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Technology and Artificial Intelligence Literacy in the Digital Age:
Insights from a Teacher Mobility Program
Nazlena Mohamad Ali
1*
, Mohamad Taha Ijab
1
, Wahiza Wahi
2
, Azwan Shaiza Nizam
2
1
Institute of Visual Informatics, Universiti Kebangsaan Malaysia
2
School of Liberal Studies (Pusat Pengajian Citra Universiti), Universiti Kebangsaan Malaysia
*Corresponding Author
DOI: https://dx.doi.org/10.47772/IJRISS.2025.910000098
Received: 06 October 2025; Accepted: 14 October 2025; Published: 05 November 2025
ABSTRACT
As digital transformation accelerates, teacher mobility programs must cultivate educators' cross-cultural
competencies alongside technological and AI literacy. Yet significant gaps persist: many academics possess only
a moderate familiarity with emerging technologies, raising concerns about their capacity to engage meaningfully
with digitally mediated pedagogical and research practices. These limitations are exacerbated by ethical
considerations, data privacy concerns, and risks of cognitive offloading inherent in AI integration. Addressing
these deficiencies is essential to maintaining the relevance and efficacy of teacher mobility programs within
global academic contexts. This study examines technology and AI literacy among academics in a teacher
mobility program and identifies key themes shaping their perceptions of AI in education and research.
Employing a mixed-methods design, the study combined quantitative demographic surveys with qualitative
reflections from fourteen participants, balanced by gender and representing diverse age groups and disciplines.
The data encompassed professional backgrounds, technological competence, familiarity with AI tools, and a
thematic analysis of participant reflections. The findings indicate predominantly average self-assessed levels of
technology and AI literacy. However, qualitative data reveals growing recognition of AI's transformative
potential, with perceptions evolving from AI as a tool to AI as a collaborative partner in pedagogy, research, and
scholarly writing. While opportunities for enhanced academic practice emerge, challenges concerning ethical
deployment and overdependence remain salient. These findings underscore the need to integrate structured
digital literacy training into teacher mobility programs to prepare educators for the contemporary digital
demands.
INTRODUCTION
Teacher mobility programs have emerged as pivotal mechanisms within the academic community to foster cross-
cultural collaboration, professional development, and international partnerships. These initiatives provide
educators opportunities to exchange knowledge, adopt innovative pedagogical approaches, and facilitate the
global circulation of ideas. In recent years, advances in educational technology have expanded the scope of
teacher mobility programs, enabling participants to engage not only in face-to-face settings but also through
virtual and blended learning environments (Knight, 2015; de Wit, 2020). Given the escalating importance of
digital skills, it is essential to investigate how academic participants adapt to technological demands during their
involvement in transnational mobility programs.
Despite the increasing integration of technology in higher education, there remains a paucity of research on how
teacher mobility participants, particularly those from China, navigate this evolving digital landscape. Although
China has made significant investments in educational technologies and artificial intelligence (AI) (Zhao &
Huang, 2020; Huang et al., 2022), little is known about the extent to which Chinese scholars incorporate these
technologies and AI-related research into their academic, pedagogical, and communicative practices within
mobility contexts. Addressing this knowledge gap is critical, as digital literacy is becoming a determining factor
in the effectiveness of academic exchange and collaboration in the twenty-first century.
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The current study aims to explore the technological and AI literacy of Chinese academics participating in an
international teacher mobility program. Specifically, it aims to investigate the relationships between participants’
professional and demographic characteristics and their levels of technological proficiency, as well as to analyze
their knowledge and competencies in applying AI within research and educational settings. By doing so, this
study contributes to the growing body of literature on digital skills in higher education and situates its findings
within the broader framework of global academic mobility (Redecker, 2017; Voogt & Roblin, 2012).
This study holds significance for policymakers, academic institutions, and program administrators by providing
insights into the readiness of higher education scholars to engage effectively in the digital era, particularly within
mobility initiatives. The findings offer valuable implications for the design of targeted training, capacity-building
efforts, and policy measures aimed at enhancing technological and AI literacy. Ultimately, these insights will
support the alignment of teacher mobility programs with global digital transformation trends and reinforce their
impact on the future of higher education.
The structure of this paper is organized as follows. The subsequent section presents a review of literature
pertaining to AI in education, digital literacy, and teacher mobility. This is followed by the methodology section,
which outlines the study design, data collection procedures, and analytical methods employed. The results
section reports on participant demographics, levels of technological literacy, and AI literacy. The discussion
contextualizes these findings in light of previous literature, and the conclusion underlines the implications,
limitations, and suggestions for future study.
LITERATURE REVIEW
A. Mobility Programs: Global Trends
Teacher mobility programs have become a cornerstone of the internationalization strategies in higher education.
Broadly defined, these programs involve the temporary physical or virtual movement of academic staff across
national borders to engage in teaching, research, and collaborative projects (Knight, 2015). The primary
objectives of such initiatives are multifaceted: they aim to foster cross-cultural understanding, facilitate the
exchange of pedagogical knowledge and innovative teaching practices, build international research networks,
and enhance the global profile of participating institutions (de Wit, 2020). The benefits of teacher mobility are
well-documented. For the individual educator, participation leads to professional development through exposure
to different academic systems and student cohorts, ultimately enriching their teaching methodologies and
research perspectives (Knight, 2015). For their home and host institutions, these programs act as conduits for
international collaboration, curriculum innovation, and the strengthening of institutional partnerships. In the
contemporary context, the nature of mobility has evolved beyond purely physical exchanges. The integration of
technology has given rise to "blended" or "virtual mobility," where educators interact with international
colleagues and students through digital platforms, thereby expanding the reach and inclusivity of these programs
(de Wit, 2020). This digital shift, however, introduces new prerequisites for participants, necessitating a level of
technological proficiency to fully engage in these hybrid academic environments.
In China, teacher and student mobility has been a central pillar of the national strategy to build world-class
universities and enhance the global competitiveness of its higher education system. The scale
of outbound mobility for students is immense, with China consistently being the top source of international
students globally, particularly in countries like the United States, the United Kingdom, and Australia (Huang et
al., 2022). For academics, outbound mobility is heavily promoted through state-sponsored programs such as the
"Chinese Government Scholarship Program" and the "Short-Term Visiting Scholar Program," which fund
lecturers and researchers to spend time at leading overseas institutions to upgrade their qualifications and
research capabilities (Wen & Hu, 2019). Conversely, inbound mobility is also actively encouraged through
initiatives like the "Study in China" initiative, which aims to attract 500,000 international students by the
2025/2026 academic year. For faculty, this involves recruiting international scholars and experts on short-term
contracts to teach specialized courses and co-supervise research, a practice often embedded in university-level
partnerships and Confucius Institutes abroad. These programs are typically characterized by a strong alignment
with national developmental goals, focusing on science, technology, engineering, and mathematics (STEM)
fields, though mobility in humanities and social sciences is also significant (Huang et al., 2022).
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Similarly, Malaysia has strategically established itself as a prominent international education hub, facilitating a
dynamic and multidirectional flow of academic mobility. Central to this effort is the Malaysia Education
Blueprint (Higher Education) 20152025, which explicitly prioritizes the internationalization of both curriculum
and academic staff. To support outbound mobility, initiatives such as the Academic Training and Mobility
Scheme for University Lecturers (SLAB) and the MyBrain15 program offer funding for Malaysian academics
to undertake doctoral studies, postdoctoral research, and sabbaticals abroad, thereby enhancing capacity and
fostering international networks (Wan & Abdullah, 2021). For students, outbound mobility is promoted through
mechanisms including credit transfer programs and semester-abroad schemes. More distinctively, Malaysia has
seen tremendous growth in inbound mobility, actively recruiting international students, particularly from China,
the Middle East, and other ASEAN nations, through twinning degrees, branch campuses of foreign universities,
and its own promoted "Edu-Tourism" initiatives Wan & Abdullah, 2021). This increasing inbound student
population has generated demand for both local and international faculty, contributing to inbound teacher
mobility via recruitment and short-term visiting professorships. The mobility programs encompass a broad
spectrum of activities, ranging from traditional faculty exchanges and collaborative research projects to
structured internationalization-at-home initiatives that integrate global perspectives into the domestic
educational environment.
B. Technology Literacy in Higher Education
The concept of digital literacy has evolved beyond fundamental computer skills to encompass a complex,
multifaceted set of competencies. It is broadly understood as the confident, critical, and responsible use of digital
technologies for learning, working, and participating in society (Redecker, 2017). Key dimensions, as outlined
in frameworks like the European Digital Competence Framework for Educators (DigCompEdu), include
information and data literacy, communication and collaboration, digital content creation, safety, and problem-
solving (Redecker, 2017). Within the academic sphere, these competencies manifest in an educator’s capacity
to effectively locate and critically evaluate digital information, employ collaborative technologies, design and
develop engaging digital instructional materials, and comprehend issues pertaining to digital identity and data
privacy.
For mobile educators, technology literacy is not merely an ancillary skill but a fundamental enabler of successful
international exchange. Its importance is twofold. Firstly, it is crucial for navigation and integration within a new
academic environment, which may rely on different learning management systems, communication tools, and
digital research infrastructures. Secondly, it is essential for sustaining collaboration beyond the physical mobility
period. Mobile educators equipped with strong digital skills can maintain the professional networks and joint
projects initiated during their mobility, leveraging technology for ongoing virtual co-teaching, research, and
publication (Voogt & Roblin, 2012). A lack of such literacy can significantly hamper an educator's ability to
integrate, collaborate, and maximize the benefits of the mobility experience.
C. Artificial Intelligence (AI) Literacy in Education
As artificial intelligence (AI) becomes increasingly pervasive, a new form of competency is required: AI literacy.
While definitions are still coalescing, AI literacy can be understood as a set of competencies that enables
individuals to critically evaluate AI technologies; communicate and collaborate effectively with AI; and use AI
as a tool online, at home, and in the workplace (Long & Magerko, 2020). For educators, this extends beyond
basic operational skills to a deeper understanding of AI's core principles, its potential and limitations, and the
profound ethical implications of its use in educational settings (Liu & Bates, 2025).
The APRU whitepaper reframes the objective from merely developing individual 'skill' to building a broad
institutional familiarity, which it defines as the understanding and comfort level of students, faculty, and staff in
using generative AI for their day-to-day work. This familiarity encompasses not only the functional application
of AI but also an awareness of the broader context, including ethics, privacy, and safety (Liu & Bates, 2025).
This aligns with UNESCO's AI competency frameworks for teachers and students, which highlight awareness
of debates around AI's impact on equity, environment, social justice, and human rights as a critical component
of AI literacy (Miao & Cukurova, 2024; Miao & Shiohira, 2024).
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The applications of AI in academia are rapidly expanding, impacting core areas of an educator’s work and
demanding a "pedagogy first" approach to ensure that student learning and educators' pedagogical intent remain
central (Liu & Bates, 2025):
Teaching and Learning: AI-powered tools can enable personalized learning pathways, provide automated
feedback, and create intelligent tutoring systems. However, a key insight is the distinction between using
unguided, general-purpose AI as a potential "crutch" and deploying intentionally designed educational AI that
promotes problem-solving and metacognitive skills (Liu & Bates, 2025). For instance, AI can act as a design
assistant for educators, helping to align learning outcomes with assessments, thereby augmenting human
capabilities rather than replacing them.
Communication: AI-driven translation tools break down language barriers, while chatbots can handle routine
student inquiries, freeing up educator time for more complex, relational interactions that students highly value
(Liu & Bates, 2025).
Research: AI is transforming research practices by accelerating systematic literature reviews, aiding in data
analysis, and assisting in manuscript preparation. However, this requires clear rules regarding data privacy and
the security of unpublished findings when using cloud-based AI platforms (Liu & Bates, 2025).
The literature reveals a discernible shift in educators’ perceptions of artificial intelligence, evolving from
viewing AI as a mere tool to recognizing it as a collaborative “partner” in the academic process. This evolving
partnership, however, introduces a range of significant challenges. The CRAFT framework outlined in the APRU
whitepaper highlights several interconnected issues, including ethical considerations, data privacy concerns, and
the potential for cognitive off-loading, a phenomenon whereby excessive dependence on AI may hinder the
cultivation of critical scholarly skills and undermine the essential cognitive engagement required for effective
learning (Liu & Bates, 2025). Accordingly, a fundamental component of AI literacy involves cultivating
metacognitive awareness that enables educators to discern not only how to utilize AI, but also when to engage it
and when to rely on their own intellectual capacities.
Ultimately, fostering AI literacy is fundamental to maintaining trust across the educational ecosystembetween
students and educators, between staff and leadership, and between universities and the public. A lack of literacy
can erode this trust, leading to adversarial mindsets and an over-reliance on imperfect AI detection tools.
Therefore, building comprehensive AI literacy is not an optional add-on but a core requirement for navigating
the future of higher education responsibly and productively.
D. Gaps in Current Study
Despite the growing emphasis on both teacher mobility and digital/AI competencies, a significant research gap
exists at the intersection of these domains. Current research often treats these domains in isolation, with extensive
literature on the structures and outcomes of mobility programs on one hand, and on the development of digital
and AI literacy in static, non-mobile faculty on the other. Notably, there is a pronounced scarcity of studies that
specifically investigate the technological and AI literacy of educators engaged in teacher mobility programs.
This gap is particularly salient and critical within the context of Chinese academia. China has made substantial
national investments in educational technology and AI (Zhao & Huang, 2020; Huang et al., 2022), and its
scholars are increasingly active in global academic exchanges. However, as highlighted in the present study,
little is known about how Chinese academics, who are central to these mobility initiatives, navigate the digital
demands of international collaboration. The extent to which they actively and effectively incorporate digital
tools and AI into their teaching, research, and communication practices within the context of mobility programs
remains insufficiently explored.
The APRU whitepaper by Liu & Bates (2025) underscores that the higher education sector's response to
generative AI has largely been "piecemeal and reactive," focusing on immediate concerns like academic integrity
rather than "systematic integration." This reactive approach is mirrored in the context of mobility programs.
There is a critical void in understanding how these programs are addressing the five interdependent elements of
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the CRAFT frameworkCulture, Rules, Access, Familiarity, and Trustfor their mobile educators. Key
unanswered questions include:
Rules & Access: What specific policies govern the use of AI tools by mobile educators working across different
national jurisdictions and digital infrastructures? How do institutions ensure equitable access to advanced AI
tools for visiting scholars, especially those from low- and middle-income countries, to prevent the "widening
[of] existing digital divides" (Liu & Bates, 2025, p. 19)?
Familiarity: How are mobility programs systematically building the AI familiarity of participants, moving
beyond basic digital literacy to a deep understanding of AI's pedagogical applications and ethical implications?
The current "lack of a generative AI strategy" in many institutions (Liu & Bates, 2025, p. 22) suggests this is
likely a major oversight in mobility planning.
Culture & Trust: How do differing regional, institutional, and disciplinary cultures around AI, as detailed by
Liu & Bates (2025), impact collaboration and trust within mobile academic teams? The role of mobility programs
in either bridging these cultural divides or inadvertently exacerbating them is entirely unexamined.
Understanding these dimensions is critical, as digital and AI competence is a key determinant of effective
academic exchange in the 21st century. The current research begins to address this void by examining the
technological and AI literacy of Chinese academics in a mobility program. However, it also reveals the need for
a more structured, framework-driven approach, as proposed by Liu & Bates (2025), to systematically embed
digital and AI literacy as a core component of academic mobility, thereby identifying a crucial area for further
scholarly inquiry and institutional support.
METHODOLOGY
Research Design
This study employed a mixed-method approach with quantitative descriptive and qualitative reflection to
examine the experiences and practices of academic staff from Taizhou University, China, who participated in a
teacher mobility program. This approach was chosen to characterize the attributes of a specific sample through
the collection of quantifiable and quantitative data.
Participants
The target samples for this study comprised academic staff from Taizhou University, China, who actively
participated in the teacher mobility program. These individuals were selected due to their distinctive experience
in cross-institutional teaching and research collaboration, rendering them well-suited to address the goals of this
study. Their participation was entirely voluntary.
Data Collection on Survey Instrument
To obtain a comprehensive understanding of the participants’ characteristics and practices, the survey instrument
was structured into several sections. The first section focused on collecting demographic information, including
age, gender to provide contextual background. The second section addressed teaching experience, encompassing
pedagogical approaches, years of service, and specialization. Distinct sections were dedicated to gauging
participants’ comfort and confidence in utilizing digital technologies and artificial intelligence (AI) within
educational settings. Additionally, to explore the impact of mobility on academic collaboration and knowledge
dissemination, the survey incorporated items related to research activities, publication practices, and professional
interactions. To capture nuanced insights beyond quantitative data, open-ended questions were also included,
allowing participants to reflect more deeply on their experiences.
All eligible participants were invited to complete the online survey through institutional communication
channels. The survey link, hosted on Google Forms, was distributed alongside clear instructions and assurances
of confidentiality. Data collection occurred within a designated timeframe, allowing participants the flexibility
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to respond at their convenience. To increase response rates and ensure adequate representation, follow-up
reminders were issued. The online distribution method facilitated a more efficient data collection process while
minimizing logistical challenges, particularly within the context of the study’s focus on academic mobility.
Data Collection on Qualitative Reflection
The qualitative data consists of written reflections gathered from participants at the conclusion of the modules.
Participants were given a set of structured, open-ended questions that prompted them to reflect on the module
content and its application to their own professional contexts.
For example, prompts included:
• "Reflect on how Artificial Intelligence can be applied in your teaching and learning context"
• "What opportunities and challenges do you foresee in integrating AI tools in your classroom or research?"
• "Provide one concrete example of how you might use an AI tool"
• "Reflect on your own academic writing and publication journey"
This method of data collection was chosen to elicit detailed, thoughtful, and personal accounts, allowing for an
in-depth exploration of the participants' evolving perspectives. The reflections served as a rich source of
qualitative data, capturing individual insights, proposed applications, and perceived challenges.
Analysis of Data
Both quantitative and qualitative methods were used in the data analysis. The quantitative results from each
survey segment were compiled and presented using descriptive statistics. Patterns in the respondents'
demographics, instructional strategies, and technological literacy were discovered according to these statistical
metrics. Thematic description was used to analyze open-ended answers from the reflection sections in order to
identify recurrent themes and viewpoints. While preserving the rigour and clarity required for quantitative
descriptive research, this combination of descriptive and thematic description provided a comprehensive
knowledge of the participants' experiences and activities.
RESULTS AND DISCUSSION
Demographics Survey
The study involved fourteen respondents, evenly balanced by gender, with seven males (50%) and seven females
(50%). Regarding age distribution, the majority of participants (n = 10) were under 49 years old, while the
remaining four were aged 50 and above. This distribution reflects a well-rounded representation of both mid-
career and senior academics, thereby capturing perspectives from individuals at varied stages of their
professional trajectories.
In terms of professional experience, the cohort comprised predominantly highly experienced educators. Notably,
eight participants reported over 20 years of teaching experience, highlighting the presence of senior teachers
with substantial pedagogical expertise. Such extensive experience is valuable for capturing insights that are
grounded in long-term academic practice, while the perspectives of those with fewer years of service enrich the
data with views shaped by more recent training and exposure to evolving educational technologies.
The participants represented a diverse range of specializations, encompassing both humanities and applied fields.
Their areas of expertise included discourse analysis, English teaching, language, literature and linguistics,
teacher development, cross-cultural communication, materials engineering, British and American literature and
translation, digital image processing, rhetoric, industrial economics, urban planning, and applied linguistics.
This diverse disciplinary spread ensures that the findings reflect not only language and literature-based
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disciplines but also perspectives from technical and professional domains, thereby providing a comprehensive,
multidimensional view of teaching and research practices.
Regarding digital competencies, participants’ technology literacy and AI literacy were predominantly
characterized as possessing average knowledge. This suggests that while the participants generally demonstrate
competence in utilizing digital tools and possess a foundational understanding of AI concepts, they do not yet
qualify as advanced users. The designation of “average knowledge” underscores significant opportunities for
targeted professional development, especially in relation to emerging technologies and the application of AI
within educational contexts.
When asked about specific AI tools, the respondents reported familiarity with several widely used platforms.
These included ChatGPT, as well as Deepseek, Tecent Yuanbao, Doubao, and Qwen. The variety of tools
reported indicates that participants are engaging with a diverse range of AI technologies rather than being limited
to a single ecosystem. This reflects both global trends, exemplified by platforms such as ChatGPT, and regionally
developed applications, such as Yuanbao and Doubao. Such exposure illustrates a willingness to integrate AI
into academic and professional practices, although the overall self-assessed proficiency remains at an
intermediate level. TABLE 1 presents a detailed demographic profile of the participants.
Table 1: Descriptive Demographic
Category
Detail
Total Participants
14
Gender
7 Male, 7 Female
Age Range
10 respondents below 49 years old
4 respondents above 50 years old
Teaching Experience
8 respondents with more than 20 years of teaching
5 respondents with 10 - 20 years
1 respondent with 5 - 10 years
Specializations
Discourse Analysis, English Teaching, Language, Literature & Linguistics, Teacher
Development, Cross-cultural Communication, Materials Engineering, British and
American Literature and Translation, Digital Image Processing, Rhetoric, Industrial
Economics, Urban Planning and Applied Linguistics.
Technology Literacy
Mostly average knowledge
AI Literacy
Mostly average knowledge
Qualitative Reflection
Key themes that emerged from this study include:
The transformative role of AI in pedagogy, shifting from a mere tool to an active collaborative partner.
The opportunities and challenges associated with AI integration, particularly ethical considerations, data privacy,
and the risk of cognitive offloading.
The influence of AI on academic research and writing processes, encompassing activities from literature review
to journal selection
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Participant reflections underscore the transformative potential of AI in educational practice, with AI increasingly
viewed not simply as a supportive instrument but as a collaborative agent in teaching and learning. Educators
highlighted AI’s capacity to enhance classroom practices by providing adaptive feedback, personalized learning
support, and improved engagement strategies. This paradigm shift, however, prompted critical discussions
regarding the redefinition of the teacher’s role, emphasizing the necessity for human expertise to balance
technological mediation and preserve the integrity and creativity inherent in the learning process.
Simultaneously, participants noted both the opportunities and challenges associated with AI integration. While
AI holds considerable potential to accelerate various research tasks, including literature review, journal selection,
and manuscript preparation, it also raises significant concerns related to ethical use, data privacy, and the
potential for over-reliance that may result in cognitive offloading. These issues reflect a growing awareness that
while AI can enhance efficiency and innovation, critical thinking and scholarly judgment must remain at the
forefront. Overall, the reflections point toward a future where AI reshapes academic practices, but its sustainable
integration will depend on striking a balance between technological possibilities and ethical responsibilities. By
integrating the quantitative finding of knowledge with the nuanced qualitative themes, the potential between
participants' moderate self-assessed skills and their understanding of AI's collaborative could be explored.
CONCLUSION
The demographic findings reveal a balanced representation of gender and age, encompassing both mid-career
and senior academics participants. A significant proportion of participants reported over twenty years of teaching
experience, demonstrating substantial pedagogical expertise across a wide range of disciplines, including applied
linguistics, literature, engineering, and urban planning. Despite this diverse and extensive academic background,
respondents consistently indicated average levels of technological and AI literacy. Their familiarity primarily
encompassed platforms such as ChatGPT, Deepseek, Tencent Yuanbao, Doubao, and Qwen. These findings
suggest a general openness to adopting digital technologies, while also highlighting the need for structured
initiatives to bolster both confidence and competence in effectively utilizing these tools.
These findings underscore the critical importance of integrating technology and AI literacy into teacher mobility
programs. As mobility initiatives aim to foster academic exchange, collaboration, and innovation, equipping
educators with stronger digital skills will enable them to fully engage with emerging teaching and research
practices across international contexts. Looking forward, the future of teacher mobility in the digital age must
prioritize not only cross-cultural and disciplinary exchange but also the cultivation of digital competence. By
embedding AI and technology training into mobility frameworks, programs can empower educators to be more
adaptable, future-ready, and capable of contributing to global academic ecosystems. The limitations of this study
arise from the limited sample size; statistical tests could not be carried out; hence the results cannot be
generalized.
Future efforts in teacher mobility programs should systematically incorporate digital and AI literacy training as
a foundational element of academic exchange, thereby ensuring that educators develop both cultural adaptability
and technological proficiency. This can be achieved through tailored workshops on emerging AI tools,
collaborative projects that integrate digital platforms, and mentorship models that pair digitally skilled academics
with those less experienced. Additionally, program designs should anticipate the rapid evolution of educational
technologies by incorporating flexible curricula that adapt to new tools and practices. By doing so, mobility
initiatives will not only enhance cross-border collaboration but also prepare educators to thrive in a global
academic landscape increasingly shaped by digital transformation.
ACKNOWLEDGEMENT
The authors wish to acknowledge Universiti Kebangsaan Malaysia for providing the research grant (ZG-2025-
023). The contents in this article are the responsibility of the authors.
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