Artificial Intelligence in Educational Data Mining and Human-in-the-Loop Machine Learning and Machine Teaching: Analysis of Scientific Knowledge
Applied Sciences,
Год журнала:
2025,
Номер
15(2), С. 772 - 772
Опубликована: Янв. 14, 2025
This
study
explores
the
integration
of
artificial
intelligence
(AI)
into
educational
data
mining
(EDM),
human-assisted
machine
learning
(HITL-ML),
and
machine-assisted
teaching,
with
aim
improving
adaptive
personalized
environments.
A
systematic
review
scientific
literature
was
conducted,
analyzing
370
articles
published
between
2006
2024.
The
research
examines
how
AI
can
support
identification
patterns
individual
student
needs.
Through
EDM,
are
analyzed
to
predict
performance
enable
timely
interventions.
HITL-ML
ensures
that
educators
remain
in
control,
allowing
them
adjust
system
according
their
pedagogical
goals
minimizing
potential
biases.
Machine-assisted
teaching
allows
processes
be
structured
around
specific
criteria,
ensuring
relevance
outcomes.
findings
suggest
these
applications
significantly
improve
learning,
tracking,
resource
optimization
institutions.
highlights
ethical
considerations,
such
as
need
protect
privacy,
ensure
transparency
algorithms,
promote
equity,
inclusive
fair
Responsible
implementation
methods
could
quality.
Язык: Английский
Educational Transformation Through Emerging Technologies: Critical Review of Scientific Impact on Learning
Education Sciences,
Год журнала:
2025,
Номер
15(3), С. 368 - 368
Опубликована: Март 16, 2025
Educational
transformation
is
increasingly
influenced
by
emerging
technologies,
which
offer
unique
opportunities
to
redefine
learning.
This
study
aims
critically
analyze
the
scientific
production
related
use
of
technologies
in
educational
field,
focusing
on
their
impact
teaching–learning
process.
A
systematic
review
literature
was
carried
out,
analyzing
a
total
1567
articles
from
2000
2024.
The
results
reveal
that,
although
there
growing
interest
integration
such
as
artificial
intelligence
and
augmented
reality,
concerns
also
emerge
about
implementation
effectiveness.
In
addition,
research
trends
are
identified
that
suggest
multidimensional
approach
these
highlighting
importance
teacher
training
context
they
applied.
conclusions
indicate
maximize
positive
an
informed
pedagogical
considers
advantages
challenges
entail
essential.
analysis
provides
foundation
for
future
studies
guidance
educators
policy
makers
effectively
incorporating
into
environment.
Язык: Английский
Hybrid Learning, Artificial Intelligence, and Indian Indigenized Values
IGI Global eBooks,
Год журнала:
2025,
Номер
unknown, С. 267 - 284
Опубликована: Март 28, 2025
In
recent
years,
the
integration
of
technology
in
education
has
transformed
traditional
teaching
methods,
paving
way
for
hybrid
learning
models
that
combine
face-to-face
instruction
with
online
resources.
This
chapter
explores
synergies
between
and
Artificial
Intelligence
(AI)
technologies
educational
settings.
By
leveraging
AI
algorithms,
machine
learning,
natural
language
processing,
educators
can
personalize
experiences,
analyze
student
data,
provide
real-time
feedback
to
enhance
engagement
academic
performance.
Indian
indigenized
context
role
assessment.
The
also
delves
into
challenges
opportunities
implementing
environments,
including
ethical
considerations,
data
privacy
concerns,
need
teacher
training.
Ultimately,
this
advocates
thoughtful
create
dynamic
adaptive
experiences
cater
diverse
needs
learners
digital
age.
Язык: Английский