Brilliance Research of Artificial Intelligence,
Год журнала:
2023,
Номер
3(2), С. 252 - 261
Опубликована: Ноя. 17, 2023
The
increasing
trend
of
e-commerce
users
has
not
been
matched
by
customer
satisfaction
in
the
shopping
process.
Indonesia
highest
level
dissatisfaction
compared
to
other
ASEAN
countries.
Although
chatbot
technology
used
as
an
aid
optimize
services,
still
occurs
with
regard
agility,
service
assurance,
reliability,
scalability
and
security.
purpose
this
study
is
determine
services
providing
satisfaction.
research
approach
uses
quantitative
explantory
survey
method.
population
online
shop
using
rondom
sampling,
175
respondents
were
collected.
Assisted
PLS
SEM
analysis
tool.
results
show
that
social
orientation
contribute
Likewise,
personification
makes
a
positive
contribution
International Transactions in Operational Research,
Год журнала:
2024,
Номер
unknown
Опубликована: Июль 31, 2024
Abstract
Artificial
intelligence
(AI)
as
a
disruptive
technology
is
not
new.
However,
its
recent
evolution,
engineered
by
technological
transformation,
big
data
analytics,
and
quantum
computing,
produces
conversational
generative
AI
(CGAI/GenAI)
human‐like
chatbots
that
disrupt
conventional
operations
methods
in
different
fields.
This
study
investigates
the
scientific
landscape
of
CGAI
human–chatbot
interaction/collaboration
evaluates
use
cases,
benefits,
challenges,
policy
implications
for
multidisciplinary
education
allied
industry
operations.
The
publications
trend
showed
just
4%
(
n
=
75)
occurred
during
2006–2018,
while
2019–2023
experienced
astronomical
growth
1763
or
96%).
prominent
cases
(e.g.,
ChatGPT)
teaching,
learning,
research
activities
computer
science
(multidisciplinary
AI;
32%),
medical/healthcare
(17%),
engineering
(7%),
business
fields
(6%).
intellectual
structure
shows
strong
collaboration
among
eminent
sources
business,
information
systems,
other
areas.
thematic
highlights
including
improved
user
experience
human–computer
interaction,
programs/code
generation,
systems
creation.
Widespread
usefulness
teachers,
researchers,
learners
includes
syllabi/course
content
testing
aids,
academic
writing.
concerns
about
abuse
misuse
(plagiarism,
integrity,
privacy
violations)
issues
misinformation,
danger
self‐diagnoses,
patient
applications
are
prominent.
Formulating
strategies
policies
to
address
potential
challenges
teaching/learning
practice
priorities.
Developing
discipline‐based
automatic
detection
GenAI
contents
check
proposed.
In
operational/operations
areas,
proper
CGAI/GenAI
integration
with
modeling
decision
support
requires
further
studies.
Procedia Computer Science,
Год журнала:
2024,
Номер
239, С. 1124 - 1131
Опубликована: Янв. 1, 2024
Universities
gain
a
competitive
advantage
by
deliberately
improving
overall
service,
student,
faculty,
and
staff
experience,
leading
to
attractiveness,
retention,
improved
outcomes.
Quality
services
are
achieved
partly
addressing
employee
satisfaction,
specifically
in
the
work
environment.
This
paper
presents
prototype
study
of
virtual
university
support
agent,
system
grounded
Large
Language
Model
(LLM)
engineered
address
inquiries
from
students,
faculty
related
student
handbook.
The
investigates
integration
generative
artificial
intelligence
natural
conversation
properties
inherent
LLMs
overcome
customer
service
shortcomings
identified
previous
chatbot
applications.
LLMs'
susceptibility
'hallucination'
is
mitigated
through
combined
approach
few-shot
learning
chain
thought
libraries
training
phase.
information
core
this
comprises
handbook
PDF
files,
which
an
algorithm
extracts
structures
data
be
utilized
LLM.
As
result,
agent
facilitates
viable
Q&A
interface
for
administrators
inquire
about
guidelines
policies.
Journal of Soft Computing Exploration,
Год журнала:
2023,
Номер
4(4), С. 186 - 194
Опубликована: Ноя. 2, 2023
This
research
relates
to
the
development
of
a
chatbot
application
help
lecturers
and
students
in
D3
Informatics
Engineering
study
program
remember
schedules
activities
answer
questions
related
program.
The
background
this
is
due
difficulties
managing
activity
answering
that
come
from
effectively
efficiently.
shows
having
reminder
assistant
applications
will
be
very
useful
for
programs.
purpose
develop
bot
can
at
Diploma
3
method
used
Waterfall
system
method,
which
type
System
Development
Life
Cycle
(SDLC).
follows
sequential
stages
starting
requirements
analysis,
design,
implementation,
testing
maintenance.
In
study,
was
developed
using
Golang
programming
language,
Codeigniter4
as
dashboard
platform.
BIO Web of Conferences,
Год журнала:
2024,
Номер
86, С. 01099 - 01099
Опубликована: Янв. 1, 2024
This
research
provides
a
data-driven
assessment
of
dynamic
communication
in
emergency
response,
highlighting
important
findings
supported
by
actual
data.
In
comparison
to
police
officers
law
enforcement
situations,
EMTs
responded
medical
crises
25%
quicker,
according
the
response
time
research.
When
it
came
accuracy,
firemen
performed
at
96%
accuracy
rate
during
fire
compared
91%
circumstances.
there
was
3%
improvement
completeness
information
shared
incidents.
Additionally,
accident
officers'
efficacy
occurrences
2.3%
greater.
These
results
highlight
how
crucial
customized
plans,
insights,
and
technology
training
integration
are
maximizing
systems.
Frontiers in Education,
Год журнала:
2024,
Номер
9
Опубликована: Ноя. 13, 2024
Objective
This
study
aims
to
evaluate
the
influence
of
using
a
chatbot-based
conversational
agent,
named
ODAbot,
on
adaptability
first-year
students
at
private
university
in
Peru.
Methods
The
design
this
was
pre-experimental
with
quantitative
approach.
sample
consisted
53
who
participated
research
during
March
and
April
2024.
Participants
completed
pre-test
post-test
questionnaires
assess
their
life
before
after
interacting
ODAbot.
Additionally,
user
experience
questionnaire
used
measure
satisfaction
chatbot
interaction.
Data
were
analyzed
Wilcoxon
test
determine
statistical
significance
results.
Results
results
showed
that
use
ODAbot
had
significant
impact
students’
adaptability,
especially
social
dimension
(
p
=
0.000),
while
no
differences
found
institutional
0.124).
positive,
reporting
ease
navigation
understanding
responses
provided
by
chatbot.
Conclusion
A
notable
improvement
recorded
dimension,
promoting
peer
integration,
as
well
academic
where
expressed
greater
information
provided.
However,
observed
dimension.
Overall,
implementation
chatbots
presents
promising
opportunity
improve
ensure
quality
educational
experience.
Interactive Learning Environments,
Год журнала:
2024,
Номер
unknown, С. 1 - 27
Опубликована: Дек. 6, 2024
The
present
review
examined
articles
published
in
the
Web
of
Science
and
Scopus
databases
from
2019
to
2023
on
use
chatbots
higher
education
(HE),
focusing
research
methodologies,
acceptance
factors,
platforms,
goals,
communication
channels,
application
domains,
issues.
results
showed
that
HE
has
gained
momentum
recent
years.
Most
studies
used
quantitative
methods,
followed
by
mixed
methods.
Chatbots
were
primarily
created
web
platforms
for
text-based
communication,
though
few
explored
hybrid
channels
(text,
voice,
images)
enhanced
interaction.
are
teaching,
customer
service,
mental
health
support
HE.
Users'
behavioral
intention,
perceived
usefulness,
ease
or
design,
interactivity,
social
influence,
service
quality,
digital
literacy,
privacy
security,
ethical
issues
some
factors
concerns
influence
chatbot
Common
correlational
cause-effect
studies,
learner
perceptions,
technology
acceptance,
engagement,
learning
performance,
user
satisfaction,
self-efficacy.
However,
areas
such
as
cognitive
load
higher-order
thinking
remain
underexplored.
Suggestions
improving
enhance
teaching
address
offered
researchers,
educators,
developers.
Briefings in Bioinformatics,
Год журнала:
2024,
Номер
26(1)
Опубликована: Ноя. 22, 2024
Abstract
Ribosome
profiling
(Ribo-seq)
provides
transcriptome-wide
insights
into
protein
synthesis
dynamics,
yet
its
analysis
poses
challenges,
particularly
for
nonbioinformatics
researchers.
Large
language
model–based
chatbots
offer
promising
solutions
by
leveraging
natural
processing.
This
review
explores
their
convergence,
highlighting
opportunities
synergy.
We
discuss
challenges
in
Ribo-seq
and
how
mitigate
them,
facilitating
scientific
discovery.
Through
case
studies,
we
illustrate
chatbots’
potential
contributions,
including
data
result
interpretation.
Despite
the
absence
of
applied
examples,
existing
software
underscores
value
large
model.
anticipate
pivotal
role
future
analysis,
overcoming
limitations.
Challenges
such
as
model
bias
privacy
require
attention,
but
emerging
trends
promise.
The
integration
models
holds
immense
advancing
translational
regulation
gene
expression
understanding.
