Educational Data Mining and Predictive Modeling in the Age of Artificial Intelligence: An In-Depth Analysis of Research Dynamics
Computers,
Год журнала:
2025,
Номер
14(2), С. 68 - 68
Опубликована: Фев. 14, 2025
This
article
provides
a
comprehensive
analysis
of
the
research
dynamics
on
use
Educational
Data
Mining
(EDM)
and
predictive
modeling
(PM)
in
era
Artificial
Intelligence
(AI)
based
review
793
articles
published
between
2000
2024
Scopus
database.
The
study
employs
bibliometric
systematic
literature
to
identify
emerging
trends,
methodologies,
applications
these
fields.
main
objective
is
examine
primary
methodologies
innovations
within
AI,
especially
context
EDM
PM.
It
highlights
how
technologies
can
optimize
prediction
student
performance,
support
personalized
learning,
enable
timely
interventions
through
data.
also
examines
role
AI
improving
teaching
practices,
ensuring
that
educators
maintain
control
over
system
minimize
potential
biases.
Furthermore,
addresses
ethical
implications
implementation
education,
such
as
privacy
protection,
algorithm
transparency,
equity
access
learning.
findings
suggest
has
significantly
improve
educational
outcomes
tracking,
resource
allocation,
overall
effectiveness
institutions.
responsible
education
emphasized
ensure
inclusive
fair
environments
for
all
students.
Язык: Английский
Smart Water Management and Resource Conservation
Advances in electronic government, digital divide, and regional development book series,
Год журнала:
2024,
Номер
unknown, С. 235 - 262
Опубликована: Ноя. 15, 2024
Water
is
essential
to
every
living
being.
management
and
resource
conservation
very
important
provide
safe
clean
water
all.
Resources
of
have
been
polluted
contaminated
due
increasing
population
urbanization.
Irrigation
hydropower
reservoir
are
other
sources
responsible
for
stress
on
earth.
The
main
aim
smart
cities
urban
development
everyone
at
low
cost
in
sustainable
ways.
Thus,
it
necessary
conserve
resources
manage
the
smartly.
Use
non-conventional
irrigation,
aquaculture
aquifer
recharge
one
solutions
decrease
use
fresh
these
purposes.
Machine
learning
solution
managing
conserving
resources.
Various
machine
models
applied
prediction
tasks.
However,
deep
categorization
regression
task.
chapter
objective
cities.
Язык: Английский
A Systematic Review of Application of Machine Learning in Curriculum Design Among Higher Education
Journal of Emerging Computer Technologies,
Год журнала:
2024,
Номер
4(1), С. 15 - 24
Опубликована: Авг. 24, 2024
Machine
learning
has
become
an
increasingly
popular
area
of
research
in
the
field
education,
with
potential
applications
various
aspects
higher
education
curriculum
design.
This
study
aims
to
review
current
AI
design
education.
We
conducted
initial
search
for
articles
on
application
machine
involved
searching
three
core
educational
databases,
including
Educational
Research
Resources
Information
Centre
(ERIC),
British
Education
Index
(BEI),
and
Complete,
identify
relevant
literature.
Subsequently,
this
performed
network
analysis
included
literature
gain
a
deeper
understanding
common
themes
topics
within
field.
The
results
showed
growing
trend
publishing
domain.
Our
pinpointed
merely
11
publications
specifically
targeting
course
design,
only
being
peer-reviewed
articles.
Through
word
cloud
visualization,
we
discerned
most
prominent
keywords
be
AI,
foreign
countries,
pedagogy,
online
courses,
e-learning,
Collectively,
these
underscore
significance
molding
landscape,
as
well
expanding
tendency
incorporate
technologies
into
technology-enhanced
experiences.
Although
there
is
significant
amount
its
specific
use
still
needs
expanded.
identified
small
number
studies
that
directly
focused
topic,
among
them.
generated
from
highlights
important
related
student
performance
models
algorithms.
However,
need
further
fully
understand
would
contribute
can
update
teacher’s
awareness
using
teaching
practice.
Additionally,
it
implies
more
researchers
conduct
area.
Future
should
consider
limitations
existing
explore
new
approaches
improve
outcomes.
Язык: Английский