Purpose – The purpose of this paper is to explore and discuss the role of motivational cultural intelligence and its related strategies in the experiential learning and cross-cultural adjustment of self-initiated expatriate (SIE) women. Design/methodology/approach – Interactive qualitative analysis (IQA) was the design and process used for this research. Two IQA focus groups were conducted with a non-probability purposive sample of 21 SIE women, aged between 26 and 53 who were living and working in the Netherlands at the time of the research. Participants were invited to brainstorm about their adjustment experience and actively construct a framework of their adjustment experiences. Findings – Evidence is provided for the role of motivational CQ, with specific reference to reinvention, self-efficacy and goal-setting as motivational strategies, in the successful adjustment of SIE women. Conceptual frameworks of the cyclical learning process and motivational strategies with choice as a moderator in the process, have been developed. Three propositions for future research are also presented. Originality/value – This study represents an under-researched group and proposes conceptual frameworks for understanding the complex, multidimensional process of SIE women adjustment and the role of motivation, from a participant perspective.
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This study empirically examines individual and organizational factors that influence expatriates’ cross-cultural adjustment and job performance. The study was a quantitative research from 117 Thai expatriates who work in Thai multinational companies (MNC) located in Indonesia. The results of the study indicated that financial perceived organizational support influence positively towards Thai expatriates’ overall cross-cultural adjustment in Indonesia. This study found that cross-cultural training influenced positively towards Thai expatriates’ adjustment. A causal relationship between the predicting variables of crosscultural adjustment and Thai expatriates’ job performance was not found. Results suggest important consequences for management strategies providing support to Thai expatriate employees increasing their adjustment in Indonesia. Keywords: Cross-Cultural Adjustment; Job
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The development of intercultural competences has become a prominent goal for many study programs in higher education. A widely used frame to measure intercultural competence is Cultural Intelligence (CQ). While empirical research has focused extensively on the development of CQ by means of (student) mobility and long-term training, the effects of short-format trainings – a more cost-effective intervention that can be provided to a large number of participants – remain understudied. Existing findings are inconclusive, and it remains unclear under which conditions, and for whom, short-format interventions are effective in improving participants’ CQ. We propose that CQ development is contingent upon individual differences in multicultural personality traits (operationalized through the Multicultural Personality Questionnaire, MPQ). More specifically, in this study we investigate (1) whether a short-format (6-hour) training improves CQ among higher education students (n = 108), and (2) whether the development of CQ is moderated by students’ social-perceptual and stress-related MPQ trait scores prior to the training. Using a pre and post-test design we found that across the whole sample, all four facets of the CQ increased after the training. We also found that some social-perceptual traits of the MPQ moderated the development of CQ: Social initiative on Metacognitive CQ, Openmindedness on Cognitive CQ, and Social initiative and Openmindedness on Motivational CQ. Additionally, we did not find a moderator effect of stress-related MPQ traits on the development of Behavioral CQ. Based on our findings, we conclude that multicultural personality influences individuals’ susceptibility to intercultural education, underscoring the importance of individualized approaches in intercultural education.
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In the book, 40 experts speak, who explain in clear language what AI is, and what questions, challenges and opportunities the technology brings.
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© Springer International Publishing Switzerland 2014. Creating agents that are capable of emulating similar socio-cultural dynamics to those found in human interaction remains as one of the hardest challenges of artificial intelligence. This problem becomes particularly important when considering embodied agents that are meant to interact with humans in a believable and empathic manner. In this article, we introduce a conceptual model for socio-cultural agents, and, based on this model, we present a set of requirements for these agents to be capable of showing appropriate socio-cultural behaviour. Our model differentiates between three levels of instantiation: the interaction level, consisting of elements that may change depending on the people involved, the group level, consisting of elements that may change depending on the group affiliation of the people involved, and the society level, consisting of elements that may change depending on the cultural background of those involved. As such, we are able to have culture alter agents’ social relationships rather than directly determining actions, allowing for virtual agents to act more appropriately in any social or cultural context.
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No organisation or project is immune from the impact of globalisation and cultural diversity. Foreign sales by multinational corporations are growing 20 - 30% faster than their sales of export. This means that project managers and project stakeholders must increasingly cope with diverse cross-cultural stakeholders including: team members, customers, suppliers, competitors, and creditors (Javidan, Dorfman, De Luque, & House, 2006). This also means the complexity of project management has increased, as work environments are now both virtual and remote and situated in different time zones and locations. Large organisatio
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Artificial intelligence (AI) is transforming language access services in healthcare, making interpretation and translation faster and more scalable than ever before. Given that there are approximately 281 million international migrants as of 2024 [1], leveraging AI technology for mitigating language barriers in healthcare presents both new opportunities and new challenges. International migrants and others may experience language discordance – when patients and health care providers do not share a common language – which can hamper communication [2], decision making [3], and lead to poor health outcomes for patients [4]. Despite ongoing advancements in AI technology, its potential to improve or deter person-centred clinical care depends on its responsible application. In this article, our multilingual, international, and multidisciplinary members of the Language and Cultural Discordance in Healthcare Communication Special Interest Group of the International Association for Communication in Healthcare (EACH) [5] discuss challenges and opportunities in leveraging AI technology, provide practical applications, and end with recommendations to promote language access in healthcare. We highlight four of Picker’s Eight Principles of Person-Centered Care [6,7] and use them as a framework to address various issues in using AI for language translation and interpretation in healthcare.
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Abstract Aims: Medical case vignettes play a crucial role in medical education, yet they often fail to authentically represent diverse patients. Moreover, these vignettes tend to oversimplify the complex relationship between patient characteristics and medical conditions, leading to biased and potentially harmful perspectives among students. Displaying aspects of patient diversity, such as ethnicity, in written cases proves challenging. Additionally, creating these cases places a significant burden on teachers in terms of labour and time. Our objective is to explore the potential of artificial intelligence (AI)-assisted computer-generated clinical cases to expedite case creation and enhance diversity, along with AI-generated patient photographs for more lifelike portrayal. Methods: In this study, we employed ChatGPT (OpenAI, GPT 3.5) to develop diverse and inclusive medical case vignettes. We evaluated various approaches and identified a set of eight consecutive prompts that can be readily customized to accommodate local contexts and specific assignments. To enhance visual representation, we utilized Adobe Firefly beta for image generation. Results: Using the described prompts, we consistently generated cases for various assignments, producing sets of 30 cases at a time. We ensured the inclusion of mandatory checks and formatting, completing the process within approximately 60 min per set. Conclusions: Our approach significantly accelerated case creation and improved diversity, although prioritizing maximum diversity compromised representativeness to some extent. While the optimized prompts are easily reusable, the process itself demands computer skills not all educators possess. To address this, we aim to share all created patients as open educational resources, empowering educators to create cases independently.
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This article examines how collaborative design practices in higher education are reshaped through postdigital entanglement with generative artificial intelligence (GenAI). We collectively explore how co-design, an inclusive, iterative, and relational approach to educational design and transformation, expands in meaning, practice, and ontology when GenAI is approached as a collaborator. The article brings together 19 authors and three open reviewers to engage with postdigital inquiry, structured in three parts: (1) a review of literature on co-design, GenAI, and postdigital theory; (2) 11 situated contributions from educators, researchers, and designers worldwide, each offering practice-based accounts of co-design with GenAI; and (3) an explorative discussion of implications for higher education designs and futures. Across these sections, we show how GenAI unsettles assumptions of collaboration, knowing, and agency, foregrounding co-design as a site of ongoing material, ethical, and epistemic negotiation. We argue that postdigital co-design with GenAI reframes educational design as a collective practice of imagining, contesting, and shaping futures that extend beyond human knowing.
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Background: The immunization uptake rates in Pakistan are much lower than desired. Major reasons include lack of awareness, parental forgetfulness regarding schedules, and misinformation regarding vaccines. In light of the COVID-19 pandemic and distancing measures, routine childhood immunization (RCI) coverage has been adversely affected, as caregivers avoid tertiary care hospitals or primary health centers. Innovative and cost-effective measures must be taken to understand and deal with the issue of low immunization rates. However, only a few smartphone-based interventions have been carried out in low- and middle-income countries (LMICs) to improve RCI. Objective: The primary objectives of this study are to evaluate whether a personalized mobile app can improve children’s on-time visits at 10 and 14 weeks of age for RCI as compared with standard care and to determine whether an artificial intelligence model can be incorporated into the app. Secondary objectives are to determine the perceptions and attitudes of caregivers regarding childhood vaccinations and to understand the factors that might influence the effect of a mobile phone–based app on vaccination improvement. Methods: A mixed methods randomized controlled trial was designed with intervention and control arms. The study will be conducted at the Aga Khan University Hospital vaccination center. Caregivers of newborns or infants visiting the center for their children’s 6-week vaccination will be recruited. The intervention arm will have access to a smartphone app with text, voice, video, and pictorial messages regarding RCI. This app will be developed based on the findings of the pretrial qualitative component of the study, in addition to no-show study findings, which will explore caregivers’ perceptions about RCI and a mobile phone–based app in improving RCI coverage. Results: Pretrial qualitative in-depth interviews were conducted in February 2020. Enrollment of study participants for the randomized controlled trial is in process. Study exit interviews will be conducted at the 14-week immunization visits, provided the caregivers visit the immunization facility at that time, or over the phone when the children are 18 weeks of age. Conclusions: This study will generate useful insights into the feasibility, acceptability, and usability of an Android-based smartphone app for improving RCI in Pakistan and in LMICs.
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