Future Business Journal,
Journal Year:
2024,
Volume and Issue:
10(1)
Published: Nov. 27, 2024
Abstract
The
increasing
integration
of
AI
technologies
such
as
ChatGPT
in
educational
systems
calls
for
an
in-depth
understanding
the
factors
influencing
students’
intentions
to
use
these
tools.
This
study
explores
shaping
university
by
analysing
three
key
dimensions:
task
characteristics,
technology
characteristics
and
individual
characteristics.
Using
task-technology
fit
(TTF)
framework,
research
examined
how
elements
impact
alignment
between
tasks
ChatGPT’s
capabilities,
ultimately
driving
behavioural
intentions.
A
survey
393
students
from
a
Saudi
Arabian
was
conducted,
structural
equation
modelling
applied
assess
relationships
among
variables.
Results
indicated
that
all
significantly
influenced
TTF,
which
turn
had
positive
on
ChatGPT.
highlighted
importance
achieving
strong
TTF
encourage
effective
tools
academic
settings.
implications
this
suggest
institutions
should
focus
aligning
with
learning
enhance
their
intent
tools,
thereby
improving
performance.
Furthermore,
extended
model
context
AI-powered
particularly
line
Arabia’s
Vision
2030.
is
one
first
investigate
within
unique
cultural
technological
higher
education
system.
By
integrating
framework
local
regional
factors,
provides
novel
insights
into
drivers
usage
education,
offering
guidance
policy
broad
practices.
BMC Psychology,
Journal Year:
2025,
Volume and Issue:
13(1)
Published: Jan. 4, 2025
In
recent
years,
the
adoption
of
artificial
intelligence
(AI)
has
become
increasingly
relevant
in
various
sectors,
including
higher
education.
This
study
investigates
psychosocial
factors
influencing
AI
among
Peruvian
university
students
and
uses
an
extended
UTAUT2
model
to
examine
constructs
that
may
impact
acceptance
use.
employed
a
quantitative
approach
with
survey-based
design.
A
total
482
from
public
private
universities
Peru
participated
research.
The
utilized
partial
least
squares
structural
equation
modeling
(PLS-SEM)
analyze
data
test
hypothesized
relationships
between
constructs.
findings
revealed
three
out
six
significantly
influenced
students.
Performance
expectancy
(β
=
0.274),
social
influence
0.355),
learning
self-efficacy
0.431)
were
found
have
significant
positive
effects
on
adoption.
contrast
expectations,
ethical
awareness,
perceived
playfulness,
readiness
anxiety
did
not
impacts
appropriation
this
context.
highlights
importance
practical
benefits,
context,
self-confidence
within
These
contribute
understanding
diverse
educational
settings
provide
framework
for
developing
effective
implementation
strategies
education
institutions.
results
can
guide
policymakers
creating
targeted
approaches
enhance
integration
academic
environments,
focusing
demonstrating
value
AI,
leveraging
networks,
building
students'
confidence
their
ability
learn
use
technologies.
Millennial Asia,
Journal Year:
2023,
Volume and Issue:
unknown
Published: June 18, 2023
The
rise
of
artificial
intelligence
(AI)
is
rapidly
influencing
our
education
system.
It
apparent
that
the
students
today
are
mostly
attached
with
their
smart
mobile
phones,
tablets,
laptops,
and
various
other
forms
advanced
technologies
for
quality
learning.
has
become
an
urgent
necessity
school
to
future
AI
ready.
Understanding
wide
potential
impact
AI,
India
started
initiatives
prepare
young
learners
Central
Board
Secondary
Education
in
direction
National
Policy
(2020)
introduces
two-fold
its
affiliated
curricula.
Using
a
systematic
review
technique,
present
study
attempted
explore
promise
potentiality
education,
provide
comprehensive
overview
current
status
development
trends
school,
initiatives,
planning,
strategies,
steps
taken
by
countries
regarding
integration
Finally,
brings
out
some
concluding
remarks
towards
innovative
integration.
Future Business Journal,
Journal Year:
2024,
Volume and Issue:
10(1)
Published: Nov. 27, 2024
Abstract
The
increasing
integration
of
AI
technologies
such
as
ChatGPT
in
educational
systems
calls
for
an
in-depth
understanding
the
factors
influencing
students’
intentions
to
use
these
tools.
This
study
explores
shaping
university
by
analysing
three
key
dimensions:
task
characteristics,
technology
characteristics
and
individual
characteristics.
Using
task-technology
fit
(TTF)
framework,
research
examined
how
elements
impact
alignment
between
tasks
ChatGPT’s
capabilities,
ultimately
driving
behavioural
intentions.
A
survey
393
students
from
a
Saudi
Arabian
was
conducted,
structural
equation
modelling
applied
assess
relationships
among
variables.
Results
indicated
that
all
significantly
influenced
TTF,
which
turn
had
positive
on
ChatGPT.
highlighted
importance
achieving
strong
TTF
encourage
effective
tools
academic
settings.
implications
this
suggest
institutions
should
focus
aligning
with
learning
enhance
their
intent
tools,
thereby
improving
performance.
Furthermore,
extended
model
context
AI-powered
particularly
line
Arabia’s
Vision
2030.
is
one
first
investigate
within
unique
cultural
technological
higher
education
system.
By
integrating
framework
local
regional
factors,
provides
novel
insights
into
drivers
usage
education,
offering
guidance
policy
broad
practices.
