IntechOpen eBooks,
Journal Year:
2024,
Volume and Issue:
unknown
Published: Nov. 11, 2024
In
this
chapter,
we
explore
the
dual
role
of
Generative
AI
in
both
harnessing
and
hampering
creativity
preservice
teacher
(PST)
education.
On
one
hand,
(GAI)
tools,
such
as
ChatGPT,
Adobe
Firefly
other
programs,
offer
novel
opportunities
for
enhancing
PST
creativity.
By
providing
automated
assistance
generating
ideas,
solving
problems,
producing
artistic
content,
these
technologies
can
empower
PSTs
to
new
avenues
expression
innovation.
Used
effectively,
they
foster
a
conducive
environment
creative
exploration
self-expression.
widespread
adoption
GAI
education
raises
concerns
regarding
its
potential
negative
impacts
on
student
An
overreliance
AI-generated
content
may
inhibit
intrinsic
motivation,
critical
thinking
skills,
originality,
leading
reduction
autonomy
self-efficacy.
share
PSTs’
impressions
experiences
related
their
use
ChatGPT
design
lesson
plans.
Education Sciences,
Journal Year:
2024,
Volume and Issue:
14(8), P. 814 - 814
Published: July 25, 2024
This
paper
investigates
the
integration
of
ChatGPT
into
educational
environments,
focusing
on
its
potential
to
enhance
personalized
learning
and
ethical
concerns
it
raises.
Through
a
systematic
literature
review,
interest
analysis,
case
studies,
research
scrutinizes
application
in
diverse
contexts,
evaluating
impact
teaching
practices.
The
key
findings
reveal
that
can
significantly
enrich
education
by
offering
dynamic,
experiences
real-time
feedback,
thereby
boosting
efficiency
learner
engagement.
However,
study
also
highlights
significant
challenges,
such
as
biases
AI
algorithms
may
distort
content
inability
replicate
emotional
interpersonal
dynamics
traditional
teacher–student
interactions.
acknowledges
fast-paced
evolution
technologies,
which
render
some
obsolete,
underscoring
need
for
ongoing
adapt
strategies
accordingly.
provides
balanced
analysis
opportunities
challenges
education,
emphasizing
considerations
strategic
insights
responsible
technologies.
These
are
valuable
educators,
policymakers,
researchers
involved
digital
transformation
education.
Journal of Educational Computing Research,
Journal Year:
2025,
Volume and Issue:
unknown
Published: Jan. 6, 2025
The
rapid
development
of
large
language
models
(LLMs)
presented
opportunities
for
the
transformation
science
and
STEM
education.
Research
on
LLMs
was
in
exploratory
phase,
characterized
by
discussions
observations
rather
than
empirical
investigations.
This
study
a
framework
incorporating
into
Science
Engineering
Practice
(SEP),
utilizing
case
submarine
construction,
followed
four-week
quasi-experimental
validation.
research
employed
conditional
cluster
sampling,
selecting
two
homogeneous
natural
classes
from
middle
school
China
to
serve
as
experimental
control
groups.
key
variable
inclusion
SEP
project.
Various
validated
self-developed
assessment
tools
were
used
measure
students’
learning
outcomes.
Statistical
analyses,
including
pre-
post-test
paired
comparisons
within
ANCOVA
between-class
differences,
performed
evaluate
effects
LLM
integration.
results
showed
that
students
participating
integrated
with
significantly
improved
their
mastery
scientific
knowledge,
attitudes
towards
science,
perceived
usefulness
technology,
understanding
engineering,
computational
thinking
skills,
problem-solving
abilities.
In
contrast,
traditional
exhibited
weaker
knowledge
acquisition,
differences
engineering
concepts,
lack
skills.
pioneering
effort
integrating
education
provided
reference
deeper
application
future.
Journal of Education and Educational Research,
Journal Year:
2025,
Volume and Issue:
12(1), P. 29 - 34
Published: Jan. 17, 2025
This
study
investigates
the
role
of
generative
artificial
intelligence
(AIGC),
particularly
large
language
models,
in
enhancing
digital
literacy
pre-service
teachers.
With
rapid
growth
AI
technologies,
integrating
into
education
has
gained
significant
attention.
The
research
focuses
on
how
varying
frequencies
usage
affect
teachers’
skills
information
processing,
problem-solving,
and
critical
thinking.
Using
a
polynomial
regression
model,
we
analyze
relationship
between
factors
such
as
frequency,
problem-solving
time,
feedback
quality,
scores.
results
indicate
that
frequent
use
substantially
improves
literacy,
with
high-frequency
group
achieving
higher
more
consistent
scores
compared
to
low-frequency
group.
Personalized
project-based
tasks,
provided
by
AI,
enhance
students’
comprehension
application
technologies.
shows
incorporating
teacher
training
programs
not
only
supports
personalized
learning
but
also
fosters
essential
competencies.
findings
provide
valuable
insights
for
teachers'
lay
foundation
future
educational
practices
involving
