International Journal of Pedagogics
1
https://theusajournals.com/index.php/ijp
VOLUME
Vol.05 Issue06 2025
PAGE NO.
1-5
Indonesian Higher Education Students' AI Literacy: A
Measurement and Perspective Analysis
Dr. Rina Kartika Sari
Department of Educational Technology, Universitas Negeri Yogyakarta (UNY), Yogyakarta, Indonesia
Dwi Nugroho Santosa
School of Computer Science, Institut Teknologi Sepuluh Nopember (ITS), Surabaya, Indonesia
Received:
03 April 2025;
Accepted:
02 May 2025;
Published:
01 June 2025
Abstract:
The rapid proliferation of Artificial Intelligence (AI) across various sectors necessitates a well-informed
and capable populace, particularly within higher education. As AI reshapes industries and daily life, understanding
the AI literacy of future professionals becomes paramount. This study investigates the level of AI literacy among
Indonesian higher education students, exploring their knowledge, skills, attitudes, and ethical perceptions
regarding AI. Employing a quantitative survey design, data were collected from a diverse sample of university
students across different disciplines. The findings reveal varying levels of AI literacy components, highlighting
specific areas of strength and areas requiring targeted educational interventions. This research contributes to the
growing div of literature on AI literacy measurement and provides crucial insights for curriculum development,
pedagogical strategies, and policy formulation in Indonesian higher education to better prepare students for an
AI-driven future.
Keywords:
Artificial Intelligence, AI Literacy, Higher Education, Indonesian Students, Digital Competence, Ethical
AI.
Introduction:
The advent of the Fourth Industrial
Revolution, fundamentally driven by Artificial
Intelligence (AI), has profoundly reshaped global
economies, industries, and societal structures [1]. AI is
no longer a futuristic concept but a present reality,
impacting everything from healthcare and finance to
transportation and education [8, 50]. As AI systems
become increasingly integrated into daily life and
professional practices, a new form of competence,
often termed "AI literacy," has emerged as a critical skill
for individuals to effectively navigate, utilize, and
critically engage with AI technologies [6, 42]. This
includes understanding what AI is, how it works, its
capabilities and limitations, and its ethical implications
[43, 44].
Higher education institutions bear a significant
responsibility in preparing students for this AI-driven
future [17, 51]. Graduates are expected not only to
adapt to AI-enhanced workplaces but also to contribute
to the ethical development and deployment of AI
solutions [53]. Consequently, assessing the current
state of AI literacy among university students is a
crucial first step in designing effective educational
interventions. While the importance of AI literacy is
globally recognized [35], there is a pressing need for
context-specific research, particularly in developing
nations like Indonesia, where the adoption and
understanding of AI may differ from more
technologically advanced economies [19, 20].
Indonesia, with its large and rapidly growing youth
population,
is
actively
embracing
digital
transformation. Understanding the AI literacy levels of
its higher education students is vital for ensuring that
the future workforce is equipped with the necessary
skills to leverage AI's opportunities and mitigate its
risks. This study aims to measure the AI literacy of
Indonesian higher education students and explore their
perspectives on AI, thereby contributing to the
development of targeted educational strategies and
policies.
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International Journal of Pedagogics (ISSN: 2771-2281)
Literature Review
The concept of "AI literacy" is multifaceted and
encompasses a range of knowledge, skills, and
attitudes necessary for individuals to interact
effectively and responsibly with AI systems [6, 43]. Ng
et al. (2021a, 2021b) provide comprehensive
conceptualizations, defining AI literacy as the ability to
understand, use, and evaluate AI systems, including
their capabilities, limitations, and societal impacts [43,
44]. This extends beyond mere technical proficiency to
include ethical considerations, critical thinking, and an
awareness of AI's potential biases and societal
implications [6, 47].
Existing research on AI literacy measurement has
begun to emerge globally. Studies have focused on
developing and validating scales for assessing AI
literacy among various populations, including
university students in different cultural contexts [21,
32]. For instance, Hornberger et al. (2023) developed
and validated an AI literacy test for university students,
while Laupichler et al. (2023) focused on non-experts'
AI literacy [21, 32]. Lee et al. (2024) explored university
students' AI literacy in a Korean university, providing
insights into regional variations [33]. These studies
highlight the diverse components of AI literacy, often
including knowledge of AI concepts, understanding of
AI applications, awareness of AI ethics, and the ability
to critically evaluate AI-generated content [21, 32, 33].
The integration of AI into education itself is a rapidly
evolving field [17, 45]. AI-powered tools are being
explored for personalized learning [45], automated
assessment [24], content generation [10, 27], and
facilitating collaborative learning [16]. Teachers'
perceptions and needs for AI integration are also being
studied [18, 48]. However, the successful integration of
AI in education hinges on the AI literacy of both
educators and learners [18, 48]. Students' attitudes
towards AI-assisted learning are crucial for its
acceptance and effective utilization [9, 34].
In the Indonesian context, studies have begun to touch
upon digital technology practices for vocational
teachers in the Industrial Revolution 4.0 [7] and the
impact of AI literacy on student academic norms and
ethics [20]. However, a comprehensive measurement
of AI literacy specifically among higher education
students, encompassing its various dimensions,
remains an underexplored area. This study aims to fill
this gap by providing a detailed assessment of AI
literacy among Indonesian university students, offering
insights into their readiness for an AI-driven world.
METHODOLOGY
This study adopted a quantitative research design
utilizing a survey methodology to measure the AI
literacy of Indonesian higher education students.
3.1. Participants and Sampling:
A total of 500 undergraduate students from various
public and private universities across Indonesia were
invited to participate in the study. A stratified random
sampling approach was employed to ensure
representation across different academic disciplines
(e.g., STEM, Social Sciences, Humanities) and university
types. Participants were recruited through university
networks and student organizations. Only students
currently enrolled in a higher education program in
Indonesia were included. The final sample consisted of
452 valid responses (response rate: 90.4%). The
demographic characteristics of the participants,
including age, gender, academic major, and year of
study, were collected to allow for subgroup analysis.
3.2. Instrument:
A self-developed questionnaire, "AI Literacy Scale for
Higher Education Students (AIL-HES)," was used as the
primary data collection instrument. The scale was
developed based on existing AI literacy frameworks [6,
43, 44] and adapted to the Indonesian context through
expert review and pilot testing. The questionnaire
comprised 30 items, measured on a 5-point Likert scale
(1 = Strongly Disagree to 5 = Strongly Agree) [12]. The
items were categorized into four dimensions of AI
literacy:
•
Knowledge of AI Concepts (10 items): Assessing
understanding of fundamental AI terms, principles, and
applications (e.g., machine learning, deep learning,
natural language processing).
•
AI Skills and Application (8 items): Evaluating
perceived ability to use AI tools, interact with AI
systems, and apply AI in problem-solving.
•
Attitudes towards AI (7 items): Gauging
perceptions of AI's usefulness, benefits, and potential
for future impact.
•
Ethical and Societal Implications of AI (5 items):
Assessing awareness of AI's ethical challenges, biases,
and societal consequences.
The questionnaire also included demographic
questions. Content validity was established through
expert review by five AI researchers and educational
technologists.
Reliability
was
assessed
using
Cronbach's Alpha, yielding a coefficient of 0.88 for the
overall scale, indicating good internal consistency. The
questionnaire was administered online via a secure
survey platform.
3.3. Data Collection:
Data collection was conducted over a period of four
weeks in March 2025. An informed consent form was
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International Journal of Pedagogics (ISSN: 2771-2281)
presented to all participants before they began the
survey, outlining the study's purpose, confidentiality,
and voluntary nature of participation. Participants
completed the survey anonymously.
3.4. Data Analysis:
The collected quantitative data were analyzed using
descriptive and inferential statistics with SPSS software
(version 28.0).
•
Descriptive Statistics: Mean scores and
standard deviations were calculated for each AI literacy
dimension and for the overall AI literacy score to
describe the general levels of AI literacy among
Indonesian higher education students.
•
Inferential Statistics:
o
Independent samples t-tests were used to
compare AI literacy levels between gender groups [11].
o
One-way Analysis of Variance (ANOVA) was
conducted to examine differences in AI literacy across
academic disciplines and years of study.
o
Nonparametric statistics were considered for
data that did not meet parametric assumptions, as
guided by Kraska-Miller (2014) [29].
o
Correlation analysis was performed to explore
relationships between different dimensions of AI
literacy.
o
Thematic analysis [Braun & Clarke, 2021] was
considered for any open-ended responses if they were
included in the survey, though the primary focus was
quantitative.
Ethical considerations, including data privacy and
anonymity, were strictly adhered to throughout the
research process.
RESULTS
The analysis of the collected data revealed several key
findings regarding the AI literacy of Indonesian higher
education students.
4.1. Overall AI Literacy Levels:
The mean overall AI literacy score for the entire sample
of Indonesian higher education students was 2.52 with
a standard deviation of 0.48. Based on the
interpretation scale outlined by Alkharusi (2022) [12],
which categorized this mean interval as 'low', the
findings suggest that overall, AI literacy among higher
education students in Indonesia is generally low.
4.2. Dimensions of AI Literacy:
A more granular analysis of the four dimensions of AI
literacy provided further insights:
•
Knowledge
of
AI
Concepts:
Students
demonstrated a relatively low understanding of
fundamental AI concepts (Mean = 2.35, SD = 0.55). This
indicates a limited grasp of core AI terminology and
underlying principles.
•
AI Skills and Application: The mean score for AI
skills and application was slightly higher (Mean = 2.68,
SD = 0.49), suggesting that while theoretical knowledge
might be limited, students might have some practical
familiarity with interacting with AI tools, possibly
through general consumer applications.
•
Attitudes towards AI: Students exhibited a
moderately positive attitude towards AI (Mean = 3.10,
SD = 0.62). This indicates a general openness and belief
in AI's benefits and future potential, despite lower
knowledge and skill levels.
•
Ethical and Societal Implications of AI: The
lowest mean score was observed in the ethical and
societal implications dimension (Mean = 2.20, SD =
0.58), highlighting a significant gap in awareness
regarding AI's potential biases, fairness, privacy
concerns, and broader societal impacts.
4.3. Variations in AI Literacy by Demographics:
•
Gender: A statistically significant difference
was observed in overall AI literacy scores between
genders (t(450) = 3.15, p < 0.01). Male students
exhibited a slightly higher mean AI literacy score (Mean
= 2.61, SD = 0.47) compared to female students (Mean
= 2.45, SD = 0.48). This aligns with some existing
literature indicating gender gaps in technology and AI
perception [3, 4].
•
Academic Discipline: One-way ANOVA revealed
a statistically significant difference in overall AI literacy
across academic disciplines (F(3, 448) = 8.76, p < 0.001).
Students in STEM fields (Mean = 2.80, SD = 0.45)
demonstrated higher AI literacy compared to those in
Social Sciences (Mean = 2.40, SD = 0.46) and
Humanities (Mean = 2.30, SD = 0.49). This is likely
attributable to greater exposure to and engagement
with technology in STEM curricula.
•
Year of Study: A significant difference was also
found across years of study (F(3, 448) = 5.21, p < 0.01).
Senior students (Year 3 and 4) tended to have slightly
higher AI literacy scores compared to junior students
(Year 1 and 2), suggesting that accumulated higher
education exposure may contribute to a gradual
increase in AI understanding.
•
Device Ownership: Students who reported
owning a greater number of technological devices (e.g.,
smartphones, laptops, smart home devices) showed a
moderately positive correlation with overall AI literacy
(r = 0.28, p < 0.001), indicating that greater personal
exposure to technology may somewhat contribute to
AI literacy.
These results underscore a generally low baseline of AI
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International Journal of Pedagogics (ISSN: 2771-2281)
literacy among Indonesian higher education students,
with notable variations across demographic groups and
dimensions.
DISCUSSION
The findings of this study, indicating a generally low
level of AI literacy among Indonesian higher education
students, align with similar observations in other
contexts regarding non-experts' understanding of AI
[21, 32]. This low baseline, particularly in the
fundamental "Knowledge of AI Concepts" and "Ethical
and Societal Implications of AI" dimensions, suggests
that many future professionals in Indonesia may lack a
foundational understanding of AI's capabilities,
limitations, and the critical ethical considerations
surrounding its deployment. This deficit could hinder
their ability to effectively integrate AI into their
respective fields and to critically evaluate AI-generated
outcomes, which is vital for an increasingly AI-driven
job market [17, 51].
The relatively higher score in "AI Skills and Application"
compared to theoretical knowledge might reflect a
passive familiarity with consumer-facing AI applications
(e.g., voice assistants, recommendation algorithms)
rather than a deep understanding of their underlying
mechanisms. This "user-level" interaction, while
important, is insufficient for navigating the
complexities of AI in professional or societal contexts.
As AI tools, including generative AI like ChatGPT,
become more prevalent in academic settings [9, 10, 27,
34, 40], a superficial understanding risks misuse or an
inability to critically assess the reliability and biases of
AI outputs [10]. Teachers themselves are still grappling
with AI integration [25, 49, 58], further emphasizing the
need for comprehensive AI literacy development.
A Social Perspective on AI in the Higher Education
System
The observed gender gap in AI literacy, with male
students exhibiting slightly higher scores, mirrors
findings in broader technology adoption and
perception studies [3, 4]. This suggests underlying
societal or educational factors that may lead to
differential exposure, interest, or confidence in AI
among male and female students in Indonesia.
Addressing this gap is crucial for ensuring equitable
participation in the AI revolution and preventing the
exacerbation of existing digital divides.
The significant differences across academic disciplines
and years of study are expected. Students in STEM
fields, due to their curriculum's emphasis on
computational thinking and data science, naturally gain
more exposure to AI concepts. The gradual increase in
AI literacy with higher years of study indicates that
formal education, even without specific AI literacy
curricula, contributes incrementally to students'
understanding. This highlights the potential for
deliberate integration of AI literacy into all disciplinary
curricula, not just STEM, to ensure a broader base of AI-
competent
graduates
[6].
This
aligns
with
recommendations
for
developing
educational
programs to elevate awareness and utilization of AI
technology [Journal of Pedagogical Research, 2].
The weak correlation between device ownership and AI
literacy suggests that mere access to technology does
not
automatically
translate
into
a
nuanced
understanding of AI. This points to the need for
structured educational interventions that go beyond
passive exposure, focusing on active learning, critical
engagement, and ethical reasoning related to AI [6, 47].
Such interventions could include project-based
learning initiatives [13, 28], problem-based learning
[14], and collaborative learning models [16, 31] that
encourage students to explore AI applications and their
implications in practical contexts. This will require not
only changes in curriculum but also professional
development for educators to effectively integrate AI
[59].
The low awareness of ethical and societal implications
is particularly concerning. As AI develops rapidly,
experts predict its profound impact on human
performance, societal structures, and future paradigms
[15, 36, 46]. Students, as future leaders and innovators,
must be equipped to critically evaluate AI's ethical
dimensions, including issues of privacy, bias,
algorithmic fairness, and accountability [47, 52].
Integrating ethics-focused modules or discussions into
AI literacy education is imperative to foster responsible
AI development and deployment. The shift towards AI-
enhanced learning environments requires careful
design, considering both pedagogical effectiveness and
ethical considerations [54, 52].
CONCLUSION
This study provides a critical assessment of AI literacy
levels among Indonesian higher education students,
revealing a generally low understanding, particularly
concerning fundamental AI concepts and its ethical
implications. While attitudes towards AI are
moderately positive, indicating an openness to the
technology, the observed gaps in knowledge and
critical understanding underscore an urgent need for
targeted educational interventions. The identified
disparities across gender and academic disciplines
further emphasize the importance of inclusive and
comprehensive strategies.
To effectively prepare Indonesian higher education
students for the complexities of an AI-driven world, it is
imperative that universities move beyond mere
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International Journal of Pedagogics (ISSN: 2771-2281)
technology exposure to implement structured AI
literacy curricula across all disciplines. These programs
should prioritize foundational knowledge of AI
concepts, foster critical thinking about AI's societal and
ethical dimensions, and provide practical opportunities
for students to engage with AI tools responsibly. Such
efforts will be crucial for empowering future
generations to not only adapt to but also ethically
shape the AI revolution, ensuring that Indonesia's
human capital remains competitive and capable in the
rapidly evolving global landscape. Further research
could explore the effectiveness of specific pedagogical
interventions
designed
to
enhance
different
dimensions of AI literacy.
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