Human Resource Development Quarterly,
Год журнала:
2024,
Номер
unknown
Опубликована: Дек. 29, 2024
ABSTRACT
The
purpose
of
this
article
is
to
analyze
the
system
motivation
scientific
and
pedagogical
workers,
which
operates
today
in
universities,
assess
satisfaction
teachers
with
current
that
exists
university
and,
based
on
results
analysis
evaluation,
formulate
recommendations
will
be
aimed
at
improving
teaching
staff
universities
Republic
Kazakhstan.
following
methods
were
used
study:
synthesis,
comparison,
economic
statistical
analysis,
generalization
interpretation
obtained,
graphical
representation
data.
data
Bureau
National
Statistics
Agency
for
Strategic
Planning
Reforms
Kazakhstan,
an
Internet
survey
conducted
Google
Forms
platform
as
a
source
information.
study
are
follows:
dynamics
number
country
has
been
studied,
labor
Kazakhstan
carried
out,
improvement
have
formulated.
practical
significance
determined
by
fact
proposed
can
basis
development
new
universities.
Advances in educational marketing, administration, and leadership book series,
Год журнала:
2024,
Номер
unknown, С. 111 - 136
Опубликована: Окт. 15, 2024
This
chapter
assesses
the
transformative
impact
of
usage
generative
artificial
intelligence
(AI)
in
context
higher
education.
As
technology
continues
to
advance,
AI
is
increasingly
used
enhance
various
aspects
education,
including
personalised
learning,
assessment,
and
content
creation.
addresses
changing
circumstances
education
research,
where
use
technologies
becoming
more
substantial
innovative.
However,
industries
are
facing
challenges
cope
up
with
academic
Integrity
ethics.
It
includes
a
consideration
theoretical
foundations
that
underpin
AI,
its
significance
potential
implications
within
The
tools
facilitates
automatic
generation
assignments
exams
across
subject.
raising
concerns
about
intellectual
integrity
justice.
Therefore,
understand
it
essential
focus
on
ethics,
quality
assurance,
integrity.
Australasian Journal of Educational Technology,
Год журнала:
2024,
Номер
unknown
Опубликована: Дек. 16, 2024
The
rapid
advancement
of
artificial
intelligence
(AI)
has
outpaced
existing
research
and
regulatory
frameworks
in
higher
education,
leading
to
varied
institutional
responses.
Although
some
educators
institutions
have
embraced
AI
generative
(GenAI),
other
individuals
remain
cautious.
This
systematic
literature
review
explored
teaching
academics'
attitudes,
perceptions
intentions
towards
GenAI,
identifying
perceived
benefits
obstacles.
Utilising
the
unified
theory
acceptance
use
technology
framework,
this
study
reveals
positive
attitudes
AI's
efficiency
enhancement,
but
also
significant
concerns
about
academic
integrity,
accuracy,
reliability,
skill
development
need
for
comprehensive
training
policies.
These
findings
underscore
necessity
support
navigate
integration
GenAI
tertiary
education.
Implications
practice
or
policy:
Attitudes
are
diverse
with
recognising
raising
ethical
practical
concerns.
indicate
a
more
understanding
dialogue
within
communities.
Academics'
these
technologies
contingent
upon
robust
guidelines
supportive
Institutional
shape
behaviours.
scarcity
formal
training,
policy
currently
limits
effective
integration.
International Journal of Educational Curriculum Management and Research,
Год журнала:
2024,
Номер
5(1)
Опубликована: Апрель 28, 2024
With
the
rapid
development
of
information
technology
and
continuous
growth
logistics
industry,
management
teaching
is
also
facing
new
challenges
opportunities.Traditional
courses
often
focus
on
imparting
theoretical
knowledge,
but
lack
cultivation
practical
problem-solving
abilities.The
introduction
big
model
provides
ideas
methods
for
teaching.By
simulating
real
scenarios,
students
can
master
core
concepts
in
practice.This
article
explores
significance
value
application
models
from
three
aspects:
breadth,
depth,
timeliness
impact
teaching.It
analyzes
specific
through
cases,
order
to
provide
reference
inspiration
practice
related
fields.
European Journal of Sustainable Development Research,
Год журнала:
2024,
Номер
8(4), С. em0273 - em0273
Опубликована: Окт. 13, 2024
The
current
study
investigates
how
artificial
intelligence
(AI)
impacts
sustainable
development
in
emerging
markets,
with
a
focus
on
Thailand.
Following
systematic
review
approach,
research
designs
are
configured
for
reviewing
empirical
evidence
within
peer-reviewed
papers
and
reports.
It
also
presents
an
overview
of
the
adoption
AI
agriculture,
health,
urban
planning.
key
findings
lend
credence
to
potential
use
achieving
resource
optimality,
reducing
environmental
damage,
urging
social
equity
its
use.
But
these
very
initiatives
hampered
by
digital
divide,
concerns
about
data
privacy,
bias
algorithms.
way
forward
should
be
establish
solid,
regulatory
frameworks
geared
towards
more
investment
infrastructure
ethical
practices
that
will
lead
optimal
gains.
huge
potentials
enable
sustainability
Thailand
there;
hence,
it
is
important
reduce
associated
risks
require
equitably
distributed
results
all
sectors.
Revista Review Index Journal of Multidisciplinary,
Год журнала:
2024,
Номер
4(1), С. 44 - 54
Опубликована: Март 31, 2024
Artificial
intelligence
(AI)
technologies
are
changing
teaching,
learning,
administrative
procedures,
and
student
support
services
as
they
progressively
incorporated
into
different
parts
of
the
higher
education
ecosystem
(Ocaña-Fernández,
Valenzuela-Fernández,
&
Garro-Aburto,
2019).
By
boosting
research
efforts,
expanding
teaching
learning
opportunities,
increasing
effectiveness,
encouraging
inclusion
accessibility,
AI
is
revolutionizing
education.
(Saaida,
2023).
To
optimize
AI's
potential
benefits
for
students,
teachers,
larger
academic
community,
institutions
must
welcome
innovation,
adjust
to
technological
changes,
assure
ethical
responsible
usage
(Guan,
Mou,
Jiang,
2020).
So,
this
paper
tries
analyse
historical
development
its’
role
in
developing
whole
process
with
help
exhaustive
literature
review
a
qualitative
approach
research.
Research Square (Research Square),
Год журнала:
2024,
Номер
unknown
Опубликована: Авг. 9, 2024
Abstract
Inspired
by
the
principles
of
Systems
Theory,
this
study
explores
modern
workplace,
as
a
multifaceted
and
ever-evolving
organisation
system
in
which
mental
wellbeing,
stress,
resilience,
counterproductive
work
behavior,
substance
abuse
are
interrelated,
impacting
one
another
via
feedback
loops.
Thus,
our
aim
was
to
evaluate
management
framework
that
addresses
how
these
constructs
connected
well
manage
them
within
workplace.
A
survey
tool
with
standardized
questionnaires
used
collect
data
from
446
employees.
The
measurement
model
demonstrated
construct
reliability
validity,
whereas
structural
examined
strength
linkages.
Higher
resilience
reduced
boosting
wellbeing
acted
stabilizing
influence
against
behavior.
This
highlights
complicated
interplay
between
variables
emphasizes
critical
significance
maintaining
balance
for
organizational
success.
Model Assisted Statistics and Applications,
Год журнала:
2024,
Номер
19(3), С. 265 - 274
Опубликована: Окт. 18, 2024
Understanding
relationships
between
stress,
resilience,
mental
wellbeing,
and
task-performance
is
critical
for
success
in
today’s
sustainable
workplaces.
Thus,
we
aimed
to
analyse
develop
a
management
framework
deal
with
this
criticality.
Inspired
by
Salutogenesis
theory
–
prioritizing
positive
variables
over
the
absence
of
negative
ones,
our
emphasis
was
on
resilience
wellbeing
stress
improving
task
performance.
Data
from
445
employees
collected
survey
instrument
employing
standardised
scales.
Reliability
validity
constructs
were
established
through
measurement
model,
while
structural
model
tested
strength
relationships.
Low
high
identified
as
having
strong
effect
which
in-turn
improved
task-performance.
This
study
highlights
that
addition
management,
significantly
improves
performance
Human Resource Development Quarterly,
Год журнала:
2024,
Номер
unknown
Опубликована: Дек. 29, 2024
ABSTRACT
The
purpose
of
this
article
is
to
analyze
the
system
motivation
scientific
and
pedagogical
workers,
which
operates
today
in
universities,
assess
satisfaction
teachers
with
current
that
exists
university
and,
based
on
results
analysis
evaluation,
formulate
recommendations
will
be
aimed
at
improving
teaching
staff
universities
Republic
Kazakhstan.
following
methods
were
used
study:
synthesis,
comparison,
economic
statistical
analysis,
generalization
interpretation
obtained,
graphical
representation
data.
data
Bureau
National
Statistics
Agency
for
Strategic
Planning
Reforms
Kazakhstan,
an
Internet
survey
conducted
Google
Forms
platform
as
a
source
information.
study
are
follows:
dynamics
number
country
has
been
studied,
labor
Kazakhstan
carried
out,
improvement
have
formulated.
practical
significance
determined
by
fact
proposed
can
basis
development
new
universities.
