PLoS ONE,
Journal Year:
2024,
Volume and Issue:
19(9), P. e0309838 - e0309838
Published: Sept. 5, 2024
Student
academic
achievement
is
an
important
indicator
for
evaluating
the
quality
of
education,
especially,
prediction
empowers
educators
in
tailoring
their
instructional
approaches,
thereby
fostering
advancements
both
student
performance
and
overall
educational
quality.
However,
extracting
valuable
insights
from
vast
data
to
develop
effective
strategies
remains
a
significant
challenge
higher
education
institutions.
Traditional
machine
learning
(ML)
algorithms
often
struggle
clearly
delineate
interplay
between
factors
that
influence
success
resulting
grades.
To
address
these
challenges,
this
paper
introduces
XGB-SHAP
model,
novel
approach
predicting
combines
Extreme
Gradient
Boosting
(XGBoost)
with
SHapley
Additive
exPlanations
(SHAP).
The
model
was
applied
dataset
public
university
Wuhan,
encompassing
records
87
students
who
were
enrolled
Japanese
course
September
2021
June
2023.
findings
indicate
excels
accuracy,
achieving
Mean
absolute
error
(MAE)
approximately
6
R-squared
value
near
0.82,
surpassing
three
other
ML
models.
further
uncovers
how
different
modes
contribute
achievement.
This
insight
supports
need
customized
feature
selection
aligns
specific
characteristics
each
teaching
mode.
Furthermore,
highlights
importance
incorporating
self-directed
skills
into
student-related
indicators
when
performance.
PeerJ Computer Science,
Journal Year:
2024,
Volume and Issue:
10, P. e2000 - e2000
Published: May 23, 2024
Immersive
technology,
especially
virtual
reality
(VR),
transforms
education.
It
offers
immersive
and
interactive
learning
experiences.
This
study
presents
a
systematic
review
focusing
on
VR’s
integration
with
educational
theories
in
higher
The
evaluates
the
literature
VR
applications
combined
pedagogical
frameworks.
aims
to
identify
effective
strategies
for
enhancing
experiences
through
VR.
process
involved
analyzing
studies
about
theories,
methodologies,
outcomes,
effectiveness.
Findings
show
that
improves
outcomes
when
aligned
such
as
constructivism,
experiential
learning,
collaborative
learning.
These
integrations
offer
personalized,
immersive,
highlights
importance
of
incorporating
principles
into
application
development.
suggests
promising
direction
future
research
implementation
approach
maximize
value,
across
settings.
Discover Sustainability,
Journal Year:
2025,
Volume and Issue:
6(1)
Published: Jan. 14, 2025
A
significant
advancement
in
artificial
intelligence
is
the
development
of
large
language
models
(LLMs).
Despite
opposition
and
explicit
bans
by
some
authorities,
LLMs
continue
to
play
a
transformative
role,
particularly
education,
improving
understanding
generation
capabilities.
This
study
explores
LLMs'
types,
history,
training
processes,
alongside
their
application
including
digital
higher
education
settings.
novel
theoretical
framework
proposed
guide
integration
into
addressing
key
challenges
such
as
personalization,
ethical
concerns,
adaptability.
Furthermore,
presents
practical
case
studies
solutions
barriers,
data
privacy
bias,
offering
insights
role
enhancing
teaching–learning
process.
By
providing
systematic
analysis
proposing
structured
framework,
this
advances
current
knowledge
highlights
potential
revolutionizing
education.
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.
Education Sciences,
Journal Year:
2024,
Volume and Issue:
14(5), P. 484 - 484
Published: May 2, 2024
The
purpose
of
this
paper
is
to
explore
the
influence
using
AI
chatbots
on
learning
within
context
engineering
education.
We
framed
study
principles
how
works
in
order
describe
contributions
and
challenges
five
categories:
(1)
facilitating
acquisition,
completion,
or
activation
prior
knowledge
helping
organize
making
connections;
(2)
enhancing
student
motivation
learn;
(3)
fostering
self-directed
practice,
application
skills
they
acquire;
(4)
supporting
goal-directed
practice
feedback;
(5)
addressing
diversity
creating
a
positive
classroom
environment.
To
elicit
uses,
benefits,
drawbacks
students’
learning,
we
conducted
thematic
analysis
qualitative
data
gathered
from
surveying
38
volunteers
5
different
electronic
mechatronic
courses
at
South
American
university.
Based
literature
review
an
evidence-based
discussion,
offer
practical
suggestions
for
instructors
who
want
promote
use
enhance
their
learning.
Frontiers in Artificial Intelligence,
Journal Year:
2024,
Volume and Issue:
7
Published: Aug. 28, 2024
In
this
study,
we
aimed
to
explore
the
frequency
of
use
and
perceived
usefulness
LLM
generative
AI
chatbots
(e.g.,
ChatGPT)
for
schoolwork,
particularly
in
relation
adolescents’
executive
functioning
(EF),
which
includes
critical
cognitive
processes
like
planning,
inhibition,
flexibility
essential
academic
success.
Two
studies
were
conducted,
encompassing
both
younger
(Study
1:
N
=
385,
46%
girls,
mean
age
14
years)
older
2:
359,
67%
17
adolescents,
comprehensively
examine
these
associations
across
different
groups.
Study
1,
approximately
14.8%
participants
reported
using
AI,
while
2,
adoption
rate
among
students
was
52.6%,
with
ChatGPT
emerging
as
preferred
tool
adolescents
studies.
Consistently
studies,
found
that
facing
more
EF
challenges
useful
completing
assignments.
Notably,
achievement
showed
no
significant
usage
or
usefulness,
revealed
1.
This
study
represents
first
exploration
into
how
individual
characteristics,
such
EF,
relate
schoolwork
adolescents.
Given
early
stage
during
survey,
future
research
should
validate
findings
delve
deeper
utilization
integration
educational
settings.
It
is
crucial
adopt
a
proactive
approach
address
potential
opportunities
associated
technologies
education.
OBM Neurobiology,
Journal Year:
2025,
Volume and Issue:
09(01), P. 1 - 12
Published: Jan. 13, 2025
The
implementation
of
modern
technologies
has
transformed
connectivity,
information-sharing,
and
education,
significantly
influencing
students'
academic
journeys.
New
offer
advantages
disadvantages,
particularly
impacting
young
students
leading
to
changes
in
habits
behaviors.
While
technology
can
improve
learning
efficiency
through
personalized
approaches,
excessive
screen
time
negatively
affect
communication
performance.
Studies
recommend
limited
for
children
mitigate
adverse
effects.
Research
highlights
the
benefits
risks
digital
usage,
emphasizing
influence
on
brain
development
cognitive
functions
younger
users.
Despite
positive
aspects
technology,
parental
control
is
essential
safeguard
children's
well-being
Integrating
education
requires
careful
consideration
balance
its
potential
risks,
need
monitoring
regulation
optimize
impact
minds
students.
