Search Results (633)

Chinese language practice, especially handwriting and typewriting practice, has always been a key method for mastering Chinese in Chinese L2 learning. However, current research on blended practice modalities that combine handwriting and typewriting remains insufficient. This study used a pilot study with 30 international students to compare the associative patterns of handwriting practice and blended practice (a sequential multimodal practice wherein handwriting instruction was followed by typewriting) on students’ Chinese skills performance, Chinese learning motivation, and attitude. Results indicated that students using the blended practice were associated with significantly better Chinese skills performance, as well as higher levels of motivation and more positive attitudes compared to those using only handwriting. Exploratory path analysis identified a notable direct association between practice modality and Chinese skills performance; however, the pathways through motivation and attitude were not statistically detectable. These findings suggest that Chinese language teachers may consider designing lessons that incorporate this sequential blended practice, which may support improvements in L2 Chinese performance, motivation, and attitudes. Furthermore, second language learners should actively apply this practice modality to improve their Chinese L2 learning performance. Full article

Previous research has shown that both victim intoxication and narrative framing can influence the levels of victim blame. However, far less attention has been paid to how coercive strategy and narrative framing may interact to shape victim-blaming judgements and perceptions of sexual assault. The present study addresses this gap by examining how combinations of coercive strategies (physical force versus alcohol facilitated), narrative framing (active versus passive), and rape myth acceptance (RMA) influence victim blame and the recognition of sexual assault. Participant gender and age were also assessed in relation to RMA and victim-blaming attitudes. A total of 202 participants aged 18–63 (78.7% of women, 21.3% of men, M_Age = 28.93, SD = 14.36) completed an online survey evaluating vignettes depicting a male perpetrator sexually assaulting a female victim. Age significantly predicted victim blaming, with older participants assigning greater blame to the victim. Gender predicted both RMA and victim blame, with men reporting higher RMA and greater victim blame than women. Active framing in both the physical force and alcohol-use conditions reduced participants’ recognition of the incident as sexual assault. Participants with lower RMA consistently reported lower victim blame across conditions, and were more likely to identify the incident as sexual assault in the physical force condition. These findings highlight the influence of coercive strategies and the importance of victim-centred language in policing, legal, and media contexts, where narrative framing can meaningfully shape the recognition of sexual assault. Full article

This study explores the multifaceted attitudes of high school students toward the use of artificial intelligence (AI) and large language models (LLMs) like ChatGPT in educational contexts. Drawing upon a tripartite model of attitudes, our research evaluates affective, cognitive, and behavioral dimensions to offer a nuanced understanding of students’ perceptions. The affective dimension assesses emotional responses to AI tools, the cognitive dimension examines beliefs about the utility and ethical considerations of AI, and the behavioral dimension evaluates actual usage patterns of AI technologies. Utilizing a newly developed survey instrument tailored for the educational context, data was collected from 93 high school students across different regions of Italy in the period that ranged from February 2024–March 2024. Exploratory factor analysis (EFA) was employed to explore the underlying structure of the survey instrument and identify underlying factors influencing AI acceptance. The analysis reveals three distinct factors—Mindful AI Learning, Embracing AI Effects, and LLM as Learning Companion, highlighting the complexity of students’ attitudes toward AI. Results indicate a cautious but optimistic reception of AI in education, offering crucial insights into Information Intelligence for enhanced learning and the design of personalized learning pathways. The study contributes to the literature by offering a novel scale to measure attitudes toward artificial intelligence, specifically focusing on both general AI and Generative AI large language models, such as ChatGPT. Moreover, it highlights the critical need for AI literacy, ethical digital learning frameworks, and robust institutional policies to bridge the digital divide. Consequently, this work is framed as a preliminary exploratory investigation. Ultimately, these findings advance our knowledge of transformative digital learning processes and inform future strategies for human–machine integration in educational systems. Full article

Language embodies traditions, values, and collective identity, bridging gaps between generations and geographies. Maintaining consistent language policies at home and in communities remains challenging, with research showing that only a few families have explicit rules about language use and few enforce them regularly. The study explores strategies for heritage language maintenance (HLM) to mitigate language attrition among Anaañ bilinguals residing in the Akpabuyo and Calabar South Local Government Areas of Cross River State, Nigeria. The study draws on social identity theory, which links language use to identity, motivation, and group affiliation, thereby influencing language maintenance. Using a qualitative approach, data were collected through semi-structured interviews with 40 participants, selected purposively from Anaañ speakers in the study areas. Thematic analysis is employed to identify patterns and themes, revealing approaches for heritage language maintenance to curb language attrition. Findings reveal that despite some Anaañ speakers’ negative attitude towards their HL, others value it, keep it alive, and are ready to pass it to the future generations. This will preserve cultural identity and foster a sense of pride, belonging and shared values among Anaañ people, especially those residing in Southern Cross River State. Full article

Background: This systematic review evaluates the evidence on sustainable practices in dentistry. It focuses on effective measures, innovative technologies, strategies for reducing the carbon footprint, life cycle assessments (LCA), attitudes toward “green” dentistry, and educational approaches. Methods: A systematic search was conducted in five databases (Cochrane Library, Embase, LILACS, MEDLINE via PubMed, and Scopus) without language restrictions in accordance with PRISMA. The review was registered in PROSPERO (CRD420251056821). Results: A total of 2395 records were identified; after removing 394 duplicates, 2001 remained for screening. After title and abstract screening, 154 full-text articles were evaluated, of which 51 studies were included. The included studies addressed life cycle assessments of dental materials, sustainable clinical practices, and educational measures. Environmentally friendly materials and procedures, such as reusable personal protective equipment and water-saving technologies, demonstrate significant potential for reducing environmental impact. Despite generally high acceptance among dentists and patients, implementation is often limited by financial and knowledge-related barriers. Conclusions: The implementation of sustainable materials and procedures is crucial for reducing environmental impact. Equally important are the integration of ecological content into education and appropriate financial and political frameworks to promote sustainable dentistry. Full article

Little is known about parents’ attitudes towards their children’s accent and the role they play in transmitting an accent (and attitudes about accents) to their children. Even less is known about how these perceptions and attitudes emerge and are transmitted in multilingual families. We draw on an online survey of parental language attitudes in Australia (n = 267), where 45% of respondents were born overseas, and 61% reported speaking a language other than English. Parents were asked whether they think their children speak with an Australian or another accent; whether they change their accent when they speak to their children, and whether their children’s accents change when they speak to their parents as compared to other people. A total of 14% of parents reported that one or more of their children had an accent that was not Australian, with about half of these children having reportedly hybrid or mixed accents, and the other half no accent at all. Over 11% of parents reported frequently or occasionally changing their accent with their children. Of those parents, several disclosed specific strategies in changing their accents around their children, such as making a conscious effort to sound ‘clear’ or deliberately exposing their children to different accents. A total of 15% of parents reported that their children’s accents frequently or occasionally change when speaking to them. These findings have implications for the complex influences on children’s language and dialect repertoires as they relate to language attitudes, language ecology, and linguistic identity. Full article

Background: Quality of life (QoL) after spinal cord injury (SCI) is influenced by psychosocial factors, yet less is known about how these factors are examined across national contexts. Objective: This scoping review mapped studies examining depression, employment, and social participation in relation to QoL or health-related QoL (HRQoL) among individuals with SCI in the United States and South Korea. Methods: Following PRISMA-ScR guidelines, five databases were searched for peer-reviewed English- and Korean-language studies published between 2007 and 2025. Results: Sixteen studies were included: nine from South Korea and seven from the United States. Depression and psychological distress were associated with lower QoL/HRQoL in both countries, although South Korean studies more often examined depression with stress and functional concerns, whereas U.S. studies situated depression within participation, spirituality, and youth psychosocial functioning. Employment was linked to QoL/HRQoL in both contexts, with South Korean studies emphasizing economic activity, vocational rehabilitation, and financial strain, and U.S. studies emphasizing employment status and vocational outcomes. Social participation was important in both countries, but South Korean studies focused more on community transition, functional independence, and social attitudes, whereas U.S. studies emphasized participation contexts, accessibility, and social relationships. Conclusions: Across the three domains, depression, employment, and social participation emerged as recurring psychosocial domains associated with QoL/HRQoL after SCI in both countries. These differences suggest that psychosocial adaptation after SCI should be understood within cultural and rehabilitation contexts. Full article

Background: Large language models and other generative artificial intelligence (AI) tools are increasingly being embedded in digital healthcare services, including mobile health applications, telerehabilitation, remote monitoring, and hybrid care pathways. In this review, digital healthcare refers to technology-mediated healthcare services in which digital platforms, mobile applications, wearables, remote communication, and AI-enabled interfaces support health assessment, self-management, rehabilitation, clinical decision support, or service delivery. When AI-generated exercise guidance moves from general education to individualized recommendations about dose, progression, contraindications, or rehabilitation, it may become directly actionable and safety-relevant. Objectives: This review aimed to clarify when AI-generated exercise guidance in digital healthcare may warrant safety-relevant governance attention and to outline implementation considerations for explainability, human oversight, and service-level governance. It addresses a gap in the literature: general AI-governance and exercise-prescription discussions rarely specify how point-of-use explanations, review thresholds, and escalation safeguards can be organized for directly actionable AI exercise guidance. Methods: We conducted a governance-oriented narrative review of peer-reviewed literature and representative regulatory or guidance documents. This review was not designed as a systematic review, scoping review, or exhaustive evidence map; transparent source mapping was used to support conceptual synthesis. Searches and source mapping focused on generative AI, large language models, explainable AI, clinical decision support, digital health, mobile health, exercise prescription, rehabilitation, trust, automation bias, and human oversight. Sources were included when they informed the safety, explainability, governance, or real-world implementation of patient-facing AI-generated exercise guidance. Extracted material was grouped by evidentiary role and synthesized through framework synthesis and governance mapping to distinguish literature-supported observations, author interpretation, and proposed implementation tools. Results: The included sources were first organized into five thematic groups: digital exercise delivery and exercise-prescription evidence; explainability, trust, and automation bias literature; professional responsibility, ethics, and patient disclosure literature; regulatory and policy documents; and digital literacy, patient/clinician attitudes, and equity literature. The synthesis then proceeded from safety relevance to explanation needs, human oversight and escalation needs, and selected regulatory and policy signals before translating these strands into conceptual and implementation-oriented outputs rather than empirically validated instruments. AI-generated exercise guidance was most safety-relevant in scenarios involving individualized dose, progression, contraindication-sensitive action, or rehabilitation strategy. Across the included sources, generic transparency alone was not sufficient to support reviewable use; relevant explanation elements included evidence sources, risk warnings, reasoning paths, and reasonable alternatives. Oversight considerations varied with embodied risk, clinical ambiguity, user vulnerability, and likelihood of direct enactment. Implementation considerations linked interface design, clinical review, escalation, auditability, and post-deployment monitoring. Conclusions: AI-generated exercise guidance in digital healthcare may warrant governance attention as a patient-safety and accountability issue when it influences actionable exercise decisions. The proposed framework offers a conceptual basis for designing more reviewable and accountable mobile and remote exercise-support services. Future work can validate these outputs in patient-facing services, clinician review workflows, usability studies, implementation pilots, and safety evaluations. Full article

We focus on the use of the Modern Lesbian dialect in the linguistic landscape (LL), highlighting its diverse forms and functions. Since LL research primarily investigates written language in public space, emphasizing the dynamic relationship between language, place, and historicity, the growing visibility of the dialect in both physical and digital contexts (cf. the online–offline nexus) is particularly noteworthy. The presence of non-standard varieties in public discourse has been widely studied, revealing that aspects of language choice and use are related to the sustainability of minority languages, the shaping of linguistic attitudes and stereotypes, and the commodification of language as a cultural and economic resource. Within this framework, the data analyzed here illustrate positive attitudes toward Modern Lesbian, expressions of pride and comfort among its speakers, efforts to destigmatize dialectal speech, and indications of broader acceptance of Modern Lesbian. Meanwhile, the increasing commodification of the dialect is evident in its use for the promotion of products and services, capitalizing on its distinctiveness, despite its historical stigmatization vis-à-vis the standard. This development does not dissolve entrenched beliefs on the incompatibility of dialects with written discourse; rather, it capitalizes on the surprise (and humor) generated by their written presence in promotional contexts without resorting to humorous stereotyping. Full article

Large Language Model (LLM)-driven social simulation offers a controllable approach for analyzing crisis responses, but existing work on online crises often emphasizes either user engagement prediction or opinion and eWOM evolution. This separation is insufficient for online firestorms, where crisis impact emerges from the coupling between what users express and how participation expands over time. In such events, responsibility attribution, KOL influence, electronic Word of Mouth (eWOM), and user engagement jointly shape collective reactions. To address this gap, we introduce the Crisis Response Interaction Simulation Pipeline (CRISP), a training-free LLM-driven multi-agent framework for online firestorm simulation. CRISP integrates an eWOM Perception module for responsibility attribution and attitude formation with an Engagement Mechanism for predicting participation under evolving KOL influence. Experiments on four heterogeneous Weibo online firestorms across beverage, automobile manufacturing, food service, and education domains show that CRISP reproduces major eWOM and engagement trajectories across different activity scales and interaction structures. Counterfactual interventions on emotional composition and responsibility attribution further produce directionally consistent responses, suggesting mechanism-level validity beyond trajectory fitting. These findings indicate that CRISP provides a framework for analyzing online firestorm evolution and evaluating crisis communication strategies in controllable simulation environments. Full article

Despite overwhelming scientific consensus that human activity drives climate change, public opinion in the United States remains sharply polarized along political lines. This project tests whether a theory-driven narrative intervention can reduce divergence between individuals skeptical of climate change and those who accept the scientific consensus. Guided by narrative transportation theory, we hypothesize that an inclusive, character-driven video grounded in the authentic language of skeptical audiences will reduce polarization and increase civic engagement. The study proceeds in three phases. Phase 1 uses focus group discussions to identify words, phrases, and perspectives used by skeptical and accepting participants. Phase 2 integrates these findings into the production of a 2–3 min narrative short film, refined through iterative audience testing. Phase 3 employs a stratified online experiment assessing climate attitudes, policy support, and activism behaviors before exposure, immediately after, and one week later. Mediators include narrative transportation, perceived similarity, and character identification. We test whether pre-exposure divergence narrows over time and whether engagement mechanisms explain observed changes. Findings will inform climate communication policy, intervention design, and broader research on depolarization in polarized public issues. Full article

Background/Objectives: Continuous quality improvement (CQI) requires timely, patient-centered evidence on how people experience healthcare delivery. Structured surveys provide important benchmarks, but their predetermined items may miss emerging or system-specific concerns. This study assesses whether unsolicited online patient reviews can serve as a scalable patient-experience data source for identifying hospital service quality priorities across contrasting healthcare systems. Methods: We analyzed 8247 Google Maps hospital reviews posted in 2024, including 5007 Chinese-language reviews from 24 Taiwanese medical centers and 3240 English-language reviews from 21 large U.S. referral hospitals. Separate language-specific preprocessing pipelines and Latent Dirichlet Allocation (LDA) topic models identified patient-salient service quality dimensions in each country. Cross-lingual semantic mapping then distinguished universal dimensions from system-specific concerns, and star-rating differences across semantically equivalent dimensions were compared. Results: Seven service quality dimensions emerged in each country: five were cross-nationally shared (emergency care, positive care experience, professional medical team, administrative process, and inpatient/treatment care), and each system had two system-specific dimensions. Taiwanese reviews foregrounded service attitude and facility/environment quality, while U.S. reviews foregrounded billing/insurance and clinic systems/access. Ratings for emergency care and administrative process were consistently low across both systems, whereas ratings for the professional medical team were substantially higher in U.S. reviews. Conclusions: Online patient reviews can complement formal patient-experience instruments by revealing actionable CQI priorities that are both universal and context dependent. Emergency care and administrative efficiency represent shared improvement needs across both systems. System-specific interventions include interpersonal training and infrastructure investment in high-utilization single-payer settings, and billing transparency and care coordination in fragmented multi-payer systems. Institutional structures appear to play a more prominent role than cultural factors in shaping which service quality dimensions emerge, though both forces contribute. Established frameworks may inadequately capture system-specific patient concerns. Full article

In 2024, Estonia launched a major educational reform: kindergartens and schools began a gradual transition to Estonian-medium education, to be completed in preschool and basic education by 2030. In Tartu, the transition began already in 2023. Until now, Estonia has maintained a dual school system—Estonian- and Russian-medium—inherited from the Soviet occupation. This paper examines the attitudes of Russian-speaking parents toward supporting their children’s mother tongue during the transition in Tartu’s bilingual schools and kindergartens. While Estonian legislative and strategic documents emphasise the importance of maintaining the mother tongue of pupils who study in a language different from their family language, institutional support and resources remain limited, placing the responsibility largely on families. The qualitative study is based on 25 in-depth interviews conducted in early 2023 with Russian-speaking parents whose children were attending transition schools and kindergartens in Tartu. The theoretical framework is based on research highlighting the importance of first-language development for additional language learning, academic achievement, and cognitive development. Content analysis reveals divergent parental attitudes. Some emphasise the need to preserve the mother tongue and expect schools to provide support, viewing multilingualism as a resource that strengthens identity and future prospects. Others prioritise rapid transition to Estonian-medium education, considering L1 development in educational settings less important. The findings highlight how legislative appreciation of multilingualism is undermined by the lack of institutional support. Full article

Time perspectives represent a fundamental dimension of adolescent development that may influence academic outcomes through emotional and interpersonal mechanisms. In this study, we examined how time attitude profiles relate to academic achievement in language and mathematics and whether emotion regulation difficulties and school well-being function as mediating mechanisms. A sample of 257 Chilean adolescents with a mean age of 14.36 years (SD = 0.57) from nine schools completed self-report measures of time attitudes, emotion regulation difficulties, and school well-being and provided school grades in language and mathematics. Latent profile analysis identified three time attitude profiles: Ambivalent, Positive, and Optimistic. Descriptive analyses showed that students with Positive and Optimistic profiles reported higher school well-being and fewer emotion regulation difficulties than Ambivalents, although mean differences in academic achievement across profiles were small. In mixed-effects models, time attitude profiles did not robustly predict language achievement once covariates were controlled, and only adolescents with an Optimistic profile showed slightly higher mathematics achievement than Ambivalents. Mediation models indicated that school well-being significantly mediated the association between the Positive time attitude profile and both mathematics and language achievement, whereas emotion regulation difficulties did not emerge as significant mediators for either subject. These findings highlight school well-being as a key psychosocial mechanism linking positive temporal orientations to academic outcomes and suggest that school-based interventions targeting time attitudes and school well-being may foster adolescents’ academic success. Full article

Vision–Language–Action (VLA) models unify visual perception, natural-language understanding, and action generation within a single foundation model, allowing a robot to follow instructions such as “fold the towel” or “fly to the red building” directly from camera images. Because VLAs inherit world knowledge from internet-scale pre-training, they have become the dominant framework for learning-based manipulation, with bimanual coordination serving as the most demanding testbed: two arms with 7+ degrees of freedom each must move in concert to fold, assemble, and reorient objects. Unmanned aerial robotics faces a structurally similar challenge: a drone must coordinate thrust, attitude, and increasingly gripper commands from visual observations under strict latency and payload constraints. This review covers 183 contributions spanning 2017–2026 and organized along seven dimensions: VLA architectures, training recipes, action representations, bimanual coordination (2022–2026), unmanned aerial vehicle (UAV) navigation and control (2017–2026), language grounding, and cross-cutting concerns including memory and world models. We show that the coordination strategies, training recipes, and action representations developed for bimanual VLAs transfer to unmanned aerial systems and identify fourteen research directions across both domains. Full article