Latent profiles of AI learning conditions among university students: Implications for educational intentions
Contemporary Educational Technology,
Год журнала:
2025,
Номер
17(2), С. ep565 - ep565
Опубликована: Янв. 30, 2025
This
investigation
aimed
to
ascertain
latent
profiles
of
university
students
predicated
on
fundamental
factors
influencing
their
intentions
acquire
knowledge
in
artificial
intelligence
(AI).
The
study
scrutinized
four
dimensions:
supportive
social
norms,
facilitating
conditions,
self-efficacy
AI
learning,
and
perceived
utility
AI.
Through
the
utilization
profile
analysis
(LPA),
endeavored
unveil
distinct
subgroups
delineated
by
unique
amalgamations
these
factors.
was
carried
out
with
a
cohort
391
from
diverse
academic
disciplines.
LPA
disclosed
five
students:
Cautious
Participants,
Enthusiastic
Advocates,
Reserved
Skeptics,
Pragmatic
Acceptors,
Disengaged
Critics.
These
categories
showed
somewhat
different
goals
learn
AI;
Advocates
highest
intention
while
Critics
lowest.
findings
enhance
growing
corpus
research
education
higher
providing
sophisticated
variation
among
about
attitudes
preparedness
Subgroups
show
that
learners
need
educational
strategies
interventions
meet
needs
attitudes.
is
changing
many
fields,
therefore
college
must
it
prepare
for
it.
advance
impact
curriculum
policy.
Язык: Английский
Students' mindset to adopt AI chatbots for effectiveness of online learning in higher education
Future Business Journal,
Год журнала:
2025,
Номер
11(1)
Опубликована: Март 10, 2025
Abstract
The
rapid
incorporation
of
Artificial
Intelligence
(AI)
technologies
into
higher
education
is
shifting
the
focus
toward
understanding
students’
perspectives
and
factors
affecting
adoption
AI
chatbots
to
maximize
their
use
in
online
virtual
educational
environments.
This
study
fills
an
important
gap
literature
by
examining
direct
mediated
relationships
key
constructs
such
as
perceived
usefulness,
ease
use,
technical
competency
chatbot
usage.
aims
investigate
mindsets
regarding
adopting
for
effectiveness
learning
education.
Data
were
collected
from
429
university
students
analyzed
using
partial
least
squares-based
structural
equation
modeling
(PLS-SEM)
technique.
results
revealed
that
usefulness
(PU),
(PEU),
tech
(TC)
have
a
significant
impact
on
capability.
Subjective
norm
(SN)
has
no
capability
significantly
influences
effectiveness.
findings
indicated
mediates
effect
PU,
PEU,
TC
chatbots;
however,
there
mediating
relationship
between
SN
Facilitating
conditions
moderate
PU
research
addresses
new
insight
within
context
education,
particularly
demonstrating
moderating
function
tech-competent
concepts.
Язык: Английский
Engineering students' perceptions and actual use of AI-based math tools for solving mathematical problems
Acta Psychologica,
Год журнала:
2025,
Номер
256, С. 105004 - 105004
Опубликована: Апрель 12, 2025
Язык: Английский
The impact of guilt on student interactions with generative AI technology
Ethics & Behavior,
Год журнала:
2025,
Номер
unknown, С. 1 - 27
Опубликована: Фев. 23, 2025
Язык: Английский
The Role of Individual Capabilities in Maximizing the Benefits for Students Using GenAI Tools in Higher Education
Behavioral Sciences,
Год журнала:
2025,
Номер
15(3), С. 328 - 328
Опубликована: Март 7, 2025
Although
the
adoption
and
benefits
of
GenAI
(Generative
Artificial
Intelligence)
tools
among
higher
education
students
have
been
widely
explored
in
existing
studies,
less
is
known
about
how
individual
capabilities
influence
use
these
tools.
Drawing
on
Information
System
Success
Model
(ISSM)
Expectation–Confirmation
(ECM),
this
study
examines
students’
capabilities,
including
critical
thinking,
self-directed
learning
ability,
AI
literacy,
impact
quality
information
obtained
from
Additionally,
it
explores
relationships
quality,
student
satisfaction,
intention
to
continue
using
education.
Survey
data
1448
users
Chinese
universities
reveal
that
with
stronger
tend
extract
higher-quality
information,
which
turn
fosters
their
satisfaction
The
findings
highlight
crucial
role
maximizing
potential
tools,
emphasizes
need
cultivate
literacy
achieve
sustainable
success
era.
Theoretically,
extends
ISSM
ECM
by
exploring
mediating
user
between
Practically,
provides
implications
for
educators
policymakers
enhance
thus
Язык: Английский
Can ChatGPT Boost Students’ Employment Confidence? A Pioneering Booster for Career Readiness
Behavioral Sciences,
Год журнала:
2025,
Номер
15(3), С. 362 - 362
Опубликована: Март 14, 2025
This
study
examines
the
impact
of
ChatGPT
on
university
students’
employment
confidence,
utilizing
comprehensive
methodologies
such
as
regression
analysis,
Inverse
Probability
Weighting
(IPW),
and
Structural
Equation
Modeling
(SEM).
The
results
indicate
that
regular
use
significantly
enhances
confidence
in
securing
employment,
with
stronger
effects
observed
among
undergraduate
students
those
social
sciences.
Additionally,
this
reveals
experience
plays
a
partial
mediating
role
effect,
underscoring
importance
user
interaction
realizing
benefits
AI
tools.
These
findings
suggest
not
only
improves
cognitive
abilities
career-related
knowledge
but
also
boosts
proactive
job-seeking
behaviors,
fostering
increased
job
market
readiness.
implications
are
far-reaching,
highlighting
how
tools
can
enhance
career
development
support,
particularly
for
at
earlier
stages
their
academic
journey.
As
technologies
continue
to
influence
education,
offers
valuable
insights
into
effectively
prepare
market,
potentially
contributing
future
research
shaping
educational
practices
ways
address
challenges.
Язык: Английский
Effects of ChatGPT-Based Human–Computer Dialogic Interaction Programming Activities on Student Engagement
Journal of Educational Computing Research,
Год журнала:
2025,
Номер
unknown
Опубликована: Апрель 14, 2025
This
study
seeks
to
deepen
the
understanding
of
direct
and
indirect
effects
human–computer
dialogic
interaction
programming
activities,
facilitated
by
ChatGPT,
on
student
engagement.
Data
were
collected
from
109
Chinese
high
school
students
who
engaged
in
tasks
using
either
ChatGPT-driven
or
traditional
pair
programming.
A
quasi-experimental
analysis
revealed
that
ChatGPT-based
activities
remarkably
boost
engagement,
outperforming
behavioral,
cognitive,
emotional
dimensions.
Results
demonstrated
such
help
minimize
off-task
behaviors,
promote
higher-order
cognitive
skills,
foster
greater
interest
Additionally,
these
interactions
enhance
students’
self-efficacy
reduce
learning
anxiety.
The
findings
underscore
potential
education.
offers
practical
recommendations
engagement
learning.
Язык: Английский
Modeling Teachers’ Acceptance of Generative Artificial Intelligence Use in Higher Education: The Role of AI Literacy, Intelligent TPACK, and Perceived Trust
Education Sciences,
Год журнала:
2024,
Номер
14(11), С. 1209 - 1209
Опубликована: Ноя. 3, 2024
This
study
delves
into
the
factors
that
drive
teachers’
adoption
of
generative
artificial
intelligence
(GenAI)
technologies
in
higher
education.
Anchored
by
technology
acceptance
model
(TAM),
research
expands
its
inquiry
integrating
constructs
intelligent
technological
pedagogical
content
knowledge
(TPACK),
AI
literacy,
and
perceived
trust.
Data
were
gathered
from
a
sample
237
university
teachers
through
structured
questionnaire.
The
employed
structural
equation
modeling
(SEM)
to
determine
relationships
among
constructs.
results
revealed
both
literacy
ease
most
influential
affecting
GenAI.
Notably,
TPACK
trust
found
be
pivotal
mediators
this
relationship.
findings
underscore
importance
fostering
adapting
frameworks
better
equip
educators
age
AI.
Furthermore,
there
is
clear
need
for
targeted
professional
development
initiatives
focusing
on
practical
training
enhances
literacy.
These
programs
should
provide
hands-on
experience
with
GenAI
tools,
boosting
educators’
confidence
ability
integrate
them
their
teaching
practices.
Язык: Английский
The Impact of AI-Suggested Content and Resources on Student Curiosity and Explorative Learning
Journal of Artificial Intelligence Machine Learning and Neural Network,
Год журнала:
2024,
Номер
51, С. 1 - 13
Опубликована: Дек. 3, 2024
As
educational
landscapes
evolve,
the
potential
of
AI
to
fuel
curiosity
and
explorative
learning
among
students
has
sparked
growing
interest.
This
study
explores
how
AI-suggested
content,
student
motivation,
Complexity
content
drive
proactive
behaviours
in
students.
Through
exploratory
confirmatory
analysis
using
SPSS
AMOS,
it
is
revealed
that
resources
(ACR)
motivation
level
(SML)
significantly
elevate
engagement.
In
contrast,
certain
combinations,
such
as
high
may
unexpectedly
hinder
exploration.
Notably,
demographic
factors
like
age,
gender,
education
showed
no
significant
impact,
underscoring
universal
personalised
learning.
These
findings
highlight
value
tailoring
fostering
cultivate
curiosity,
offering
a
roadmap
for
educators
developers
aiming
unlock
full
education.
Язык: Английский