Technology-supported differentiated biology education: Trends, methods, content, and impacts
Eurasia Journal of Mathematics Science and Technology Education,
Год журнала:
2025,
Номер
21(3), С. em2598 - em2598
Опубликована: Фев. 25, 2025
This
study
aims
to
fill
the
gap
in
understanding
trends,
methods,
content,
and
impacts
of
technology
implementation
differentiated
biology
education
at
secondary
higher
levels.
The
methodology
employed
is
a
systematic
literature
review
on
use
education.
search
was
conducted
using
terms
‘technology’
AND
(‘differentiated
instruction’
OR
‘personalized
learning’
‘adaptive
teaching’
‘learning
style’)
‘biology
education’
Scopus
database,
yielding
922
articles,
which
only
18
met
criteria
for
further
analysis.
findings
indicate
rapid
increase
publications,
with
61%
articles
published
between
2022
2024.
majority
publications
come
from
journals
fields
<i>social
sciences/education</i>,
while
contributions
biochemistry,
genetics,
molecular
remain
limited,
suggesting
need
cross-disciplinary
collaboration.
Most
studies
(78%)
used
quantitative
mixed
72%
focusing
most
commonly
technologies
include
hands-on
tools,
data
analysis
collaborative
animal
anatomy
physiology
as
dominant
topics.
These
support
learning
by
enhancing
understanding,
engagement,
outcomes,
well
observation
scientific
explanation
skills
school
level,
research
bioinformatics
level.
Язык: Английский
Personalized learning through AI: Pedagogical approaches and critical insights
Contemporary Educational Technology,
Год журнала:
2025,
Номер
17(2), С. ep574 - ep574
Опубликована: Март 10, 2025
In
this
analysis,
we
review
artificial
intelligence
(AI)-supported
personalized
learning
(PL)
systems,
with
an
emphasis
on
pedagogical
approaches
and
implementation
challenges.
We
searched
the
Web
of
Science
Scopus
databases.
After
preliminary
review,
examined
30
publications
in
detail.
ChatGPT
machine
technologies
are
among
most
often
utilized
tools;
studies
show
that
general
education
language
account
for
majority
AI
applications
field
education.
Supported
by
particular
stressing
student
characteristics
expectations,
results
automated
feedback
systems
adaptive
content
distribution
define
AI’s
educational
responsibilities
mostly.
The
study
notes
major
difficulties
three
areas:
technical
constraints
data
privacy
concerns;
pragmatic
barriers.
Although
curriculum
integration
teacher
preparation
considered
concerns,
challenges
come
first
above
technology
integration.
also
underline
need
thorough
professional
development
activities
teachers
tools
especially
targeted
instruction.
shows
efficient
application
AI-enabled
PL
requires
a
comprehensive
strategy
addressing
technological,
pedagogical,
ethical
issues
all
at
once.
These
help
to
describe
current
state
provide
ideas
future
developments
as
well
techniques
its
use.
Язык: Английский