Harnessing Generative Artificial Intelligence for Digital Literacy Innovation: A Comparative Study between Early Childhood Education and Computer Science Undergraduates
AI,
Год журнала:
2024,
Номер
5(3), С. 1427 - 1445
Опубликована: Авг. 15, 2024
The
recent
surge
of
generative
artificial
intelligence
(AI)
in
higher
education
presents
a
fascinating
landscape
opportunities
and
challenges.
AI
has
the
potential
to
personalize
create
more
engaging
learning
experiences.
However,
effectiveness
interventions
relies
on
well-considered
implementation
strategies.
impact
platforms
is
largely
determined
by
particular
environment
distinct
needs
each
student.
Consequently,
investigating
attitudes
future
educators
towards
this
technology
becoming
critical
area
research.
This
study
explores
students’
performance,
experience,
satisfaction
within
education.
It
specifically
focuses
experiences
with
varying
levels
technological
proficiency.
A
comparative
was
conducted
two
groups
from
different
academic
contexts
undergoing
same
experimental
condition
design,
develop,
implement
instructional
design
projects
using
various
produce
multimedia
content
tailored
their
respective
subjects.
Undergraduates
disciplines—Early
Childhood
Education
(n
=
32)
Computer
Science
34)—participated
study,
which
examined
integration
into
educational
implementation.
Results
indicate
that
both
demonstrated
similar
performance
designing,
developing,
implementing
projects.
Regarding
user
general
outcomes
were
across
groups;
however,
Early
students
rated
usefulness
significantly
higher.
Conversely,
reported
slightly
comfort
level
these
tools.
In
terms
overall
satisfaction,
expressed
greater
software
than
counterparts,
acknowledging
its
importance
for
careers.
contributes
understanding
how
affect
diverse
backgrounds,
bridging
gap
knowledge
experience
outcomes.
Furthermore,
exploring
best
practices
integrating
contexts,
it
provides
valuable
insights
scholars
seeking
optimize
enhance
Язык: Английский
Learning and Teaching in the Era of Generative Artificial Intelligence Technologies: An In‐Depth Exploration Using Multi‐Analytical SEM‐ANN Approach
European Journal of Education,
Год журнала:
2025,
Номер
60(1)
Опубликована: Фев. 18, 2025
ABSTRACT
The
arrival
of
generative
artificial
intelligence
(GAI)
technologies
marks
a
significant
transformation
in
the
educational
landscape,
with
implications
for
teaching
and
learning
performance.
These
can
generate
content,
simulate
interactions,
adapt
to
learners'
needs,
offering
opportunities
interactive
experiences.
In
China's
education
sector,
incorporating
GAI
address
challenges,
enhance
practices,
improve
This
study
scrutinises
impact
on
performance
focusing
mediating
roles
e‐learning
competence
(EC),
desire
(DL),
beliefs
about
future
(BF),
as
well
moderating
role
facilitating
conditions
amongst
Chinese
educators.
Data
was
collected
from
411
teachers
across
various
institutions
China
using
purposive
sampling.
PLS‐SEM
ANN
were
employed
assess
suggested
structural
model.
results
indicate
that
significantly
influence
by
EC,
DL,
BF
roles.
Furthermore,
positively
moderate
association
BF.
underscores
critical
self‐determination
theory
shaping
effective
incorporation
education,
valuable
insights
outcomes
sector.
Язык: Английский
Integrating IBM Watson BEAT generative AI software into flute music learning: the impact of advanced AI tools on students’ learning strategies
Education and Information Technologies,
Год журнала:
2025,
Номер
unknown
Опубликована: Янв. 31, 2025
Язык: Английский
Artificial Intelligence Tool Adoption in Higher Education: A Structural Equation Modeling Approach to Understanding Impact Factors among Economics Students
Electronics,
Год журнала:
2024,
Номер
13(18), С. 3632 - 3632
Опубликована: Сен. 12, 2024
The
integration
of
Artificial
Intelligence
(AI)
in
higher
education
has
the
potential
to
significantly
enhance
educational
process
and
student
outcomes.
However,
there
is
a
limited
understanding
factors
influencing
AI
adoption
among
university
students,
particularly
economic
programs.
This
study
examines
relationship
between
students’
perceptions
efficacy
usefulness
tools,
their
access
these
concerns
regarding
usage.
A
comprehensive
survey
Romanian
focusing
on
economics
was
undertaken.
identifies
critical
latent
investigates
interrelationships
by
employing
advanced
analytical
techniques,
such
as
Exploratory
Factor
Analysis
(EFA),
Confirmatory
(CFA),
Structural
Equation
Modeling
(SEM),
with
robust
standard
errors.
results
suggest
that
formal
training
integration,
AI,
perceived
utility,
positive
attitudes
towards
are
positively
influenced
general
awareness
familiarity
tools.
frequency
tool
usage
substantially
increased
usefulness,
attitudes,
integration.
Conversely,
utility
adversely
affected
AI-related
concerns.
Indirect
effects
indirectly
increase
increasing
awareness.
research
relevant
computer
science,
it
helps
build
strategies
integrate
technologies
into
processes.
Increasing
tools
addressing
can
facilitate
widespread
effective
technologies,
improving
academic
experiences
Язык: Английский
Generative artificial intelligence attitude analysis of undergraduate students and their precise improvement strategies: A differential analysis of multifactorial influences
Education and Information Technologies,
Год журнала:
2024,
Номер
unknown
Опубликована: Дек. 19, 2024
Язык: Английский
Analisis Tingkat Penerimaan Mahasiswa terhadap Model Hybrid Learning Pada Perguruan Tinggi
Dedi Gunawan Saputra,
Fajriani Azis,
Ekha Mustika Putri
и другие.
Journal of Vocational Informatics and Computer Education,
Год журнала:
2024,
Номер
unknown, С. 40 - 57
Опубликована: Июнь 3, 2024
Pembelajaran
campuran
pada
pendidikan
tinggi
jarak
jauh
menjadi
penelitian
yang
cukup
menarik
dalam
beberapa
tahun
terakhir,
dimana
pembelajaran
digunakan
saat
pandemic
covid-19
lalu
untuk
mendukung
walapun
terbatas
karena
adanya
virus
mengharuskan
orang-orang
berada
di
rumah
bekerja.
Penelitian
ini
bertujuan
mengukur
aspek
online
berbasis
LMS
atau
teknologi
Blended
sehingga
tatap
muka
terdegradasi.
Dengan
hasil
diharapakan
adalah
pengembangan
dari
validasi
melalui
model
persamaan
struktural
kuadrat
terkecil
parsial
dan
Learning
Acceptance
Scale
(BLAS)
digabungkan
dengan
penerimaan
Pendidikan
jauh.
menerapkan
metode
kuantitatif
memvalidasi
BLAS.
Untuk
mencapai
tujuan
ini,
kuesioner
sembilan
sesi
mengumpulkan
data
sampel
43
tutor
total
100
program
survei
interupsi.
Sebanyak
berpartisipasi
uji
coba
proyek
secara
nasional.
Survei
cross-sectional
responden
tersebar
seluruh
negeri
berbagai
pusat
penelitian,
berbeda
(Matematika
Sains;
Perdagangan;
Pendidikan)
tingkat
dukungan
(Gelar,
Sarjana
Pascasarjana).
Hasilnya
Teknik
proses
tetapi
manfaat
dirasakan
masih
kurang
pembelajarannya.
Investigasi Persepsi Mahasiswa terhadap ChatGPT dalam Model Blended Learning pada Pembelajaran Matematika
Hersiyati Palayukan,
Hajar Dewantara,
Elma Nurjannah
и другие.
Journal of Vocational Informatics and Computer Education,
Год журнала:
2024,
Номер
unknown, С. 14 - 26
Опубликована: Июнь 3, 2024
Pengembangan
teknologi
kecerdasan
buatan,
terutama
pemanfaatan
ChatGPT,
menciptakan
dampak
signifikan
dalam
dunia
akademik
dan
pendidikan.
Penelitian
ini
bertujuan
untuk
menginvestigasi
persepsi
mahasiswa
terhdap
penggunaan
chatGPT
pada
pembelajaran
matematika
model
blended
learning.
berfokus
bagaimana
alat
buatan
dapat
mempengaruhi
perolehan
keterampilan
berpikir
kritis,
pemecahan
masalah,
kerja
kelompok
di
kalangan
siswa,
serta
mengetahui
tentang
keandalan,
pentingnya
akademis.
menggunakan
metode
kuantitatif
dengan
pendekatan
cross-sectional,
91
responden
kuesioner
sebagai
instrumen
pengumpulan
data.
Hasil
analisis
deskriptif,
termasuk
presentasi
statistik
seperti
mean,
median,
modus,
sum,
max,
min,
menunjukkan
bahwa
rata-rata
3,34
berpendapat
sebagian
terhadap
ChatGPT
yang
andal
jawaban
teori
matematika,
meskipun
ada
keraguan
terkait
kemampuannya
menangani
perhitungan
numerik
kompleks.
Sementara
itu,
lainnya,
3,68,
mengekspresikan
pandangan
positif
potensi
penting
menjadi
berharga
mendukung
pendidikan
perguruan
tinggi.
Analisis Literasi Artifical Intelligence Mahasiswa Pada Perguruan Tinggi
Israwati Hamsar,
Hajar Dewantara,
Hijri Andini
и другие.
Journal of Vocational Informatics and Computer Education,
Год журнала:
2024,
Номер
unknown, С. 72 - 81
Опубликована: Июнь 19, 2024
Penelitian
ini
bertujuan
untuk
menganalisis
kemampuan
mahasiswa
Fakultas
Ilmu
Komputer
dan
Informasi
(JTIK)
Universitas
Negeri
Makassar
(UNM)
pada
bidang
kecerdasan
buatan
(AI).
Dengan
menggunakan
pendekatan
lintas
disiplin
desain
penelitian
kuantitatif,
data
dikumpulkan
melalui
kuesioner
yang
mencakup
aspek-aspek
seperti
pemahaman
konsep
dasar
AI,
aplikasi
kesadaran
akan
masalah
etika
dalam
penggunaan
AI.
Berdasarkan
survei,
mayoritas
JTIK
UNM
memiliki
baik
tentang
AI
dapat
aktivitas
sehari-hari,
namun
masih
perlu
perbaikan
dari
segi
etika.
Wawasan
membantu
universitas
merancang
program
lebih
baik,
mendukung
pendidikan
efektif,
memotivasi
melakukan
terkait
Studi
juga
memberikan
wawasan
mengenai
perkembangan
sains
berkontribusi
terhadap
di
masyarakat.
Oleh
karena
itu,
analisis
lanjut
dampak
kompetensi
prospek
karir
siswa
setelah
lulus,
perbandingan
seluruh
institusi
pendidikan,
identifikasi
hambatan
serta
hubungan
antara
minat
Berguna
sebagai
titik
awal.
Proyek
kampus.