Multidisciplinary Science Journal,
Год журнала:
2025,
Номер
7(8), С. 2025416 - 2025416
Опубликована: Фев. 9, 2025
The
rapid
advancement
of
artificial
intelligence
(AI)
has
significantly
transformed
various
industries,
including
online
advertising
on
social
networks.
Businesses
are
increasingly
investing
in
and
developing
AI-driven
strategies.
advent
Artificial
Intelligence
been
recognized
as
a
revolutionary
force
across
industries
fields,
with
networks
regarded
prominent
trend
that
is
actively
being
developed
invested
by
businesses.
This
study
was
conducted
to
identify
the
factors
influencing
intention
utilize
AI
media
platforms.
Emphasis
placed
analyzing
impact
Personalization,
Informativeness,
Entertainment,
Competitiveness,
Performance,
Advertising
Value,
these
were
examined
for
their
role
shaping
adopt
A
comprehensive
understanding
provided,
offering
insights
into
influence
decision-making
processes
related
intentions.
Such
expected
assist
businesses
optimizing
strategies
enhancing
effectiveness
reaching
target
customers.
used
quantitative
research
methods
through
questionnaire
survey
350
small
medium
enterprises
qualitative
focus
group
discussion,
text
analysis
rational
an
effort
help
understand
context
depth
problem.
In
addition,
Smart
PLS
techniques
structural
equation
modeling,
along
descriptive
statistics
summarize
data.
Measurement
models
analyze
interpret
relationships
between
variables.
findings
indicated
exert
significant
use
advertising,
Entertainment
identified
most
impactful
factor
positively
affecting
consumer
acceptance.
results
offer
valuable
guidance
businesses,
enabling
them
leverage
effectively,
optimize
costs,
enhance
competitiveness,
attract
larger
base
loyal
potential
Journal of Computer Assisted Learning,
Год журнала:
2025,
Номер
41(1)
Опубликована: Янв. 15, 2025
ABSTRACT
Background
ChatGPT,
as
a
cutting‐edge
technology
in
education,
is
set
to
significantly
transform
the
educational
landscape,
raising
concerns
about
technological
ethics
and
equity.
Existing
studies
have
not
fully
explored
learners'
intentions
adopt
artificial
intelligence
generated
content
(AIGC)
technology,
highlighting
need
for
deeper
insights
into
factors
influencing
adoption.
Objectives
This
study
aims
investigate
higher
education
adoption
towards
AIGC
with
focus
on
understanding
underlying
reasons
future
prospects
its
application
education.
Methods
The
research
divided
two
phases.
First,
an
exploratory
analysis
involving
practical
activities
interviews
develops
action
decision
framework
Second,
confirmatory
using
fuzzy‐set
qualitative
comparative
233
valid
questionnaires
identifies
six
configurations
associated
high
intentions,
emphasising
roles
of
AI
literacy
perceived
behavioural
control.
Results
Conclusions
reveals
key
adoption,
including
importance
It
provides
actionable
educators
learners
prepare
effectively
integrate
ensuring
equitable
adaptive
practices.
Journal of Systems and Information Technology,
Год журнала:
2025,
Номер
unknown
Опубликована: Янв. 14, 2025
Purpose
The
purpose
of
this
study
is
to
investigate
the
primary
determinants
influencing
acceptance
generative
artificial
intelligence
(GAI)
adoption
within
Blockchain-enabled
environments.
Further
research
will
examine
impact
GAI
on
supply
chain
efficiency
(SCE)
through
enhancement
Blockchain.
Design/methodology/approach
Drawing
innovation
diffusion
theory
(IDT),
used
partial
least
square
structural
equation
modelling
(PLS-SEM)
look
into
hypotheses.
data
were
gathered
via
online
questionnaires
from
employers
Chinese
enterprises
that
have
already
integrated
Findings
findings
demonstrate
relative
advantages
(RAs),
compatibility,
trialability
and
observability
a
significant
positive
effect
adoption,
while
complexity
harms
adoption.
Above
all,
has
significantly
enhanced
Blockchain,
thus
effectively
improving
SCE.
Practical
implications
outcomes
furnish
organizations
with
valuable
insights
proficiently
integrate
Blockchain
capability,
optimize
management
bolster
market
competitiveness.
Also,
help
accelerate
successful
integration
business
processes
attain
Sustainability
Development
Goals
9,
industrial
growth
diversification.
Originality/value
To
extent
author’s
knowledge,
current
status
remains
largely
exploratory,
there
limited
empirical
evidence
integrating
capability
GAI.
This
bridges
knowledge
gap
by
fully
revealing
optimal
these
two
transformative
technologies
leverage
their
potential
in
management.
E-learning
has
revolutionized
the
educational
landscape,
changing
how
knowledge
is
imparted
to
students
and
enhancing
learning
process.
Despite
growing
popularity
of
e-learning
worldwide,
a
lingering
question
remains
regarding
behavioral
intentions
Physical
Education
toward
its
use.
This
study
endeavors
address
this
issue
by
utilizing
structural
equation
model
(SEM)
explore
factors
mechanisms
influencing
adoption
among
students.
The
collected
data
from
504
enrolled
in
system
at
universities
China.
results
reveal
that
attitudes
(β
=
.37),
subjective
norms
.29),
facilitating
conditions
.45)
significantly
influence
students’
intention
use
e-learning.
Interestingly,
expected
association
between
perceived
usefulness
−.11)
was
nonsignificant.
These
findings
highlight
importance
improving
technical
organizational
support,
as
well
necessity
for
further
empirical
research
on
instructional
strategies
promote
effective
Humanities and Social Sciences Communications,
Год журнала:
2024,
Номер
11(1)
Опубликована: Авг. 31, 2024
The
rapid
expansion
of
information
technology
and
the
intensification
population
aging
are
two
prominent
features
contemporary
societal
development.
Investigating
older
adults'
acceptance
use
is
key
to
facilitating
their
integration
into
an
information-driven
society.
Given
this
context,
adults
has
emerged
as
a
prioritized
research
topic,
attracting
widespread
attention
in
academic
community.
However,
existing
remains
fragmented
lacks
systematic
framework.
To
address
gap,
we
employed
bibliometric
methods,
utilizing
Web
Science
Core
Collection
conduct
comprehensive
review
literature
on
from
2013
2023.
Utilizing
VOSviewer
CiteSpace
for
data
assessment
visualization,
created
knowledge
mappings
acceptance.
Our
study
multidimensional
methods
such
co-occurrence
analysis,
clustering,
burst
analysis
to:
(1)
reveal
dynamics,
journals,
domains
field;
(2)
identify
leading
countries,
collaborative
networks,
core
institutions
authors;
(3)
recognize
foundational
system
centered
theoretical
model
deepening,
emerging
applications,
evaluation,
uncovering
seminal
observing
shift
early
influential
factor
analyses
empirical
studies
focusing
individual
factors
technologies;
(4)
moreover,
current
hotspots
primarily
areas
influencing
adoption,
human-robot
interaction
experiences,
mobile
health
management,
aging-in-place
technology,
highlighting
evolutionary
context
quality
distribution
themes.
Finally,
recommend
that
future
should
deeply
explore
improvements
models,
long-term
usage,
user
experience
evaluation.
Overall,
presents
clear
framework
field
acceptance,
providing
important
reference
exploration
innovative
applications.
Journal of Computer Assisted Learning,
Год журнала:
2024,
Номер
41(1)
Опубликована: Дек. 19, 2024
ABSTRACT
Background
Generative
artificial
intelligence
(AI)
represents
a
significant
technological
leap,
with
platforms
like
OpenAI's
ChatGPT
and
Baidu's
Ernie
Bot
at
the
forefront
of
innovation.
This
technology
has
seen
widespread
adoption
across
various
sectors
society
is
anticipated
to
revolutionise
educational
landscape,
especially
in
domain
tertiary
education.
However,
there
gap
understanding
factors
influencing
university
students'
behavioural
intention
use
generative
AI,
leading
hesitation
its
adoption.
Objectives
The
primary
objective
this
study
was
investigate
that
influence
engage
utilise
AI.
sought
delve
into
fundamental
reasons
obstacles
students
encounter
when
contemplating
for
their
academic
endeavours.
Methods
used
quantitative
research
design,
utilising
revised
version
Unified
Theory
Acceptance
Use
Technology
2
(UTAUT2)
model.
Data
were
collected
from
sample
380
Changsha,
capital
city
Hunan
China.
Partial
least
squares
structural
equation
modelling
(PLS‐SEM)
analyse
relationships
between
variables
model,
which
included
performance
expectancy
(PE),
effort
(EE),
social
(SI),
facilitating
conditions
(FC),
learning
value,
habit
intention.
Results
analysis
revealed
PE
EE
have
direct
impact
on
value.
Additionally,
SI
FC
found
directly
affect
formation
habit.
Among
these
factors,
value
emerged
as
most
potent
predictor
Habit
also
demonstrated
significant,
albeit
smaller,
effect
Conclusions
study's
findings
underscore
importance
driving
AI
among
students.
Efforts
enhance
could
significantly
increase
uptake
higher
Furthermore,
role
habit,
while
less
pronounced,
suggests
consistent
exposure
can
foster
greater
inclination
towards
These
insights
provide
foundation
targeted
interventions
aimed
improving
integration
application
within
settings.
Stakeholders,
including
educators,
policymakers
designers
leverage
create
an
environment
conducive
effective
International Journal of Applied Linguistics,
Год журнала:
2025,
Номер
unknown
Опубликована: Янв. 7, 2025
ABSTRACT
In
the
context
of
globalization,
Tibetan
students’
second
language
(L2)
communication
skills
are
crucial
to
allow
effective
intercultural
and
personal
development.
To
better
understand
promote
willingness
university
students
communicate
in
their
L2,
this
study
adapts
theory
planned
behavior
(TPB)
by
introducing
concept
“language
growth
mindset
(LGM)”
replace
original
model's
“Attitude
(ATT)”
component
conjunction
with
L2
motivational
self
system
(L2MSS).
This
mixed
methods
utilized
structural
equation
modelling
(SEM)
for
quantitative
analysis
NVivo
open
coding
qualitative
interview
data.
The
participants
were
409
from
four
universities
China.
Data
collected
using
questionnaires
in‐depth
interviews.
SEM
model
validated
applicability
TPB
L2MSS
explaining
an
(L2WTC).
findings
indicate
that
(a)
a
comprehensive
based
on
can
explain
52.9%
variance
L2WTC;
(b)
LGM,
Ideal
Self
(IS),
Ought‐to
(OS)
positively
influence
(c)
perceived
behavioral
control
(PBC)
impacts
while
subjective
norms
(SN)
do
not
affect
LGM;
(d)
LGM
does
mediate
relationship
between
SN
OS.
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.
F1000Research,
Год журнала:
2025,
Номер
13, С. 812 - 812
Опубликована: Янв. 20, 2025
Purpose
This
study
evaluated
the
effectiveness
of
integrating
Chinese
checkers
into
Comparative
Politics
courses
across
Asia-Pacific
universities
during
2021-2022,
examining
its
impact
on
students’
strategic
thinking,
negotiation
skills,
and
academic
performance.
Methods
The
research
employed
paired
independent-samples
t-tests
to
assess
outcomes
among
93
students
who
played
versus
86
control
participants.
Assessment
metrics
included
thinking
capabilities
overall
course
Findings
Students
participated
in
demonstrated
statistically
significant
improvements
(p
<
0.05)
achieved
higher
scores
(M
=
4.38,
SD
0.18)
compared
group
3.87,
0.13).
Significance
establishes
as
an
effective
pedagogical
tool
for
developing
undergraduate
political
science
education.
findings
support
incorporating
game-based
learning
approaches
enhance
critical
skills
understanding
politics.