How AI Tools are Accepted and Utilized in Academia: A Mixed Methods Study
Journal of Social and Scientific Education,
Год журнала:
2025,
Номер
2(1), С. 24 - 41
Опубликована: Фев. 9, 2025
This
mixed
methods
study
investigates
the
factors
influencing
acceptance
and
utilization
of
Artificial
Intelligence
(AI)
tools
among
students
associates
in
a
Philippine
higher
education
institution,
using
Unified
Theory
Acceptance
Use
Technology
(UTAUT)
model.
The
reveals
that
both
groups
exhibit
high
familiarity
with
AI
utilize
it
for
various
academic
tasks,
performance
expectancy
facilitating
conditions
identified
as
primary
drivers
acceptance.
employed
cross-sectional
design
an
embedded
parallel
mixed-methods
approach.
An
online
survey
questionnaire
was
used
to
investigate
usage
associates.
findings
underscore
importance
comprehensive
training,
transparent
governance,
ethical
guidelines
foster
responsible
integration
academia.
also
discusses
considerations
surrounding
AI's
use
education,
emphasizing
need
implementation
maximize
its
benefits
while
minimizing
potential
risks.
Язык: Английский
Evolving Perceptions of AI Use and Academic Integrity: Insights from EFL Learners in Turkish Higher Education
Journal of Academic Ethics,
Год журнала:
2025,
Номер
unknown
Опубликована: Апрель 8, 2025
Язык: Английский
AI-Enhanced Project-Based Learning
Advances in computational intelligence and robotics book series,
Год журнала:
2025,
Номер
unknown, С. 125 - 142
Опубликована: Март 13, 2025
The
integration
of
generative
AI
into
project-based
learning
(PBL)
is
examined
in
this
chapter
as
a
means
revolutionizing
the
teaching
commerce.
It
starts
by
summarizing
main
ideas
PBL
and
highlighting
how
it
helps
students
develop
their
critical
thinking
creative
problem-solving
abilities.
explores
technologies
like
simulations
predictive
models
improve
these
objectives
giving
access
to
real-world
business
scenarios.
AI-driven
solutions
make
commerce
education
more
dynamic
enable
tailored
adaptable
experiences
when
they
are
integrated
problem-based
(PBL).
Case
studies
show
can
be
successfully
used
student
engagement
outcomes.
difficulties
incorporating
educational
frameworks
also
covered
including
infrastructure
teacher
training
requirements
ethical
conundrums
privacy
issues
relating
data.
Язык: Английский
Application of Artificial Intelligence Techniques on Lesson Delivery in Senior High Schools in Ghana: Enhancing Student Engagement, Personalised Learning, Performance Assessment and Holistic Development
Опубликована: Апрель 16, 2025
Abstract
The
integration
of
Artificial
Intelligence
in
education
has
significantly
transformed
lesson
delivery
by
fostering
increased
student
engagement,
customised
learning
experiences,
and
improved
performance
assessments.
This
research
aims
to
evaluate
the
effectiveness
AI-driven
teaching
methods
enhancing
addressing
engagement
disparities,
facilitating
adaptive
instruction,
refining
evaluation.
A
quasi-experimental
design
that
incorporated
a
correlational
methodology
was
employed.
sample
size
1,200
students
teachers
used.
These
participants
were
chosen
through
stratified
random
sampling
technique,
ensuring
representative
cross-section
population
enrich
findings.
Data
collection
included
structured
surveys,
standardized
academic
assessments,
classroom
observations.
Descriptive
inferential
statistical
analyses
performed
using
SPSS,
employing
t-tests,
ANOVA,
regression
analysis,
Pearson
correlation
explore
relationships
between
AI
outcomes.
findings
revealed
incorporation
boosts
personalised
learning,
assessment,
holistic
development.
results
align
with
existing
literature
on
AI-enhanced
while
emphasising
necessity
for
context-specific
implementation
strategies
Ghana.
Furthermore,
study
emphasises
importance
policy-driven
adoption,
teacher
training
initiatives,
infrastructure
improvements
fully
harness
AI's
potential
Senior
High
Schools
Язык: Английский
Efficiency Analysis and Optimization Techniques for Base Conversion Algorithms in Computational Systems
Japheth Kodua Wiredu,
Basel Atiyire,
Nelson Seidu Abuba
и другие.
International Journal of Innovative Science and Research Technology (IJISRT),
Год журнала:
2024,
Номер
unknown, С. 235 - 244
Опубликована: Авг. 17, 2024
The
performance
of
base
conversion
methods
varies
greatly
across
several
techniques,
and
this
is
important
for
computer-based
systems.
This
research
paper
therefore
examines
the
efficiency
three
namely;
Successive
Multiplication
Method,
Positional
Notation
Horner’s
Method.
Their
execution
times
are
evaluated
binary,
octal,
decimal,
hexadecimal
bases
with
input
sizes
that
range
from
1000
to
10,000
digits.
Empirical
results
show
on
average
Method
outperforms
other
by
having
about
40%
better
up
30%
more
uniformity
than
based
upon
repeated
application
decimal
points.
Specifically
speaking,
conversions,
it
took
0.009
seconds
method
as
against
0.460
another
method.
These
observations
indicate
most
efficient
in
terms
time
taken
during
a
process
well
its
consistency
when
compared
techniques
used
performing
same
task
throughout
different
such
point
addition
repeatedly
considered
positional
notation
numeral
system.
Notably,
completed
at
an
rate
one
every
nine
milliseconds
hand
Approach
finished
per
second
while
Technique
performed
best
zero
conversions
within
given
unit
time.
It
accomplishes
these
tasks
much
faster
previous
approaches
because
does
not
require
multiplication
steps
or
many
intermediate
calculations
before
obtaining
answers
like
Problem
I;
instead,
only
few
additions
digit
required
which
can
be
done
quickly
using
modern
hardware
programmable
logic
arrays
(PLAs)
according
writer
P1
-
R3
even
printed
circuit
boards
(PCBs).
Язык: Английский
Embrace, Don’t Avoid: Reimagining Higher Education with Generative Artificial Intelligence
Journal of Educational Management and Learning,
Год журнала:
2024,
Номер
2(2), С. 81 - 90
Опубликована: Ноя. 28, 2024
This
paper
explores
the
potential
of
generative
artificial
intelligence
(AI)
to
transform
higher
education.
Generative
AI
is
a
technology
that
can
create
new
content,
like
text,
images,
and
code,
by
learning
patterns
from
existing
data.
As
tools
become
more
popular,
there
growing
interest
in
how
improve
teaching,
learning,
research.
Higher
education
faces
many
challenges,
such
as
meeting
diverse
needs
preparing
students
for
fast-changing
careers.
offers
solutions
personalizing
experiences,
making
engaging,
supporting
skill
development
through
adaptive
content.
It
also
help
researchers
automating
tasks
data
analysis
hypothesis
generation,
research
faster
efficient.
Moreover,
streamline
administrative
tasks,
improving
efficiency
across
institutions.
However,
using
raises
concerns
about
privacy,
bias,
academic
integrity,
equal
access.
To
address
these
issues,
institutions
must
establish
clear
ethical
guidelines,
ensure
security,
promote
fairness
use.
Training
faculty
literacy
are
essential
maximize
benefits
while
minimizing
risks.
The
suggests
strategic
framework
integrating
education,
focusing
on
infrastructure,
practices,
continuous
learning.
By
adopting
responsibly,
inclusive,
practical,
demands
technology-driven
world.
Язык: Английский
Optimizing Heap Sort for Repeated Values: A Modified Approach to Improve Efficiency in Duplicate-Heavy Data Sets
International Journal of Advanced Research in Computer Science,
Год журнала:
2024,
Номер
15(6), С. 12 - 18
Опубликована: Дек. 20, 2024
Sorting
algorithms
are
critical
to
various
computer
science
applications,
including
database
management,
big
data
analytics,
and
real-time
systems.
While
Heap
Sort
is
a
widely
used
comparison-based
sorting
algorithm,
its
efficiency
significantly
diminishes
when
dealing
with
sets
containing
high
volume
of
duplicate
values.
To
address
this
limitation,
paper
introduces
modified
algorithm
optimized
for
duplicate-heavy
data.
The
proposed
modification
detects
handles
values
more
efficiently
by
reducing
unnecessary
comparisons
swaps
at
the
root
heap
restructuring
strategically.
Experimental
results
demonstrate
that
achieves
up
15%
reduction
in
time,
30%
decrease
number
swaps,
10%
tested
on
varying
levels
duplication.
These
improvements
highlight
enhanced
computational
scalability
scenarios.
This
advancement
offers
significant
potential
improving
performance
practical
domains
such
as
operations,
processing.
Язык: Английский