Medical Teacher,
Год журнала:
2024,
Номер
46(10), С. 1258 - 1271
Опубликована: Авг. 8, 2024
Generative
Artificial
Intelligence
(GenAI)
caught
Health
Professions
Education
(HPE)
institutions
off-guard,
and
they
are
currently
adjusting
to
a
changed
educational
environment.
On
the
horizon,
however,
is
BMC Medical Education,
Год журнала:
2025,
Номер
25(1)
Опубликована: Фев. 20, 2025
Artificial
Intelligence
is
currently
being
applied
in
healthcare
for
diagnosis,
decision-making
and
education.
ChatGPT-4o,
with
its
advanced
language
problem-solving
capabilities,
offers
an
innovative
alternative
as
a
virtual
standardised
patient
clinical
training.
Intern
physicians
are
expected
to
develop
case
management
skills
such
problem-solving,
reasoning
crisis
management.
In
this
study,
ChatGPT-4o's
served
medical
interns
on
This
study
aimed
evaluate
intern
physicians'
competencies
management;
reasoning,
explore
the
impact
potential
of
ChatGPT-4o
viable
tool
assessing
these
competencies.
used
simultaneous
triangulation
design,
integrating
quantitative
qualitative
data.
Conducted
at
Aydın
Adnan
Menderes
University,
21
sixth-year
students,
simulated
realistic
interactions
requiring
Data
were
gathered
through
self-assessment
survey,
semi-structured
interviews,
observations
students
during
process.
Analyses
included
Pearson
correlation,
Chi-square,
Kruskal-Wallis
tests,
content
analysis
conducted
data
using
MAXQDA
software
coding.
According
findings,
observation
survey
scores
positively
correlated.
There
was
significant
gap
between
participants'
actual
performance,
indicating
discrepancies
self-perceived
versus
real
competence.
Participants
reported
feeling
inadequate
their
experienced
time
pressure.
They
satisfied
Intelligence-powered
process
willing
continue
similar
practices.
engaged
uniform
experience.
Although
participants
satisfied,
application
sometimes
negatively
affected
due
disconnection
problems
processing
challenges.
successfully
interactions,
providing
controlled
environment
without
risking
harm
patients
practicing
some
technological
challenges
limited
effectiveness,
it
useful,
cost-effective
accessible.
It
thought
that
will
be
better
supported
acquiring
varied
scenarios
method.
Not
applicable.
JMIR Medical Education,
Год журнала:
2025,
Номер
11, С. e65108 - e65108
Опубликована: Март 5, 2025
Advancements
in
ChatGPT
are
transforming
medical
education
by
providing
new
tools
for
assessment
and
learning,
potentially
enhancing
evaluations
doctors
improving
instructional
effectiveness.
This
study
evaluates
the
performance
consistency
of
ChatGPT-3.5
Turbo
ChatGPT-4o
mini
solving
European
Portuguese
examination
questions
(2023
National
Examination
Access
to
Specialized
Training;
Prova
Nacional
de
Acesso
à
Formação
Especializada
[PNA])
compares
their
human
candidates.
was
tested
on
first
part
(74
questions)
July
18,
2024,
second
19,
2024.
Each
model
generated
an
answer
using
its
natural
language
processing
capabilities.
To
test
consistency,
each
asked,
"Are
you
sure?"
after
answer.
Differences
between
responses
were
analyzed
McNemar
with
continuity
correction.
A
single-parameter
t
compared
models'
Frequencies
percentages
used
categorical
variables,
means
CIs
numerical
variables.
Statistical
significance
set
at
P<.05.
achieved
accuracy
rate
65%
(48/74)
2023
PNA
examination,
surpassing
Turbo.
outperformed
candidates,
while
had
a
more
moderate
performance.
highlights
advancements
potential
models
education,
emphasizing
need
careful
implementation
teacher
oversight
further
research.
Asian Education and Development Studies,
Год журнала:
2024,
Номер
13(5), С. 412 - 431
Опубликована: Июль 7, 2024
Purpose
This
is
a
dual-focused
study
that
anticipates
qualitatively
and
quantitatively
examining
the
literature
on
recently
initiated
revolutionizing
concept
of
ChatGPT
in
education
by
performing
Systematic
Literature
Review
(SLR)
bibliometric
analysis.
Current
analyzed
eight
research
questions:
(1)
main
information
annual
scientific
publications
education,
(2)
pioneer
authors
collaborative
exploring
(3)
authors'
productivity
through
Lotka’s
Law
Authors’
Scientific
Productivity,
(4)
most
pertinent
sources
how
are
clustered
Bradford’s
Scattering,
(5)
related,
cited
countries
nature
international
collaborations
(6)
relevant
(7)
occurring
trending
keywords
empirical
studies
(8)
themes
areas
for
future
investigations
education.
Design/methodology/approach
The
current
was
designed
as
SLR
analysis,
extracting
articles
from
Scopus
database
utilizing
both
Biblioshiny
VOSviewer
software
advanced
mapping
visualizations
via
quantitative
qualitative
analysis
approaches.
Findings
results
indicated
progressively
evolving
worldwide
generating
45
2023
to
2024
(May).
USA,
China,
Indonesia
productive
have
published
systems,
AI,
students,
educational
computing,
human
experiments,
teaching,
status,
chatbots,
generative
academic
integrity,
technology,
technology
acceptance
directions
field
Originality/value
analysis’s
outcomes
will
enhance
area
with
theoretical
practical
implications
benefit
teachers,
policymakers,
regulators
higher
sectors,
government,
general
public
effective
utilization
Science Editing,
Год журнала:
2024,
Номер
11(2), С. 96 - 106
Опубликована: Авг. 20, 2024
While
generative
artificial
intelligence
(AI)
technology
has
become
increasingly
competitive
since
OpenAI
introduced
ChatGPT,
its
widespread
use
poses
significant
ethical
challenges
in
research.
Excessive
reliance
on
tools
like
ChatGPT
may
intensify
concerns
scholarly
articles.
Therefore,
this
article
aims
to
provide
a
comprehensive
narrative
review
of
the
issues
associated
with
using
AI
academic
writing
and
inform
researchers
current
trends.
Our
methodology
involved
detailed
examination
literature
related
research
We
conducted
searches
major
databases
identify
additional
relevant
articles
cited
literature,
from
which
we
collected
analyzed
papers.
identified
categorized
into
problems
faced
by
authors
nonacademic
platforms
detection
acceptance
AI-generated
content
reviewers
editors.
explored
eight
specific
highlighted
thorough
five
key
topics
ethics.
Given
that
often
do
not
disclose
their
training
data
sources,
there
is
substantial
risk
unattributed
plagiarism.
must
verify
accuracy
authenticity
before
incorporating
it
article,
ensuring
adherence
principles
integrity
ethics,
including
avoidance
fabrication,
falsification,
UNSTRUCTURED
Purpose:
This
systematic
review
examines
the
potential
of
ChatGPT
as
a
tool
in
medical
education,
focusing
on
its
role
enhancing
learning
experiences,
student
performance,
and
critical
thinking
skills.
ChatGPT's
integration
aims
to
address
shortage
faculty
resources
create
personalized,
interactive
experiences
for
students.
Methods:
Following
PRISMA
AMSTAR
guidelines,
we
conducted
across
four
databases
(Embase,
PubMed,
Web
Science,
Cochrane
Library)
up
October
2024.
Data
from
seven
studies
various
disciplines
educational
levels
were
included,
analyzed
descriptively,
evaluated
quality.
Results:
Seven
demonstrated
that
ChatGPT-assisted
education
improves
academic
clinical
skills,
SDL
capabilities.
Notably,
students
using
showed
higher
scores
short-term
assessments
final
exams.
4.0,
compared
version
3.5,
provided
enhanced
case
generation
communication
skills
training.
Additionally,
ChatGPT-supported
boosted
students'
SDL,
thinking,
engagement
levels,
while
helping
educators
manage
instructional
workload.
Conclusion:
study
highlights
ChatGPT’s
strong
significantly
self-directed
learning,
thinking.
It
underscores
personalized
supporting
development
essential
competencies.
4.0
outperforms
3.5
with
improved
abilities.
Research Square (Research Square),
Год журнала:
2025,
Номер
unknown
Опубликована: Март 13, 2025
Abstract
Large
language
models
(LLMs)
show
potential
for
medical
education,
but
their
domain-specific
capabilities
need
systematic
evaluation.
This
study
presents
a
comparative
assessment
of
thirteen
LLMs
in
urinary
system
histology
education.
Using
multi-dimensional
framework,
we
evaluated
across
two
tasks:
answering
65
validated
multiple-choice
questions
(MCQs)
and
generating
clinical
scenarios
with
items.
For
MCQ
performance,
assessed
accuracy
along
explanation
quality
through
relevance
comprehensiveness
metrics.
scenario
generation,
Quality,
Complexity,
Relevance,
Correctness,
Variety
dimensions.
Performance
varied
substantially
tasks,
ChatGPT-o1
achieving
highest
(96.31
±
17.85%)
Claude-3.5
demonstrating
superior
generation
(91.4%
maximum
possible
score).
All
significantly
outperformed
random
guessing
large
effect
sizes.
Statistical
analyses
revealed
significant
differences
consistency
multiple
attempts
dimensional
most
showing
higher
Correctness
than
Quality
scores
generation.
Term
frequency
analysis
content
imbalances
all
models,
overemphasis
certain
anatomical
structures
complete
omission
others.
Our
findings
demonstrate
that
while
considerable
promise
reliable
implementation
requires
matching
specific
to
appropriate
educational
implementing
verification
mechanisms,
recognizing
current
limitations
pedagogically
balanced
content.
