This mixed-methods study examined the challenges in preschool music education in Saudi Arabia and their influence on classroom practices. Guided by the theory of educational change, it explored the extent to which policy reforms have been translated into practice. In the first phase, 686 teachers were randomly selected to complete self-administered questionnaires. In the second phase, 18 teachers participated in semi-structured interviews. Quantitative findings revealed high levels of psychological, professional, organizational, and cultural challenges. Training did not significantly alter teacher perceptions, suggesting that current professional development programs are insufficient. Qualitative results showed that music instruction is often informal, unstructured, and limited by cultural beliefs, heavy workloads, resource deficits, and inadequate support. Teachers also demonstrated minimal integration of artificial intelligence into music teaching, reflecting limited awareness and confidence. These findings highlight the need for long-term, practice-oriented training, specialist support, and culturally responsive strategies.
Qualitative narratives surrounding French language didactics offer substantial historical grounding. However, the structural evolution of this domain remains empirically under-investigated. To interrogate these disciplinary shifts, the present study adopts a bibliometric approach anchored in the synthetic knowledge synthesis (SKS) framework, analyzing 503 articles published in Le français aujourd’hui (2007–2023) through keyword co-occurrence, hierarchical clustering, and citation metrics. Results suggest that the field tends to exhibit a sedimentary layering of methodologies, rather than a linear paradigm replacement. The historical triad (i.e., literature, reading, and writing) consistently constitutes the disciplinary bedrock, even as it is reconfigured to absorb complex techno-pedagogical demands and accommodate a growing turn toward plurilingualism. Oral didactics, nevertheless, tends to be marginalized despite ongoing communicative shifts, a pattern attributable in part to entrenched institutional graphocentrism and persistent methodological bottlenecks. Citation data further support the field’s progressive decoupling from applied linguistics, pointing toward its consolidation as an autonomous, inclusively oriented discipline. French didactics, consequently, appears to maintain a distinctly localized resilience, negotiating the globalized pressures of superdiversity while sustaining its foundational humanist rationale. By charting these bibliometric dynamics, this study maps the discipline’s current state and emergent intellectual horizons.
This mixed-methods study explores first-year EFL students’ perceptions and experiences of AI-supported learning in comparison with peer collaboration for critical reading. Specifically, it examines students’ perceived helpfulness of AI and peer support across critical reading processes and their preferences for these two learning modes, using a phenomenological stance to deeply explore these experiences. A total of 48 students participated in two learning sessions involving peer collaboration and AI-supported reading. Data were collected through a Likert-type questionnaire and semi-structured interviews. Wilcoxon signed-rank tests showed no statistically significant differences between AI support and peer collaboration in students’ perceived helpfulness across most critical reading processes, including identifying main ideas, analyzing arguments, detecting bias, and evaluating overall meaning. However, AI was perceived as significantly more helpful for understanding difficult vocabulary. Qualitative findings revealed complementary roles of the two learning modes: AI supported vocabulary processing, efficiency, and procedural assistance, whereas peer collaboration promoted diverse perspectives, shared meaning-making, and affective support. Students also expressed strong preference for combining AI and peer collaboration. Interpreted through the Technology Acceptance Model, the findings suggest that AI acceptance was shaped not only by perceived usefulness but also by trust in AI outputs and learners’ trust or confidence in their own critical judgment when interacting with AI for critical reading.
This study investigates how structural inequalities based on socio-economic status, geographic origin, and ethnic identity can perpetuate achievement gaps in China’s college English classrooms, and evaluates a context-specific pedagogical framework designed to address these disparities. Employing a transformative mixed-methods design across six universities, the research piloted a tripartite framework integrating Academic Inequality Mitigation, Deliberative Interdependence, and Transformative Translation. Quantitative results demonstrated a 15% narrowing of the urban-rural performance gap on the College English Test Band 4 and statistically significant increases in students’ academic belonging. Qualitatively, students from under-resourced backgrounds reported a 28% reduction in classroom anxiety and 41% stronger connection to curricula validating their cultural assets. The study contributes an empirically validated model of harmonized equity pedagogy—a strategic approach reconciling universal equity principles with centralized system realities—offering actionable insights for fostering empowerment in contexts where standardized curricula and socio-political sensitivities shape educational discourse on diversity.
The integration of artificial intelligence (AI) into education holds significant potential to develop innovative and inclusive learning environments. This study investigated the relationship between teachers’ AI literacy and their AI-TPACK (Technological Pedagogical Content Knowledge integrated with AI). It further explored the mediating role of innovative thinking and the moderating effect of AI anxiety within this relationship. The research was conducted with 378 Turkish teachers (50.8% female). Findings demonstrated statistically significant positive relationships among AI literacy, AI-TPACK, and innovative thinking. Conversely, AI anxiety was negatively correlated with the other variables. Moreover, innovative thinking was found to significantly mediate the relationship between AI literacy and AI-TPACK. Additionally, AI anxiety moderates the AI literacy-AI-TPACK relationship; specifically, this relationship strengthens as teachers’ AI anxiety diminishes. The results underscore the critical importance of promoting innovative thinking and reducing AI anxiety to empower teachers to integrate AI effectively in education.
Amid China’s rapid social transformation, women’s life courses are shaped by both historical constraints and changing family expectations. This study develops the concept of intergenerational regret as an empirically grounded analytical construct for understanding how women interpret unrealised life possibilities and how these interpretations are transmitted and reworked across generations. Based on an embedded multiple-case design, the study draws on in-depth interviews and participant observation with three generations of women in four families in Hunan Province. Using affective politics and relational self theory, it examines how regret is produced under gendered institutional constraints, how it enters family interaction, and how it may be ethically renegotiated. The findings show that women’s regret is shaped by period-specific institutional arrangements, gendered family roles and intra-household power relations. Regret is transmitted through two recurring but context-sensitive processes: ‘expectation projection’, through which elders redirect unrealised aspirations into hopes for younger women, and ‘experiential discipline’, through which past hardship is used to frame caution and protection. The study further shows that, under specific material and relational conditions, shared experiences of constraint can support forms of emotional resonance and more reciprocal dialogue. This article proposes ‘bidirectional ethics’ as a framework for understanding how critique and care may be negotiated together within Chinese family life, offering a culturally situated account of women’s relational agency under enduring gendered obligations and uneven material conditions.
In globalized and increasingly competitive business environment, learning and knowing make it easier for small and medium-sized enterprises (SMEs) to increase their competitive power and gain competitive advantage. SMEs can develop the ability through learning to evaluate the present and the future and, respond correctly, timely and competently to environmental changes and uncertainties. This research was conducted to determine the effect of intellectual capital (IC), organizational ambidexterity (OA) and organizational agility (OAG) on the competitive advantage (CA) of SMEs operating in Türkiye (TR) and the United Kingdom (UK). In the study, which is an empirical research, survey technique was used as a data collection tool. A questionnaire was applied to 792 employees working in managerial positions in SMEs operating in TR and the UK by using convenience sampling method and the collected data was analysed using the structural equation modelling technique. The results show that the IC has a statistically significant, positive effect on OA and OAG in SMEs operating in TR and the UK. In addition, OA has a statistically significant, positive effect on OAG and the OAG has a statistically significant, positive effect on CA in both countries. The analysis results show that there are differences between countries in terms of how intellectual capital, organizational ambidexterity and organizational agility have impact on competitive advantage. The findings facilitate to understand how SMEs have competitive advantage in the developed and developing countries.
The proposal and advancement of new quality productive forces have endowed firm upgrading in China with deeper implications. By lowering financing costs, optimizing resource allocation, and alleviating information asymmetries, digital finance may provide important support for firm upgrading. Based on panel data of 1,116 A-share listed firms in China from 2011 to 2023, this study constructs an index to measure the level of firm upgrading under the policy context of developing new quality productive forces and employs a multi-way fixed effects model to examine the impact of digital finance on firm upgrading. The results indicate that the development of digital finance significantly promotes firm upgrading, and that the innovation willingness of both governments and enterprises serves as an important mechanism through which digital finance exerts this effect. Moreover, digital finance markedly facilitates firm upgrading in the eastern region, with stronger effects observed in technology-intensive industries, high-tech firms, and small non-state-owned enterprises. Based on these findings, the study proposes targeted policy recommendations aimed at improving the institutional mechanisms for developing new quality productive forces in accordance with local conditions, thereby offering insights for research on firm upgrading under this policy framework.
Accession to the EU of some Central and CEE Countries led to a shift in migration patterns, with countries switching from being characterized solely by emigration to attracting immigrants. This paper maps the migration in this region over the last three decades (1990 -2020), considering emigration dispersion and immigration diversification. Starting from the core-periphery model, and employing network analysis, the purpose of the paper is to test if CEE increased in diversity of origins and destinations and in magnitude or if CEE evolved from periphery to semi-periphery. Network analysis was employed on migrant stock data for 17 countries from CEE and analysing measures for network, nodes and edges. Changing migration patterns show that the semi-periphery status is confirmed. The evolving socioeconomic status of the countries in the region attracts more migration, confirming the world-systems theory. Furthermore, dependency theory shows that migration is structural due to inequalities that continue to exist between countries in their economic, legal and social standards and conditions. Our findings also demonstrate that path dependency in regional migration inflows/outflows constitutes a significant factor influencing migration. Evolving migration trajectories provide empirical support for the designation of semi-periphery status while simultaneously indicating that shifts in regional dynamics can attract further migratory flows, providing more information on the structural nature of migration that has been historically built into a region. We argue that in semi-peripheries migration diversification is inevitable as they need labour migration, self-perpetuation and self-protection, which has implications for policymaking and decision-making on migration.
This study investigates the impact of artificial intelligence (AI) adoption on employee productivity within Vietnam’s technology sector, with a particular focus on telecommunications and information technology firms. Using survey data collected from 710 employees, Python-based structural equation modeling (SEM) was applied to evaluate both the measurement and structural models. Reliability and validity analyses confirmed that all constructs satisfied the required thresholds, demonstrating robust internal consistency, convergent validity, and discriminant validity. The results reveal that AI adoption exerts a strong positive effect on employee productivity and organizational performance. Mediation analyses indicate that employee engagement, well-being, and knowledge sharing play significant roles in transmitting the benefits of AI adoption to productivity gains. In addition, moderation tests show that digital literacy enhances, while resistance to AI weakens, the effect of AI adoption on productivity. At the outcome level, employee productivity mediates the relationship between AI adoption and customer satisfaction, underscoring its pivotal role in delivering value from technological investments. By situating the analysis in Vietnam’s telecommunications and IT firms, this study contributes to the emerging literature on AI adoption in developing economies. Vietnam, as one of the fastest-growing digital economies in Southeast Asia, provides a particularly relevant setting to understand how firms in emerging markets leverage AI to enhance both employee and organizational outcomes. It emphasizes that realizing the full benefits of AI requires not only technological readiness but also proactive management of employee capabilities and attitudes.
Online golf apparel rental has emerged as an alternative to ownership-based consumption; however, its adoption remains limited due to various consumer barriers. This study investigates how perceived risk functions as a key barrier influencing consumer attitudes, trust, and purchase intention toward online golf apparel rental platforms. Using judgment sampling, survey data were collected from 313 female golfers who had experience using online rental services. Frequency analysis, correlation analysis, and structural equation modeling were conducted to examine the proposed relationships. The results indicate that size risk and social risk exert significant negative effects on consumer attitudes, while financial risk and performance risk show significant but positive effects contrary to the hypothesized directions, revealing a risk perception structure distinct from conventional online retail contexts. Consumer attitudes were found to positively influence trust, and both attitude and trust significantly increased purchase intention. These findings suggest that perceived risk, particularly related to fit and social image, represents a critical barrier to the adoption of online golf apparel rental services. Accordingly, this study suggests that strategies aimed at reducing size- and image-related risks are essential for building consumer trust, encouraging continued use, and supporting the growth of online golf apparel rental services.
This paper examines the role of the Google Search Volume Index (GSVI) in forecasting FDI inflows to different countries worldwide. The study utilized annual panel-series data for 155 countries over 19 years, spanning from 2004 to 2022. GSVI data is transformed into a structured panel dataset by aggregating monthly GSVI values across the “Finance”, “Business & Industrial”, and “Law & Government” categories into annual values to align with FDI inflow data. The relationship between variables was examined by using two-step GMM and Feasible Generalized Least Squares (FGLS) models, which effectively address endogeneity, serial correlation, and groupwise heteroscedasticity. The empirical analysis is conducted separately for 33 “Advanced” and 122 “Emerging and Developing” countries, accounting for heterogeneity in information environments, institutional quality, and development levels that may influence the association between web search behavior and investor attention. The results confirm the usefulness of web search frequency, measured by GSVI, in capturing investors’ attention to FDI inflows. The lagged value of GSVI across all search categories indicates a positive and statistically significant association with FDI inflows to emerging and developing countries. The same positive association is also observed between FDI inflows and GSVI in the “Finance” category for the sample of advanced countries. According to empirical findings, GSVI is capturing investors’ attention and shows great potential as a new source of non-traditional data for countries well represented in web searches.
This study proposes an two-step methodology for psychosocial risk assessment. In the first step for each psychosocial factor, latent classes are estimated as a function of the level of exposure. In the second step, exposure to the psychosocial factors is related to harm by studying the criterion validity of the estimated classes. To test this approach we first adaptation of the Short Inventory to Monitor Psychosocial Hazards – 5A (SAMU) to the Norwegian context. To this aim, a sample of 1,002 Norwegian employees from various sectors was drawn. The confirmatory factor analysis in Mplus 8.4 supported the factorial validity. With Latent Gold 6.0 we identified different levels of exposure to each psychosocial hazard. The criterion validity showed significant and substantive effect sizes, allowing us to distinguish between varying levels of risk for burnout and engagement. Compared to no high or very high exposure to psychosocial demands, a greater risk of burnout was observed. A lack of or very low job resources was associated with little or no job engagement. This mixture approach offers an alternative to traditional correlational and covariance methods used for risk assessment. This configural approach to risk assessment potentially aligns more effectively with the complementary view that contemporary occupational stress and health theories offer on why employees experience stress or demotivation. However, the study acknowledges certain limitations, including common method bias, reliance on self-reported data, and issues with generalizability. This highlights the need for future research to include invariance testing and longitudinal and registry-based studies.
Social-emotional development plays a key role in second language acquisition (SLA). With recent advancements in artificial intelligence (AI), there is increasing interest in how AI technologies can enhance social-emotional factors in SLA. This study aims to systematically synthesize empirical research on the role of AI in shaping social-emotional experiences in SLA, identify prevailing trends, summarize patterns in reported outcomes, examine proposed mechanisms, and highlight directions for future research. Following PRISMA-ScR (Preferred Reporting Items for Systematic Reviews and Meta-Analyses Extension for Scoping Reviews) guidelines, this scoping review encompasses 66 empirical studies published between 2022 and April 2025. All studies were independently reviewed by two researchers and appraised using the Mixed Methods Appraisal Tool (MMAT). Results: (1) a marked increase in scholarly attention to AI-supported social-emotional development in SLA; (2) AI’s reported potential in enhancing motivation and reducing anxiety, but evidence is limited by positivity bias, methodological inconsistencies, and concentration in East Asian contexts; and (3) five reported mechanisms through which AI may support social-emotional growth in SLA: dialogic interaction and perceived social presence; perceived competence, agency, and task value; emotion regulation and timely affective support; immersion, flow, and sustained engagement; and reduced evaluative pressure and psychological safety. At the same time, the review identifies insufficient critical attention to potentially negative or constraining aspects of AI-supported language learning, including learner over-reliance and reduced autonomy. This review offers a balanced synthesis of the current evidence and highlights implications for future AI–SLA research, pedagogy, and design.
Tourism education, in response to the global transformation, has expanded significantly, but theoretical exploration still remain divided across, theories, themes and geographical contexts. This research aims to examine comprehensive bibliometric review of tourism education research to systematically map its thematic evolution, scholarly structure, and demographical patterns. Based on 490 published articles, bibliometric techniques were exercised to assess future trends of publication, prominent sources, global contributions, collaboration and themetic mapping. The results revealed a maturing but fragmented knowledge domain indicating strong emphasis on learning, employability, and learner-centered pedagogy, with growing attention to digital transformation. However, theoretical contribution was found to be limited, and majority of the researches were conextually concentrated. This study adds knowledge to tourism education field by identifying underexplored areas critical for future educational innovation. The study provides several implications for educators, curriculum designers, and researchers to develop theoretically informed, inclusive, and future-oriented tourism education. To the best of current study author knowledge, this research extends the scope of bibliometric review in tourism and hospitality education.
Guided by the Unified Theory of Acceptance and Use of Technology 2 (UTAUT2) framework, this qualitative study explores English as a Foreign Language (EFL) teachers’ continuance intention to use Learning Management Systems (LMS) at a regional Chinese university. Data were collected through semi-structured interviews with 15 teachers who use the Chaoxing LMS. The results indicate that six of the seven UTAUT2 constructs — Performance Expectancy, Effort Expectancy, Social Influence, Facilitating Conditions, Habit, and Hedonic Motivation — collectively drive teachers sustained LMS engagement, whereas Price Value exerts negligible influence since the university provides the LMS free of charge. All seven dimensions exhibit distinct context-specific manifestations shaped by large EFL class sizes, intergenerational digital literacy divides, and institutional administrative rules. Beyond UTAUT2’s original dimensions, this study identifies three context-specific institutional and pedagogical factors: Institutionalized Collective Lesson Preparation, Teaching Evaluation Orientation, and EFL-Specific Resource Demand. These factors reconfigure the functional relationships among core constructs. This research further elaborates interactive mechanisms across UTAUT2 variables and distinguishes policy-induced passive compliance from voluntary habitual LMS integration. Theoretically, it extends the generic UTAUT2 framework by embedding the institutional logic of centralized collectivist Chinese higher education and discipline-specific EFL pedagogical requirements, filling the gap of localized qualitative extensions in existing educational technology scholarship. Practically, differentiated actionable strategies are proposed for university administrators, LMS developers, and EFL instructors to advance in-depth, pedagogy-centered digital integration.
Mobile learning has been widely applied in language learning. However, empirical evidence regarding its use on vocabulary development remains limited. This study employed Rain Classroom, an interactive blended-learning tool, to provide tailored vocabulary support for college students with varying levels of English proficiency. 50 first-year college students were recruited and stratified into three groups (low, intermediate, and advanced) according to their English proficiency. The participants took part in a one-semester English vocabulary intervention delivered via the Rain Classroom mobile application. Three vocabulary quizzes were administered via Rain Classroom at the beginning, middle, and end of the practice to assess students’ vocabulary acquisition during the study. After the intervention, students completed a questionnaire regarding their perceptions of vocabulary instruction and their acceptance of Rain Classroom. The results showed that all groups made progress in their vocabulary learning, with the intermediate- and low-English-level groups showing notable improvement. The majority of students reported satisfaction with their English vocabulary development using Rain Classroom. The findings suggested potential benefits of implementing mobile applications in English vocabulary instruction to enhance EFL learners’ English proficiency in similar contexts.
This study examines the effect of the Working Capital Management (WCM), its elements, Cash Conversion Cycle (CCC), and liquidity, on the Chinese SMEs Financial Performance (FP) in the FMCG industry. Based on a quantitative, cross-sectional survey-based design, data were collected through 320 finance professionals in SMEs listed in the Shanghai and Shenzhen stock exchanges, and major companies of the private sector. The key variables, including inventory, receivables, payables, CCC, liquidity, return on Assets (ROA), Return on Equity (ROE), Net Profit Margin (NPM), and Digital Finance Adoption (DFA), were measured with the help of the 7-point Likert scales with a high level of validity. Data was analyzed using SPSS and R, which have Confirmatory Factor Analysis (CFA) and Structural Equation Modeling (SEM), to evaluate reliability, validity, and hypothesized relationships. The findings demonstrate that effective WCM practices lead to a tremendous improvement in SME financial performance, where liquidity presents the most significant impact (β = 0.62, p < 0.01). Moreover, DFA further enhances the positive relationship between WCM and financial performance. The reliability and robustness of the findings were validated by robustness tests such as multi-collinearity, endogeneity, heteroskedasticity test, and bootstrapping. Multi-group analyses revealed a uniformity in the findings of the different firms in terms of size and geographical coverage. The study provides a theoretical contribution by combining WCM and DFA in the context of SMEs and also gives practical suggestions that can be offered by managers and policymakers to maximize liquidity and enhance operational efficiency.
Human-generative AI (HGenAI) collaboration is increasingly embedded in university-level writing practices, as learners interact with both human and AI-generated writing support. However, research on how HGenAI collaboration, trust, and reception are associated with perceived English writing capabilities among second-language learners remains limited. To address this gap, this study draws on the complementary lenses of HGenAI collaboration perspective, multidimensional trust, and reception theory to examine how HGenAI collaboration, technological innovativeness, multidimensional trust, and reception of generative AI jointly relate to perceived English writing capabilities. Methodologically, using survey data from 420 undergraduates, this study applied partial least squares structural equation modeling (PLS-SEM), fuzzy-set qualitative comparative analysis (fsQCA), and artificial neural networks (ANN) to examine relationships, configurations, and predictions. Results showed HGenAI collaboration was positively associated with perceived English writing capabilities ( β = 0.228), although the effect was modest. Technological innovativeness is associated with perceived English writing capabilities indirectly through multidimensional trust (competence- and integrity-based via emotional trust). Reception of generative AI had a positive association with perceived English writing capabilities ( β = 0.145), and a weak moderating role on the relationship between emotional trust and perceived English writing capabilities. FsQCA revealed equifinal pathways to high perceived English writing capabilities, while ANN highlighted emotional trust as the most important predictor, although linear models showed higher predictive accuracy (MLR, R 2 = 0.267; ANN, R 2 = 0.050). These findings indicate that HGenAI collaboration, technological innovativeness, and reception of generative AI are associated with perceived English writing capabilities, with emotional trust as an important explanatory factor.
The study examined the roles of academic self-efficacy and locus of control in relation to academic adjustment of students in public universities in Ghana. The study adopted the positivist paradigm, a quantitative approach and the correlational research design. A sample of 2,300 Level 200 students was selected using proportionate stratified random sampling from three public universities in Ghana. Data were collected using adapted versions of Student Adaptation to College Questionnaire, Self-Efficacy for Learning Form by Zimmerman and Kitsantas and the Internal – External Locus of Control Scale. Structural Equation Modelling was used in testing the hypotheses. The study found a statistically significant relationship between academic self-efficacy and academic adjustment but no statistically significant relationship between locus of control and academic adjustment. The study recommended that Deans of Students Affairs in the various universities could strengthen ongoing adjustment support after the initial orientations given to students by addressing issues of time management, balancing coursework with extracurricular activities, and navigating institutional systems.
