BIO Web of Conferences,
Год журнала:
2024,
Номер
138, С. 04032 - 04032
Опубликована: Янв. 1, 2024
The
paper
provides
an
analytical
review
of
studies
on
the
problem
resources
and
risks
digitalization
professional
training
system.
article
considers
use
information
interaction
in
network
process
engineering
specialists
as
a
factor
their
personal
growth.
content
students'
ideas
about
features
self-realization
new
conditions
digital
environment
is
identified
systematized.
attitudes
to
learning
context
are
shown.
presents
main
results
empirical
study
methods
selfpresentation,
motivation
obstacles
achieving
success
multi-level
formats
educational
environment.
specifics
advantages
limitations
Personal,
cognitive,
communicative,
social
didactic
technologies
described.
indicate
that
students
consider
resource
space
opportunities
vectors
self-realization,
while
adequately
assessing
learning.
A
model
psychological
support
for
student
subject
selfrealization
proposed.
European Journal of Education,
Год журнала:
2024,
Номер
unknown
Опубликована: Дек. 13, 2024
ABSTRACT
The
rise
of
artificial
intelligence
(AI)
has
significantly
impacted
education,
yet
few
scholars
have
explored
AI‐assisted
classrooms,
particularly
in
language
education
China.
Understanding
the
roles
classroom
climate,
AI
literacy,
and
resilience
is
essential,
as
these
factors
foster
positive
learning
environments
enhance
student
engagement.
In
this
sense,
study,
grounded
Social
Cognitive
Theory,
employs
structural
equation
modelling
to
investigate
influencing
engagement
Chinese
English
a
Foreign
Language
(EFL)
classrooms.
It
examines
data
from
606
university
EFL
learners
explore
interactions
among
variables
mediating
role
resilience.
findings
indicate
that
all
predict
engagement,
highlighting
importance
both
environmental
cognitive
fostering
active
participation.
Furthermore,
serves
crucial
mediator,
linking
climate
literacy
This
study
provides
some
insights
for
educators
policymakers,
emphasising
need
cultivate
supportive
environments,
promote
programs,
strengthen
students'
optimise
educational
settings.
Behavioral Sciences,
Год журнала:
2024,
Номер
14(10), С. 956 - 956
Опубликована: Окт. 16, 2024
As
artificial
intelligence
(AI)
technology
becomes
increasingly
integrated
into
education,
understanding
the
theoretical
mechanisms
that
drive
university
students
to
adopt
new
learning
behaviors
through
these
tools
is
essential.
This
study
extends
Expectation-Confirmation
Model
(ECM)
by
incorporating
both
cognitive
and
affective
variables
examine
students'
current
AI
usage
their
future
expectations.
The
model
includes
intrinsic
extrinsic
motivations,
focusing
on
three
key
factors:
positive
emotions,
digital
efficacy,
willingness
for
autonomous
learning.
A
survey
of
721
valid
responses
revealed
satisfaction
significantly
influence
continued
usage,
with
emotions
being
particularly
critical.
Digital
efficacy
perceived
usefulness
also
impact
satisfaction,
but
long-term
intentions
are
more
effectively
driven
emotions.
Furthermore,
strongly
affects
Therefore,
higher
education
institutions
should
promote
technology,
enhance
expectation-confirmation
levels,
emphasize
emotional
experiences
during
use.
Adopting
a
"human-machine
symbiosis"
can
foster
active
learning,
personalized
pathways,
development
innovation
capabilities.
Journal of Computer and Education Research,
Год журнала:
2025,
Номер
13(25), С. 80 - 105
Опубликована: Фев. 26, 2025
This
research
explored
the
relationships
between
online
learning
self-efficacy,
academic
intrinsic
motivation,
and
student
engagement
in
learning,
with
particular
attention
given
to
mediating
role
of
motivation
on
self-efficacy's
influence
engagement.
A
model
was
formulated
alignment
study's
hypotheses.
Using
a
quantitative
approach,
study
applied
both
descriptive
relational
survey
models.
The
sample
comprised
185
associate
degree
students
participating
distance
education
program
at
state
university.
Data
collection
conducted
through
structured
questionnaire.
hypotheses
were
tested
using
Partial
Least
Squares
Structural
Equation
Modeling
(PLS-SEM)
method.
findings
supported
hypotheses,
revealing
that
self-efficacy
positively
influenced
Additionally,
it
discovered
indirectly
affected
engagement,
serving
as
mediator.
Journal of Librarianship and Information Science,
Год журнала:
2025,
Номер
unknown
Опубликована: Янв. 9, 2025
The
paper
employs
text
analysis
techniques
to
conduct
a
systematic
quantitative
of
literature
in
the
field
digital
literacy,
aiming
recognize
and
organize
research
topics
their
evolutionary
process
within
this
field.
study
selected
data
on
literacy
from
Web
Science
database
between
2004
2023
as
subjects,
dividing
them
into
10
stages.
Subsequently,
LDA2vec
method
was
used
these
analyzed
two
aspects:
evolution
topic
content
intensity.
results
indicate
that
scholars
primarily
focus
such
education,
technology,
practice,
cybersecurity.
can
be
summarized
three
stages:
exploration,
expansion.
In
terms
content,
identified
types
include
division,
merging,
inheritance,
disappearance,
generation.
aspect
intensity
evolution,
it
found
changes
are
influenced
by
factors
policy,
primary
study.
future,
education
technology
will
remain
literacy.
At
same
time,
concentrate
conducting
in-depth
social
health,
aging
society,
challenges
risks
associated
with
transformation.
