International Journal of New Education,
Journal Year:
2024,
Volume and Issue:
14
Published: Dec. 9, 2024
Integrating
Artificial
Intelligence
(AI)
in
education
holds
transformative
potential
for
bridging
community
gaps,
particularly
under-resourced
and
marginalized
communities.
This
study
explores
the
multifaceted
ways
AI
technologies
can
enhance
educational
accessibility,
quality,
equity,
thereby
fostering
inclusive
development.
The
disparity
between
resourced
communities
Nigeria
is
a
pressing
issue,
primarily
driven
by
unequal
funding,
insecurity,
corruption,
resource
allocation,
teacher
shortages.
gap
affects
academic
performance
limits
future
opportunities
learners
under-sourced
delves
into
AI-driven
initiatives
to
reduce
digital
divide,
such
as
deploying
AI-powered
tools
underserved
with
limited
access
quality
education,
which
imminent.
By
leveraging
AI,
this
research
underscores
democratize
offering
tailored
learning
experiences
that
adapt
students'
diverse
needs
across
different
geographical
locations
Nigeria.
study's
core
objective
bridge
via
using
phenomenological
approach.
qualitative
adopted
population
comprised
all
secondary
school
teachers
Fifteen
public
from
constituted
sample
drew
purposively
based
on
availability.
data
were
thematically
evaluated,
three
themes
(i.e.,
assistance,
infrastructural
deficiency)
emerged
research.
findings
indicate
provide
assistance
improve
education.
While
may
potentially
experiences,
stakeholders
must
quickly
address
concerns
about
deficiency,
impediment
of
social
interaction
concluded
incorporating
AI-based
technology
will
enable
compete
favourably,
regardless
where
they
reside.
STEM Education,
Journal Year:
2025,
Volume and Issue:
5(1), P. 109 - 129
Published: Jan. 1, 2025
<p>Integrating
artificial
intelligence
(AI)
into
primary
inclusive
classrooms
can
significantly
enhance
teacher
well-being
by
streamlining
tasks,
preventing
burnout,
fostering
collaboration,
and
supporting
diverse
learning
needs.
However,
for
teachers
to
effectively
use
AI,
they
need
recognize
its
relevance,
engage
with
benefits,
promote
their
own
well-being.
The
goal
of
this
study
is
examine
the
moderator
effect
leadership
support
on
adoption
AI
applications
tools
psychological
in
our
hypothesized
research
model.
To
address
purpose,
a
quantitative
methodology
structural
equation
modeling
was
utilized.
Data
retrieved
through
an
online
questionnaire
from
342
teachers,
most
being
regular
users.
Our
findings
indicate
that
extensive
linked
engagement,
relationships,
accomplishment
but
not
positive
emotions
or
meaning.
Surprisingly,
school
negatively
moderates
factors
outcomes,
except
accomplishment,
which
remained
effective.
Leadership
appeared
less
crucial
promoting
enhancing
emerged
as
critical
factor
tool
Professional
programs
should
incorporate
impact
AI-based
educational
well-being,
emphasizing
key
role
adoption.
Additionally,
these
offer
opportunities
sharing
best
practices
effective
integration
settings.</p>
IGI Global eBooks,
Journal Year:
2025,
Volume and Issue:
unknown, P. 165 - 192
Published: Feb. 13, 2025
Artificial
intelligence
(AI)
has
rapidly
evolved
from
a
speculative
concept
into
transformative
force
impacting
multiple
domains,
with
education
being
one
of
its
most
promising
areas
influence.
The
potential
AI
lies
in
creating
dynamic,
adaptive,
and
student-centered
learning
ecosystems
that
enhance
the
teaching
process.
In
this
chapter,
we
will
delve
how
can
transform
education,
starting
AI-integrated
smart
classrooms
foster
personalized
efficient
learning.
We
explore
use
for
asset
tracking
to
ensure
safety
support
inclusive
students
special
needs.
Furthermore,
chapter
discuss
integration
design
thinking,
enhancing
creativity
problem-solving
skills.
also
examine
generative
AI's
impact
on
learning,
revolutionize
assessment
methods.
These
discussions,
supported
by
scholarly
references,
aim
provide
comprehensive
understanding
role
shaping
future
while
addressing
associated
challenges.
Advances in multimedia and interactive technologies book series,
Journal Year:
2025,
Volume and Issue:
unknown, P. 29 - 50
Published: Jan. 17, 2025
Artificial
Intelligence
has
brought
the
emergence
of
AI-ALL,
providing
learners
with
smart
learning
experiences
based
on
personalization
and
efficiency.
AI-ALL
is
a
promising
technique
for
improving
language
by
utilizing
AI
techniques
such
as
natural
processing,
automatic
grading,
intelligent
tutoring.
A
review
12
articles
Scopus
database
from
2014
to
May
2024
highlights
AI-ALL's
potential
improve
learning.
However,
challenges
like
quality
issues,
privacy
concerns,
over-reliance
technology
persist.
Future
research
should
examine
long-term
effects
scalability,
considering
different
educational
settings
proficiency
levels.
Ethical,
accurate
apps
while
maintaining
security
are
crucial.
To
personalized
academic
students
globally
where
tools
can
be
seamlessly
integrated
into
teaching
practices,
proper
training
programs
need
in
place.
Abstract
Background
The
rapid
advancement
of
generative
Artificial
Intelligence
(AI)
in
recent
years
has
led
to
its
increased
application
across
various
fields
including
education.
One
area
where
AI
can
significantly
impact
is
clinical
education,
particularly
the
preparation
and
execution
Objective
Structured
Clinical
Examinations
(OSCEs).
This
study
aimed
evaluate
AI-generated
material
feedback
on
academic
performance
level
anxiety
pharmacy
students
formative
OSCE.
Method
was
a
4-week
(June-July
2024)
randomized
controlled
study.
Students
6th
semester
PharmD
program
were
into
either
an
intervention
or
control
group.
group
received
which
comprised
comprehensive
training
session
how
use
tools
(ChatGPT,
Gemini
Perplexity)
for
generating
materials
practice
OSCE
stations
with
personalized
feedback,
addition
usual
instructions.
only
In
addition,
all
completed
Test
Anxiety
Inventory
(TAI)
questionnaire
before
Result
Eighty-eight
(40
male,
48
female)
out
92
(96%)
attended
TAI
questionnaire.
Each
had
44
(50%)
students.
mean
mark
13.26
(±5.05)
30.
No
significant
difference
found
between
[12.98
(±5.15)]
[13.54
(±5.00)]
groups
regarding
marks
(p=0.550).
Similarly,
no
emotionality
subscale
worry
(p=0.736;
p=0.329)
as
well
total
score
(p=0.917).
Conclusion
While
did
not
improve
reduce
test-related
anxiety,
they
negatively
these
outcomes
either.
Future
research
should
investigate
long-term
effects
AI-based
interventions
educational
outcomes.
