Advances in marketing, customer relationship management, and e-services book series,
Journal Year:
2024,
Volume and Issue:
unknown, P. 147 - 176
Published: Dec. 13, 2024
The
rapid
growth
of
educational
technology
highlights
the
essential
need
for
personalized
learning
in
blended
environments.
This
study
uses
Multi-Criteria
Decision
Making
(MCDM)
methodologies,
including
Analytic
Hierarchy
Process
(AHP),
Fuzzy
AHP,
and
Network
(ANP),
to
evaluate
prioritize
personalization
strategies
EdTech
platforms.
research
identifies
data-driven
adaptive
as
most
critical
strategy
(36.46%),
followed
by
AI-powered
content
recommendations
(15.46%)
paths
(15.11%).
It
reveals
that
are
interconnected,
creating
dynamic
feedback
loops
reinforce
one
another,
enabling
continuous
optimization.
provides
a
holistic
framework
technologists,
policymakers,
designers.
approach
bridges
technological
innovation
with
pedagogy,
emphasizing
adaptive,
data-informed
systems
respond
dynamically
learner
needs,
ensuring
balance
between
quality.
Future Internet,
Journal Year:
2025,
Volume and Issue:
17(2), P. 63 - 63
Published: Feb. 4, 2025
Modern
education
faces
persistent
challenges,
including
disengagement,
inequitable
access
to
learning
resources,
and
the
lack
of
personalized
instruction,
particularly
in
virtual
environments.
In
this
perspective,
we
envision
a
transformative
Metaverse
classroom
model,
Multi-layered
Immersive
Learning
Environment
(Meta-MILE)
address
these
critical
issues.
The
Meta-MILE
framework
integrates
essential
components
such
as
immersive
infrastructure,
interactions,
social
collaboration,
advanced
assessment
techniques
enhance
student
engagement
inclusivity.
By
leveraging
three-dimensional
(3D)
environments,
artificial
intelligence
(AI)-driven
personalization,
gamified
pathways,
scenario-based
evaluations,
model
offers
tailored
experiences
that
traditional
classrooms
often
struggle
achieve.
Acknowledging
potential
challenges
accessibility,
infrastructure
demands,
data
security,
study
proposed
practical
strategies
ensure
equitable
safe
interactions
within
Metaverse.
Empirical
findings
from
our
pilot
experiment
demonstrated
framework’s
effectiveness
improving
skill
acquisition,
with
broader
implications
for
educational
policy
competency-based,
experiential
approaches.
Looking
ahead,
advocate
ongoing
research
validate
long-term
outcomes
technological
advancements
make
more
accessible
secure.
Our
perspective
underscores
shaping
inclusive,
future-ready
environments
capable
meeting
diverse
needs
learners
worldwide.
Computers,
Journal Year:
2025,
Volume and Issue:
14(3), P. 93 - 93
Published: March 6, 2025
Machine
learning
(ML)
and
deep
(DL),
subsets
of
artificial
intelligence
(AI),
are
the
core
technologies
that
lead
significant
transformation
innovation
in
various
industries
by
integrating
AI-driven
solutions.
Understanding
ML
DL
is
essential
to
logically
analyse
applicability
identify
their
effectiveness
different
areas
like
healthcare,
finance,
agriculture,
manufacturing,
transportation.
consists
supervised,
unsupervised,
semi-supervised,
reinforcement
techniques.
On
other
hand,
DL,
a
subfield
ML,
comprising
neural
networks
(NNs),
can
deal
with
complicated
datasets
health,
autonomous
systems,
finance
industries.
This
study
presents
holistic
view
technologies,
analysing
algorithms
application’s
capacity
address
real-world
problems.
The
investigates
application
which
techniques
implemented.
Moreover,
highlights
latest
trends
possible
future
avenues
for
research
development
(R&D),
consist
developing
hybrid
models,
generative
AI,
incorporating
technologies.
aims
provide
comprehensive
on
serve
as
reference
guide
researchers,
industry
professionals,
practitioners,
policy
makers.
Discover Sustainability,
Journal Year:
2025,
Volume and Issue:
6(1)
Published: Jan. 13, 2025
As
higher
education
faces
technological
advancement
and
environmental
imperatives,
AI
becomes
a
key
instrument
for
revolutionizing
instructional
methods
institutional
operations.
can
improve
educational
outcomes,
resource
management,
long-term
sustainability
in
education,
according
to
this
study.
The
research
uses
case
studies
best
practices
show
how
AI-driven
innovations
minimize
impact,
enhance
energy
efficiency,
customize
learning,
creating
more
sustainable
inclusive
academic
environment.
document
discusses
ethics,
including
data
privacy,
algorithmic
prejudice,
the
digital
divide.
It
emphasizes
need
strong
ethical
frameworks
use
ethically
make
decisions
with
transparency
fairness.
study
also
robust
rules
infrastructure
promote
integration,
protecting
student
privacy
supporting
fair
access
technologies.
shows
curriculum-building
tools
educate
students
future
concerns
stimulate
innovation.
prospects
difficulties
of
are
critically
examined,
its
potential
change
traditional
roles,
performance,
maintain
profitability.
Actionable
recommendations
educators,
politicians,
leaders
contribute
conversation.
Focusing
on
creates
framework
where
technology
stewardship
intimately
connected,
ensuring
that
institutions
prosper
fast-changing
world.
Human computer interaction.,
Journal Year:
2025,
Volume and Issue:
8(1), P. 173 - 173
Published: Jan. 8, 2025
The
integration
of
Artificial
Intelligence
(AI)
in
personalized
education
is
revolutionizing
traditional
learning
paradigms,
enabling
adaptive,
data-driven
approaches
to
enhance
outcomes.
This
research
investigates
how
AI-driven
technologies,
including
intelligent
tutoring
systems,
adaptive
platforms,
and
predictive
analytics,
transform
the
educational
landscape
by
providing
tailored,
learner-centered
experiences.
AI
facilitates
identification
individual
patterns,
preferences,
challenges,
offering
customized
content
delivery
real-time
feedback
optimize
student
engagement
comprehension.
study
emphasizes
role
fostering
equitable
access
quality
bridging
gaps
opportunities
addressing
diverse
needs.
Furthermore,
it
explores
ethical
implications
education,
such
as
data
privacy,
algorithmic
bias,
balance
between
human
machine-driven
instruction.
By
examining
current
advancements,
case
studies,
future
prospects,
this
aims
provide
a
comprehensive
understanding
technologies
can
drive
innovation
contribute
more
effective,
inclusive,
sustainable
environments.
Advances in finance, accounting, and economics book series,
Journal Year:
2025,
Volume and Issue:
unknown, P. 395 - 414
Published: Jan. 14, 2025
The
incorporation
of
digital
technology
into
the
educational
sector
marks
remarkable
change
in
how
teaching
and
learning
systems
are
operational
today.
present
study
targets
to
scrutinize
AI
tools,
like
virtual
education
platforms
smart
systems,
significantly
influence
students'
understanding
attainment.
findings
point
out
that
artificial
intelligence
(AI)
tools
could
lead
a
noteworthy
revolution
schooling
by
supporting
transformation
journeys,
thereby
enlightening
their
professions
overall
academic
realization.
In
conclusion,
it's
essential
be
familiar
with
aspects
such
ethical
concerns,
as
approaches,
technological
restrictions
when
incorporating
environments,
illustrated
study.
International Journal of Knowledge Management,
Journal Year:
2025,
Volume and Issue:
21(1), P. 1 - 19
Published: Feb. 13, 2025
This
paper
introduces
a
framework
for
enhancing
the
quality
and
effectiveness
of
remote
Chinese
language
teaching.
It
leverages
interactive
features
online
platforms,
such
as
live
streaming
group
discussions,
to
bridge
gap
between
traditional
teaching
methods.
The
includes
practical
guidelines,
comparative
analysis
popular
emphasizes
continuous
feedback
improvement.
aim
is
provide
valuable
insights
solutions
educators,
ultimately
improving
learning
experience
students.
IGI Global eBooks,
Journal Year:
2025,
Volume and Issue:
unknown, P. 73 - 90
Published: Feb. 13, 2025
Special
education
encompasses
a
unique
landscape
of
challenge
in
trying
to
address
all
diversified
needs
students
with
disability.
Traditional
teaching
methods
typically
fail
provide
individual
support
needed
for
effective
learning
take
place,
especially
concerning
children
disabilities
and
autism
spectrum
disorder.
How
AI
data
science
integration
may
revolutionize
the
response
educators
these
challenges
is
yet
be
observed.
This
chapter
talks
about
use
AI-driven
tools
data-informed
strategies
improve
educators'
capabilities
creating
personalized
experiences.
The
explores
how
predictive
models
identify
at-risk
timely
interventions
uses
assistive
technologies,
such
as
speech-to-text,
increase
accessibility.
Data
methods,
clustering
anomaly
detection,
shed
light
on
performance
behavior
inform
instructional
decisions
program
effectiveness.
Data & Metadata,
Journal Year:
2025,
Volume and Issue:
4, P. 203 - 203
Published: Feb. 10, 2025
This
study
aims
to
examine
the
factors
that
motivate,
attract,
and
anchor
students
adopt
AI
tools
during
writing
process
in
context
of
push-pull-mooring
(PPM)
theory.
Utilizing
a
narrative
inquiry
research
approach,
this
employed
observation,
in-depth
interviews,
document
analysis
for
data
collection.
The
identified
key
through
reflexive
thematic
methods.
Key
pull
include
generation
credit
authorship
contributions
integration
into
academic
writing.
encompass
topic
selection,
dynamic
literature
review,
questions,
proposal
conceptualization,
designing
methods,
analysis,
revising
drafts,
managing
references.
incorporates
active
learning,
self-regulated
learning
(SRL),
inquiry-based
overcoming
linguistic
challenges.
push
reference
inaccuracies,
confidentiality
research,
overreliance
on
AI.
Three
anchoring
principles
guide
ethical
incorporation
thesis
writing:
institutional
policies,
augmentation,
comprehensive
contextual
approach.
But
study's
limitations
small
sample
size
ten
from
single
university,
which
affects
generalizability
results.
