Mathematics,
Год журнала:
2024,
Номер
12(15), С. 2324 - 2324
Опубликована: Июль 25, 2024
With
the
implementation
of
conceptual
labeling
on
online
learning
resources,
knowledge-concept
recommendations
have
been
introduced
to
pinpoint
concepts
that
learners
may
wish
delve
into
more
deeply.
As
core
subject
learning,
learners’
preferences
in
knowledge
should
be
given
greater
attention.
Research
indicates
for
are
influenced
by
characteristics
their
group
structure.
There
is
a
high
degree
homogeneity
within
group,
and
notable
distinctions
exist
between
internal
external
configurations
group.
To
strengthen
group-structure
behaviors,
multi-task
strategy
proposed;
this
called
Knowledge-Concept
Recommendations
with
Heterogeneous
Graph-Contrastive
Learning.
Specifically,
due
difficulty
accessing
authentic
social
networks,
structural
neighbors
considered
positive
contrastive
pairs
construct
self-supervision
signals
predefined
meta-path
from
heterogeneous
information
networks
as
auxiliary
tasks,
which
capture
higher-order
presenting
different
perspectives.
Then,
Information
Noise-Contrastive
Estimation
loss
regarded
main
training
objective
increase
differentiation
professional
backgrounds.
Extensive
experiments
constructed
MOOCCube,
we
find
our
proposed
method
outperforms
other
state-of-the-art
concept-recommendation
methods,
achieving
6.66%
HR@5,
8.85%
NDCG@5,
8.68%
MRR.
Frontiers in Education,
Год журнала:
2024,
Номер
9
Опубликована: Сен. 9, 2024
Introduction
The
learning
experience
has
undergone
significant
changes
recently,
particularly
with
the
adoption
of
advanced
technology
and
online
lectures
to
address
challenges
such
as
pandemics.
In
fields
like
engineering,
where
hands-on
classes
are
essential,
environment
plays
a
crucial
role
in
shaping
students’
experiences
satisfaction.
Methods
This
study
aimed
explore
key
factors
affecting
engineering
satisfaction
learning.
A
structured
survey
was
administered
263
students
across
various
disciplines
academic
levels,
all
whom
had
experienced
both
in-person
before
pandemic
during
pandemic.
Factor
analysis
multiple
linear
regression
were
employed
analyze
data.
Results
identified
interactions,
services,
main
positively
influencing
further
revealed
that
is
significantly
dependent
on
availability
quality
assessment
interaction
tools,
technology.
Discussion
highlights
critical
enhance
It
offers
strategies
for
educators
improve
environments,
emphasizing
importance
assessment,
tools.
These
findings
can
guide
development
more
effective
education.
GSC Advanced Research and Reviews,
Год журнала:
2024,
Номер
19(1), С. 132 - 145
Опубликована: Апрель 26, 2024
Digital
technology
has
become
an
integral
part
of
modern
society,
influencing
various
aspects
daily
life,
including
education
and
leadership
development.
This
study
aims
to
evaluate
the
impact
digital
on
youth
development
in
USA.
The
research
explores
how
technology,
such
as
social
media,
online
platforms,
communication
tools,
influences
skills
qualities
among
young
people.
employs
a
mixed-methods
approach,
combining
quantitative
surveys
qualitative
interviews
gather
data
from
diverse
sample
leaders
across
Quantitative
are
used
assess
extent
which
is
programs
its
perceived
skills.
Qualitative
provide
deeper
insights
into
qualities,
communication,
collaboration,
problem-solving
Preliminary
findings
suggest
that
plays
significant
role
development,
offering
new
opportunities
for
learning
growth.
Social
media
particular,
identified
valuable
tools
connecting
with
peers,
sharing
ideas,
mobilizing
support
causes.
However,
also
highlights
challenges
associated
use
risk
information
overload
potential
harassment
bullying.
concludes
by
emphasizing
need
educators,
policymakers,
organizations
recognize
enhancing
while
addressing
challenges.
Recommendations
provided
integrating
effectively,
importance
literacy
policies
promote
safe
responsible
practices
leaders.
Overall,
this
contributes
growing
body
literature
providing
practitioners
policymakers
seeking
harness
power
Mathematics,
Год журнала:
2024,
Номер
12(15), С. 2324 - 2324
Опубликована: Июль 25, 2024
With
the
implementation
of
conceptual
labeling
on
online
learning
resources,
knowledge-concept
recommendations
have
been
introduced
to
pinpoint
concepts
that
learners
may
wish
delve
into
more
deeply.
As
core
subject
learning,
learners’
preferences
in
knowledge
should
be
given
greater
attention.
Research
indicates
for
are
influenced
by
characteristics
their
group
structure.
There
is
a
high
degree
homogeneity
within
group,
and
notable
distinctions
exist
between
internal
external
configurations
group.
To
strengthen
group-structure
behaviors,
multi-task
strategy
proposed;
this
called
Knowledge-Concept
Recommendations
with
Heterogeneous
Graph-Contrastive
Learning.
Specifically,
due
difficulty
accessing
authentic
social
networks,
structural
neighbors
considered
positive
contrastive
pairs
construct
self-supervision
signals
predefined
meta-path
from
heterogeneous
information
networks
as
auxiliary
tasks,
which
capture
higher-order
presenting
different
perspectives.
Then,
Information
Noise-Contrastive
Estimation
loss
regarded
main
training
objective
increase
differentiation
professional
backgrounds.
Extensive
experiments
constructed
MOOCCube,
we
find
our
proposed
method
outperforms
other
state-of-the-art
concept-recommendation
methods,
achieving
6.66%
HR@5,
8.85%
NDCG@5,
8.68%
MRR.
