Generative AI: A systematic review using topic modelling techniques
Data and Information Management,
Год журнала:
2024,
Номер
8(2), С. 100066 - 100066
Опубликована: Фев. 15, 2024
Generative
artificial
intelligence
(GAI)
is
a
rapidly
growing
field
with
wide
range
of
applications.
In
this
paper,
thorough
examination
the
research
landscape
in
GAI
presented,
encompassing
comprehensive
overview
prevailing
themes
and
topics
within
field.
The
study
analyzes
corpus
1319
records
from
Scopus
spanning
1985
to
2023
comprises
journal
articles,
books,
book
chapters,
conference
papers,
selected
working
papers.
analysis
revealed
seven
distinct
clusters
research:
image
processing
content
analysis,
generation,
emerging
use
cases,
engineering,
cognitive
inference
planning,
data
privacy
security,
Pre-Trained
Transformer
(GPT)
academic
paper
discusses
findings
identifies
some
key
challenges
opportunities
research.
concludes
by
calling
for
further
GAI,
particularly
areas
explainability,
robustness,
cross-modal
multi-modal
interactive
co-creation.
also
highlights
importance
addressing
security
responsible
GAI.
Язык: Английский
Evaluation criteria for artificial intelligence
New Directions for Evaluation,
Год журнала:
2023,
Номер
2023(178-179), С. 123 - 134
Опубликована: Июнь 1, 2023
Abstract
Criteria
identify
and
define
the
aspects
on
which
what
we
evaluate
is
judged
play
a
central
role
in
evaluation
practice.
While
work
use
of
AI
burgeoning,
at
time
writing,
set
criteria
to
consider
evaluating
has
not
been
proposed.
As
first
step
this
direction,
Teasdale's
Domains
Framework
was
used
as
lens
through
critically
read
articles
included
special
issue.
This
resulted
identification
eight
domains
for
evaluation.
Three
these
relate
conceptualization
implementation
Five
are
focused
outcomes,
specifically
those
stemming
from
More
needed
further
deliberate
possible
Язык: Английский
Finding a safe zone in the highlands: Exploring evaluator competencies in the world of AI
New Directions for Evaluation,
Год журнала:
2023,
Номер
2023(178-179), С. 11 - 22
Опубликована: Июнь 1, 2023
Abstract
Since
the
public
launch
of
ChatGPT
in
November
2022,
disciplines
across
globe
have
grappled
with
questions
about
how
emerging
artificial
intelligence
will
impact
their
fields.
In
this
article
I
explore
a
set
foundational
concepts
(AI),
then
apply
them
to
field
evaluation
broadly,
and
American
Evaluation
Association's
evaluator
competencies
more
specifically.
Given
recent
developments
narrow
AI,
two
potential
frameworks
for
considering
which
are
most
likely
be
impacted—and
potentially
replaced—by
AI
tools.
Building
on
Moravec's
Landscape
Human
Competencies
Lee's
Risk
Replacement
Matrix
create
an
exploratory
Evaluator
Evaluation‐Specific
help
conceptualize
may
contribute
long‐term
sustainability
field.
Overall,
argue
that
interpersonal,
contextually‐responsive
aspects
work—in
contrast
technical,
program
management,
or
methodological
field—may
least
impacted
replaced
by
AI.
As
such,
these
we
continue
emphasize,
both
day‐to‐day
our
operations,
training
new
evaluators.
This
is
intended
starting
point
discussions
throughout
remainder
issue.
Язык: Английский
Relational Systems Evaluation rubrics as tools for building and measuring evaluation capacity
New Directions for Evaluation,
Год журнала:
2024,
Номер
2024(183), С. 59 - 79
Опубликована: Сен. 1, 2024
Abstract
Evaluation
capacity
building
(ECB)
is
still
an
emerging
area
of
study
in
the
field
evaluation.
The
purpose
ECB
to
assist
program
practitioners
with
implementing
higher‐quality
evaluation;
however,
we
need
better
tools
and
resources
effectively
assess
efforts.
Existing
measures
typically
depend
on
self‐report
as
opposed
assessing
artifacts
training.
Among
few
non‐self‐report
that
support
assessment
efforts
are
Relational
Systems
rubrics
designed
evaluate
logic
models,
pathway
evaluation
plans.
These
were
first
developed
tested
several
years
ago.
current
update
reflect
knowledge.
updated
have
good
excellent
inter‐rater
reliability
high
internal
consistency.
results
this
contribute
by
providing
measurement
for
quality
artifacts.
can
also
be
used
organizations
funders
who
a
systematic
approach
(and
comparing)
plans
visual
theory
change
models
(e.g.,
models).
Язык: Английский
The Role of Artificial Intelligence-Based Technology with ChatGPT as an Educational Learning Media Innovation in Indonesia
International Journal of Multidisciplinary Sciences and Arts,
Год журнала:
2023,
Номер
2(2), С. 235 - 241
Опубликована: Дек. 22, 2023
ChatGPT
with
OpenAI
is
an
artificial
intelligence-based
machine
technology
that
trained
to
imitate
human
conversation
using
NLP
(Natural
Language
Processing)
technology.
can
be
used
produce
quite
scientific
writing
good
and
effective
formulation
techniques.
With
the
help
of
technology,
ChatGpt
innovate
in
creating
learning
media
tools
such
as
RPS
(Semester
Learning
Plans)
textbooks
for
teaching
staff,
especially
at
tertiary
level.
The
aim
this
research
clarify
role
intelligence
world
education
method
uses
qualitative
methods.
results
experiments
carried
out
by
researchers
produced
+
693
words
writing,
number
still
developed
further.
time
speed
only
requires
5-7
minutes
complete
experiment
includes
document
processing
from
ChatGPT.In
conclusion,
useful,
namely
teaching,
community
service.
So
presence
a
tool
works,
(RPS)
textbooks.
Another
benefit
ChatGpt,
developing
competencies
(skills)
staff
(lecturers),
carry
Tri
Dharma
Higher
Education
opens
up
opportunities
utilize
AI
chatbot
Indonesia
Язык: Английский