Deleted Journal,
Год журнала:
2025,
Номер
3(1), С. 129 - 137
Опубликована: Фев. 5, 2025
There
are
several
areas
where
self-learning
AI
is
actively
used.
Machine
learning
and
deep
allow
you
to
identify
patterns
improve
performance.
Algorithms
such
as
neural
networks
can
adapt
based
on
experience.
Self-learning
GPTs
used
dialogue
with
humans.
Computer
vision
recognizes
classifies
images.
Recommender
systems
analyze
user
preferences
offer
personalized
solutions.
Adaptive
robotic
industrial
control
optimize
processes
by
adapting
changing
conditions
data.
intelligent
help
detect
respond
new
threats
attacks
analyzing
network
traffic
behavior.
These
technologies
continue
evolve,
opening
up
research
opportunities
for
students
in
the
field
of
education.
helps
programs
learn,
draw
conclusions,
use
them
future.
Programming
languages
do
not
consider
algorithms
Programs
have
access
themselves.
To
need
change,
this
your
own
code.
Then
becomes
possible.
By
generating
logic
algorithms,
they
program,
it
different
from
its
source
code,
these
changes
must
be
saved.
The
interpreter
algorithm
improves
intelligence
author
optimal
programming
language
Author
allows
form
create
that
activities.
able
independently
their
skills
accuracy
without
explicit
each
type
task.
Journal of Educational Cultural and Psychological Studies (ECPS Journal),
Год журнала:
2025,
Номер
30
Опубликована: Янв. 15, 2025
DESIGNING
AND
ASSESSING
WITH
THE
SUPPORT
OF
ARTIFICIAL
INTELLIGENCE:
ELEMENTS
FOR
A
CRITICAL
APPROACH
TO
USE
CHATBOTS
Abstract
This
paper
explores
the
critical
integration
of
artificial
intelligence
(AI),
specifically
focusing
on
using
chatbots
in
training
design
and
learning
assessment,
aiming
to
uncover
both
potential
challenges
educational
contexts.
Through
two
exploratory
empirical
studies
–
one
centered
use
ChatGPT
other
its
application
school
assessments
analysis
examines
perceptions
teachers
students.
The
findings
reveal
that
chatbots,
such
as
ChatGPT,
can
significantly
reduce
workload
future
designers,
improve
access
resources,
provide
timely
feedback.
However,
concerns
emerge
regarding
technological
dependency
superficial
learning,
with
ethical
pedagogical
implications
warrant
a
examination
effectiveness
AI
tools.
concludes
by
proposing
strategies
for
AI’s
thoughtful
education,
promoting
balance
between
technology
reflective,
practice.
Advances in educational technologies and instructional design book series,
Год журнала:
2025,
Номер
unknown, С. 231 - 264
Опубликована: Янв. 3, 2025
The
creation
of
artificial
intelligence
(AI)
in
training
presents
each
possibilities
and
challenges,
reshaping
traditional
coaching
roles
methodologies.
This
paper
explores
the
evolving
position
teachers
an
AI-improved
instructional
panorama,
emphasizing
significance
human-centric
abilities
along
with
empathy,
creativity,
critical
wondering.
While
AI
can
automate
administrative
tasks
offer
personalized
learning
studies,
instructors
remain
fostering
a
supportive
tasty
mastering
surroundings.
take
look
at
highlights
symbiotic
courting
among
equipment
educators,
advocating
for
expert
improvement
coverage
reforms
to
maximize
benefits
integration.
By
analyzing
contemporary
traits
future
possibilities,
this
objectives
roadmap
educators
navigating
transformative
generation.
Deleted Journal,
Год журнала:
2025,
Номер
3(1), С. 129 - 137
Опубликована: Фев. 5, 2025
There
are
several
areas
where
self-learning
AI
is
actively
used.
Machine
learning
and
deep
allow
you
to
identify
patterns
improve
performance.
Algorithms
such
as
neural
networks
can
adapt
based
on
experience.
Self-learning
GPTs
used
dialogue
with
humans.
Computer
vision
recognizes
classifies
images.
Recommender
systems
analyze
user
preferences
offer
personalized
solutions.
Adaptive
robotic
industrial
control
optimize
processes
by
adapting
changing
conditions
data.
intelligent
help
detect
respond
new
threats
attacks
analyzing
network
traffic
behavior.
These
technologies
continue
evolve,
opening
up
research
opportunities
for
students
in
the
field
of
education.
helps
programs
learn,
draw
conclusions,
use
them
future.
Programming
languages
do
not
consider
algorithms
Programs
have
access
themselves.
To
need
change,
this
your
own
code.
Then
becomes
possible.
By
generating
logic
algorithms,
they
program,
it
different
from
its
source
code,
these
changes
must
be
saved.
The
interpreter
algorithm
improves
intelligence
author
optimal
programming
language
Author
allows
form
create
that
activities.
able
independently
their
skills
accuracy
without
explicit
each
type
task.
