Journal of Global Information Management,
Год журнала:
2024,
Номер
32(1), С. 1 - 32
Опубликована: Дек. 28, 2024
Despite
the
risks
associated
with
generative
AI
(GenAI)
chatbots,
people
increasingly
use
these
technologies,
which
may
seem
contradictory.
This
study
identified
and
explored
factors
related
to
trust,
perceived
values,
satisfaction,
sustainable
of
GenAI
chatbots.
Relying
on
IS
theories
build
a
stimulus-organism-response
model,
authors
tested
model
using
PLS-SEM
data
from
393
ChatGPT
users.
The
results
show
that
user
competence
autonomy
dramatically
increase
user's
trust
in
ChatGPT,
improves
hedonic
value
(HV),
utilitarian
(UV),
value-in-use,
task-technology
fit
(TTF),
information
accuracy,
knowledge
acquisition,
informativeness,
satisfaction.
In
addition
satisfaction
depends
HV,
UV,
TTF.
sustainability
HV
However,
privacy
concerns,
risks,
awareness
do
not
affect
consumer
trust.
There
is
complete
mediation
between
sustainability,
as
well
sustainability.
Over
the
recent
years,
technology
has
brought
huge
benefits
to
academics,
enabling
their
work
more
efficient
and
flexible.
However,
usage
also
poses
challenges
for
academics
may
lead
technostress.
This
study
aims
understand
academics'
technostress
by
examining
effects
of
information
communications
(ICT)
self-efficacy
work-home
conflict
on
techno-stressors
(techno-overload,
techno-complexity,
techno-invasion,
techno-insecurity,
techno-uncertainty)
and,
furthermore,
how
impact
psychological
well-being.
A
research
model
is
proposed
based
previous
literature.
sample
251
from
several
higher
education
institutions
in
China
was
collected
analyzed
using
structural
equation
modeling.
The
results
modelling
reveal
that:
(a)
ICT
significantly
negatively
associated
with
techno-complexity
techno-insecurity;
(b)
Work-home
a
crucial
contributor
techno-overload,
techno-invasion;
(c)
Among
five
typical
techno-stressors,
only
techno-invasion
decreases
informs
organizations
should
improve
self-efficacy,
monitor
well-being
promptly
replace
outdated
facilities,
assign
dedicated
personnel
responsible
maintenance
problem-solving.
Academics
adjust
themselves
seek
compatibility
between
family.
Systems,
Год журнала:
2025,
Номер
13(2), С. 82 - 82
Опубликована: Янв. 29, 2025
The
current
study
examines
the
psychological
factors
shaping
AI
adoption,
focusing
on
anxiety,
motivation,
and
dependency.
It
identifies
two
dimensions
of
anxiety:
anticipatory
driven
by
fears
future
disruptions,
annihilation
reflecting
existential
concerns
about
human
identity
autonomy.
We
demonstrate
a
U-shaped
relationship
between
anxiety
usage,
where
moderate
engagement
reduces
high
or
low
levels
increase
it.
Perceived
utility,
interest,
attainment
significantly
correlate
with
engagement,
while
frequent
usage
is
linked
to
dependency
but
not
anxiety.
These
findings
highlight
dual
role
in
hindering
alleviating
usage.
This
enriches
understanding
emotional
motivational
drivers
adoption
highlights
importance
balanced
implementation
strategies
foster
sustainable
effective
integration
mitigating
risks
over-reliance.
International Journal of Human-Computer Interaction,
Год журнала:
2024,
Номер
unknown, С. 1 - 16
Опубликована: Май 24, 2024
Little
is
known
about
the
dark
side
of
ChatGPT
adoption
in
higher
education
context;
current
study,
therefore,
adopts
stressor-strain-outcome
model
to
examine
how
compulsive
use
and
its
consequences,
such
as
loneliness
social
avoidance
(stressors),
lead
increased
level
psychological
distress
(strain),
which,
turn,
negatively
has
detrimental
impacts
on
student
life
satisfaction
academic
performance
(outcomes).
Moreover,
recent
study
also
aims
test
moderating
role
technostress
strain-outcome
relationship.
Drawing
sample
2709
students
collected
across
16
universities
Vietnam
using
a
stratified
random
sampling
approach,
results
reveal
positive
correlation
between
ChatGPT,
loneliness,
avoidance,
distress.
Furthermore,
mediates
relationship
use,
diminished
satisfaction,
reduced
performance.
The
shows
series
indirect
effects
through
sequential
mediation
pathways
involving
avoidance.
Noticeably,
research
reveals
that
not
only
reinforces
negative
but
weakens
effect
Based
findings
this
research,
some
practical
interventional
recommendations
are
provided.
Technology Knowledge and Learning,
Год журнала:
2025,
Номер
unknown
Опубликована: Фев. 20, 2025
Abstract
The
emergence
of
ChatGPT
and
other
AI-based
tools
has
revolutionized
the
professional
educational
world.
This
paper
aims
to
analyze
factors
that
may
lead
university
teachers
consider
adopting
in
their
work.
study
examines
how
some
relevant
Unified
Theory
Acceptance
Use
Technology
(UTAUT)
model
variables
(effort
expectancy,
facilitating
conditions,
performance
expectancy),
technology-related
anxiety
gender
influence
teachers’
intentions
use
ChatGPT.
A
questionnaire
was
developed
sent
professors
at
Spanish
public
universities,
resulting
a
sample
249
valid
responses.
results
indicate
related
student
learning
are
main
determinants
intention
by
teachers.
After
conducting
an
exploratory
analysis
segmented
gender,
it
found
men
women
possibility
through
different
variables.
For
male
teachers,
expectancy
conditions
affect
In
contrast,
female
is
influenced
technology
use,
addition
conditions.
Therefore,
these
suggest
crucial
individual
perceptions,
as
well
contextual
when
promoting
adoption
such
among
Educational
institutions
should
provide
with
skills
needed
create,
adapt
information
communication
technologies,
especially
those
based
on
generative
AI.
training
adopt
new
strategies
take
differences
into
account.
F1000Research,
Год журнала:
2025,
Номер
14, С. 258 - 258
Опубликована: Март 4, 2025
Background
The
rapid
integration
of
Artificial
Intelligence
(AI)
in
education
offers
transformative
opportunities
to
enhance
teaching
and
learning.
Among
these
innovations,
Large
Language
Models
(LLMs)
like
ChatGPT
hold
immense
potential
for
instructional
design,
personalized
learning,
administrative
efficiency.
However,
integrating
tools
into
resource-constrained
settings
such
as
Nigeria
presents
significant
challenges,
including
inadequate
infrastructure,
digital
inequities,
teacher
readiness.
Despite
the
growing
research
on
AI
adoption,
limited
studies
focus
developing
regions,
leaving
a
critical
gap
understanding
how
educators
perceive
adopt
technologies.
Methods
We
adopted
hybrid
approach,
combining
Partial
Least
Squares
Structural
Equation
Modelling
(PLS-SEM)
Neural
Networks
(ANN)
uncover
both
linear
nonlinear
dynamics
influencing
behavioral
intention
(BI)
260
Nigerian
in-service
teachers
regarding
after
participating
structured
training.
Key
predictors
examined
include
Perceived
Ease
Use
(PEU),
Usefulness
(PUC),
Attitude
Towards
(ATC),
Your
Colleagues
(YCC),
Technology
Anxiety
(TA),
Teachers’
Trust
(TTC),
Privacy
Issues
(PIU).
Results
Our
PLS-SEM
results
highlight
PUC,
TA,
YCC,
PEU,
that
order
importance,
predictors,
explaining
15.8%
variance
BI.
Complementing
these,
ANN
analysis
identified
ATC,
PUC
most
factors,
demonstrating
substantial
predictive
accuracy
with
an
RMSE
0.87.
This
suggests
while
drives
PEU
positive
attitudes
are
foundational
fostering
engagement
Conclusion
need
targeted
professional
development
initiatives
teachers’
competencies,
reduce
technology-related
anxiety,
build
trust
ChatGPT.
study
actionable
insights
policymakers
educational
stakeholders,
emphasizing
importance
inclusive
ethical
ecosystem.
aim
empower
support
AI-driven
transformation
resource-limited
environments
by
addressing
contextual
barriers.
Acta Psychologica,
Год журнала:
2024,
Номер
251, С. 104622 - 104622
Опубликована: Ноя. 1, 2024
The
limited
understanding
of
the
detrimental
repercussions
stemming
from
adoption
artificial
intelligence,
exemplified
by
ChatGPT,
on
users'
mental
health
issues
underscores
urgency
our
current
research
endeavor.
In
response
to
this
knowledge
gap,
study
employs
stimulus-organism-response
(SOR)
framework
and
implements
a
serial
mediation
model
probe
into
impacts
compulsive
ChatGPT
usage
outcomes.
This
serves
as
powerful
analytical
lens,
allowing
us
unravel
relationships
between
stimulus
(compulsive
usage),
organism
(anxiety
burnout),
(sleep
disturbance).
Using
cross-sectional
survey
design,
we
collected
data
2602
users
in
Vietnam
via
purposive
sampling
utilized
structural
equation
modeling
assess
hypothesis
model.
findings
confirm
that
directly
correlates
with
heightened
anxiety,
burnout,
sleep
disturbance.
Moreover,
indirectly
contributes
disturbance
through
anxiety
demonstrating
significant
effect.
expanded
understanding,
derived
sizable
diverse
user
base,
positions
at
forefront
unraveling
intricate
dynamics
AI
well-being.
