The
integration
of
Artificial
Intelligence
(AI)
in
dissertation
examination
presents
a
transformative
opportunity
for
higher
education
institutions
Zambia,
Rwanda,
and
Kenya.
As
student
enrollments
continue
to
rise,
universities
face
challenges
efficiently
evaluating
dissertations
while
maintaining
academic
integrity.
AI-driven
tools
offer
innovative
solutions
by
automating
tasks
such
as
plagiarism
detection,
language
quality
assessment,
contract
cheating
identification.
This
study
aims
explore
the
opportunities,
challenges,
impact
AI
adoption
assessment
across
selected
universities.
A
mixed-methods
research
design
was
employed,
incorporating
surveys,
semi-structured
interviews,
data
analysis
from
AI-assisted
evaluations
at
Copperbelt
University
(Zambia),
Jomo
Kenyatta
Agriculture
Technology
(Kenya).
Findings
indicate
that
enhances
efficiency
reducing
faculty
workload
improving
feedback
students.
However,
digital
literacy
gaps,
infrastructure
limitations,
concerns
over
AI’s
fairness
ethical
implications
hinder
full
adoption.
Despite
these
obstacles,
there
is
strong
support
among
students
integration,
provided
it
complemented
human
oversight.
concludes
has
significant
potential
revolutionize
evaluation
but
requires
investment
infrastructure,
training,
policy
frameworks
ensure
responsible
implementation.
Collaboration
universities,
policymakers,
technology
providers
essential
optimizing
upholding
rigour.
EarthArXiv (California Digital Library),
Год журнала:
2024,
Номер
unknown
Опубликована: Май 1, 2024
The
rapid
advancement
of
Large
Language
Models
(LLMs),
such
as
ChatGPT,
has
opened
new
horizons
in
the
field
Artificial
Intelligence
(AI),
revolutionizing
way
we
can
engage
with
and
disseminate
complex
information.
This
paper
presents
an
innovative
application
ChatGPT
domain
Water
Quality
(WQ)
management,
through
development
AI
Hub.
Hub
encompasses
a
suite
conversational
agents,
each
designed
to
address
different
aspects
water
quality
including
nitrogen
pollution,
local
issues,
actionable
planning
for
conservation.
These
agents
utilize
advanced
natural
language
processing
capabilities
complemented
quality-related
data,
provide
users
accurate,
up-to-date,
contextually
relevant
objective
is
empower
communities
knowledge
necessary
understand
challenges
effectively.
Our
comprehensive
evaluation
these
demonstrates
their
proficiency
delivering
valuable
insights,
overall
performance
accuracy
exceeding
89%.
underscores
potential
AI-enabled
platforms
enhancing
public
understanding
engagement
environmental
conservation
efforts.
By
bridging
gap
between
data
awareness,
sets
precedent
sustainable
management.
Recent
studies
have
showcased
the
exceptional
performance
of
LLMs
(Large
Language
Models)
on
assessment
questions
across
various
discipline
areas.
This
can
be
helpful
if
used
to
support
learning
process,
for
example
by
enabling
students
quickly
generate
and
contrast
alternative
solution
approaches.
However,
concerns
about
student
over-reliance
inappropriate
use
in
education
are
common.
Understanding
capabilities
is
essential
instructors
make
informed
decisions
question
choices
tasks.
In
CS
(Computer
Science),
previous
evaluations
focused
CS1
CS2
questions,
little
known
how
well
perform
upper-level
courses
such
as
CG
Graphics),
which
covers
a
wide
variety
concepts
types.
To
address
this
gap,
we
compiled
dataset
past
final-year
undergraduate
course
introductory
CG,
evaluated
GPT-4
dataset.
We
also
classified
different
types
questions.
found
that
tended
best
simple
mathematical
worst
requiring
creative
thinking,
those
with
complex
descriptions
and/or
images.
share
our
benchmark
community
provide
new
insights
into
context
courses.
highlight
opportunities
teaching
staff
improve
guiding
inform
around
SSRN Electronic Journal,
Год журнала:
2024,
Номер
unknown
Опубликована: Янв. 1, 2024
This
research
delves
into
the
utilization
of
advanced
artificial
intelligence
(AI),
specifically
ChatGPT
or
Bard,
to
improve
strategies
for
monitoring
and
controlling
water
air
pollution.
Given
escalating
concerns
surrounding
environmental
degradation
its
repercussions
on
public
health,
there
is
a
pressing
demand
innovative
pollution
management
techniques.
investigation
centers
harnessing
capabilities
ChatGPT,
an
language
model,
address
real-time
data
analysis,
decision-making,
engagement
challenges
within
realm
quality.
Incorporating
cutting-edge
methods
in
monitoring,
such
as
sensor
networks,
satellite
imagery,
IoT
devices,
this
aims
obtain
comprehensive
understanding
dynamics.
Nevertheless,
substantial
volume
presents
processing
extracting
meaningful
insights.
employed
intelligent
tool
proficient
comprehending
natural
queries
delivering
insightful
analyses.
integration
streamlines
interpretation
intricate
sets,
enabling
swift
decision-making
control
authorities.
Moreover,
assumes
pivotal
role
by
serving
user-friendly
interface
disseminating
information
levels,
regulatory
measures,
preventive
actions.
Through
interactive
conversations,
it
enhances
communication
between
agencies
general
public,
cultivating
awareness
encouraging
participation
initiatives.
paper
underscores
significance
collaborative
human-AI
approach
tackling
multifaceted
The
also
ethical
considerations
associated
with
AI-driven
emphasizing
importance
responsible
AI
implementation.
As
technologies
progress,
proposed
framework
contribute
ongoing
discourse
sustainable
involvement.
By
synergizing
state-of-the-art
techniques,
seeks
offer
efficacious
solution
advancing
contemporary
landscape.
SSRN Electronic Journal,
Год журнала:
2024,
Номер
unknown
Опубликована: Янв. 1, 2024
The
infusion
of
generative
artificial
intelligence
(AI)
stands
out
as
a
transformative
influence
in
civil
engineering,
reshaping
conventional
methodologies
and
elevating
the
effectiveness
precision
across
various
domains.
This
study
delves
into
nuanced
impact
ChatGPT,
potent
language
model,
key
realms
within
engineering:
Structural
Engineering,
Geotechnical
Transportation
Environmental
Water
Resources
Urban
Regional
Planning,
Materials
Coastal
Earthquake
Engineering.
Within
ChatGPT
assumes
central
role
formulating
refining
structural
designs.
By
deciphering
intricate
engineering
concepts
proposing
inventive
solutions,
assists
engineers
crafting
structures
that
not
only
exhibit
resilience
but
also
optimize
resource
utilization.
Its
proficiency
scrutinizing
extensive
datasets
delivering
insights
positions
it
an
invaluable
tool
for
augmenting
integrity
safety.
Engineering
benefits
from
ChatGPT's
aptitude
processing
interpreting
geological
geophysical
data.
Through
generation
reports
analyses,
aids
recognizing
potential
risks
suggesting
mitigation
strategies,
thereby
expediting
decision-making
geotechnical
projects.
In
realm
application
involves
streamlining
traffic
flow,
devising
intelligent
transportation
systems,
overall
infrastructure
planning.
natural
capabilities
facilitate
seamless
communication
collaboration
among
diverse
stakeholders
engaged
contributes
to
evaluation
environmental
studies,
assisting
planners
making
well-informed
decisions
prioritizing
sustainability.
Moreover,
its
capability
simulate
scenarios
formulation
effective
pollution
control
measures.
leverages
data
interpretation
modeling,
enabling
precise
predictions
water
flow
patterns
aiding
design
efficient
management
systems.
extends
contributions
where
urban
development
optimizing
land
use,
addressing
challenges
associated
with
population
growth
urbanization.
prowess
analysis
materials
enhanced
properties,
resilient
coastal
structures,
creation
earthquake-resistant
infrastructure.
research
paper
scrutinizes
how
integration
these
disciplines
heightens
efficiency
practices
unlocks
new
avenues
innovation,
sustainability,
face
evolving
challenges.
HINEF Jurnal Rumpun Ilmu Pendidikan,
Год журнала:
2024,
Номер
3(1), С. 13 - 25
Опубликована: Янв. 27, 2024
Abstract.
The
utilization
of
individually
tailored
learning
systems
facilitated
by
artificial
intelligence
(AI)
yields
substantial
advantages
in
comprehending
mathematical
concepts
among
students.
Through
the
capability
to
adapt
pace
each
student's
comprehension
level,
AI
fosters
a
personalized
and
efficacious
experience.
This
enables
students
concentrate
on
areas
demanding
more
attention,
thereby
enhancing
their
comfort
confidence
process
mathematics.
integration
this
technology
not
only
expedites
material
assimilation
but
also
establishes
an
environment
conducive
holistic
development
skills.
research
proposes
examination
that
seeks
scrutinize
perspective
intelligence,
specifically
focusing
application
ChatGPT,
mathematics
education
at
SMA
Negeri
6
Gorontalo.
methodology
employed
involves
descriptive
analysis
through
distribution
questionnaires
These
are
crafted
probe
opinions
efficacy
ChatGPT
engagement
learning.
Anticipated
outcomes
aim
furnish
profound
insights
into
repercussions
integrating
realm
secondary
school
level.
findings
revealed
disjunction
between
satisfaction
levels
Gorontalo
with
infrequent
tool
schools.
discrepancy
necessitates
thorough
evaluation
policy
adjustments,
encompassing
flexibility
smartphone
usage
regulations,
improvements
internet
connectivity,
proactive
approach
enhance
student
participation
process.
Based
results,
it
appears
there
is
gap
level
use
frequency
which
less
frequent
school.
Although
some
stated
they
were
satisfied
using
majority
indicated
rarely
used
application.
Therefore,
concluded
several
barriers
or
inhibiting
factors
may
influence
low
environment.
Abstrak.
Pemanfaatan
sistem
pembelajaran
yang
dirancang
secara
individual
difasilitasi
oleh
kecerdasan
buatan
menghasilkan
keuntungan
besar
dalam
pemahaman
konsep
matematika
di
kalangan
siswa.
Melalui
kemampuan
untuk
menyesuaikan
kecepatan
dengan
tingkat
setiap
siswa,
menumbuhkan
pengalaman
belajar
dipersonalisasi
dan
efektif.
Hal
ini
memungkinkan
siswa
berkonsentrasi
pada
bidang
memerlukan
perhatian
lebih,
sehingga
meningkatkan
kenyamanan
kepercayaan
diri
mereka
proses
matematika.
Integrasi
teknologi
tidak
hanya
mempercepat
asimilasi
materi
tetapi
juga
menciptakan
lingkungan
kondusif
bagi
pengembangan
keterampilan
holistik.
Penelitian
mengusulkan
suatu
kajian
berupaya
mencermati
perspektif
buatan,
khususnya
berfokus
penerapan
pendidikan
Metodologi
penelitian
digunakan
meliputi
analisis
deskriptif.
dibuat
menyelidiki
pendapat
tentang
kemanjuran
keterlibatan
Hasil
diharapkan
bertujuan
memberikan
wawasan
mendalam
dampak
pengintegrasian
sekolah
menengah.
Temuan
menunjukkan
adanya
perbedaan
antara
kepuasan
terhadap
jarangnya
pemanfaatan
alat
tersebut
sekolah.
Kesenjangan
evaluasi
menyeluruh
penyesuaian
kebijakan,
mencakup
fleksibilitas
peraturan
penggunaan
ponsel
cerdas,
peningkatan
konektivitas
internet,
pendekatan
proaktif
partisipasi
ke
pembelajaran.
Berdasarkan
hasil
penelitian,
terlihat
kesenjangan
frekuensi
kurang
sering
Meskipun
sebagian
menyatakan
puas
namun
mayoritas
mengindikasikan
bahwa
jarang
menggunakan
aplikasi
tersebut.
Oleh
karena
itu,
disimpulkan
terdapat
beberapa
hambatan
atau
faktor
penghambat
mungkin
mempengaruhi
rendahnya
ACM Transactions on Computing Education,
Год журнала:
2024,
Номер
24(3), С. 1 - 56
Опубликована: Июнь 20, 2024
The
recent
integration
of
visual
capabilities
into
Large
Language
Models
(LLMs)
has
the
potential
to
play
a
pivotal
role
in
science
and
technology
education,
where
elements
such
as
diagrams,
charts,
tables
are
commonly
used
improve
learning
experience.
This
study
investigates
performance
ChatGPT-4
Vision,
OpenAI’s
most
advanced
model
at
time
was
conducted,
on
Bachelor
Computer
Science
section
Brazil’s
2021
National
Undergraduate
Exam
(ENADE).
By
presenting
with
exam’s
open
multiple-choice
questions
their
original
image
format
allowing
for
reassessment
response
differing
answer
keys,
we
were
able
evaluate
model’s
reasoning
self-reflecting
large-scale
academic
assessment
involving
textual
content.
Vision
significantly
outperformed
average
exam
participant,
positioning
itself
within
top
10
best
score
percentile.
While
it
excelled
that
incorporated
elements,
also
encountered
challenges
question
interpretation,
logical
reasoning,
acuity.
A
positive
correlation
between
distribution
human
participants
suggests
multimodal
LLMs
can
provide
useful
tool
testing
refinement.
However,
involvement
an
independent
expert
panel
review
cases
disagreement
key
revealed
some
poorly
constructed
containing
vague
or
ambiguous
statements,
calling
attention
critical
need
improved
design
future
exams.
Our
findings
suggest
while
shows
promise
evaluations,
oversight
remains
crucial
verifying
accuracy
ensuring
fairness
high-stakes
educational
paper’s
research
materials
publicly
available
https://github.com/nabormendonca/gpt-4v-enade-cs-2021
.
Computer Applications in Engineering Education,
Год журнала:
2024,
Номер
32(6)
Опубликована: Июль 14, 2024
Abstract
The
launch
of
Generative
Pretrained
Transformer
(ChatGPT)
at
the
end
2022
generated
large
interest
in
possible
applications
artificial
intelligence
(AI)
science,
technology,
engineering,
and
mathematics
(STEM)
education
among
STEM
professions.
As
a
result
many
questions
surrounding
capabilities
generative
AI
tools
inside
outside
classroom
have
been
raised
are
starting
to
be
explored.
This
study
examines
ChatGPT
within
discipline
mechanical
engineering.
It
aims
examine
use
cases
pitfalls
such
technology
professional
settings.
was
presented
with
set
from
junior‐
senior‐level
engineering
exams
provided
private
university,
as
well
practice
for
Fundamentals
Engineering
(FE)
exam
responses
two
models,
one
free
paid
subscription,
were
analyzed.
paper
found
that
subscription
model
(GPT‐4,
May
12,
2023)
greatly
outperformed
version
(GPT‐3.5,
2023),
achieving
76%
correct
versus
51%
correct,
but
limitation
text
only
input
on
both
models
makes
neither
likely
pass
FE
exam.
results
confirm
findings
literature
regard
types
errors
made
by
ChatGPT.
due
its
inconsistency
tendency
confidently
produce
incorrect
answers,
tool
is
best
suited
users
expert
knowledge.
Hydrology,
Год журнала:
2024,
Номер
11(9), С. 148 - 148
Опубликована: Сен. 11, 2024
Large
Language
Models
(LLMs)
combined
with
visual
foundation
models
have
demonstrated
significant
advancements,
achieving
intelligence
levels
comparable
to
human
capabilities.
This
study
analyzes
the
latest
Multimodal
LLMs
(MLLMs),
including
Multimodal-GPT,
GPT-4
Vision,
Gemini,
and
LLaVa,
a
focus
on
hydrological
applications
such
as
flood
management,
water
level
monitoring,
agricultural
discharge,
pollution
management.
We
evaluated
these
MLLMs
hydrology-specific
tasks,
testing
their
response
generation
real-time
suitability
in
complex
real-world
scenarios.
Prompts
were
designed
enhance
models’
inference
capabilities
contextual
comprehension
from
images.
Our
findings
reveal
that
Vision
exceptional
proficiency
interpreting
data,
providing
accurate
assessments
of
severity
quality.
Additionally,
showed
potential
various
applications,
drought
prediction,
streamflow
forecasting,
groundwater
wetland
conservation.
These
can
optimize
resource
management
by
predicting
rainfall,
evaporation
rates,
soil
moisture
levels,
thereby
promoting
sustainable
practices.
research
provides
valuable
insights
into
advanced
AI
addressing
challenges
improving
decision-making
