A Scoping Survey of ChatGPT in Mathematics Education
Digital Experiences in Mathematics Education,
Год журнала:
2025,
Номер
unknown
Опубликована: Фев. 17, 2025
Язык: Английский
Can Generative AI and ChatGPT Break Human Supremacy in Mathematics and Reshape Competence in Cognitive-Demanding Problem-Solving Tasks?
Journal of Intelligence,
Год журнала:
2025,
Номер
13(4), С. 43 - 43
Опубликована: Апрель 2, 2025
This
study
investigates
the
potential
of
generative
artificial
intelligence
tools
in
addressing
cognitive
challenges
encountered
by
humans
during
problem-solving.
The
performance
ChatGPT-4o
and
GPT-4
models
NAEP
mathematics
assessments
was
evaluated,
particularly
relation
to
demands
placed
on
students.
Sixty
assessment
tasks,
coded
field
experts,
were
analyzed
within
a
framework
complexity.
provided
responses
each
question,
which
then
evaluated
using
NAEP’s
scoring
criteria.
study’s
dataset
average
scores
students
who
answered
correctly
item-wise
response
percentages.
results
indicated
that
outperformed
most
individual
items
assessment.
Furthermore,
as
demand
increased,
higher
required
answer
questions
correctly.
trend
observed
across
4th,
8th,
12th
grades,
though
did
not
demonstrate
statistically
significant
sensitivity
increased
at
12th-grade
level.
Язык: Английский
Role of Mathematics Teachers in Learner’s Diversity Using AI Tools
Опубликована: Фев. 26, 2025
Язык: Английский
A scoping survey of ChatGPT in mathematics education
Research Square (Research Square),
Год журнала:
2024,
Номер
unknown
Опубликована: Сен. 26, 2024
Abstract
This
initial
article
of
the
Special
Issue
on
Chat
GPT
in
mathematics
education
is
two
parts:
(1)
a
report
scoping
review
study
that
provides
background
to
articles
Issue;
and
(2)
editorial
affords
glance
at
seven
Issue.
Язык: Английский
Using large language models to support pre-service teachers mathematical reasoning—an exploratory study on ChatGPT as an instrument for creating mathematical proofs in geometry
Frontiers in Artificial Intelligence,
Год журнала:
2024,
Номер
7
Опубликована: Окт. 23, 2024
In
this
exploratory
study,
the
potential
of
large
language
models
(LLMs),
specifically
ChatGPT
to
support
pre-service
primary
education
mathematics
teachers
in
constructing
mathematical
proofs
geometry
is
investigated.
Utilizing
theoretical
framework
instrumental
genesis,
prior
experiences
students
with
LLMs,
their
beliefs
about
operating
principle
and
interactions
chatbot
are
analyzed.
Using
qualitative
content
analysis,
inductive
categories
for
these
aspects
formed.
Results
indicate
that
had
limited
LLMs
used
them
predominantly
applications
not
specific.
Regarding
beliefs,
most
show
only
superficial
knowledge
technology
misconceptions
common.
The
analysis
showed
multiple
types
parts
mathematics-specific
prompts
patterns
on
three
different
levels
from
single
whole
chat
interactions.
Язык: Английский
Communicative AI Agents in Mathematical Task Design: A Qualitative Study of GPT Network Acting as a Multi-professional Team
Digital Experiences in Mathematics Education,
Год журнала:
2024,
Номер
unknown
Опубликована: Окт. 24, 2024
Abstract
This
study
explores
the
application
of
communicative
AI
agents,
specifically
a
network
customized
generative
pretrained
transformer
in
designing
mathematical
tasks.
It
focuses
on
how
these
functioning
as
multi-professional
team,
can
perform
task
design
(concerning
collection
activities
and
not
curriculum
materials/textbooks)
through
collaborative
context-aware
communication.
Concentrating
four
perspectives—mathematical
depth,
language
sensitivity,
natural
differentiation,
competence
orientation—four
different
agents
were
instructed
to
evaluate
modify
six
tasks
based
individual
research
knowledge
bases.
In
consensus-seeking
process,
connected
via
chat
chain,
prompting
multiple
iterations
The
output
(six
AI-modified
tasks)
was
then
evaluated
by
in-service
teachers
human
experts
making
them
choose
blindly
between
original
analyzing
additional
comments
their
decisions
qualitative
content
analysis.
Furthermore,
rated
multidimensional
Likert
scale.
results
indicate
that
for
tasks,
achieving
balance
substantial
text
generation
precise
formulation
is
crucial
always
found
GPT
output.
At
same
time,
combination
able
enrich
with
potential
solution
approaches
specific
calls
action.
Язык: Английский
Influence of Prompts Structure on the Perception and Enhancement of Learning through LLMs in Online Educational Contexts
IntechOpen eBooks,
Год журнала:
2024,
Номер
unknown
Опубликована: Окт. 15, 2024
This
research
examines
how
the
structure
of
prompts
impacts
perceived
depth
and
accuracy
responses
generated
by
generative
Large
Language
Models
(LLMs)
in
educational
settings.
It
specifically
investigates
prompt
design
influences
students’
learning
experiences.
The
study
involved
an
experiment
with
183
students
enrolled
a
mandatory
Business
Administration
course
at
Universitat
Oberta
de
Catalunya
(UOC).
Data
from
were
analyzed
using
both
qualitative
quantitative
methods.
results
show
that
well-structured
significantly
improve
perception
GenAI-generated
responses,
leading
to
more
effective
process.
underscores
crucial
role
maximizing
effectiveness
GenAI.
findings
suggest
thoughtful
can
enhance
outcomes,
although
study’s
limited
sample
size
context-specific
nature
may
restrict
generalizability
results.
contributes
field
highlighting
importance
harnessing
GenAI
tools
for
improvement.
Язык: Английский