International Journal of Human-Computer Interaction,
Journal Year:
2024,
Volume and Issue:
unknown, P. 1 - 14
Published: Dec. 4, 2024
Generative
Artificial
Intelligence
(GAI)
holds
significant
potential
to
enhance
pre-service
teacher
professional
development.
However,
research
has
primarily
focused
on
initial
acceptance,
neglecting
post-acceptance
behaviours,
particularly
the
factors
influencing
continued
GAI
use
among
teachers.
To
address
this
gap,
study
extends
an
Expectation-Confirmation
Model
(ECM)
include
information
quality
and
AI
self-efficacy
as
additional
determinants.
Using
partial
least
squares
structural
equation
modelling
(PLS-SEM)
approach,
we
analysed
data
from
506
Chinese
Findings
reveal
that
positively
impacts
perceived
usefulness
expectation
confirmation,
both
of
which
satisfaction.
Together
with
self-efficacy,
these
elements
emerged
key
predictors
intention
continue
using
GAI,
most
direct
factor.
Contrary
hypothesis,
personal
major
did
not
moderate
relationships.
This
contributes
a
deeper
understanding
behaviours
motivations
teachers
post-GAI
adoption,
offering
new
insights
into
sustained
development
integration
in
education.
Tourism and Hospitality,
Journal Year:
2025,
Volume and Issue:
6(1), P. 36 - 36
Published: Feb. 21, 2025
AI-controlled
chatbots
have
been
used
in
travel
services
for
some
time
and
range
from
simple
hotel
reservations
to
personalized
recommendations.
However,
the
acceptance
of
compared
human
interlocutors
has
not
yet
extensively
studied
experimentally
tourism
context.
In
this
experimental,
randomized,
vignette-based,
preregistered
2
(agent:
AI
chatbot/human
counterpart)
×
3
(situation:
positive/neutral/negative)
between-subjects
design,
we
hypothesized
that
booking
intention
is
reduced
agents
situations
where
can
only
be
made
under
more
negative
than
original
conditions.
Additionally,
an
interaction
effect
between
agent
situation,
presuming
decrease
would
less
strong
chatbots.
Structural
equation
modelling
data
indicates
support
Technology
Acceptance
Model
As
presumed,
was
lower
situation
borderline
chatbot.
The
shown
descriptively
data.
Chatbots
are
recognized
during
process
accepted
bookings
their
counterparts.
Therefore,
managers
should
design
as
human-like
possible
avoid
losing
sales
when
outsourcing
customer
contact
activities
technologies.
STEM Education,
Journal Year:
2024,
Volume and Issue:
5(1), P. 445 - 465
Published: Jan. 1, 2024
<p>We
verified
a
pre-service
teachers'
Extended
Technology
Acceptance
Model
(ETAM)
for
AI
application
use
in
education.
Partial
least
squares
structural
equation
modeling
(PLS-SEM)
examined
data
from
400
teachers
Central
Visayas,
Philippines.
Perceived
usefulness
and
attitudes,
ease
of
intention
to
apps
were
significantly
correlated.
However,
subjective
norms,
experience,
voluntariness
did
not
affect
how
valuable
was
viewed
or
intended
be
used.
Attitudes
toward
mediated
specific
correlations
use.
These
findings
improve
the
ETAM
model
highlight
significance
user-friendly
interfaces,
educational
activities
highlighting
AI's
benefits,
institutional
support
enhance
adoption
applications
Despite
its
limitations,
this
study
establishes
foundation
further
research
on
settings.</p>
Journal of Computer Information Systems,
Journal Year:
2024,
Volume and Issue:
unknown, P. 1 - 12
Published: Dec. 20, 2024
This
research
explores
the
relationship
between
social
influence,
students'
views,
behavioral
intention,
and
use
of
ChatGPT.
It
involved
a
cross-sectional
survey
from
cohort
international
students
in
Taiwan.
SmartPLS
SPSS
were
employed
to
analyze
data
test
hypothesized
model.
The
results
indicated
that
views
intentions
significantly
predicted
ChatGPT,
while
influence
did
not.
Specific
indirect
effects
revealed
intention
mediates
ChatGPT
use.
Furthermore,
also
findings
provide
theoretical
basis
for
understanding
adoption
by
students,
who
often
experience
stress
with
their
academic
tasks.
Additionally,
these
insights
are
significant
educators,
emphasizing
importance
ongoing
monitoring
Research Square (Research Square),
Journal Year:
2024,
Volume and Issue:
unknown
Published: Nov. 11, 2024
Abstract
This
study
investigates
the
factors
influencing
Mainland
Chinese
students'
satisfaction
with
AI-based
chatbots
and
their
academic
performance
in
Malaysian
universities.
By
integrating
Technology
Acceptance
Model
(TAM),
Social
Cognitive
Theory
(SCT),
Expectancy-Value
(EVT),
research
examines
roles
of
perceived
risk,
enjoyment,
trust,
emotional
value,
internet
addiction,
reuse
intention,
satisfaction,
AI
self-efficacy.
A
cross-sectional
survey
was
conducted
among
400
students
using
stratified
random
sampling.
Data
analysis
Partial
Least
Squares
Structural
Equation
Modeling
(PLS-SEM)
reveals
that
risk
negatively
influences
while
enjoyment
trust
positively
affect
intention.
Emotional
value
indirectly
enhances
through
self-efficacy
moderates
relationships
between
performance.
The
findings
contribute
to
theoretical
frameworks
by
expanding
TAM
include
trust-related
factors,
also
offering
practical
implications
for
improving
educational
tools
higher
education
settings.
Future
should
explore
additional
mediators
moderators
deepen
understanding
chatbot
adoption
its
impact
on
outcomes.
International Journal of Human-Computer Interaction,
Journal Year:
2024,
Volume and Issue:
unknown, P. 1 - 14
Published: Dec. 4, 2024
Generative
Artificial
Intelligence
(GAI)
holds
significant
potential
to
enhance
pre-service
teacher
professional
development.
However,
research
has
primarily
focused
on
initial
acceptance,
neglecting
post-acceptance
behaviours,
particularly
the
factors
influencing
continued
GAI
use
among
teachers.
To
address
this
gap,
study
extends
an
Expectation-Confirmation
Model
(ECM)
include
information
quality
and
AI
self-efficacy
as
additional
determinants.
Using
partial
least
squares
structural
equation
modelling
(PLS-SEM)
approach,
we
analysed
data
from
506
Chinese
Findings
reveal
that
positively
impacts
perceived
usefulness
expectation
confirmation,
both
of
which
satisfaction.
Together
with
self-efficacy,
these
elements
emerged
key
predictors
intention
continue
using
GAI,
most
direct
factor.
Contrary
hypothesis,
personal
major
did
not
moderate
relationships.
This
contributes
a
deeper
understanding
behaviours
motivations
teachers
post-GAI
adoption,
offering
new
insights
into
sustained
development
integration
in
education.
