Applied Mathematics and Nonlinear Sciences,
Год журнала:
2024,
Номер
9(1)
Опубликована: Янв. 1, 2024
Abstract
This
paper
explains
the
dilemma
of
artificial
intelligence
in
relation
to
development
teacher
education
based
on
functional
structure
and
activity
characteristics
education.
Then,
after
designing
a
survey
questionnaire
factors
affecting
empowered
by
completing
reliability
test,
collects
initial
data
form
distributing
questionnaires
analyzes
detail
least
squares
estimation
mean,
variance,
standard
deviation,
correlation
coefficient,
regression
coefficient
needed
process
analyzing
carry
out
analysis
instances.
The
coefficients
training,
professional
development,
policy
support,
resource
allocation,
literacy,
educational
information
technology
behaviors,
AI-enabled
are
0.674
(0.003),
0.496
(0.001),
0.259
(0.009),
0.371
(0.008),
0.639
(0.004),
0.325
(0.007).
Their
corresponding
were
0.616
(t=59.852,
P=0.003),
0.021
(t=0.018,
P=0.007),
0.078
(t=5.668,
P=0.005),
0.032
(t=3.282,
P=0.009),
0.239
(t=29.734,
P=0.008),
0.137
(t=5.406,
P=0.001),
indicating
that
these
have
significant
impact
relationship
Vocational education and labour market,
Год журнала:
2024,
Номер
12(3(58)), С. 6 - 21
Опубликована: Сен. 12, 2024
Введение.
Появление
и
массовое
распространение
генеративного
искусственного
интеллекта
(ГИИ),
в
том
числе
больших
языковых
моделей,
2022–2023
гг.
привело
к
масштабным
трансформациям
во
многих
сферах,
благодаря
новым
возможностям
работы
с
текстами,
изображениями,
видео
звуком.
Научное
сообщество,
предвосхищая
масштабные
изменения
области
образования
под
влиянием
технологий
на
базе
ГИИ,
задумывается
о
поиске
новых
парадигм
сфере
образования.
Данная
работа
исследует
технологические
возможности
применения
ГИИ
системе
образования,
а
также
обозначает
наметившуюся
тенденцию
масштабированию
персонализированного
Цель.
Описание
существующих
образовательных
практики
их
применения.
Методы.
Глубинные
интервью
экспертами
интеллекта.
Результаты.
Дано
описание
сфер
раскрыты
преимущества,
проблемы
риски
внедрения
технологий,
рассмотрена
практика
даны
рекомендации
образовательным
организациям
по
адаптации
цифровой
трансформации,
части
ГИИ.
Научная
новизна
состоит
систематизации
исследований
различным
направлениям
использования
образовательном
процессе
прогнозировании
развития
образовании.
Практическая
значимость.
результаты
исследования
могут
быть
использованы
педагогами
для
актуализации
учебных
курсов,
изменению
системы
оценки
контроля
учащихся,
обучающих
программ
учеников
использованием
понимания
общемировой
тенденции
подхода
образованию
целом.
Introduction.
The
emergence
and
mass
distribution
of
generative
artificial
intelligence
(GAI),
including
large
language
models
in
2022–2023,
have
led
to
large-scale
transformations
many
areas,
thanks
new
opportunities
for
working
with
text,
images,
video,
sound.
scientific
community,
anticipating
significant
changes
the
field
education
under
influence
GAI-based
technologies,
is
considering
paradigms
education.
This
work
explores
technological
possibilities
using
GAI
system
highlights
emerging
trend
toward
scaling
up
personalised
Aim.
purpose
study
describe
existing
educational
technologies
based
on
GAI,
as
well
practice
their
application.
Methods.
In-depth
interviews
experts
intelligence.
Results.
described
areas
application
system,
revealed
advantages,
problems
risks
introducing
considered
applying
proposed
recommendations
organisations
adapting
digital
transformation,
terms
GAI.
Scientific
novelty
lies
systematising
research
different
directions
process
forecasting
further
development
Practical
significance.
results
can
be
used
by
teachers
update
curriculums,
change
assessment
control
students,
adapt
training
programmes
capabilities
students
understand
global
changing
approach
general.
Keywords:
intelligence,
ChatGPT,
education,
curriculum
adaptation,
customisation,
learning.
Pacific Journal of Technology Enhanced Learning,
Год журнала:
2024,
Номер
6(2), С. 23 - 32
Опубликована: Июнь 7, 2024
In
this
second
editorial
for
the
Pacific
Journal
of
Technology
Enhanced
Learning,
PJTEL,
lead
editors
reflect
upon
first
five
years
journal
leading
to
indexing
in
EBSCO
and
explore
impact
statistics
date.
We
also
future
directions
themes
particularly
considering
Generative
AI
on
education.
Applied Mathematics and Nonlinear Sciences,
Год журнала:
2024,
Номер
9(1)
Опубликована: Янв. 1, 2024
Abstract
This
paper
explains
the
dilemma
of
artificial
intelligence
in
relation
to
development
teacher
education
based
on
functional
structure
and
activity
characteristics
education.
Then,
after
designing
a
survey
questionnaire
factors
affecting
empowered
by
completing
reliability
test,
collects
initial
data
form
distributing
questionnaires
analyzes
detail
least
squares
estimation
mean,
variance,
standard
deviation,
correlation
coefficient,
regression
coefficient
needed
process
analyzing
carry
out
analysis
instances.
The
coefficients
training,
professional
development,
policy
support,
resource
allocation,
literacy,
educational
information
technology
behaviors,
AI-enabled
are
0.674
(0.003),
0.496
(0.001),
0.259
(0.009),
0.371
(0.008),
0.639
(0.004),
0.325
(0.007).
Their
corresponding
were
0.616
(t=59.852,
P=0.003),
0.021
(t=0.018,
P=0.007),
0.078
(t=5.668,
P=0.005),
0.032
(t=3.282,
P=0.009),
0.239
(t=29.734,
P=0.008),
0.137
(t=5.406,
P=0.001),
indicating
that
these
have
significant
impact
relationship
