Diversity of frontier processes in Amazonian subnational jurisdictions: Frontier metrics reveal major patterns of human–nature interactions
Ecological Indicators,
Год журнала:
2025,
Номер
171, С. 113198 - 113198
Опубликована: Фев. 1, 2025
Язык: Английский
Heterogeneity of early-onset conduct problems: assessing different profiles, predictors and outcomes across childhood
Child and Adolescent Psychiatry and Mental Health,
Год журнала:
2025,
Номер
19(1)
Опубликована: Апрель 16, 2025
Язык: Английский
A guide to plant morphometrics using Gaussian Mixture Models
bioRxiv (Cold Spring Harbor Laboratory),
Год журнала:
2024,
Номер
unknown
Опубликована: Апрель 22, 2024
Summary
Plant
morphology
is
crucial
in
defining
and
circumscribing
the
plant
diversity
around
us.
Statistically
speaking,
study
of
done
using
morphometry,
that
context
systematics
used
to
verify
hypotheses
morphological
independence
between
taxa.
Nevertheless,
methods
currently
analyse
data
do
not
match
with
conceptual
model
behind
species
circumscription
on
grounds.
Here
we
1)
provide
a
step-by-step
guide
perform
linear
morphometric
analyses
2)
develop
new
conceptual,
statistical,
probabilistic
framework
for
analyzing
Gaussian
Mixture
Models
(GMMs)
taxonomy
compare
alternative
taxonomic
hypotheses.
Язык: Английский
Capturing the Wealth and Diversity of Learning Processes with Learning Analytics Methods
Опубликована: Янв. 1, 2024
Abstract
The
unique
position
of
learning
analytics
at
the
intersection
education
and
computer
science
while
reaching
out
to
several
other
disciplines
such
as
statistics,
psychometrics,
econometrics,
mathematics,
linguistics
has
accelerated
growth
expansion
field.
Therefore,
it
is
a
crucial
endeavor
for
researchers
stay
abreast
latest
methodological
computational
advances
drive
their
research
forward.
diversity
complexity
existing
methods
can
make
this
task
overwhelming
both
newcomers
field
experienced
researchers.
With
motivation
accompany
in
challenging
journey,
book
“Learning
Analytics
Methods
Tutorials—A
Practical
Guide
Using
R”
aims
provide
guide
study,
consult,
take
first
steps
toward
innovation
Thanks
wealth
authors’
backgrounds
expertise,
which
include
authors
R
packages
experts
applications,
offers
comprehensive
array
that
are
described
thoroughly
with
primer
on
usage
prior
education.
These
sequence
analysis,
Markov
models,
factor
process
mining,
network
predictive
modeling,
cluster
analysis
among
others.
A
step-by-step
tutorial
using
programming
language
real-life
datasets
case
studies
presented
each
method.
In
addition,
initial
chapters
devoted
getting
novice
up
speed
learners
basics
data
analysis.
present
chapter
serves
an
introduction
describing
its
main
aim
intended
audience.
It
describes
structure
covered
by
chapter.
also
points
readers
companion
code
repositories
facilitate
following
tutorials
Язык: Английский
Modeling the Dynamics of Longitudinal Processes in Education. A Tutorial with R for the VaSSTra Method
Опубликована: Янв. 1, 2024
Abstract
Modeling
a
longitudinal
process
in
educational
research
brings
lot
of
variability
over
time.
The
modeling
procedure
becomes
even
harder
when
using
multivariate
continuous
variables,
e.g.,
clicks
on
learning
resources,
time
spent
online,
and
interactions
with
peers.
In
fact,
most
human
behavioral
constructs
are
an
amalgam
interrelated
features
complex
fluctuations
such
processes
requires
method
that
takes
into
account
the
multidimensional
nature
examined
construct
as
well
temporal
evolution.
this
chapter
we
describe
VaSSTra
method,
which
combines
person-based
methods,
sequence
analysis
life-events
methods.
Throughout
chapter,
discuss
how
to
derive
states
from
different
variables
related
students,
sequences
students’
progression
states,
identify
study
distinct
trajectories
undergo
similar
We
also
cover
some
advanced
properties
can
help
us
analyze
compare
trajectories.
illustrate
through
tutorial
R
programming
language.
Язык: Английский
Dissimilarity-Based Cluster Analysis of Educational Data: A Comparative Tutorial Using R
Опубликована: Янв. 1, 2024
Abstract
Clustering
is
a
collective
term
which
refers
to
broad
range
of
techniques
aimed
at
uncovering
patterns
and
subgroups
within
data.
Interest
lies
in
partitioning
heterogeneous
data
into
homogeneous
groups,
whereby
cases
group
are
more
similar
each
other
than
assigned
without
foreknowledge
the
labels.
also
an
important
component
several
exploratory
methods,
analytical
techniques,
modelling
approaches
therefore
has
been
practiced
for
decades
education
research.
In
this
context,
finding
or
differences
among
students
enables
teachers
researchers
improve
their
understanding
diversity
students—and
learning
processes—and
tailor
supports
different
needs.
This
chapter
introduces
theory
underpinning
dissimilarity-based
clustering
methods.
Then,
we
focus
on
some
most
widely-used
heuristic
algorithms;
namely,
K
-means,
-medoids,
agglomerative
hierarchical
clustering.
The
-means
algorithm
described
including
outline
arguments
relevant
R
functions
main
limitations
practical
concerns
be
aware
order
obtain
best
performance.
We
discuss
related
-medoids
its
own
associated
function
arguments.
later
introduce
while
outlining
various
choices
available
practitioners
implications.
Methods
choosing
optimal
number
clusters
provided,
especially
criteria
that
can
guide
choice
solution
multiple
competing
methodologies—with
particular
evaluating
solutions
obtained
using
dissimilarity
measures—and
not
only
given
method.
All
these
issues
demonstrated
detail
with
tutorial
real-life
educational
set.
Язык: Английский
Capturing temporal pathways of collaborative roles: A multilayered analytical approach using community of inquiry
International Journal of Computer-Supported Collaborative Learning,
Год журнала:
2024,
Номер
unknown
Опубликована: Авг. 14, 2024
Abstract
In
collaborative
learning,
students
may
follow
different
trajectories
that
evolve
over
time.
This
study
used
a
multilayered
approach
to
map
the
temporal
dynamics
of
online
problem-based
learning
(PBL)
and
transition
students’
roles
across
time
full
year
duration.
Based
on
data
from
135
dental
four
consecutive
courses
throughout
academic
year,
discourses
were
coded
based
community
inquiry
(CoI).
A
mixture
model
was
identify
roles.
The
identified
leaders,
social
mediators,
peripheral
explorer
roles,
they
visualized
using
epistemic
network
analysis
(ENA).
Similar
sequence
process
mining.
results
showed
varying
activity
levels
three
trajectories.
Students
in
active-constructive
trajectory
took
leadership
while
interactive
mostly
free
rider
predominant
role.
all
returned
their
initial
showing
features
typical
stable
dispositions.
Both
active
(active
constructive
interactive)
had
very
close
achievement,
whereas
riders
demonstrated
lower
grades
compared
peers.
research
suggests
understanding
role
evolving
can
help
teachers
better
design
future
activities,
assign
form
groups,
distribute
tasks,
and,
more
importantly,
be
able
support
students.
Язык: Английский