The Impact of AI-Generated Instructional Videos on Problem-Based Learning in Science Teacher Education
Education Sciences,
Год журнала:
2025,
Номер
15(1), С. 102 - 102
Опубликована: Янв. 18, 2025
Artificial
Intelligence
(AI)
has
gained
significant
prominence
in
science
education,
yet
its
practical
applications,
particularly
teacher
training,
remain
underexplored.
Specifically,
there
is
a
lack
of
research
on
AI’s
potential
to
support
personalized
professional
development
through
automated
analysis
classroom
interactions
and
tailored
feedback.
As
education
requires
skill
complex
scientific
concepts
within
problem-based
learning
(PBL)
contexts,
growing
need
for
innovative,
technology-driven
instructional
tools.
AI-generated
videos
are
increasingly
recognized
as
powerful
tools
enhancing
educational
experiences.
This
study
investigates
the
impact
videos,
designed
using
established
design
principles,
self-efficacy,
task
performance,
outcomes
education.
Employing
within-subjects
design,
current
included
pre-test,
post-test,
transfer
assessments
evaluate
durability
transferability,
consistent
with
design-based
methodology.
Moreover,
this
compares
effectiveness
two
video
formats:
one
an
embedded
preview
feature
allowing
learners
key
before
detailed
instruction
(video-with-preview
condition)
another
without
(video-without-preview
condition).
It
specifically
examines
role
features
these
during
training
55
Greek
pre-service
teachers
(n
=
55;
mean
age
27.3
years;
range
22–35).
The
results
demonstrated
that
effectively
supported
knowledge
retention.
However,
no
differences
were
observed
between
across
all
assessed
metrics
tests.
These
findings
also
indicate
can
enhance
retention,
transfer,
positioning
them
promising
assets
limited
highlights
careful
evaluation
elements,
such
interactivity
adaptive
algorithms,
fully
realize
their
potential.
Язык: Английский
Wellness under pandemic: a study of family support and religious commitment as antidotes to psychological distress under social disconnectedness policy in Pakistan
Current Psychology,
Год журнала:
2025,
Номер
unknown
Опубликована: Янв. 14, 2025
Язык: Английский
Understanding Recruiters’ Acceptance of Artificial Intelligence: Insights from the Technology Acceptance Model
Applied Sciences,
Год журнала:
2025,
Номер
15(2), С. 746 - 746
Опубликована: Янв. 14, 2025
The
integration
of
new
technologies
in
professional
contexts
has
emerged
as
a
critical
determinant
organizational
efficiency
and
competitiveness.
In
this
regard,
the
application
Artificial
Intelligence
(AI)
recruitment
processes
facilitates
faster
more
accurate
decision-making
by
processing
large
volumes
data,
minimizing
human
bias,
offering
personalized
recommendations
to
enhance
talent
development
candidate
selection.
Technology
Acceptance
Model
(TAM)
provides
valuable
framework
for
understanding
recruiters’
perceptions
innovative
technologies,
such
AI
tools
GenAI.
Drawing
on
TAM,
model
was
developed
explain
intention
use
tools,
proposing
that
perceived
ease
usefulness
influence
attitudes
toward
AI,
which
subsequently
affect
selection
processes.
Two
studies
were
conducted
Portugal
address
research
objective.
first
qualitative
exploratory
study
involving
100
interviews
with
recruiters
who
regularly
utilize
their
activities.
second
employed
quantitative
confirmatory
approach,
utilizing
an
online
questionnaire
completed
355
recruiters.
findings
underscored
transformative
role
recruitment,
emphasizing
its
potential
optimize
resource
management.
However,
also
highlighted
concerns
regarding
loss
personal
interaction
need
adapt
roles
within
domain.
results
supported
indirect
effect
via
positive
these
tools.
This
suggests
is
best
positioned
complementary
tool
rather
than
replacement
decision-making.
insights
gathered
from
perspectives
provide
actionable
organizations
seeking
leverage
Specifically,
show
importance
ethical
considerations
maintaining
involvement
ensure
balanced
effective
Язык: Английский
Generative Artificial Intelligence (ChatGPT‐4) and Social Media Impact on Academic Performance and Psychological Well‐Being in China's Higher Education
European Journal of Education,
Год журнала:
2024,
Номер
unknown
Опубликована: Ноя. 13, 2024
ABSTRACT
The
rapid
advancement
of
generative
artificial
intelligence
(GAI)
and
the
extensive
use
social
media
have
transformed
how
students
engage
with
educational
materials
interact
their
peers.
Collaborative
learning
(CL)
platforms,
empowered
by
(AI)
algorithms,
gained
popularity
due
to
potential
enhance
outcomes
provide
personalised
experiences.
This
research
examines
effects
AI
(ChatGPT‐4)
on
young
students'
academic
performance
psychological
well‐being,
focusing
CL.
study
conceptual
framework
was
examined
based
a
sample
441
Chinese
university
students.
statistical
technique
PLS‐SEM
is
put
into
practice
measure
structural
well‐being.
findings
this
show
that
positively
influence
Additionally,
results
CL
mediates
between
media,
Conversely,
it
negatively
association
(ChatGPT‐4),
(AP),
can
facilitate
better
understanding
implications
technologies
in
context
subsequently
aid
formulating
evidence‐based
strategies
optimise
impact
students's
success
Язык: Английский
Social Influence, Personal Views, and Behavioral Intention in ChatGPT Adoption
Journal of Computer Information Systems,
Год журнала:
2024,
Номер
unknown, С. 1 - 12
Опубликована: Дек. 20, 2024
This
research
explores
the
relationship
between
social
influence,
students'
views,
behavioral
intention,
and
use
of
ChatGPT.
It
involved
a
cross-sectional
survey
from
cohort
international
students
in
Taiwan.
SmartPLS
SPSS
were
employed
to
analyze
data
test
hypothesized
model.
The
results
indicated
that
views
intentions
significantly
predicted
ChatGPT,
while
influence
did
not.
Specific
indirect
effects
revealed
intention
mediates
ChatGPT
use.
Furthermore,
also
findings
provide
theoretical
basis
for
understanding
adoption
by
students,
who
often
experience
stress
with
their
academic
tasks.
Additionally,
these
insights
are
significant
educators,
emphasizing
importance
ongoing
monitoring
Язык: Английский
Understanding what, how and when green logistics practices influence carbon-neutral supply chain performance
International Journal of Productivity and Performance Management,
Год журнала:
2024,
Номер
unknown
Опубликована: Дек. 24, 2024
Purpose
Integrating
green
(sustainable)
practices
in
logistics
management
play
a
crucial
role
accelerating
the
transition
to
circular
economy,
realizing
its
sustainability
potential
and
position
net
zero
emission
target
by
2050.
Over
past
decade,
this
integration
has
attracted
significant
attention
both
academic
industrial
discourse.
Despite
increasing
recognition
of
benefits
(GLPs),
only
few
firms
have
implemented
green-oriented
or
sustainable
practices;
hence,
comprehensive
understanding
what
could
drive
implementation
as
well
how
when
can
benefit
from
GLPs
is
key
importance
for
theory,
policy
practice.
Drawing
on
dual
theoretical
lenses,
study
investigated
supply
chain
ethical
leadership
(SCEL)
stimulate
building
core
competencies
(GCC)
under
varying
conditions
corporate
culture
(CGC).
Design/methodology/approach
An
integrated
model
motivated
social
learning
contingency
theories
was
tested
using
responses
208
managers
Ghana.
SPSS
23
covariance-based
structural
equation
modeling
(CB-SEM)
were
used
data
analyses.
Findings
Both
SCEL
GCC
significantly
influenced
GLPs.
The
findings
also
showed
that
enhanced
carbon-neutral
performance
(CNSCP).
results
further
mediates
SCEL–GLPs
link.
We
found
effect
amplified
at
high
level
CGC.
Practical
implications
This
offers
fresh
insight
into
leverage
support
GLP
they
combine
competence
achieve
form
SCP.
implies
alone
may
not
be
sufficient
superior
reduction
subsequent
sustainability;
rather,
cultivating
values
fully
realize
enabling
subsequently
enhancing
Originality/value
novelty
present
lies
unearth
mechanism
conditional
roles
optimizing
SCEL–GLPs–GLP
relationship.
among
attempts
shed
light
enhance
performance,
which
rare.
Язык: Английский