Education Sciences,
Год журнала:
2024,
Номер
14(12), С. 1325 - 1325
Опубликована: Ноя. 30, 2024
In
diverse
classrooms,
one
of
the
challenges
educators
face
is
creating
assessments
that
reflect
different
cultural
background
every
student.
this
study
presents
a
novel
approach
to
automatic
generation
and
context-specific
science
items
for
K-12
education
using
generative
AI
(GenAI).
We
first
developed
GenAI
Culturally
Responsive
Science
Assessment
(GenAI-CRSciA)
framework
connects
CRSciA,
specifically
key
tenets
such
as
indigenous
language,
Indigenous
knowledge,
ethnicity/race,
religion,
with
capabilities
GenAI.
Using
CRSciA
framework,
along
interactive
guided
dynamic
prompt
strategies,
was
used
develop
CRSciA-Generator
tool
within
OpenAI
platform.
The
allows
users
automatically
generate
assessment
item
are
customized
align
their
students’
contextual
needs.
conducted
pilot
demonstration
between
base
GPT-4o
(using
standard
prompts),
both
tools
were
tasked
generating
CRSciAs
aligned
Next
Generation
Standard
on
predator
prey
relationship
students
from
Ghana,
USA,
China.
results
showed
output
incorporated
more
tailored
context
each
specific
group
examples,
traditional
stories
lions
antelopes
in
Native
American
views
wolves
Taoist
or
Buddhist
teachings
Amur
tiger
China
compared
GPT-4o.
However,
due
focus
nationality
demonstration,
treated
countries
culturally
homogeneous,
overlooking
subcultural
diversity
these
countries.
Therefore,
we
recommend
provide
detailed
information
about
when
CRSciA-Generator.
further
future
studies
involving
expert
reviews
assess
validity
generated
by
Electronics,
Год журнала:
2025,
Номер
14(5), С. 1053 - 1053
Опубликована: Март 6, 2025
In
this
paper,
we
investigated
the
role
of
generative
AI
in
education
academic
publications
extracted
from
Web
Science
(3506
records;
2019–2024).
The
proposed
methodology
included
three
main
streams:
(1)
Monthly
analysis
trends;
top-ranking
research
areas,
keywords
and
universities;
frequency
over
time;
a
keyword
co-occurrence
map;
collaboration
networks;
Sankey
diagram
illustrating
relationship
between
AI-related
terms,
publication
years
areas;
(2)
Sentiment
using
custom
list
words,
VADER
TextBlob;
(3)
Topic
modeling
Latent
Dirichlet
Allocation
(LDA).
Terms
such
as
“artificial
intelligence”
“generative
artificial
were
predominant,
but
they
diverged
evolved
time.
By
2024,
applications
had
branched
into
specialized
fields,
including
educational
research,
computer
science,
engineering,
psychology,
medical
informatics,
healthcare
sciences,
general
medicine
surgery.
sentiment
reveals
growing
optimism
regarding
education,
with
steady
increase
positive
2023
to
while
maintaining
predominantly
neutral
tone.
Five
topics
derived
based
on
an
most
relevant
terms
by
LDA:
Gen-AI’s
impact
research;
ChatGPT
tool
for
university
students
teachers;
Large
language
models
(LLMs)
prompting
computing
education;
(4)
Applications
patient
(5)
ChatGPT’s
performance
examinations.
identified
several
emerging
topics:
discipline-specific
application
LLMs,
multimodal
gen-AI,
personalized
learning,
peer
or
tutor
cross-cultural
multilingual
tools
aimed
at
developing
culturally
content
supporting
teaching
lesser-known
languages.
Further,
gamification
involves
designing
interactive
storytelling
adaptive
games
enhance
engagement
hybrid
human–AI
classrooms
explore
co-teaching
dynamics,
teacher–student
relationships
classroom
authority.
CTE Workshop Proceedings,
Год журнала:
2025,
Номер
unknown
Опубликована: Март 11, 2025
The
emergence
of
generative
artificial
intelligence
(GenAI)
has
transformed
various
sectors,
including
education.
This
narrative
scoping
review
examines
how
GenAI
is
being
integrated
into
teacher
training
programs,
exploring
its
applications,
benefits,
challenges,
and
implementation
frameworks.
By
synthesizing
findings
from
recent
literature
(2022-2025),
we
identify
key
themes
the
development
AI
literacy
among
teachers,
impact
on
pedagogical
content
knowledge,
ethical
considerations
in
implementation.
Our
analysis
reveals
significant
benefits
enhancing
teaching
performance
facilitating
personalized
learning,
while
also
highlighting
challenges
such
as
technical
limitations,
concerns,
resistance
to
change.
We
gaps
current
research,
particularly
non-STEM
subjects
framework
development,
suggest
directions
for
future
research
advance
responsible
integration
Journal of Digital Educational Technology,
Год журнала:
2025,
Номер
5(1), С. ep2508 - ep2508
Опубликована: Янв. 28, 2025
This
rapid
study
explores
teacher
educators’
perceptions
of
generative
artificial
intelligence
(GenAI)
in
education,
conducted
through
a
descriptive
survey
involving
55
educators
from
two
colleges
education
Ghana.
A
convenience
sampling
technique
was
adopted
for
data
collection,
and
analysis
using
<i>exploratory
factor
analysis</i>
used
to
identify
primary
factors
shaping
preparedness
GenAI
integration.
Key
findings
reveal
generally
positive
perception
among
the
educators,
who
recognize
GenAI’s
potential
support
academic
achievement,
increase
student
engagement,
improve
communication
within
settings.
The
further
indicate
that
background
factors,
such
as
age,
years
teaching
experience,
department,
college,
do
not
significantly
predict
their
GenAI.
Since
none
these
measured
were
significant
predictors,
this
suggests
training
resources
should
be
broadly
prioritized,
accessible,
heavily
tailored
specific
demographic
groups.
However,
identified
concerns
<i>barriers
challenges</i>
including
ethical
issues,
fairness
assessment,
possible
adverse
effects
on
educator-student
relationship.
<i>communication
independence</i>
highlight
need
professional
development,
with
emphasizing
importance
usage
optimize
its
educational
potential.
concludes
while
benefits,
there
are
essential
practical
challenges
address.
Recommendations
include
establishing
clear
policies
guidelines
guide
implementation
ensure
usage.
We
recommend
expansion
research
larger
sample
gather
comprehensive
insights
acceptance
levels
Advances in computational intelligence and robotics book series,
Год журнала:
2025,
Номер
unknown, С. 351 - 370
Опубликована: Март 13, 2025
The
purpose
of
this
chapter
was
to
examine
the
role
self-regulation
as
a
mediator
in
relationship
between
use
artificial
intelligence
(AI)
learning
tool
on
student
happiness
among
private
university
students
Bahrain.
data
were
collected
from
171
at
Using
theoretical
framework
social
cognitive
theory,
results
showed
that
directly
positively
related
perceived
usefulness
AI
and
attitude
toward
use.
finding
also,
indicated
significantly
mediates
Ai
usage
students'
happiness.
recommendation
develop
students′
increase
positive
impact
their
well-being
overall
Sustainability,
Год журнала:
2025,
Номер
17(7), С. 2962 - 2962
Опубликована: Март 27, 2025
As
AI
integration
in
education
increases,
it
is
crucial
to
evaluate
its
effectiveness
elementary
science
learning,
particularly
promoting
sustainable
through
equitable
access
knowledge.
This
study
aims
assess
the
validity
and
applicability
of
ChatGPT3.5
(free
version)
responses
Earth
Space
science.
A
document
analysis
1200
AI-generated
was
conducted
scientific
validity,
explanatory
clarity,
pedagogical
relevance.
The
employed
quantitative
methods
accuracy
alignment
with
curricula,
while
qualitative
insights
identified
linguistic
conceptual
challenges.
findings
indicate
that
94.2%
were
scientifically
valid,
70.6%
clear,
but
only
12.8%
aligned
curricula.
While
ChatGPT
provides
accurate
information,
many
included
complex
terminology
unsuitable
for
young
learners.
Additionally,
87.2%
lacked
posing
challenges
effective
classroom
integration.
Despite
these
limitations,
shows
potential
simplifying
concepts
expanding
educational
resources.
Refining
content
curriculum-based
filtering,
adaptive
language
processing,
teacher
mediation
necessary.
Strengthening
AI-driven
strategies
a
sustainability
focus
can
ensure
long-term
improvements
learning.
highlights
need
further
research
on
optimizing
tools
education.
