IntechOpen eBooks,
Год журнала:
2024,
Номер
unknown
Опубликована: Дек. 23, 2024
This
chapter
employs
a
system
dynamics
lens
to
examine
the
intricate
interplay
between
artificial
intelligence
(AI)
integration
and
landscape
of
higher
education.
Employing
causal
loop
diagrams,
it
delves
into
evolving
various
key
indicators
in
education
affected
by
AI
implementation.
Beginning
with
an
overview
disruptive
technologies’
current
roles
academia,
including
AI,
proceeds
illustrate
interrelationships
form
feedback
loops
technological
advancements,
pedagogical
methodologies,
institutional
structures,
societal
factors.
Subsequently,
explores
systemic
shifts
student
learning
experiences,
faculty
roles,
administrative
practices
catalysed
infusion.
By
illuminating
complex
web
interactions,
this
aims
provide
insights
crucial
for
fostering
harmonious
effective
within
systems.
Abstract
Limited
studies
exist
on
faculty
members
or
lecturers’
perception
and
behavioural
acceptance
of
artificial
intelligence
(AI)
(e.g.
ChatGPT)
for
their
students'
benefit.
Teachers
are
the
decision-makers
teaching
classroom
activities.
In
this
regard,
study
examined
use
AI-powered
tools
factors
that
influence
AI
in
learning
universities.
An
online
survey
was
conducted
using
a
cross-sectional
design,
results
were
analysed
SPSS
SmartPLS.
The
findings
revealed
more
than
two-thirds
(84%)
lecturers
willing
to
accept
students,
while
16%
stated
non-acceptance
students.
Factors
such
as
years
experience,
institutional
support
use,
attitude
towards
proved
be
significant
predictors
education.
Key
influencing
lecturers'
students
include
perceived
pedagogical
affordances,
organisational
policies
incentives,
complexity
usability
socio-cultural
context.
By
addressing
teacher
concerns
through
supportive
policies,
user-friendly
interfaces,
alignment
with
goals,
higher
education
institutions
can
create
fertile
ground
adoption.
Internet Reference Services Quarterly,
Год журнала:
2024,
Номер
unknown, С. 1 - 26
Опубликована: Ноя. 13, 2024
The
integration
of
AI
technologies
like
ChatGPT
has
transformed
academic
research,
yet
substantial
gaps
exist
in
understanding
the
implications
AI-generated
non-existent
references
literature
searches.
While
prior
studies
have
predominantly
focused
on
medical
and
geography
fields
using
descriptive
statistics,
a
systematic
investigation
into
4.0's
effectiveness
generating
accurate
within
realm
science
technology
education
remains
unexplored,
highlighting
significant
dearth
research
this
critical
area.
This
study,
therefore,
investigates
reliability
writing
utilizing
4.0.
Employing
non-experimental
correlational
design,
examines
impact
prompt
specificity
citation
accuracy
across
various
types
prompts,
including
general,
specific,
methodological,
review,
interdisciplinary
prompts.
findings
indicate
that
prompts
correlate
positively
with
references,
while
general
frequently
result
references.
Visualizations,
confusion
matrix
precision-recall
curve,
illustrate
model's
performance.
Ultimately,
study
underscores
necessity
well-structured
to
enhance
reference
quality
cautions
against
AI-induced
hallucinations
produce
which
can
significantly
undermine
credibility.
A
central
focus
of
this
study
was
the
methodology
used
to
evaluate
both
humans
and
AI
platforms,
particularly
in
terms
their
competitiveness
implications
six
key
challenges
society
resulting
from
development
increasing
use
artificial
intelligence
(AI)
technologies.
The
list
compiled
by
consulting
various
online
sources
cross-referencing
with
academics
15
countries
across
Europe
USA.
Professors,
scientific
researchers,
PhD
students
were
invited
independently
remotely
challenges.
Rather
than
contributing
another
discussion
based
solely
on
social
arguments,
paper
seeks
provide
a
logical
evaluation
framework,
moving
beyond
qualitative
discourse
incorporating
numerical
values.
pairwise
comparison
conducted
two
groups
participants
using
multicriteria
decision-making
model
known
as
analytic
hierarchy
process
(AHP).
Thirty-eight
performed
comparisons
after
they
listed
distributed
questionnaire.
same
procedure
carried
out
four
platforms—ChatGPT,
Gemini
(BardAI),
Perplexity,
DedaAI—who
responded
requests
human
participants.
results
grouped
compared,
revealing
interesting
differences
prioritization
challenges’
impact
society.
Both
agreed
highest
importance
data
privacy
security,
well
lowest
cultural
resistance,
specifically
clash
existing
norms
societal
Journal of English Teaching and Linguistics Studies (JET Li),
Год журнала:
2024,
Номер
6(1), С. 42 - 59
Опубликована: Апрель 30, 2024
This
qualitative
study
investigates
the
integration
of
Artificial
Intelligence
(AI)
in
English
Language
Teaching
(ELT)
within
university
settings,
with
a
specific
focus
on
viewpoints
and
experiences
university-level
teachers
Nepal.
The
research
was
conducted
Lumbini
Province,
Nepal,
where
14
were
purposively
selected
from
seven
constituent
campuses.
Through
unstructured
smartphone
interviews,
participants
shared
insights
AI
ELT.
findings
reveal
diverse
range
expectations
concerns
among
regarding
AI’s
role
language
instruction.
While
expressed
optimism
about
potential
to
revolutionize
learning
through
personalized
immediate
feedback,
they
also
voiced
apprehensions.
These
encompassed
job
displacement,
erosion
human
interaction,
ethical
implications
related
usage.
To
address
these
challenges,
employed
various
strategies.
They
navigated
considerations
by
raising
awareness,
engaging
reflection,
advocating
for
guidelines.
emphasizes
importance
balanced
approach
integration-one
that
harnesses
its
promises
while
addressing
pitfalls.
Responsible
inclusive
usage
education
necessitates
thoughtful
consideration
both
benefits
challenges.
Italian Journal of Medicine,
Год журнала:
2024,
Номер
18(2)
Опубликована: Апрель 15, 2024
In
hospital
settings,
effective
risk
management
is
critical
to
ensuring
patient
safety,
regulatory
compliance,
and
operational
effectiveness.
Conventional
approaches
assessment
mitigation
frequently
rely
on
manual
procedures
retroactive
analysis,
which
might
not
be
sufficient
recognize
respond
new
risks
as
they
arise.
This
study
examines
how
artificial
intelligence
(AI)
technologies
can
improve
in
healthcare
facilities,
fortifying
safety
precautions
guidelines
while
improving
the
standard
of
care
overall.
Hospitals
proactively
identify
mitigate
risks,
optimize
resource
allocation,
clinical
outcomes
by
utilizing
AI-driven
predictive
analytics,
natural
language
processing,
machine
learning
algorithms.
The
different
applications
AI
are
discussed
this
paper,
along
with
opportunities,
problems,
suggestions
for
their
use
settings.
Sustainability,
Год журнала:
2025,
Номер
17(4), С. 1411 - 1411
Опубликована: Фев. 9, 2025
Tree
growth
potential
is
crucial
for
maintaining
forest
health
and
sustainable
development.
Traditional
expert-based
assessments
of
are
inherently
subjective.
To
address
this
subjectivity
improve
accuracy,
study
proposed
a
method
using
Backpropagation
Neural
network
(BPNN)
to
classify
tree
potential.
60
Pinus
tabulaeformis
(Carr.)
Platycladus
orientalis
(Linn.)
were
selected
as
experimental
trees
in
the
Miyun
Reservoir
Water
Conservation
Forest
Demonstration
Zone
Beijing,
95
massoniana
(Lamb.)
Cunninghamia
lanceolate
Jigongshan
Nature
Reserve.
The
average
annual
ring
width
outermost
2
cm
xylem
measured
by
discs
or
increment
cores,
wood
volume
each
recent
years
calculated.
According
increment,
was
divided
into
three
levels:
strong,
medium,
weak.
Using
height,
breast
height
diameter,
crown
input
variables,
level
output
four
sub
models
species
established;
species,
generalized
model
established
these
species.
test
results
showed
that
accuracy
tabulaeformis,
orientalis,
massoniana,
68.42%,
77.78%,
86.21%,
78.95%,
respectively,
71.19%.
These
findings
suggested
employing
BPNN
viable
approach
accurately
estimating
