The Impact of AI on the Personal and Collaborative Learning Environments in Higher Education
European Journal of Education,
Год журнала:
2025,
Номер
60(1)
Опубликована: Янв. 7, 2025
ABSTRACT
Artificial
intelligence
(AI)
has
extensively
developed,
impacting
different
sectors
of
society,
including
higher
education,
and
attracted
the
attention
various
educational
stakeholders,
leading
to
a
growing
number
research
on
its
integration
into
education.
Hence,
this
systematic
literature
review
examines
impact
integrating
AI
tools
in
education
students'
personal
collaborative
learning
environments.
Analysis
148
articles
published
between
2021
2024
indicates
that
Tools
improve
personalised
assessments,
communication
engagement,
scaffolding
performance
motivation.
Additionally,
they
promote
environment
by
providing
peer‐learning
opportunities,
enhanced
learner‐content
interaction
cooperative
support.
Indeed,
strategies
such
as
skills
development,
ethical
use,
academic
integrity
instructional
content
design.
Acknowledged
limitations
include
considerations,
particularly
privacy
bias,
which
require
ongoing
attention.
it
is
recommended
create
good
balance
AI‐mediated
human
environments,
key
area
future
exploration.
Язык: Английский
Examining Artificial Intelligence and Ethics in Education With Bibliometric Analysis
Advances in educational technologies and instructional design book series,
Год журнала:
2025,
Номер
unknown, С. 1 - 30
Опубликована: Янв. 3, 2025
The
utilisation
of
artificial
intelligence
(AI)
in
the
field
education
has
witnessed
a
notable
surge
recent
years,
with
growth
technology.
This
increase
given
rise
to
number
ethical
issues.
study
will
provide
comprehensive
examination
implications
AI
education.
A
bibliometric
analysis
studies
conducted
this
be
through
existing
literature.
allows
for
numerical
relationships
between
keywords
identified
and
on
intersection
ethics
It
also
accesses
evaluates
data
such
as
publications
field,
countries,
authors,
publication
citation
counts,
keywords.
obtained
insight
into
evolution
discourse
within
academic
findings
indicate
that
crucial
step
development
applications
is
establish
clear
framework.
Язык: Английский
Generative AI in Education: Perspectives Through an Academic Lens
Electronics,
Год журнала:
2025,
Номер
14(5), С. 1053 - 1053
Опубликована: Март 6, 2025
In
this
paper,
we
investigated
the
role
of
generative
AI
in
education
academic
publications
extracted
from
Web
Science
(3506
records;
2019–2024).
The
proposed
methodology
included
three
main
streams:
(1)
Monthly
analysis
trends;
top-ranking
research
areas,
keywords
and
universities;
frequency
over
time;
a
keyword
co-occurrence
map;
collaboration
networks;
Sankey
diagram
illustrating
relationship
between
AI-related
terms,
publication
years
areas;
(2)
Sentiment
using
custom
list
words,
VADER
TextBlob;
(3)
Topic
modeling
Latent
Dirichlet
Allocation
(LDA).
Terms
such
as
“artificial
intelligence”
“generative
artificial
were
predominant,
but
they
diverged
evolved
time.
By
2024,
applications
had
branched
into
specialized
fields,
including
educational
research,
computer
science,
engineering,
psychology,
medical
informatics,
healthcare
sciences,
general
medicine
surgery.
sentiment
reveals
growing
optimism
regarding
education,
with
steady
increase
positive
2023
to
while
maintaining
predominantly
neutral
tone.
Five
topics
derived
based
on
an
most
relevant
terms
by
LDA:
Gen-AI’s
impact
research;
ChatGPT
tool
for
university
students
teachers;
Large
language
models
(LLMs)
prompting
computing
education;
(4)
Applications
patient
(5)
ChatGPT’s
performance
examinations.
identified
several
emerging
topics:
discipline-specific
application
LLMs,
multimodal
gen-AI,
personalized
learning,
peer
or
tutor
cross-cultural
multilingual
tools
aimed
at
developing
culturally
content
supporting
teaching
lesser-known
languages.
Further,
gamification
involves
designing
interactive
storytelling
adaptive
games
enhance
engagement
hybrid
human–AI
classrooms
explore
co-teaching
dynamics,
teacher–student
relationships
classroom
authority.
Язык: Английский
A Comparative Analysis of Virtual Education Technology, E-Learning Systems Research Advances, and Digital Divide in the Global South
Informatics,
Год журнала:
2024,
Номер
11(3), С. 53 - 53
Опубликована: Июль 23, 2024
This
pioneering
study
evaluates
the
digital
divide
and
advances
in
virtual
education
(VE)
e-learning
research
Global
South
Countries
(GSCs).
Using
metadata
from
bibliographic
World
Bank
data
on
development
(R&D),
we
conduct
quantitative
bibliometric
performance
analyses
evaluate
connection
between
R&D
expenditures
VE/e-learning
GSCs.
The
results
show
that
‘East
Asia
Pacific’
(EAP)
spent
significantly
more
(R&D)
achieved
highest
scientific
literature
publication
(SLP),
with
significant
impacts.
Other
GSCs’
expenditure
was
flat
until
2020
(during
COVID-19),
when
funding
increased,
achieving
a
corresponding
42%
rise
SLPs.
About
67%
of
‘Arab
States’
(AS)
SLPs
60%
citation
impact
came
produced
global
north
other
GSCs
regions,
indicating
high
dependence.
Also,
51%
high-impact
were
‘Multiple
Country
Publications’,
mainly
non-GSC
institutions,
collaboration
impact.
EAP,
AS,
‘South
Asia’
(SA)
regions
experienced
lower
disparity.
In
contrast,
less
developed
countries
(LDCs),
including
‘Sub-Sahara
Africa’,
‘Latin
America
Caribbean’,
‘Europe
(Eastern)
Central
Asia’,
showed
few
dominant
higher
divides.
We
advocate
for
increased
educational
to
enhance
innovative
GSCs,
especially
LDCs.
Язык: Английский
Technologies and Approaches to Support Community Flood Initiatives—A Bibliometric Analysis Around the Theme
Springer geography,
Год журнала:
2025,
Номер
unknown, С. 51 - 70
Опубликована: Янв. 1, 2025
Язык: Английский
The advancement of Artificial Intelligence in Education: Insights from a 1976–2024 bibliometric analysis
Journal of Research on Technology in Education,
Год журнала:
2025,
Номер
unknown, С. 1 - 17
Опубликована: Фев. 11, 2025
Язык: Английский
Can Generative AI Revolutionise Academic Skills Development in Higher Education? A Systematic Literature Review
European Journal of Education,
Год журнала:
2025,
Номер
60(1)
Опубликована: Фев. 14, 2025
ABSTRACT
This
systematic
review
investigates
the
impact
of
generative
artificial
intelligence
(GenAI)
tools
on
developing
academic
skills
in
higher
education.
Analysing
158
studies
published
between
2021
and
2024,
it
focuses
GenAI
development
cognitive,
technical
interpersonal
skills.
The
results
reveal
that
94%
sampled
reported
significant
improvements
cognitive
skills,
like
critical
thinking,
problem‐solving,
analytical
metacognitive
abilities,
facilitated
by
personalised
learning
feedback.
Indeed,
was
research
(24%),
writing
(26%),
data
analysis
(33%)
literacy
(18%).
Additionally,
were
found
to
promote
fostering
interactive
engaging
environments,
with
notable
communication
organisation
empathy
(5%)
teamwork
(45%).
Hence,
this
underscores
importance
ethical
responsible
use
tools,
ongoing
monitoring
active
stakeholder
engagement
maximise
their
benefits
They
offer
a
promising
avenue
for
advancement
enhancing
proficiency
promoting
effective
teamwork.
Therefore,
significantly
enhance
skills;
however,
integration
requires
robust
framework
sustained
examination
long‐term
impacts.
Язык: Английский
Analysing the Impact of Generative AI in Arts Education: A Cross-Disciplinary Perspective of Educators and Students in Higher Education
Informatics,
Год журнала:
2024,
Номер
11(2), С. 37 - 37
Опубликована: Июнь 3, 2024
Generative
AI
refers
specifically
to
a
class
of
Artificial
Intelligence
models
that
use
existing
data
create
new
content
reflects
the
underlying
patterns
real-world
data.
This
contribution
presents
study
aims
show
what
current
perception
arts
educators
and
students
education
is
with
regard
generative
Intelligence.
It
qualitative
research
using
focus
groups
as
collection
technique
in
order
obtain
an
overview
participating
subjects.
The
design
consists
two
phases:
(1)
generation
illustrations
from
prompts
by
students,
professionals
tool;
(2)
(N
=
5)
artistic
education.
In
general,
coincides
usefulness
tool
support
illustrations.
However,
they
agree
human
factor
cannot
be
replaced
AI.
results
obtained
allow
us
conclude
can
used
motivating
educational
strategy
for
Язык: Английский
Analyzing the Impact of a Structured LLM Workshop in Different Education Levels
Applied Sciences,
Год журнала:
2024,
Номер
14(14), С. 6280 - 6280
Опубликована: Июль 18, 2024
An
observation
on
the
current
state
of
teaching
large
language
models
(LLMs)
in
education
is
made.
The
problem
lacking
a
structural
approach
defined.
A
methodology
created
order
to
serve
as
basis
workshop
students
with
different
types
backgrounds
correct
use
LLMs
and
their
capabilities.
plan
created;
instructions
materials
are
presented.
practical
experiment
has
been
conducted
by
dividing
into
teams
guiding
them
create
small
project.
Different
used
for
purposes
creating
fictional
story,
images
relating
very
simple
HTML,
JS,
CSS
code.
Participants
given
requirements
that
consider
limitations
LLMs,
approaches
creatively
solving
arising
issues
due
observed.
students’
projects
hosted
web,
so
they
can
see
results
work.
They
opportunity
motivation
future
development.
survey
distributed
all
participating
students.
analyzed
from
angles
conclusions
made
effectiveness
completing
its
goal
defined
problem.
Язык: Английский
A Bibliometric Analysis of Artificial Intelligence Applications in Global Higher Education
International Journal of Information System Modeling and Design,
Год журнала:
2024,
Номер
16(1), С. 1 - 24
Опубликована: Дек. 27, 2024
Artificial
Intelligence
(AI)
in
education
has
rapidly
increased
during
and
after
the
pandemic,
necessitating
an
understanding
of
development
trends
for
technological
innovations
implementation
higher
education.
This
bibliometric
analysis
Web
Science
Core
Collection
database
revealed
that
China,
US,
England
led
research
productivity.
The
collaboration
networks
among
countries,
institutions,
authors
emphasized
need
enhanced
international
regional
partnerships.
Sustainability
was
identified
as
most
influential
journal
field.
Cluster
content
explored
AI's
impact,
pinpointing
hotspots
global
Future
directions
include
AI-VR
integration,
sentiment
educational
improvement,
predictive
student
performance
models,
enhancing
academic
integrity.
study
offers
critical
insights
guiding
AI
applications
education,
benefitting
researchers
practitioners.
Язык: Английский