Search Results (233)

Schools in Sweden support multilingual students’ language and knowledge development in various ways, including through pedagogical collaboration among multiple professionals. Despite the recognized benefits, however, little is known about how such pedagogical collaboration is understood and practiced by classroom teachers in Sweden. The purpose of the present study is to deepen the understanding of how teachers in the early years of schooling collaborate with heritage language teachers, Swedish as a second language teachers, and special educational needs teachers, in order to support language and knowledge development in second language learners. Individual semi-structured interviews were conducted with 15 Swedish teachers working in the early years of schooling, i.e., from reception year to Grade 3. The interviews were analyzed thematically. Results showed that teachers generally perceive collaboration with other professionals as beneficial. They conceptualized varying forms of pedagogical collaboration, encompassing frequent and flexible collaboration with close colleagues, interdependent collaboration with heritage language teachers (often complicated by structural constraints), and regular, structured collaboration within the student health team. Identified opportunities associated with pedagogical collaboration included the provision of holistic support for second language learners, as well as opportunities for professional development and collegial support. At the same time, several challenges were highlighted, including time-related and structural constraints that hinder collaboration, as well as language barriers and the influence of individual characteristics. Student health teams were highlighted as important for integrating expertise; however, limited teacher insight and the infrequent inclusion of Swedish as a second language teachers were reported to result in multilingual perspectives being overlooked. This study therefore recommends greater consideration of multilingual expertise in assessments of special educational needs and calls for further research on the role of student health teams in supporting second language learners. 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

The aim of this study is to analyse the active role of volunteers in the Italian reception system and to assess how their actions and strategies contribute to the construction of an environment that promotes the autonomy and protagonism of unaccompanied minors in the development of their migration project. Based on a theoretical framework that combines socio-educational and psychosocial approaches and theories of community participation, the study addresses the importance of volunteering as a key tool in processes of inclusion and the development of personal migration projects. A qualitative approach is adopted under the interpretative paradigm, using a collective case study carried out at the Scuola Penny Wirton in Rome. The sample was selected through purposive and convenience sampling, integrating 25 volunteer agents (68% women and 32% men), aged between 60 and 84. Semi-structured interviews were conducted. The results show that volunteers deploy flexible and personalised strategies, prioritising the creation of a climate of trust and contextualised language learning as a vehicle for integration. Likewise, the importance of emotional support, identification and attention to psychosocial needs, and the promotion of a sense of belonging is evident. However, a lack of formal mechanisms for interdisciplinary collaboration is detected. Full article

From the early Middle Ages, but mostly the late twelfth century, the love story involving Tristan and Isolde (also Yseut) attracted much attention, originating in the Celtic world but fully developed first by the Old French poet Béroul (ca. 1160) and Thomas of England, of Britain, or of Brittanny, around 1170. It was rendered into virtually every European language since then and has also appealed to artists and musicians throughout time. We know, for example, of tiles, tapestry, sculptures, paintings, musical tunes, manuscript illuminations, and other visual representations of the intense but highly problematic relationship between these two young people. In essence, while Yseult is married to the King of Cornwall, Mark/Marke, a love potion, a metaphorical symbol of their deep feelings, bonds her with Tristan for the rest of their lives (a limited number of years in the earlier versions). Ultimately, at least in most versions, they are destined to die because of their love, which is incompatible with the social norms of their time, and this Romantic theme has hence also played a huge role in the nineteenth and twentieth centuries, and is perhaps highly important also today, as expressed by modern movies and music engaging with this love story. This study first traces in rough brushstrokes the history of the reception of this literary theme from the twelfth to the twenty-first century; then, it returns to the various medieval versions to investigate the critical issues contained in this highly popular story, which has never lost its relevance and attraction for audiences throughout time. Since the focus rests on the history of reception, less on comparative literature, the main tradition to be traced will be the German one. Full article

As the iconic concept of the I Ching, the “image” (xiang 象) is the linchpin for understanding its philosophical ideas. In its reception by scholars in Europe and North America, many have explored the “image” from religious, psychological, historical, philological, and other perspectives. These studies, however, have largely centered on epistemological and consciousness-based analyses of the “image”, whereas the discourse on the “image” in the Great Commentaries on the I Ching (Yizhuan 易傳) carries inherent ontological implications. Deploying appropriate philosophical language to elaborate the ontological foundation of the “image” is therefore crucial for communicating the I Ching’s philosophical ideas to the English-speaking world. By clarifying the connotations of “visible image” (xingxiang 形象), “analogical image” (nixiang 擬象), and “manifest image” (xianxiang 見象) as articulated in the Great Commentaries on the I Ching, this study demonstrates that the Yi (易) exhibits absolute ontological identity with Spinoza’s Substance, while the “image” corresponds to Spinoza’s concept of “expression”. Rombach’s structural phenomenology reinterprets the ontology of “Substance” as the genesis of “the One”, enabling an elaboration of the emergent character of the Yi as “the Ultimate One” (Taiyi 太一). This further reveals that the ”image” is not only an expression of the existence of the “Yi/Substance/One” but also a marker of the Yi’s—or Substance’s—transformation. Drawing on Spinoza’s concept of “Substance” and Rombach’s structural phenomenology thus aids in clarifying the ontological foundation of the “image” and promotes the cross-cultural dissemination of I Ching thought in Europe and North America. Full article

Background/Objectives: This study describes the development and validation of the Danish Sentence Test (DAST), a Danish-language, adaptive speech-in-noise test constructed from a linguistically balanced corpus using a template-based method. This approach enables controlled linguistic variation while maintaining lexical consistency and may serve as a model for developing similar speech materials in other languages. Methods: Sentences spoken by one female talker from the DAST corpus were sorted into 44 balanced lists of 20 sentences using a psychometric optimization procedure. Speech reception thresholds (SRTs) were measured in 20 normal-hearing participants using headphone playback with speech-shaped noise. Results: Across the 44 sentence lists, the mean SRT was −5.3 dB SNR, with list means within ±0.5 dB of the grand average under the tested configuration. The average within-subject standard deviation was 0.7 dB, and the grand-average psychometric slope was 18.5%/dB. A statistically significant within-session training effect of approximately 0.02 dB per measurement. Conclusions: This study provides normative speech reception threshold (SRT) data for the adaptive Danish Sentence Test (DAST) in normal-hearing listeners under a defined headphone-based speech-in-noise paradigm and demonstrates that the resulting sentence lists yield comparable performance across lists. The template-based construction and optimization approach offers a framework for developing linguistically rich sentence-in-noise tests in other languages. Full article

With Transformers achieving breakthrough results in natural language processing and computer vision, researchers have attempted to leverage their powerful modeling capabilities in 3D point cloud processing. However, the inherent unordered and unstructured nature of point cloud data poses significant challenges to directly applying Transformer architectures. This research proposes a novel point cloud processing method by introducing point cloud serialization and a serialization-based attention mechanism to enhance the performance of the PointNeXt model in semantic segmentation tasks. Traditional point cloud processing methods typically treat point clouds as unstructured data collections, resulting in low computational efficiency and scalability limitations. Our proposed approach breaks through the constraints of point cloud data’s unordered nature by serializing point clouds into a structured format. We employ spatial filling curves (such as Z-order and Hilbert curves) to sort point clouds, enabling efficient grouping of points into non-overlapping patches and applying more efficient attention mechanisms on these patches. Based on the serialization point cloud, we incorporate the segment attention mechanism from Point Transformer V3 (PTv3), which leverages the ordered characteristics of Serialization. By designing segment interactions (such as sequential shifting and sequential random mixing), we expand the model’s receptive field while maintaining computational efficiency. Full article

Automatic modulation recognition (AMR) is increasingly relevant to communication-sensing front ends in robotic and human–robot collaborative systems, where reliable spectrum awareness and adaptive wireless reception are desired. However, existing methods often degrade sharply at low signal-to-noise ratios (SNRs), and large language models (LLMs) are not natively compatible with continuous I/Q signals due to the inherent modality gap. We propose BioLAMR, a GPT-2 adaptation framework for AMR inspired by the auditory system’s parallel time–frequency processing and cortical hierarchy. The framework combines bio-inspired dual-domain feature extraction with parameter-efficient LLM adaptation. BioLAMR includes three components. First, a lightweight dual-domain fusion (LDDF) module extracts complementary time- and frequency-domain features and fuses them through channel and spatial attention. Second, a convolutional embedding module converts continuous I/Q signals into GPT-2-compatible sequences without discrete tokenization. Third, a hierarchical fine-tuning strategy updates only 8.9% of parameters to preserve pretrained knowledge while adapting to modulation recognition. Experiments on the RadioML2016.10a and RadioML2016.10b benchmarks show that BioLAMR achieves overall accuracies of 64.99% and 67.43%, outperforming the strongest competing method by 2.60 and 2.47 percentage points, respectively. Under low-SNR conditions, it reaches 36.78% and 38.14%, the best results among the compared methods. Ablation studies verify the contribution of each component. These results demonstrate that combining dual-domain signal modeling with parameter-efficient GPT-2 adaptation is an effective route to robust AMR in challenging wireless environments. Full article

This study examined the association between sensory-rich messy play and language development in children with Down syndrome (DS) and children with intellectual disabilities of unknown etiology (IDUE). Drawing on Vygotsky’s sociocultural theory and the framework of embodied cognition, the study investigated whether different play contexts are differentially associated with expressive and receptive language outcomes across developmental populations. A 2 × 2 quasi-experimental pretest–posttest design was employed. Forty children aged 4 to 6 years were assigned to one of four conditions based on diagnostic group (DS vs. IDUE) and intervention type (sensory-rich messy play vs. structured non-sensory play). Language development was assessed before and after a 12-week intervention using the LaTo standardized test. Mixed-design analyses of variance revealed significant improvements in language performance over time, as well as significant effects of intervention type and diagnostic group. Children who participated in sensory-rich messy play demonstrated greater gains in expressive and receptive language compared to those engaged in structured play. A significant interaction between diagnostic group and intervention type was also observed, indicating that the association between play context and language development differed across groups. In particular, children with DS in the messy play condition showed the most pronounced improvements, especially in expressive language. These findings suggest that sensory-rich play contexts are associated with enhanced language outcomes, particularly for children with DS. However, due to the quasi-experimental design, causal interpretations should be made with caution. These findings suggest that sensory-rich play contexts are associated with enhanced short-term language outcomes, particularly for children with DS. However, due to the quasi-experimental design and the absence of follow-up assessment, conclusions regarding long-term or causal effects should be made with caution. Full article

Extra-curricular activities (EAs) have become a billion-dollar industry in Asia, and many parents in Singapore enroll their children in enrichment classes to improve English and mother tongue language performance. Despite the heavy investment, it remains unclear how much children could benefit from such exposure. The present study examines this issue with 123 English–Mandarin bilingual children aged four to five. The number of hours children spent in language-related EAs, together with a set of internal factors (e.g., nonverbal intelligence) and external factors (e.g., home input), were used to predict children’s receptive vocabulary and word-reading skills in both languages using path models. Results show that 36% of the children attended English or Mandarin enrichment classes. Participation in English enrichment classes was not significantly associated with children’s English receptive vocabulary or English word-reading skills. In contrast, Mandarin enrichment classes were significantly associated with better Mandarin word-reading performance. The differential effects of enrichment classes may reflect the bilingual context of Singapore, where English dominates daily communication while Mandarin is mainly learned as a subject in preschool and receives relatively limited exposure outside school. The findings highlight the importance of considering sociolinguistic context when evaluating the effectiveness of language enrichment programs. Full article

Background and Objectives: Endometrial polyps are common in women presenting with subfertility, yet uncertainty persists regarding which lesions warrant removal and how best to integrate hysteroscopic management with contemporary fertility treatment pathways. This narrative review synthesizes current evidence on pathophysiological mechanisms, diagnostic approaches, fertility outcomes, and practical clinical management for women under 40 years of age. Materials and Methods: PubMed/MEDLINE, Embase, Scopus, Web of Science, and the Cochrane Library were searched for English-language human studies published between January 2005 and December 2025. From 2352 records identified, 83 studies were included after screening of 1517 unique records (7 randomized controlled trials, 12 systematic reviews/meta-analyses, 14 prospective cohort studies, 31 retrospective cohort studies, 5 case–control and other study designs, 11 narrative reviews and supporting evidence studies, 1 clinical guideline, and 2 targeted 2025 additions). This structured narrative review employed a systematic search strategy to ensure comprehensive coverage, with evidence synthesized thematically in accordance with the SANRA guidelines. No formal risk-of-bias assessment or pre-registered protocol was used. Results: Across treatment modalities, hysteroscopic polypectomy was consistently associated with improved fertility outcomes. The landmark Pérez-Medina randomized trial reported a relative risk of 2.1 (95% CI 1.5–2.9) for pregnancy after polypectomy before intrauterine insemination. For IVF/ICSI, reported clinical pregnancy rates after polypectomy range from 53–72% and live birth rates from 43–66%. Proposed mechanisms include mechanical interference, chronic inflammation with cytokine dysregulation, altered endometrial receptivity (including dysregulation of HOXA10/HOXA11), and impaired decidualization. Conclusions: Current evidence supports hysteroscopic polypectomy as an effective intervention to improve fertility outcomes in subfertile women with endometrial polyps, particularly prior to intrauterine insemination. For IVF/ICSI, polypectomy of documented polyps appears beneficial, though evidence quality is moderate and heterogeneity exists across studies. It is critical to distinguish routine screening hysteroscopy before IVF from targeted polypectomy when a polyp has been documented. Contemporary guidance (including the 2024 SOGC guideline) favors polypectomy for symptomatic polyps and those that meet specific clinical criteria; for small asymptomatic polyps (<10 mm), individualized decision-making is appropriate, given limited direct evidence and the potential for spontaneous regression. Future research should clarify molecular predictors of polyp-associated infertility, optimal timing relative to fertility treatment, and long-term reproductive outcomes. Full article

Background/Objectives: Receptive vocabulary is essential for children’s language, academic, and cognitive development. While cochlear implants (CIs) help children with severe to profound hearing loss develop spoken language, their vocabulary skills often fall behind their typical hearing (TH) peers, although early implantation and auditory-verbal therapy (AVT) can help narrow this gap. Children with CIs and other developmental difficulties face additional challenges, but can still progress, with outcomes depending on the disabilities’ type and severity. Limited research exists on Arabic-speaking children with CIs, where cultural factors may delay intervention, and outcomes vary widely. It remains unclear how well these children develop receptive vocabulary compared to hearing peers and which factors influence their progress. Methodology: A multicenter, cross-sectional study in six GCC hospitals compared 103 children with CIs to a control group of 94 children with TH. Children with CIs were divided into those with and without additional difficulties. Receptive vocabulary was evaluated utilizing the Peabody Picture Vocabulary Test, Fifth Edition. Results: Children with CIs in the GCC scored lower (mean 89.5; SD = 20.5) than the TH control group (mean 104; SD = 16.8). Children with CIs without additional difficulties (mean 97.7; SD = 18.8) scored similarly to TH, while children with CIs and additional difficulties scored significantly lower (mean 76.7; SD = 15). Age at switch-on and presence of additional difficulties significantly affected receptive vocabulary outcomes. Conclusions: Children with CI who have no additional disabilities can reach receptive vocabulary levels similar to typical hearing peers, while those with extra difficulties show very diverse outcomes and continue to face challenges. Full article

This study investigated the effects of “The Golden Triangle”, a blended-learning intervention program designed to promote academic language literacy among Arabic-speaking seventh-grade students in Israel. Receptive and productive academic vocabulary and academic reading comprehension were assessed before and after the intervention (Grade 7), and again five months later at the beginning of the eighth grade. Participants were 70 Arabic-speaking students from four middle schools, divided into a high/average reading comprehension (HRC) group and a low reading comprehension (LRC) group. Results showed that the LRC group improved its reading comprehension immediately after the intervention but declined at follow-up, whereas the HRC group improved during the program and maintained gains. Moreover, in the HRC group, baseline receptive academic vocabulary predicted reading comprehension at follow-up, whereas no similar predictive effect was found in the LRC group. These findings highlight the need to address persistent heterogeneity in reading abilities and to design differentiated interventions that support the long-term consolidation of academic language among struggling readers. Full article

The establishment of AI ethics bylaws in academia is needed for teaching, learning, and assessment. The adaptive parameters of these bylaws define the ethical, pedagogical, and operational standards for the use of artificial intelligence tools within academia. The main aim is to ensure that AI tools are used to enhance educational practices while preserving human judgment, safeguarding academic integrity, and promoting critical thinking. Specifically, these are intended to mentor all domains of academia to uphold the core values of fairness and transparency while adapting to the advent of modern technologies. While many are enthused by the support provided by large language models, it is also important to prevent over-reliance or misuse of AI technologies. This establishes clear responsibility for faculty, students, and administration. These significant bylaws pay more attention to these issues to provide a foundation for good governance, evaluation, and amendment of AI-related practices. To provide normative insight into the anticipated reception of these bylaws, we conducted a small exploratory pilot study with STEM faculty. The resulting observations offer preliminary indications of the feasibility of the proposed method for future research and policy development. Full article

Background/Objectives: The rise of artificial intelligence is injecting intelligence into the healthcare sector, including surgery. Vision-based intelligent systems that assist surgical procedures can significantly increase productivity, safety, and effectiveness during surgery. Surgical instruments are central components of any surgical intervention, yet detecting and locating them during live surgeries remains challenging due to adverse imaging conditions such as blood occlusion, smoke, blur, glare, low-contrast, instrument scale variation, and other artifacts. Methods: To address these challenges, we developed an advanced segmentation architecture termed the frozen-filters-based morphology-aware segmentation network (FFMS-Net). Accurate surgical instrument segmentation strongly depends on edge and morphology information; however, in conventional neural networks, this spatial information is progressively degraded during spatial processing. FFMS-Net introduces a frozen and learnable feature pipeline (FLFP) that simultaneously exploits frozen edge representations and learnable features. Within FLFP, Sobel and Laplacian filters are frozen to preserve edge and orientation information, which is subsequently fused with learnable initial spatial features. Moreover, a tri-atrous blending (TAB) block is employed at the end of the encoder to fuse multi-receptive-field-based contextual information, preserving instrument morphology and improving robustness under challenging conditions such as blur, blood occlusion, and smoke. Datasets focused on surgical instruments often suffer from severe class imbalance and poor instrument visibility. To mitigate these issues, FFMS-Net incorporates a progressively structure-preserving decoder (PSPD) that aggregates dilated and standard spatial information after each upsampling stage to maintain class structure. Multi-scale spatial features from different encoder levels are further fused using light skip paths (LSPs) to project channels with task-relevant patterns. Results/Conclusions: FFMS-Net is extensively evaluated on three challenging datasets: UW-Sinus-surgery-live, UW-Sinus-cadaveric, and CholecSeg8k. The proposed method demonstrates promising performance compared with state-of-the-art approaches while requiring only 1.5 million trainable parameters. In addition, an open-source large language model is integrated for non-clinical summarization of the surgical scene based on the predicted mask and deterministic descriptors derived from it. Full article