Intersezione tra intelligenza artificiale generativa e educazione: un’ipotesi
Journal of Educational Cultural and Psychological Studies (ECPS Journal),
Год журнала:
2025,
Номер
30
Опубликована: Янв. 15, 2025
INTERSECTION
BETWEEN
GENERATIVE
ARTIFICIAL
INTELLIGENCE
AND
EDUCATION:
A
HYPHOTHESIS
Abstract
This
study
explores
the
impact
of
integrating
Generative
Artificial
Intelligence
(GenAI)
into
adaptive
and
personalized
learning
environments,
focusing
on
its
diverse
applications
in
field
education.
It
begins
with
an
examination
evolution
GenAI
models
frameworks,
establishing
selection
criteria
to
curate
case
studies
that
showcase
The
analysis
these
highlights
tangible
benefits
GenAI,
such
as
increased
student
engagement,
improved
test
scores,
accelerated
skill
development.
Ethical,
technical,
pedagogical
challenges
are
also
identified,
emphasizing
need
for
careful
collaboration
between
educators
computer
science
experts.
findings
underscore
potential
revolutionize
By
addressing
technological
ethical
concerns,
embracing
human-centered
approaches,
experts
can
leverage
create
innovative
inclusive
environments.
Finally,
importance
socio-emotional
personalization
evolutionary
process
will
future
Язык: Английский
Advancing SDG 4: Harnessing Generative AI to Transform Learning, Teaching, and Educational Equity in Higher Education
Journal of Lifestyle and SDGs Review,
Год журнала:
2025,
Номер
5(2), С. e03774 - e03774
Опубликована: Янв. 7, 2025
Objective:
The
objective
of
this
study
is
to
investigate
the
transformative
potential
generative
AI
in
advancing
Sustainable
Development
Goal
4
(SDG
4),
with
aim
enhancing
equity,
accessibility,
and
quality
higher
education
through
integration
AI-driven
systems
practices.
Theoretical
Framework:
This
research
underpinned
by
Academic
Convergence
(AIAC)
Framework,
which
aligns
theories
such
as
constructivism,
Vygotsky’s
cultural-historical
theory,
Bloom’s
Taxonomy.
These
frameworks
provide
a
solid
basis
for
understanding
interplay
between
personalized
learning,
cognitive
engagement,
stakeholder
collaboration,
ethical
governance
educational
ecosystems.
Method:
methodology
adopted
comprises
Literature-Driven
Conceptual
Framework
approach,
synthesizing
peer-reviewed
studies
across
key
themes:
operational
efficiency,
collaborative
governance.
Data
collection
involved
systematic
literature
reviews
scholarly
articles,
books,
conference
proceedings
within
past
decade.
Results
Discussion:
results
reveal
that
AIAC
promotes
tailored,
adaptive
learning
pathways,
enhances
faculty
roles
AI-enabled
mentors,
optimizes
administrative
workflows
predictive
analytics.
discussion
contextualizes
these
findings
existing
theories,
emphasizing
framework's
ability
mitigate
challenges
algorithmic
bias,
equity
gaps,
data
privacy
concerns.
Limitations
include
need
empirical
validation
addressing
resource
disparities
underprivileged
contexts.
Research
Implications:
practical
theoretical
implications
are
significant
institutions,
policymakers,
practitioners.
fostering
innovative
teaching
practices,
equitable
access
AI-enhanced
tools,
aligning
strategies
labor
market
demands
analytics
Originality/Value:
contributes
introducing
an
scalable
model
integrating
into
education.
Its
value
lies
bridging
digital
divide,
lifelong
positioning
institutions
leaders
sustainable
integration,
ultimately
mission
SDG
4.
Язык: Английский
Improving The Process of Developing Management Personnel Competencies Through Artificial Intelligence
American Journal of Economics and Business Management,
Год журнала:
2025,
Номер
8(1), С. 33 - 44
Опубликована: Янв. 4, 2025
The
rapid
development
of
artificial
intelligence
(AI)
technologies
has
introduced
intelligent
approaches
in
various
fields.
In
particular,
these
play
an
invaluable
role
modernizing
the
processes
training,
retraining,
and
ensuring
continuous
professional
managerial
personnel.
This
article
presents
results
a
survey
conducted
among
more
than
500
managers
working
public
sector
to
assess
effectiveness
organizing
courses
use
AI
this
process.
Based
on
research
results,
taking
into
account
advanced
international
practices,
information
system
model
is
proposed.
designed
competencies
personnel
automatically
recommend
key
that
they
need
develop.
addition,
offers
suggestions
for
mechanisms
digitally
manage
process
improving
competencies,
assessing
its
economic
efficiency,
integrating
tools
area.
Язык: Английский
Shaping generative AI governance in higher education: Insights from student perception
International Journal of Educational Research Open,
Год журнала:
2025,
Номер
8, С. 100452 - 100452
Опубликована: Фев. 12, 2025
Язык: Английский
Personalized Learning in STEAM
IGI Global eBooks,
Год журнала:
2025,
Номер
unknown, С. 1 - 30
Опубликована: Март 4, 2025
In
contemporary
education,
personalized
learning
is
emerging
as
a
significant
trend
to
enhance
the
learner
experience
and
augment
teaching
efficacy.
When
integrated
into
STEAM,
improves
customization
of
educational
content
promotes
cultivation
creative
thinking,
problem-solving
capacities,
practical
skills.
This
chapter
synthesizes
theories
knowledge
from
many
recent
research
papers
on
in
field
theoretical
foundations
implementation
models,
well
characteristics
this
approach.
The
study
focuses
highlighting
role
teachers
guiding,
supporting,
personalizing
each
student's
journey
experience.
Teachers
apply
appropriate
technology
strategies
convey
interdisciplinary
cultivate
project-based
skills,
attitudes,
motivation
learner.
also
highlights
some
effective
ways
implement
ensure
that
STEAM
can
develop
sustainably
future.
Язык: Английский
Personalized learning through AI: Pedagogical approaches and critical insights
Contemporary Educational Technology,
Год журнала:
2025,
Номер
17(2), С. ep574 - ep574
Опубликована: Март 10, 2025
In
this
analysis,
we
review
artificial
intelligence
(AI)-supported
personalized
learning
(PL)
systems,
with
an
emphasis
on
pedagogical
approaches
and
implementation
challenges.
We
searched
the
Web
of
Science
Scopus
databases.
After
preliminary
review,
examined
30
publications
in
detail.
ChatGPT
machine
technologies
are
among
most
often
utilized
tools;
studies
show
that
general
education
language
account
for
majority
AI
applications
field
education.
Supported
by
particular
stressing
student
characteristics
expectations,
results
automated
feedback
systems
adaptive
content
distribution
define
AI’s
educational
responsibilities
mostly.
The
study
notes
major
difficulties
three
areas:
technical
constraints
data
privacy
concerns;
pragmatic
barriers.
Although
curriculum
integration
teacher
preparation
considered
concerns,
challenges
come
first
above
technology
integration.
also
underline
need
thorough
professional
development
activities
teachers
tools
especially
targeted
instruction.
shows
efficient
application
AI-enabled
PL
requires
a
comprehensive
strategy
addressing
technological,
pedagogical,
ethical
issues
all
at
once.
These
help
to
describe
current
state
provide
ideas
future
developments
as
well
techniques
its
use.
Язык: Английский
Control vs. Agency: Exploring the History of AI in Education
TechTrends,
Год журнала:
2025,
Номер
unknown
Опубликована: Март 14, 2025
Язык: Английский
Generative artificial intelligence 4: training companion
Journal of Paramedic Practice,
Год журнала:
2025,
Номер
17(4), С. 1 - 7
Опубликована: Апрель 2, 2025
Generative
artificial
intelligence
(Gen
AI)
has
gained
the
spotlight
within
education
since
large
language
models
became
publicly
available.
Gen
AI
demonstrated
its
ability
to
generate
high-quality
academic
content
and
even
pass
medical
exams
these
concerns
have,
at
times,
overshadowed
potential
benefits.
This
paper
explores
as
a
training
companion
in
paramedic
continuing
professional
development
(CPD),
highlighting
how
it
can
enhance
learning,
improve
accessibility
address
individual
learner
needs
while
acknowledging
problems.
Язык: Английский
Inteligencia artificial y personalización del aprendizaje: ¿innovación educativa o promesas recicladas?
Edutec Revista Electrónica de Tecnología Educativa,
Год журнала:
2024,
Номер
89, С. 1 - 17
Опубликована: Сен. 30, 2024
Este
artículo
editorial
introduce
la
sección
especial
titulada
"Inteligencia
artificial
en
evaluación
y
personalización
del
aprendizaje".
Se
presentan
contrastan
las
conclusiones
de
los
siete
estudios
seleccionados
relación
con
investigaciones
recientes.
En
este
se
ofrecen
cinco
principales
aportaciones.
Primero,
muestran
avances
integración
aprendizaje
adaptativo
inteligencia
generativa
para
aprendizaje.
A
continuación,
explora
el
uso
educativo
chatbots,
destacando
su
capacidad
facilitar
experiencias
más
dinámicas
ajustadas
a
necesidades
estudiantes.
tercer
lugar,
analiza
automático
creación
modelos
predictivos
que
apoyen
toma
decisiones
formativas.
Posteriormente,
desafíos
oportunidades
sistemas
tutoría
inteligente
proporcionar
retroalimentación
inmediata
ofrecer
recomendaciones
diseñar
ajustar
itinerarios
personalizados
Finalmente,
comparten
prácticas
reflexiones
sobre
éticos
pedagógicos,
dependencia
algunos
retos
enfrenta
investigación
educativa.