Fırat Üniversitesi Sosyal Bilimler Dergisi,
Год журнала:
2025,
Номер
35(1), С. 1 - 24
Опубликована: Янв. 24, 2025
Artificial
intelligence
is
not
a
new
concept.
However,
it
has
reached
an
important
point
with
technological
development.
Today,
there
are
many
software
developed
using
artificial
and
various
application
areas
where
they
used.
Generative
intelligence,
one
of
these
areas,
technology
in
machine
learning
aiming
to
generate
content
by
training
on
large
data
sets.
used
fields
such
as
health,
business,
finance,
e-commerce,
academic
studies,
R&D.
This
study
evaluates
the
use
generative
applications
field.
In
this
context,
differences
similarities
between
texts
generated
ChatGPT,
Claude
Sonet,
Google
Gemini
prepared
human
were
analyzed
regarding
subject
integrity,
language,
ethics,
plagiarism
rate.
Descriptive
analysis,
qualitative
methods,
was
study.
As
result,
concluded
that
similar
integrity
content,
rates
vary
according
language.
Advances in educational technologies and instructional design book series,
Год журнала:
2024,
Номер
unknown, С. 231 - 262
Опубликована: Авг. 27, 2024
This
chapter
explores
the
transformative
role
of
Generative
Artificial
Intelligence
(Generative
AI)
in
reshaping
development
higher
education
curricula.
AI,
as
exemplified
by
advanced
models
like
GPT-3,
employs
sophisticated
algorithms
to
generate
scientifically
relevant
content,
surpassing
traditional
norms
teaching
and
learning.
The
overview
delves
into
fundamental
principles
emphasizing
significance
generative
such
Adversarial
Networks
(GANs)
technical
intricacies
involved
their
training.
Essentially,
discourse
on
AI
curriculum
underscores
its
disruptive
potential
education.
By
providing
personalized
adaptable
pathways
for
growth,
addresses
diverse
needs
students,
fostering
engagement
comprehension.
It
also
overcoming
limitations
education,
facilitating
creation
virtual
laboratories
simulations
that
enhance
hands-on
Background:
The
impact
of
generative
artificial
intelligence-based
Chatbots
on
medical
education,
particularly
in
Southeast
Asia,
is
understudied
regarding
healthcare
students'
perceptions
its
academic
utility.
Sociodemographic
profiles
and
educational
strategies
influence
prospective
practitioners'
attitudes
toward
AI
tools.
Aim
objectives:
This
study
aimed
to
assess
university
knowledge,
attitude,
practice
ChatGPT
for
purposes.
It
explored
chatbot
usage
frequency,
purposes,
satisfaction
levels,
associations
between
age,
gender,
variables.
Methodology:
Four
hundred
forty-three
undergraduate
students
at
a
Malaysian
tertiary
institute
participated,
revealing
varying
awareness
levels
ChatGPT's
Despite
concerns
about
accuracy,
ethics,
dependency,
participants
generally
held
positive
academics.
Results:
Multiple
logistic
regression
highlighted
demographics,
use.
MBBS
were
significantly
more
likely
use
academics
than
BDS
FIS
students.
Final-year
exhibited
the
highest
likelihood
Higher
knowledge
correlated
with
increased
usage.
Most
users
(45.8%)
employed
aid
specific
assignment
sections
while
completing
most
work
independently.
Some
did
not
it
(41.1%),
others
heavily
relied
(9.3%).
Users
also
various
from
generating
questions
understanding
concepts.
Thematic
analysis
responses
showed
data
plagiarism,
ethical
issues,
dependency
tasks.
Conclusion:
aids
creating
guidelines
implementing
GAI
chatbots
emphasizing
benefits,
risks,
informing
developers
educators
potential
academia.
International Journal of Human-Computer Interaction,
Год журнала:
2024,
Номер
unknown, С. 1 - 23
Опубликована: Март 8, 2024
The
study
aims
to
explore
the
factors
that
influence
university
students'
behavioral
intention
(BI)
and
use
behavior
(UB)
of
generative
AI
products
from
an
ethical
perspective.
Referring
decision-making
theory,
research
model
extends
UTAUT2
with
three
influencing
factors:
awareness
(EA),
perceived
risks
(PER),
anxiety
(AIEA).
A
sample
226
students
was
analysed
using
Partial
Least
Squares
Structural
Equation
Modelling
technique
(PLS-SEM).
results
further
validate
effectiveness
UTAUT2.
Furthermore,
performance
expectancy,
hedonistic
motivation,
price
value,
social
all
positively
BI
products,
except
for
effort
expectancy.
Facilitating
conditions
habit
show
no
significant
impact
on
BI,
but
they
can
determine
UB.
extended
perspective
play
roles
as
well.
AIEA
PER
are
not
key
determinants
BI.
However,
directly
inhibit
From
mediation
analysis,
although
do
have
a
direct
UB,
it
inhibits
UB
indirectly
through
AIEA.
Ethical
Nevertheless,
also
increase
PER.
These
findings
help
better
accept
ethically
products.
Trends in Higher Education,
Год журнала:
2025,
Номер
4(1), С. 2 - 2
Опубликована: Янв. 8, 2025
This
collective
systematic
literature
review
is
part
of
an
Erasmus+
project,
“TaLAI:
Teaching
and
Learning
with
AI
in
Higher
Education”.
The
investigates
the
current
state
Generative
Artificial
Intelligence
(GenAI)
higher
education,
aiming
to
inform
curriculum
design
further
developments
within
digital
education.
Employing
a
descriptive,
textual
narrative
synthesis
approach,
study
analysed
across
four
thematic
areas:
learning
objectives,
teaching
activities,
development,
institutional
support
for
ethical
responsible
GenAI
use.
93
peer-reviewed
articles
from
eight
databases
using
keyword-based
search
strategy,
collaborative
coding
process
involving
multiple
researchers,
vivo
transparent
documentation.
findings
provide
overview
recommendations
integrating
into
learning,
contributing
development
effective
AI-enhanced
environments
reveals
consensus
on
importance
incorporating
Common
themes
like
mentorship,
personalised
creativity,
emotional
intelligence,
higher-order
thinking
highlight
persistent
need
align
human-centred
educational
practices
capabilities
technologies.
Innovative Higher Education,
Год журнала:
2025,
Номер
unknown
Опубликована: Янв. 24, 2025
Abstract
As
generative
artificial
intelligence
(GenAI)
tools
such
as
ChatGPT
become
more
capable
and
accessible,
their
use
in
educational
settings
is
likely
to
grow.
However,
the
academic
community
lacks
a
comprehensive
understanding
of
perceptions
attitudes
students
instructors
toward
these
new
tools.
In
Fall
2023
semester,
we
surveyed
982
76
faculty
at
large
public
university
United
States,
focusing
on
topics
perceived
ease
use,
ethical
concerns,
impact
GenAI
learning,
differences
responses
by
role,
gender,
discipline.
We
found
that
did
not
differ
significantly
higher
education,
except
regarding
hedonic
motivation,
habit,
interest
exploring
technologies.
Students
also
used
for
coursework
or
teaching
similar
rates,
although
regular
was
still
low
across
both
groups.
Among
students,
significant
between
males
STEM
majors
females
non-STEM
majors.
These
findings
underscore
importance
considering
demographic
disciplinary
diversity
when
developing
policies
practices
integrating
contexts,
may
influence
learning
outcomes
differently
various
groups
students.
This
study
contributes
broader
how
can
be
leveraged
education
while
highlighting
potential
areas
inequality
need
addressed
widely
used.
Social Sciences,
Год журнала:
2024,
Номер
13(8), С. 410 - 410
Опубликована: Авг. 7, 2024
In
this
paper,
the
effects
of
rapid
advancement
generative
artificial
intelligence
(Gen
AI)
in
higher
education
(HE)
are
discussed.
A
mixed
exploratory
research
approach
was
employed
to
understand
these
impacts,
combining
analysis
current
trends
and
students’
perceptions
Gen
AI
tools
academia.
Through
bibliometric
systematic
literature
review,
64
publications
(indexed
SCOPUS
Web
Science
databases)
were
examined,
highlighting
AI’s
disruptive
effect
on
pedagogical
aspects
HE.
The
impacts
identified
by
compared
with
held
computer
science
students
two
different
HE
institutions
(HEIs)
topic.
An
study
developed
based
application
a
questionnaire
group
112
students.
results
suggest
that
while
can
enhance
academic
work
learning
feedback,
it
requires
appropriate
support
foster
critical,
ethical,
digital
literacy
competencies.
Students
demonstrate
awareness
both
risks
benefits
associated
settings.
concludes
failing
recognize
effectively
use
impedes
educational
progress
adequate
preparation
citizens
workers
think
act
an
AI-mediated
world.
Informatics,
Год журнала:
2024,
Номер
11(1), С. 10 - 10
Опубликована: Фев. 25, 2024
The
penetration
of
intelligent
applications
in
education
is
rapidly
increasing,
posing
a
number
questions
different
nature
to
the
educational
community.
This
paper
coming
analyze
and
outline
influence
artificial
intelligence
(AI)
on
teaching
practice
which
an
essential
problem
considering
its
growing
utilization
pervasion
global
scale.
A
bibliometric
approach
applied
outdraw
“big
picture”
gathered
bibliographic
data
from
scientific
databases
Scopus
Web
Science.
Data
relevant
publications
matching
query
“artificial
teaching”
over
past
5
years
have
been
researched
processed
through
Biblioshiny
R
environment
order
establish
descriptive
structure
production,
determine
impact
publications,
trace
collaboration
patterns
identify
key
research
areas
emerging
trends.
results
point
out
growth
production
lately
that
indicator
increased
interest
investigated
topic
by
researchers
who
mainly
work
collaborative
teams
as
some
them
are
countries
institutions.
identified
include
techniques
used
applications,
such
intelligence,
machine
learning,
deep
learning.
Additionally,
there
focus
applicable
technologies
like
ChatGPT,
learning
analytics,
virtual
reality.
also
explores
context
application
for
these
various
settings,
including
teaching,
higher
education,
active
e-learning,
online
Based
our
findings,
trending
topics
can
be
encapsulated
terms
chatbots,
AI,
generative
emotion
recognition,
large
language
models,
convolutional
neural
networks,
decision
theory.
These
findings
offer
valuable
insights
into
current
landscape
interests
field.
Digital Education Review,
Год журнала:
2024,
Номер
45, С. 151 - 157
Опубликована: Июль 1, 2024
Artificial
Intelligence
(AI)
has
been
part
of
every
citizen's
life
for
several
years.
Still,
the
emergence
generative
AI
(GenAI),
accessible
to
all,
raised
discussions
about
ethical
issues
they
raise,
particularly
in
education.
GenAI
tools
generate
content
according
user
requests,
but
are
students
using
these
ethically
and
safely?
Can
teachers
guide
this
use
their
teaching
activities?
This
paper
argues
that
teacher
professional
development
(TPD)
is
an
essential
key
trigger
adopting
emerging
technologies.
The
will
present
integrative
literature
review
discusses
components
TPD
may
empower
towards
safe
GenAI.
According
review,
one
component
should
be
literacy,
which
involves
understanding
AI,
its
capabilities
limitations,
potential
benefits
drawbacks
Another
hands-on
activities
engage
teachers,
peers,
actively
during
training
process.
discuss
advantages
working
with
designing
lesson
plans
implement
them
critically
classroom.
Education Sciences,
Год журнала:
2025,
Номер
15(2), С. 174 - 174
Опубликована: Фев. 2, 2025
The
emergence
of
generative
artificial
intelligence
(Gen
AI)
in
education
offers
both
opportunities
and
challenges,
particularly
the
context
student
assessment.
This
study
examines
faculty
members’
motivations
to
redesign
assessments
for
their
courses
Gen
AI
era
introduces
a
framework
this
purpose.
A
qualitative
methodology
was
employed,
gathering
data
through
semi-structured
interviews
focus
groups,
along
with
examples
redesigned
assessments.
Sixty-one
members
participated
study,
were
analyzed
using
deductive
inductive
thematic
approaches.
Key
redesigning
included
maintaining
academic
integrity,
preparing
learners
future
careers,
adapting
technological
advancements,
aligning
institutional
policies.
However,
also
highlighted
significant
such
as
need
professional
development
addressing
equity
accessibility
concerns.
findings
identified
various
innovative
assessment
approaches
tailored
requirements
era.
Based
on
these
insights,
developed
conceptual
titled
“Against,
Avoid,
Adopt,
Explore”.
Future
research
is
needed
validate
further
refine
its
application
educational
contexts.
