
reflecting
on
implications
for
educational
policy
and
practice.
Drawing
a
dataset
guidelines
from
top-ranked
universities,
we
compared
evaluations
with
human
evaluations,
focusing
acceptance,
expectancy,
facilitating
conditions,
perceived
risk.
Our
revealed
strong
positive
correlation
between
ChatGPT-rated
human-rated
AI,
suggesting
that
can
accurately
reflect
judgment
this
context.
Further,
found
associations
expectancy
while
negative
These
results
validate
evaluation,
which
also
extends
application
Technology
Acceptance
Model
Unified
Theory
Use
framework
individual
to
institutional
perspectives.
Participatory Educational Research,
Journal Year:
2024,
Volume and Issue:
11(H. Ferhan Odabaşı Gift Issue), P. 151 - 167
Published: Dec. 30, 2024
Although
artificial
intelligence
is
present
in
many
areas
of
life,
making
life
easier,
it
also
necessitates
the
updating
certain
professions
or
curriculum
university
departments.
In
this
regard,
considered
important
to
determine
how
AI-based
translation
tools
will
specifically
affect
studies
and
gather
opinions
students
faculty
members
these
This
study
aims
examine
Translation
Interpreting
Department
on
use
studies.
The
research
was
conducted
with
7
members,
1
expert,
15
final-year
at
a
foundation
university.
Data
were
collected
through
semi-structured
interview
forms
evaluated
using
content
analysis.
Students
expressed
concerns
that
reduce
job
opportunities
profession.
They
believe
AI
weakens
memory
leads
laziness.
Some
have
noted
undermines
teacher-student
relationship.
Faculty
other
hand,
think
redefine
translator’s
roles
profession
provide
significant
support.
Whilst
advocate
for
inclusion
post-graduate
professional
rather
than
undergraduate
education
support
extracurricular
activities,
underline
need
increase
integration
into
education,
in-service
training,
expedite
development
These
results
highlight
different
perspectives
field
suggest
recommendations
could
contribute
This
study
investigates
the
performance
of
generative
artificial
intelligence
(AI)
in
evaluating
acceptance
AI
technologies
within
higher
education
guidelines,
reflecting
on
implications
for
educational
policy
and
practice.
Drawing
a
dataset
guidelines
from
top-ranked
universities,
we
compared
evaluations
with
human
evaluations,
focusing
acceptance,
expectancy,
facilitating
conditions,
perceived
risk.
Our
revealed
strong
positive
correlation
between
ChatGPT-rated
human-rated
AI,
suggesting
that
can
accurately
reflect
judgment
this
context.
Further,
found
associations
expectancy
while
negative
These
results
validate
evaluation,
which
also
extends
application
Technology
Acceptance
Model
Unified
Theory
Use
framework
individual
to
institutional
perspectives.
Studies in Media and Communication,
Journal Year:
2024,
Volume and Issue:
12(4), P. 10 - 10
Published: Aug. 23, 2024
This
research
delves
into
the
transformative
impact
of
Artificial
Intelligence
(AI)
on
marketing
communication
within
Indonesian
higher
education
sector.
By
adopting
advanced
AI
technologies
like
machine
learning
algorithms,
universities
aim
to
enhance
customer
engagement,
understand
student
behavior,
and
personalize
strategies.
The
study
combines
quantitative
data,
showcasing
extent
adoption
its
outcomes,
with
qualitative
insights
highlight
effectiveness
in
improving
key
metrics.
Post-AI
integration,
there
were
significant
increases
inquiries,
application
rates,
enrollment
numbers,
underscoring
tangible
benefits
AI-driven
findings
emphasize
strategic
shift
towards
data-driven
decision-making
personalized
positioning
at
forefront
innovative
practices.
contributes
valuable
for
academia,
industry
practitioners,
policymakers
looking
leverage
initiatives
education.
Computers in the Schools,
Journal Year:
2024,
Volume and Issue:
unknown, P. 1 - 21
Published: Dec. 14, 2024
Artificial
intelligence
(AI)
offers
numerous
benefits
to
the
field
of
language
education,
making
it
crucial
understand
factors
influencing
teachers'
adoption
these
technologies.
This
study
investigates
determinants
AI
chatbots
in
educational
settings.
Drawing
on
Unified
Theory
Acceptance
and
Use
Technology
(UTAUT)
Technological
Pedagogical
Content
Knowledge
(TPACK)
framework,
a
comprehensive
model
among
teachers
is
proposed
tested.
Data
were
collected
from
276
Vietnam
through
an
online
survey.
Partial
Least
Square-Structural
Equation
Modeling
(PLS-SEM)
was
employed
analyze
data.
Results
indicate
that
intent
significantly
predicts
integration,
while
performance
expectancy,
effort
self-efficacy
are
key
intent.
AI-TPACK
emerges
as
factor,
strongly
self-efficacy,
expectancy.
Facilitation
found
be
significant
predictor
AI-TPACK.
These
findings
enhance
theoretical
framework
education
provide
valuable
insights
for
fostering
effective
integration
teachers.
The TQM Journal,
Journal Year:
2024,
Volume and Issue:
unknown
Published: Dec. 20, 2024
Purpose
The
purpose
of
this
research
is
to
examine
the
potential
impact
technologies
on
enhancing
efficiency
and
effectiveness
supply
chain
performance
inside
healthcare
organizations,
with
a
particular
focus
cost
quality
improvement.
Design/methodology/approach
present
investigation
employs
survey
method
hypothesis
objective.
A
total
630
surveys
were
collected
using
an
online
platform,
all
which
deemed
be
valid.
gathered
data
analyzed
SPSS
version
20.0
Smart-PLS
3.0
software.
Findings
finding
represents
holistic
into
Industry
4.0
technologies,
management
practices,
organizational
essential
for
industry’s
evolution.
Embracing
these
elements
collectively
has
redefine
delivery,
improve
patient
outcomes
drive
operational
excellence.
results
seek
shed
light
broader
implications
care,
optimizing
resources
improving
within
evolving
landscape
4.0-driven
environments.
Research
limitations/implications
Exploration
incorporation
domain
augment
efficacy,
care
administration.
Examination
repercussions
procedures
in
environments
imparts
understanding
enhancement
service
outcomes.
Practical
Implementing
encompass
Internet
Things
devices
analytics
driven
by
artificial
intelligence,
sector
streamline
procedures,
minimize
errors
optimize
resource
distribution.
This,
turn,
may
result
heightened
precision
diagnostic
refined
treatment
strategies
overall
provided
patients.
Social
There
exist
certain
constraints
inherent
study.
In
initial
instance,
from
moderately
sizable
medical
institutions
situated
India.
As
was
conducted
India,
it
possible
other
countries
order
identify
disparities
social
conditions.
Future
should
consider,
cross-cultural
longitudinal
studies
performance.
Originality/value
investigation,
writer
presents
innovative
that
assist
industry
identifying
most
crucial
component
relevant
personnel.
notable
relationship
between
healthcare,
formerly
central
focus.
With
specific
emphasis
big
data,
things,
cloud
computing,
blockchain,
intelligence
3D
printing,
authors
current
study
have
showcased
connection
practice
employing
technologies.
This
paves
way
place
Interactive Learning Environments,
Journal Year:
2024,
Volume and Issue:
unknown, P. 1 - 25
Published: Dec. 17, 2024
In
actual
blended
learning
environments,
the
quality
and
depth
of
peer
interaction
still
face
many
challenges.
The
current
research
on
factors
influencing
is
not
comprehensive,
particularly
lacking
systematic
analysis
how
to
improve
level
interaction.
Based
Social
Learning
Theory
Community
Inquiry
(CoI)
framework,
this
study
constructs
a
hypothetical
model
explore
key
affecting
university
students'
Structural
Equation
Modeling
(SEM)
was
used
analyze
300
questionnaire
samples,
indicating
that
motivation,
personality
traits,
diverse
tasks,
grouping
methods,
teacher
support
significantly
influence
effectiveness.
Complementary
Artificial
Neural
Networks
shows
methods
most
important
factor
in
predicting
interaction,
followed
by
environment,
motivation.
these
findings,
proposes
several
strategies
enhance
levels,
including
self-paced
based
micro-videos,
collaborative
heterogeneous
grouping,
teacher-student
assistance
Blended
Environment,
review
self-reflection.
This
provides
valuable
insights
into
optimizing
learning,
contributing
development
more
effective
educational
practices.
