How eTwinning scaffolds pedagogical transformation through generative AI: a European cross-national study

Introduction. This paper uses the affordances framework to investigate how Generation Z (GenZ) students in higher education use generative AI (GenAI). There is an increasing need to gain a deeper understanding of GenZ’s interaction with artificial intelligence tools to better support their integration into higher education and the workforce. Method. Data was collated from semi-structured interviews with 34 GenZ students in higher education. Analysis. Thematic analysis was conducted on the qualitative data collected from the semi-structured interviews. Results. The findings suggest GenZ students have seamlessly integrated GenAI into diverse aspects of their lives. This study highlighted three main GenAI affordances that resonate with GenZ students: a) content searching and curation b) content generation and ideation, and c) content enhancement and refinement, revealing new opportunities for information access. Conclusions. This study shed light on the perceived affordances of GenAI for GenZs, addressing a gap in the current literature on GenAI. The findings underscore the significant extent to which GenAI has been integrated into GenZ students’ daily lives. Our study contributes to a better understanding of how GenAI’s affordances facilitate and support GenZ students, providing invaluable insights that can inform future policies on developing literacy for AI use tailored to this group.

Although artificial intelligence is fundamentally reshaping the ecology of music learning, existing research has disproportionately emphasized performance outcomes while underexamining psychological mechanisms, leaving the tension between technological empowerment and cognitive dependence theoretically underarticulated. Following PRISMA 2020, we systematically searched four databases and included 21 empirical studies to examine how three AI tool types-assessment-oriented AI, generative AI, and Comprehensive/adaptive AI-differentially shape learners' self-beliefs and cognitive agency in music education. The evidence base remains geographically and developmentally concentrated: most studies were conducted in China and in higher education, while early childhood settings were absent. Using thematic analysis, we conducted cross-type comparisons and synthesized psychological pathways. Assessment-oriented AI most consistently strengthened ability beliefs via objectified, visualized feedback and positioned cognitive agency around self-monitoring, self-reactiveness, and self-reflectiveness. Generative AI tended to enhance value-attitude beliefs and intentionality by lowering technical barriers and reconfiguring learners' creative roles toward aesthetic decision-making and output curation. Comprehensive/Adaptive AI more often supported forethought and sustained engagement by dynamically maintaining alignment between task challenge and learner capability. Across studies, psychological empowerment manifested as increased perceived competence and control, heightened motivation and engagement, and visible self-regulated learning behaviors. Cognitive dependence, however, emerged through outsourcing evaluative authority, score-driven goal distortion, algorithm-accommodating self-censorship, and attributional shifts that tether confidence to technological support. Developmental differences were also observed regarding dependence mechanisms: primary learners tended to perceive AI as a restrictive "scoring referee," whereas higher education students demonstrated strategic agency in orchestrating AI assistance. Specifically, a critical construct-tool mismatch was identified: while assessment AI consistently supports self-reflectiveness, generative AI currently lacks sufficient evidence for fostering learners' forethought. In light of the identified construct-tool mismatch, future research should prioritize addressing the paucity of evidence on how generative and adaptive AI foster forethought and intentionality, thereby clarifying whether such technologies ultimately reconstruct or erode learners' cognitive agency.

This paper revisits Kling's (1994) framework for analyzing technology discourse by applying it to expert commentary on Generative AI (GenAI) posted on X (formerly Twitter) from November 2022 to June 2023. Using thematic content analysis on 1,000 top‐engaged posts, we assessed Kling's five genres—utopianism, anti‐utopianism, social realism, social theory, and analytical reduction—map onto current GenAI discussions. We found notable discourses fell outside these categories, prompting us to introduce a new genre called Enhanced Technological Realism (ETR), which includes Collaborative Tech Assessment (CTA) —current evaluative nature of GenAI discourse, and Tech‐futurism —speculative discourse depending on present scenarios of GenAI. This study establishes a foundational mapping of how online communities frame GenAI by applying and extending Kling's (1994) genre framework.

Purpose This study investigates the challenges faced by Vietnamese master's students enrolled in bilingual and English-Medium Instruction (EMI) programs in Taiwan. It examines how institutional, linguistic, cultural, financial, and health-related factors shape their academic and social adaptation within the bilingualization framework of Taiwan's Bilingual 2030 Policy (BN2030). By doing so, it highlights implementation gaps and the sociolinguistic tensions embedded in Taiwan's push for bilingual higher education. Design/methodology/approach A mixed-methods design was employed. Six semi-structured interviews with Vietnamese master's students were analyzed using thematic analysis to capture lived experiences. To complement these qualitative insights, Latent Dirichlet Allocation (LDA) topic modeling was applied to the interview transcripts, enabling computational validation of emerging themes. The research adapts Cheung's (2013) Transactional Acculturation Stress and Adjustment Model (TASAM) to interpret the dynamic process of adaptation. Findings Four major challenges emerged: socio-cultural adjustment, academic challenges, financial constraints, and health and well-being challenges. Students reported uneven EMI delivery, linguistic hierarchies, limited institutional support, and reliance on peer networks. LDA analysis confirmed these patterns and revealed hidden subthemes of identity negotiation and coping strategies. Research limitations/implications This exploratory study is based on a small sample of six Vietnamese master's students in Taiwan; therefore, the findings are not statistically generalizable. The results identify emerging patterns of adaptation rather than causal relationships. Future research may expand to other Southeast Asian student groups and employ comparative or longitudinal designs to examine institutional responses across disciplines, thereby strengthening generalizability and further refining the TASAM framework in bilingual and international higher-education contexts. Practical implications This study demonstrates how combining qualitative thematic analysis with Latent Dirichlet Allocation (LDA) can provide institutions with richer, evidence-based insights into international student challenges. Practically, universities can adopt similar mixed-method approaches to systematically analyze student feedback and detect hidden patterns that may not emerge from surveys alone. Beyond methodological innovation, the findings emphasize the need for consistent EMI practices, Mandarin language support, and culturally inclusive services. By leveraging computational tools like LDA alongside traditional methods, administrators can make data-driven decisions that directly improve student well-being and institutional competitiveness. Social implications This study highlights the social dimensions of bilingualization and international student inclusion in Taiwan. Vietnamese master's students' experiences reveal how language policies intersect with identity, belonging, and equity in multicultural academic settings. Strengthening institutional trust and intercultural communication can reduce social isolation and promote empathy among local and international communities. The LDA–TASAM integration also demonstrates how data-informed qualitative research can uncover hidden social mechanisms of adaptation, providing actionable evidence for creating linguistically inclusive environments that foster cross-cultural understanding and contribute to Taiwan's broader goals of social sustainability and educational globalization. Originality/value This study contributes by combining qualitative and computational approaches under a single framework (TASAM–LDA). It provides new insights into how Southeast Asian students experience Taiwan's bilingualization in practice and suggests directions for more inclusive EMI implementation.

The rapid development of generative artificial intelligence (generative AI) has reshaped the landscape of digital entrepreneurship, particularly in value and ethics-based markets such as the halal lifestyle economy. This study examines how generative AI influences the communication practices of digital entrepreneurs operating in halal sectors including fashion, culinary businesses, health, and finance. Using a qualitative case-study approach and thematic content analysis, the research identifies three major shifts. First, the emergence of hybrid communication models that combine human creativity with AI-generated content. Second, changes in the frequency, style, and tone of brand messages tailored to value-driven Muslim audiences. Third, new dynamics in audience interaction, trust-building, and the management of authenticity within AI-assisted communication environments. The theoretical contribution of this study is the introduction of the “faith-aligned automation” model, which illustrates how AI technologies can be utilized without compromising religious and cultural values. The practical implications are directed at content strategists, platform developers, and halal business practitioners seeking to maintain ethical integrity while adopting automation. This study also outlines its limitations and proposes future research directions, particularly concerning AI governance in digital economies that are sensitive to identity.

The rapid rise of Generative AI (GenAI) tools is reshaping conversations about assessment and feedback in higher education. While much institutional attention focuses on detection, compliance, and academic integrity (Cotton et al., 2024), this presentation shifts the lens to educators and how they are actually using GenAI in assessment practice. We present findings from a grant-funded initiative at UNSW that explores educator-led innovation through a Postcards of Practice approach. The Postcards of Practice are one-page, practice-based narratives where educators document their use of GenAI tools. These postcards highlight applications including formative feedback generation, student prompting literacy, assessment redesign, and co-creation with AI. They reveal how educators are experimenting with GenAI to support student learning while navigating ethical concerns, transparency, and pedagogical alignment. Our study uses a qualitative interpretive methodology, combining thematic analysis of the postcards with follow-up interviews. The analysis draws on theoretical frameworks including feedback literacy (Carless & Boud, 2018), dialogic assessment (Nicol, 2010), and new paradigm feedback design (Winstone & Carless, 2020). We also apply institutional and national GenAI guidelines (Liu & Bridgeman, 2023; Perkins, 2023) to surface shared values such as authenticity, inclusivity, and responsible innovation that guide educators’ decisions. The aim of this study is to explore how educators are experimenting with GenAI in assessment and feedback, and to capture their emerging practices and reflections through the Postcards of Practice initiative. The central research question guiding this work is: How are educators integrating GenAI into assessment and feedback, and what opportunities, challenges, and support needs arise from these practices? This work advances Technology Enhanced Learning (TEL) by providing empirical insights into how GenAI is actually integrated at the coalface of teaching. Educators describe how GenAI supports more frequent, personalised feedback and builds student agency in learning. At the same time, they raise concerns about over-reliance, AI hallucination, and the need for clear pedagogical scaffolding. These reflections point to the need for professional development that is discipline-sensitive, responsive, and grounded in practice. The postcard approach also functions as a professional learning intervention. It prompts reflection, encourages cross-disciplinary dialogue, and helps build a local community of practice around GenAI use. Through this model, we demonstrate an innovative and scalable method of capturing and supporting TEL innovation in real time. The findings suggest GenAI is prompting a rethinking of assessment: from summative, compliance-driven models to more transparent, formative, and student-centred designs. Educators begin to embed feedback literacy, ethical AI use, and critical prompting into their teaching, with clear implications for program-level assessment and graduate capability development. To strengthen clarity, we propose a concise diagram mapping the emerging practices captured in the postcards against the theoretical frameworks of feedback literacy, dialogic assessment, and new paradigm feedback design. This visual representation illustrates how practical insights align with, extend, or challenge these frameworks, making the study’s contribution accessible across diverse tertiary contexts. This proposal offers exemplary innovation in TEL by foregrounding bottom-up, practice-led experimentation with GenAI. It is grounded in strong theoretical frameworks and applicable across diverse tertiary contexts. The Pecha Kucha format will present key insights through rich visual storytelling, including excerpts from the postcards themselves. We conclude by proposing future directions for research and institutional strategy, including how to embed GenAI into assessment ecosystems in ways that enhance learning, uphold integrity, and empower educators to lead digital transformation from within.

Objective: To investigate how public marketing and intercultural communication strategies, informed by the COM-B model, can expand digital access to justice through Digital Inclusion Points (PIDs) in the Kalunga territory, identifying barriers and facilitators to the target behavior of service use. Theoretical Framework: There is a scholarship integration on access to justice, public/ service marketing, and public communication with the COM-B model (Capability, Opportunity, Motivation) as a structure for diagnosis and intervention design in behavior change. Method: The present research uses qualitative, exploratory study using semi-structured interviews with seven staff members responsible for the PIDs. Analysis followed thematic content analysis with a priori categories guiding coding and interpretation. Results and Discussion: Findings reveal deficits in Capability, constraints in Opportunity and dynamics of Motivation. Enhancements in Capability and Opportunity fed Motivation and translated into effective use when the service was nearby, intelligible, and welcoming. Research Implications: We propose a three-pillar implementation: (1) user enablement routines (coaching, micro-learning), (2) logistical/environmental reconfiguration (itinerant outreach, flexible hours, climate control/accessibility), and (3) motivational nurturing (utility/dignity narratives, feedback, peer modeling). Originality/Value: The study offers an operational grammar to turn PIDs into public intermediation ecosystems, linking public-marketing decisions to measurable behavioral mechanisms in a traditional territory.

The emergence of generative AI has significantly impacted English Language Teaching (ELT), presenting both opportunities and challenges. This study adopts a hermeneutic phenomenological approach to examine the experiences of four university-level English teacher educators who have incorporated generative AI into their teaching methodologies. By employing theoretical frameworks such as sociocultural theory and connectivism, the research explores how generative AI can tailor learning experiences, enhance language practice, and promote greater accessibility and inclusivity. The study also addresses issues related to the accuracy of AI outputs, ethical concerns, the need for teacher training, and the associated costs. Through semi-structured interviews and thematic analysis, the research offers comprehensive insights into the practical ramifications of AI in ELT. The results emphasize the importance of thoughtful integration, ongoing evaluation, adherence to ethical standards, and extensive professional development. This study contributes valuable perspectives to the discussion on AI in education and provides actionable insights for educators, policymakers, and developers.

Generative AI (GenAI) is rapidly integrating into nursing education, acting as a novel tool for knowledge mediation. While it offers new learning opportunities, its application risks disrupting essential social interactions and clinical contextualization. Double-qualified nursing educators (DQNEs) play a pivotal role in navigating this technological shift. This study adopts a social constructivist framework to examine the pedagogical functional boundaries of GenAI in nursing education and to analyze how DQNEs reconstruct their roles to facilitate knowledge co-construction and clinical meaning-making. A qualitative study using semi-structured focus group interviews. The study was conducted at a medical college in eastern China. Eighteen DQNEs with experience in GenAI integration participated. Data were collected through three focus group discussions and analyzed using thematic analysis to identify key themes. Three key themes emerged: (1) Application value of GenAI in nursing education, where GenAI served as a scaffolding tool to trigger cognitive conflict, support differentiated instruction, and bridge theory with simulated scenarios; (2) Core obstacles to GenAI application, revealing challenges of tool dependency displacing human interaction, erosion of teacher authority, and institutional ambiguity; and (3) Adaptive pedagogical strategies for anchoring learning in clinical practice, where teachers employed deconstruction and reconstruction strategies and enforced social rules to anchor AI-generated plans in clinical practice. GenAI functions as a double-edged mediating tool that can expand the zone of proximal development but also threatens to social learning. To mitigate epistemic risks, DQNEs must evolve from information transmitters to contextual anchors, guiding students to validate GenAI outputs against clinical reality.

ABSTRACT: Background: Local sports in Kenema City, Eastern Sierra Leone, often suffer from low visibility and limited institutional support. FM radio is the most accessible medium in the region, yet its specific role and effectiveness in promoting local sports remain under-examined. Objectives: This study assessed the strategies used by FM radio stations in Kenema to promote local sports, examined listener perceptions and attitudes, and identified the challenges faced by sports presenters. Methods: A mixed-methods approach was employed. Quantitative data were collected via structured questionnaires from 120 listeners and stakeholders. Qualitative data were gathered through 10 interviews with sports presenters and 3 focus group discussions with community sports fans. Data were analyzed using descriptive statistics and thematic content analysis. Findings: Findings indicate that while most FM stations offer sports coverage, programming is often irregular and lacks depth. Key promotional strategies include discussions (33.3%), call-in shows (16.7%), and interviews (16.7%). Coverage is heavily dominated by international football (79.2%), with local sports receiving minimal attention. Listeners value sports programming for community cohesion but report dissatisfaction due to presentation quality and perceived bias. Presenters face significant constraints, including inadequate funding (33.3%), lack of training (33.3%), and poor equipment. Conclusion: FM radio holds significant potential to enhance local sports promotion in Kenema. However, structural and capacity limitations hinder its effectiveness. Stations should establish regular, dedicated sports slots, improve presenter training, and actively engage with local sports associations. Diversifying coverage beyond football is critical for fostering a more inclusive local sports culture.

MARQUIS (Multi-Center Medication Reconciliation Quality Improvement Study) provided participating hospitals with a toolkit to assist in developing robust medication reconciliation programs. Here we describe hospitals' implementation of the MARQUIS toolkit, barriers and facilitators, and important factors that may enhance the spread and sustainability of the toolkit. We used a mixed methods, quantitative-qualitative study design. We invited site leaders of the 5 hospitals that participated in MARQUIS to complete a Web-based survey and phone interview. The Consolidated Framework for Implementation Research guided question development. We analyzed the collected data using descriptive statistics (for survey responses) and thematic content analysis (for interview results). Site leaders from each MARQUIS hospital participated. They reported that MARQUIS toolkit implementation augmented their hospitals' existing but limited medication reconciliation practices. Survey results indicated executive leadership support for toolkit implementation but limited institutional support for hiring staff (reported by 20% of respondents) and/or budgetary support for implementation (reported by 60% of respondents). Most participating hospitals (80%) shifted staff responsibilities to support medication reconciliation. Interview findings showed that inner setting (ie, organizational setting) and process factors (eg, designation of champions) both inhibited and facilitated implementation. Hospitals adopted a variety of toolkit interventions (eg, discharge medication counseling) using a range of implementation strategies, including development of educational tools and tip sheets for staff members and electronic health record templates. Despite limited institutional support, hospitals can successfully implement, spread, and sustain the MARQUIS toolkit by shifting staff responsibilities, adding pharmacy staff, and using a variety of strategies to facilitate implementation. Although leadership support and resources for data collection and dissemination facilitated implementation, limited staff buy-in and competing priorities may hinder implementation.

This study was conducted to examine the preparedness of primary school choral teachers in Changzhou, Jiangsu Province; to investigate systemic barriers to inclusive choral instruction; and to propose instructional strategies aligned with gender diversity. A quantitative research design was employed, in which data were collected through a structured questionnaire administered to 105 music teachers across 50 public and private schools in Zhonglou District. The instrument was designed to address demographic characteristics, teaching practices, training experiences, and challenges specific to inclusive choral education. Content validity was established through expert review (Index of Item-Objective Congruence = 0.95), and reliability was confirmed using Cronbach’s alpha. Data were analyzed using SPSS, applying descriptive statistics, Pearson’s correlation, and thematic content analysis. The findings indicated that although many teachers expressed openness to gender-inclusive practices, actual implementation was hindered by insufficient training, limited institutional support, and cultural resistance, particularly in public schools. Private schools were found to exhibit greater flexibility and responsiveness, which were attributed to increased administrative autonomy and less bureaucratic constraint. While inclusive strategies such as repertoire adaptation, the use of gender-neutral language, and mixed-voice arrangements were reported, a clear disconnect was identified between national-level policy recommendations and classroom-level execution. Based on the results, it was suggested that integrated efforts be undertaken to embed gender diversity into pre-service and in-service teacher training, revise national music education standards to reflect inclusive values, and foster supportive school environments through collaborative leadership and policy engagement. These measures are regarded as essential to advancing gender-inclusive choral pedagogy in Chinese primary schools. The study’s contributions are intended to inform educational policymakers, curriculum developers, and teacher educators, and to support the ongoing transformation of music education toward a more equitable, inclusive, and culturally responsive practice.

Generative AI (GenAI) use is increasing across society in many different industries. Despite widespread adoption in workplaces, there is little consensus on the scope of its benefits and challenges at the level of most industries. Universities are being called upon to equip graduates with important knowledge and skills using GenAI for their professional contexts. Higher education, however, faces issues in effectively and sustainability embedding a use of GenAI in the student experience, which requires adjustments to learning and teaching activities, assessment, and learning outcomes and in access to useful GenAI platforms relevant to the various disciplines. As pedagogical models, ethical debates, and technologies continue to develop in this space, university teachers’ experiences of teaching with GenAI have yet to be explored in detail. Adopting a phenomenographic perspective, this study examines university teachers’ conceptions, perceptions, and approaches to using GenAI in teaching. Leveraging semi-structured interviews with 30 teaching academics, variations of teaching using GenAI were identified. Quantitative analysis was also conducted to capture the associations between these variations. By exploring the qualitative differences between these variations, a nuanced and important contribution to the GenAI discussion from the understanding of university teachers is uncovered. The results show that some ways of understanding and teaching with GenAI are more likely to help students develop effective knowledge and skills for the workplace than others. The findings also offer education leaders evidence to help design effective support for teachers using GenAI to innovate in the student experience. Through investigating the university teacher experience of GenAI, this research adds to the growing debate on the GenAI enabled benefits and challenges that are set to shape the higher education sector.

AimThis study aimed to explore the emotions of operating room nurses in Japan towards perioperative nursing using generative AI and human analysis, and to identify factors contributing to burnout and turnover.MethodsA single-center cross-sectional study was conducted from February 2023 to February 2024, involving semi-structured interviews with 10 operating room nurses from a national hospital in Japan. Interview transcripts were analyzed using generative AI (ChatGPT-4o) and human researchers for thematic, emotional, and subjectivity analysis. A comparison between AI and human analysis was performed, and data visualization techniques, including keyword co-occurrence networks and cluster analysis, were employed to identify patterns and relationships.ResultsKey themes such as patient care, surgical safety, and nursing skills were identified through thematic analysis. Emotional analysis revealed a range of tones, with AI providing an efficient overview and human researchers capturing nuanced emotional insights. High subjectivity scores indicated deeply personal reflections. Keyword co-occurrence networks and cluster analysis highlighted connections between themes and distinct emotional experiences.ConclusionsCombining generative AI with human expertise offered nuanced insights into the emotions of operating room nurses. The findings emphasize the importance of emotional support, effective communication, and safety protocols in improving nurse well-being and job satisfaction. This hybrid approach can help address emotional challenges, reduce burnout, and enhance retention rates. Future research with larger and more diverse samples is needed to validate these findings and explore the broader applications of AI in healthcare.

This study examines whether crises act as catalysts for sustainable digital transformation in Montenegrin small and medium-sized enterprises (SMEs) and identifies the organizational and HR barriers that mediate change. Using a quantitative online survey conducted August 2023–January 2024 with 209 firms (response rate 24.7%), descriptive statistics and chi-square tests assess adoption patterns across marketing, advanced digital tools, platforms, and employee attitudes. Findings show substantial digital presence (≈95% maintain a website or social profile), 37% report full adoption of digital marketing, and 48% use generative AI (ChatGPT), yet over half lack familiarity with other advanced technologies. Primary obstacles are time constraints, organizational and individual resistance, and limited institutional support; substantive transformation frequently occurs reactively during crises rather than through proactive capability development. The findings suggest that technology adoption alone does not ensure sustained value creation. Effective digital transformation requires complementary investments in leadership, HR practices, employee training, and governance. The study is limited by its convenience sample and single-country focus; future research should adopt longitudinal and multivariate designs.