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Education is widely recognized as a key domain for the promotion of the sustainable development goals (SDGs), prompting an increased focus on sustainable development in foreign language education. Despite increased attention, guidelines about SDGs are often primarily policy-based without concrete guidance, and the integration of education for sustainable development (ESD) within higher education curricula has been slow. This paper aims to mitigate this gap by providing an outline for the curriculum development for three elective English courses integrating SDG themes.

The paper begins by introducing the SDGs, ESD and its application to language education. From there, this paper outlines three content and language integrated learning courses that integrate global issues into their curriculum. Finally, there is a discussion and consideration of various factors to consider when implementing global issues into an English language classroom.

Following practical examples of how to integrate global issues into an English language classroom, considerations such as socio-cultural context, teaching context and the expertise of the instructor are discussed.

This paper covers a variety of social topics related to sustainable development in addition to the often addressed environmental topics. Many guidelines about integrating SDGs into education are policy-based without concrete guidance, so this paper aims to provide practical examples and considerations.

This study aims to improve the Unified Theory of Acceptance and Use of Technology (UTAUT) model by examining technological anxiety and other influential factors on international students' adoption of mobile learning (m-learning) during COVID-19 emergency remote teaching (ERT).

This study utilized the modified UTAUT framework to test hypotheses through a cross-sectional survey method. Participants were university students studying Chinese as a foreign language who were selected using a convenience sampling approach. An online questionnaire was then administered. The data collected from the surveys were analyzed using the partial least squares method with SmartPLS 4 software.

The study examined 16 hypotheses and found support for six of them. The results confirmed that performance expectancy (PE) is a significant predictor of behavioral intention (BI), and anxiety influences both PE and effort expectancy. The negative effect of social influence on anxiety was found to be significant, while facilitating conditions had a negative impact on learners' self-efficacy. The model fit indices indicated a good overall fit for the model.

This study presents a valuable contribution to the literature on m-learning in emergency education by incorporating technological anxiety into the enhanced UTAUT model. Examining the relationships between the key factors of the model provides a better understanding of learners' intentions and can inspire researchers to establish new theoretical foundations to evaluate the roles of these factors in diverse educational settings.

The study found that performance expectations are linked to learners' intentions, and anxiety indirectly affects BIs to use mobile learning platforms. Thus, these platforms should be designed to meet learners' expectations with minimum effort and eliminate anxiety triggers to facilitate ease of use. Language curriculum developers and policymakers should incorporate mobile learning applications to support diverse language skills, address students' needs and encourage their use through professional development opportunities for instructors.

Social factors have been found to significantly influence anxiety levels among learners. Therefore, it is crucial for teachers and family members to play an essential role in mitigating anxiety's adverse effects. Discussing related issues can enhance the quality of mobile learning and stimulate social initiative by providers, ultimately improving the learning experience for all learners, regardless of their location or circumstances. This can also contribute to the growth and development of society.

This study contributes to the originality of m-learning development by proposing an enhanced UTAUT model that considers anxiety and emphasizes the critical role of foreign learners' BIs. It provides fundamental guidelines for designing and evaluating m-learning in ERT contexts.

Despite the large number of Indonesian health-care workers working as migrant care workers in Japan, there is a lack of studies that have investigated this phenomenon or assessed the working conditions of Indonesian care workers working in Japanese aged-care facilities. This study aims to explore the work experiences of Indonesian care workers in Japan.

A qualitative descriptive research design was used, and a purposive sample of 18 Indonesian health-care workers (12 nurses and six midwives) who work as care workers in Japan participated in this study. Semistructured interviews were conducted with these participants between December 2022 and January 2023. The data were analyzed using content analysis. The Consolidated Criteria for Reporting Qualitative Research checklist was used to report this study.

Four key themes emerged from the data: easy but mentally challenging, being a care worker is a blessing, working in a partially Muslim-friendly environment and enjoy living: prefer to stay longer.

The work experiences of Indonesian care workers in Japan are complex and multifaceted. By understanding their experiences and needs, the authors can work toward creating more inclusive and supportive workplaces for all.

This study aims to investigate a unique approach to learning languages through self-directed online learning. Specifically, it explores the self-management abilities and skills learners need while learning a language outside traditional classroom settings when using mobile-assisted learning technology.

A mixed-methods approach was used in this study, including an online survey of 84 people and 10 semi-structured interviews.

Findings reveal the significant role of specific and well-defined learning goals in enhancing learners’ performance. These goals can be either self-initiated by the learners themselves or defined by the technological features of the learning platform. However, the presence of distractions in learners’ daily lives presents challenges to effective time management, affecting learners both physically and psychologically. A key aspect of self-directed language learning lies in the learners’ ability to seek out relevant human and material resources beyond the confines of a single mobile-assisted language learning (MALL) tool. The authenticity of these resources is crucial in ensuring meaningful and effective learning experiences.

Understanding how learners navigate and discover valuable resources is a central focus of this study. This research offers valuable insights into the field of self-directed language learning, revealing the pivotal role of self-management skills with mobile-assisted learning technology. The findings contribute to the broader field of language education and offer practical implications for educators and developers seeking to optimize self-directed language learning experiences through innovative and technologically driven approaches.

MALL is often ideal for individualized informal learning, but the existing literature focuses heavily on formal learning situations, underestimating the importance of MALL practices in various informal settings. Most research reports on MALL-based self-directed learning primarily sample traditional English-learning university students. Therefore, there is a need for research on how nontraditional older adult learners self-direct their language learning with mobile technology outside the classroom.

This study aims to develop an extended social attachment model for expatriates, integrating a multiple stakeholder perspective, to understand evacuation decisions during disasters.

Through interviews with 12 Tokyo-based expatriates who experienced the 2011 Tohoku earthquake, tsunami and nuclear disasters, this study collects the lived experiences of a diverse set of expatriates. This data is analyzed abductively to map relevant evacuation factors and to propose a reaction typology.

While the 2011 Tohoku disasters caused regional destruction and fears of nuclear fallout, Tokyo remained largely unscathed. Still, many expatriates based in Tokyo chose to leave the country. Evacuation decisions were shaped by an interplay of threat assessment, location of attachment figures and cross-cultural adjustment. The study also discusses the influence of expatriate types.

Disaster planning is often overlooked or designed primarily with host country nationals in mind. Expatriates often lack the disaster experience and readiness of host country nationals in disaster-prone regions in Asia and beyond, and thus might need special attention when disaster strikes. This study provides advice for how to do so.

By unpacking the under-researched and complex phenomenon of expatriate reactions to disasters, this study contributes to the fields of international human resource and disaster management. Specifically, seven proposition on casual links leading to expatriate evacuation are suggested, paving the way for future research.

The proliferation of ChatGPT, as in many other digital technologies and social media, has increasingly impacted many aspects of modern life, including second and foreign language education. This study, building on a common theoretical position of all these advances in Artificial intelligence (AI), seeks to establish a model for ChatGPT research on English language learning. It specifically explores the dimensions in which ChatGPT aids students in their English language learning.

The study adopts grounded theory in collecting and analyzing data from 20 ResearchGater (RG) through a two-week RG discussion about ChatGPT uses in their language learning contexts. Data collected via the discussion was analyzed thematically.

Preliminary findings show that ChatGPT can be used in developing learners' language skills; scaffolding the learning process by providing feedback to students on their language use and acting as partners in practicing language with recommended activities for more language practice.

The study contributes a five-dimension model for artificial intelligence assisted language learning (AIALL). The model involves flexible teacher's role to consolidate learner autonomy and provide enjoyable learning, urges future innovation, and celebrates various applications. Examining the AIALL model of ChatGPT for language learning, teachers should provide some directions for properly using this new application.

Given the persistent receptive skills challenges faced by language learners and the numerous merits of using technologically-enhanced learning in the form of mobile-assisted language learning in language teaching, this study decides to incorporate a context-analysis-practice-exploration lesson-planning framework with mobile learning to improve the receptive skills of learners. This step is necessary on the recommendation by scholarly research that while implementing technology, teacher training, digital literacy and expertise, incorporating good teaching practices and lesson planning frameworks may assist in yielding positive results.

This study decides to utilize a mixed-method research design through an experimental approach to elicit information from 90 EFL students concerning the effectiveness of incorporating the context-analysis-practice-exploration framework in a mobile-leaning mode instructional delivery to improve their reading and listening skills.

After collecting and analyzing data, the study found that while the participants perceived enhanced-mobile learning to make lessons enjoyable, integrating this framework and m-learning improved their reading skills. This study used notable findings to make pedagogical conclusions on the objective of this study.

This study contributes through empirical evidence on the effectiveness of incorporating mobile learning and a responsive lesson planning framework towards improving English as a foreign language learners' learning outcome. Besides, this study is the first to probe and unpack the effectiveness of a responsive lesson-planning framework in language education.

This study aims to analyze translanguaging practices and beliefs of Iranian English for General Purposes (EGP) teachers and find discrepancies between the practice and perception of educators in bi/multilingual species in Iranian educational settings.

The study involved interviewing ten teachers and observing six of their sessions, which yielded qualitative data.

The results showed that the participating teachers produced recurring themes such as the significance and limitations of translanguaging, techniques for training multilingual learners and the restrictions imposed by policies that discourage the use of L1 in language institutes in Iran. A noteworthy observation made in this investigation was that educators who possessed competency in three or more languages exhibited greater endorsement of translanguaging in both their perceptions and practices.

This study has significant implications for instructors, teacher trainers and policymakers operating within multilingual environments. It serves as a pioneering study that invites a productive synergy between Western and Asian researchers in exploring bi/multilingual spaces within Asian educational contexts.

This study brings a fresh perspective to the current body of research on teacher agency in bi/multilingual educational settings. By utilizing qualitative methods, it offers unique and original insights. Particularly noteworthy is the discovery that educators who are proficient in three or more languages are more inclined to support translanguaging. This observation adds a distinctive understanding of translanguaging in language education. It opens up new possibilities for exploring the application and efficacy of the translanguaging approach in Asian bi/multilingual spaces in education.

This paper aims to use text mining methods to explore the similarities and differences between countries’ national digital transformation (DT) and Industry 4.0 (I4.0) policies. The study examines the applicability of text mining as an alternative for comprehensive clustering of national I4.0 and DT strategies, encouraging policy researchers toward data science that can offer rapid policy analysis and benchmarking.

With an exploratory research approach, topic modeling, principal component analysis and unsupervised machine learning algorithms (k-means and hierarchical clustering) are used for clustering national I4.0 and DT strategies. This paper uses a corpus of policy documents and related scientific publications from several countries and integrate their science and technology performance. The paper also presents the positioning of Türkiye’s I4.0 and DT national policy as a case from a developing country context.

Text mining provides meaningful clustering results on similarities and differences between countries regarding their national I4.0 and DT policies, aligned with their geographic, economic and political circumstances. Findings also shed light on the DT strategic landscape and the key themes spanning various policy dimensions. Drawing from the Turkish case, political options are discussed in the context of developing (follower) countries’ I4.0 and DT.

The paper reveals meaningful clustering results on similarities and differences between countries regarding their national I4.0 and DT policies, reflecting political proximities aligned with their geographic, economic and political circumstances. This can help policymakers to comparatively understand national DT and I4.0 policies and use this knowledge to reflect collaborative and competitive measures to their policies.

This paper provides a unique combined methodology for text mining-based policy analysis in the DT context, which has not been adopted. In an era where computational social science and machine learning have gained importance and adaptability to political and social science fields, and in the technology and innovation management discipline, clustering applications showed similar and different policy patterns in a timely and unbiased manner.

The global landscape of higher education has witnessed a steady increase in the mobility of international students, as more individuals seek diverse academic experiences and cross-cultural learning opportunities. This paper conducts a systematic literature review to investigate trends, research directions and key themes in the literature. By utilising the push–pull factor model the aim is to provide a comprehensive understanding of the factors influencing international students' choices to pursue higher education and future career opportunities abroad.

A systematic literature review approach was applied. The selection was made using PRISMA framework-based inclusion and exclusion criteria. The review includes 43 publications from 2010 to 2022.

The review results revealed five themes of scholarly conversations labelled as (1) betterment of life, (2) policy of the host country, (3) role of institutions, (4) return to home country and (5) social, economic, environmental, individual and cultural factors. The findings emphasise on the significance of factors such as the quality of education, visa requirements, academic reputation, tuition fees, availability of scholarships, job opportunities, social, economic, environmental, individual and cultural factors. The paper also identifies language barriers, visa policies and social integration difficulties as major barriers to international students' stay in the host country after graduation.

This research enhances the current body of literature by conducting a comprehensive analysis of the empirical evidence available in literature that investigates the mobility of international students. The outcomes of this study will make a valuable contribution towards developing a more profound comprehension of the primary factors that influence international students' decision to pursue their education abroad.