A Systematic Review of Responses, Attitudes, and Utilization Behaviors on Generative AI for Teaching and Learning in Higher Education
Behavioral Sciences,
Год журнала:
2025,
Номер
15(4), С. 467 - 467
Опубликована: Апрель 4, 2025
The
utilization
of
Generative
AI
(GenAI)
in
higher
education
classrooms
has
significantly
increased
recent
years.
Studies
show
that
GenAI
holds
promise
impacting
the
learning
experiences
both
students
and
teachers,
offering
personalized
assessment
opportunities.
This
study
conducts
a
systematic
review
responses,
attitudes,
behaviors
related
to
application
within
classrooms.
To
this
end,
we
synthesized
99
papers
published
between
2020
August
2024,
focusing
on
settings.
analysis
addresses
three
key
inquiries:
behaviors.
provides
an
updated
understanding
from
psychological
perspectives
GenAI’s
role
teaching
processes
education,
with
particular
emphasis
technologies.
Язык: Английский
Will AI-enabled Conversational Agents Acting as Digital Employees Enhance Employee Job Identity?
Information & Management,
Год журнала:
2025,
Номер
unknown, С. 104099 - 104099
Опубликована: Янв. 1, 2025
Язык: Английский
Project-work Artificial Intelligence Integration Framework (PAIIF): Developing a CDIO-based framework for educational integration
STEM Education,
Год журнала:
2025,
Номер
5(2), С. 310 - 332
Опубликована: Янв. 1, 2025
Язык: Английский
A systematic literature review of attitudes, intentions and behaviours of teaching academics pertaining to AI and generative AI (GenAI) in higher education: An analysis of GenAI adoption using the UTAUT framework
Australasian Journal of Educational Technology,
Год журнала:
2024,
Номер
unknown
Опубликована: Дек. 16, 2024
The
rapid
advancement
of
artificial
intelligence
(AI)
has
outpaced
existing
research
and
regulatory
frameworks
in
higher
education,
leading
to
varied
institutional
responses.
Although
some
educators
institutions
have
embraced
AI
generative
(GenAI),
other
individuals
remain
cautious.
This
systematic
literature
review
explored
teaching
academics'
attitudes,
perceptions
intentions
towards
GenAI,
identifying
perceived
benefits
obstacles.
Utilising
the
unified
theory
acceptance
use
technology
framework,
this
study
reveals
positive
attitudes
AI's
efficiency
enhancement,
but
also
significant
concerns
about
academic
integrity,
accuracy,
reliability,
skill
development
need
for
comprehensive
training
policies.
These
findings
underscore
necessity
support
navigate
integration
GenAI
tertiary
education.
Implications
practice
or
policy:
Attitudes
are
diverse
with
recognising
raising
ethical
practical
concerns.
indicate
a
more
understanding
dialogue
within
communities.
Academics'
these
technologies
contingent
upon
robust
guidelines
supportive
Institutional
shape
behaviours.
scarcity
formal
training,
policy
currently
limits
effective
integration.
Язык: Английский