Search Results (261)

The present study examined differences in reading comprehension performance between good and poor comprehenders, across paper-based and computer-based formats. The sample consisted of 197 students (Mage = 10.9, SDage = 1.22), categorized into three groups based on their reading comprehension proficiency: good (n = 73), average (n = 90), and poor (n = 33). Using a pseudo-randomized within-subjects design, participants read two texts and completed both a cloze task and a proofreading task in paper and digital formats. Results showed that poor comprehenders consistently performed worse on both tasks; however, group performances were not influenced by the modality. Both tasks required more time in the digital modality and were associated with greater calibration bias. In the proof-reading task, nouns and adjectives were more difficult to retrieve than verbs and function words, whereas in the cloze task, function words were the easiest to supply. The discussion emphasizes the need to account the for task type and linguistic complexity when evaluating comprehension. Importantly, the lack of interaction between reading proficiency and modality suggests that digital assessments are comparably effective and reliable across different levels of reading ability. Full article

In some languages, prosodic cues on word stems can be used to predict upcoming suffixes. Previous studies have shown that second language (L2) users can process such cues predictively in their L2 from approximately intermediate proficiency. This ability may depend on the mapping of the L2 prosody onto first language (L1) perceptual and functional prosodic categories. Taking as an example the Danish stød, a complex prosodic cue, we investigate an acquisition context of a predictive cue where L2 users are unfamiliar with both its perceptual correlates and its functionality. This differs from previous studies on predictive prosodic cues in Swedish and Spanish, where L2 users were only unfamiliar with either the perceptual make-up or functionality of the cue. In a speeded number judgement task, L2 users of Danish with German as their L1 (N = 39) and L1 users of Danish (N = 40) listened to noun stems with a prosodic feature (stød or non-stød) that either matched or mismatched the inflectional suffix (singular vs. plural). While L1 users efficiently utilised stød predictively for rapid and accurate grammatical processing, L2 users showed no such behaviour. These findings underscore the importance of mapping between L1 and L2 prosodic categories in second language acquisition. Full article

This study examines diurnal surface temperature dynamics across major Moroccan cities during the growing season and explores the interaction between urban and vegetated surfaces. We also introduce the Urban Thermal Impact Ratio (UTIR), a novel metric designed to quantify urban thermal comfort as a function of the surface urban heat island (SUHI) intensity. The analysis is based on outputs from a land surface model (LSM) for the year 2010, integrating high-resolution Landsat and MODIS data to characterize land cover and biophysical parameters across twelve land cover types. Our findings reveal moderate urban–vegetation temperature differences in coastal cities like Tangier (1.8 °C) and Rabat (1.0 °C), where winter vegetation remains active. In inland areas, urban morphology plays a more dominant role: Fes, with a 20% impervious surface area (ISA), exhibits a smaller SUHI than Meknes (5% ISA), due to higher urban heating in the latter. The Atlantic desert city of Dakhla shows a distinct pattern, with a nighttime SUHI of 2.1 °C and a daytime urban cooling of −0.7 °C, driven by irrigated parks and lawns enhancing evapotranspiration and shading. At the regional scale, summer UTIR values remain below one in Tangier-Tetouan-Al Hoceima, Rabat-Sale-Kenitra, and Casablanca-Settat, suggesting that urban conditions generally stay within thermal comfort thresholds. In contrast, higher UTIR values in Marrakech-Safi, Beni Mellal-Khénifra, and Guelmim-Oued Noun indicate elevated heat discomfort. At the city scale, the UTIR in Tangier, Rabat, and Casablanca demonstrates a clear diurnal pattern: it emerges around 11:00 a.m., peaks at 1:00 p.m., and fades by 3:00 p.m. This study highlights the critical role of vegetation in regulating urban surface temperatures and modulating urban–rural thermal contrasts. The UTIR provides a practical, scalable indicator of urban heat stress, particularly valuable in data-scarce settings. These findings carry significant implications for climate-resilient urban planning, optimized energy use, and the design of public health early warning systems in the context of climate change. Full article

Toponyms are fundamental geographical resources characterized by their spatial attributes, distinct from general nouns. While natural language provides rich toponymic data beyond traditional surveying methods, its qualitative ambiguity and inherent uncertainty challenge systematic extraction. Traditional toponym recognition methods based on part-of-speech tagging only focus on the surface-level features of words, failing to effectively handle complex scenarios such as alias nesting, metonymy ambiguity, and mixed punctuation. This leads to the loss of toponym semantic integrity and deviations in geographic entity recognition. This study proposes a set of Chinese toponym annotation specifications that integrate spatial semantics. By leveraging the XML markup language, it deeply combines the spatial location characteristics of toponyms with linguistic features, and designs fine-grained annotation rules to address the limitations of traditional methods in semantic integrity and geographic entity recognition. On this basis, by integrating multi-source corpora from the Encyclopedia of China: Chinese Geography and People’s Daily, a large-scale Chinese toponym annotation corpus (CHTopo) covering five major categories of toponyms has been constructed. The performance of this annotated corpus was evaluated through toponym recognition, exploring the construction methods of a large-scale, diversified, and high-coverage Chinese toponym annotated corpus from the perspectives of applicability and practicality. CHTopo is conducive to providing foundational support for geographic information extraction, spatial knowledge graphs, and geoparsing research, bridging linguistic and geospatial intelligence. Full article

Text-based person search (TPS), a critical technology for security and surveillance, aims to retrieve target individuals from image galleries using textual descriptions. The existing methods face two challenges: (1) ambiguous attribute–noun association (AANA), where syntactic ambiguities lead to incorrect associations between attributes and the intended nouns; and (2) textual noise and relevance imbalance (TNRI), where irrelevant or non-discriminative tokens (e.g., ‘wearing’) reduce the saliency of critical visual attributes in the textual description. To address these aspects, we propose the dependency-aware entity–attribute alignment network (DEAAN), a novel framework that explicitly tackles AANA through dependency-guided attention and TNRI via adaptive token filtering. The DEAAN introduces two modules: (1) dependency-assisted implicit reasoning (DAIR) to resolve AANA through syntactic parsing, and (2) relevance-adaptive token selection (RATS) to suppress TNRI by learning token saliency. Experiments on CUHK-PEDES, ICFG-PEDES, and RSTPReid demonstrate state-of-the-art performance, with the DEAAN achieving a Rank-1 accuracy of 76.71% and an mAP of 69.07% on CUHK-PEDES, surpassing RDE by 0.77% in Rank-1 and 1.51% in mAP. Ablation studies reveal that DAIR and RATS individually improve Rank-1 by 2.54% and 3.42%, while their combination elevates the performance by 6.35%, validating their synergy. This work bridges structured linguistic analysis with adaptive feature selection, demonstrating practical robustness in surveillance-oriented TPS scenarios. Full article

Bare nouns representing kinship terms (KNs) and body parts (BPNs) can be assumed to project a null possessor argument, which allows for the interpretation of such nouns relative to other linguistically present NPs. In Vietnamese, the distribution of KNs and BPNs is subject to different locality conditions and leads to the analysis of null possessors with KNs as covert anaphors, while null possessors with BPNs are null pronominals (pro). This contrasts with Mandarin Chinese, where it has been suggested that null possessors of KNs and BPNs are two different types of null anaphors. The observed distributional differences and analyses of bare KNs and BPNs in Vietnamese vs. Chinese raise questions of parametric variation with regard to null elements with parallel interpretive properties and also whether linking mechanisms may occur with other bare nouns without the projection of null possessors that are subject to binding theoretic locality restrictions. Full article

This paper examines morphosyntactic agreement in gender and number within the spontaneous spoken discourse of Spanish-speaking adults with Williams syndrome (WS), compared to that of typically developing (TD) speakers. Data were collected through natural speech transcriptions from both WS and TD groups. The analysis was conducted using Netlang 1.0.0—a piece of corpus annotation software—based on Dependency Grammar, to capture agreement patterns among determiners, nouns, and adjectives. The findings reveal that WS speakers’ gender and number agreement patterns are closely aligned with those observed in TD speakers, with only minor variations, such as a slight tendency toward unmarked gender forms among TD participants. Additionally, error rates are low in both groups, suggesting that observed discrepancies might be due to individual variation rather than condition-specific deficits, even though the statistical power of the study is limited. These results contribute to the ongoing debate on language abilities in WS, indicating that individuals with WS produce morphosyntactic agreement similarly to individuals with TD. Further research with larger datasets is recommended to validate these results, as individual variability within the WS group underscores the need for a more nuanced approach to analysis. Full article

Background/Objectives: Three distinct language comprehension phenotypes have previously been identified in individuals with language deficits: (1) individuals with the Command Phenotype are limited to understanding simple commands; (2) individuals with the Modifier Phenotype demonstrate additional comprehension of combinations of nouns and adjectives; and (3) individuals with the Syntactic Phenotype possess full syntactic comprehension. We hypothesized that typically developing children progress through these same three language comprehension phenotypes and aimed to determine the typical age at which each phenotype emerges. Methods: To assess comprehension in young children, we developed the 15-item Language Phenotype Assessment (LPA). This tool uses toy-animal manipulatives to avoid reliance on picture interpretation and employs brief instructions to reduce auditory memory load. LPA items incorporate elements such as colors, sizes, numbers, spatial prepositions, and other syntactic components, posing novel combinations of words that children had not previously encountered. The LPA was administered to 116 typically-developing children aged 1.5–7 years, recruited by approaching parents in local parks and inviting them to participate. Results: Findings revealed a developmental trajectory consistent with the three previously described phenotypes: 50% of children attained the Command Phenotype by 1.6 years of age, the Modifier Phenotype by 3.0 years of age, and the Syntactic Phenotype by 3.7 years of age. All children acquired the Command Phenotype by 3, the Modifier Phenotype by 4, and the Syntactic Phenotype by 5 years of age. Conclusions: The LPA is an effective tool for assessing comprehension in children aged 1.5–5 years. It allows for the early identification of comprehension difficulties, supporting the timely initiation of appropriate language interventions. Full article

This study offers a detailed comparative analysis of the reflexes of Proto-Bantu noun class prefixes within nine Gabonese languages belonging to the B50, B60, and B70 groups of Guthrie’s referential inventory of the Bantu languages. Genealogically speaking, all of them are part of the Kwilu-Ngounie subclade of the Bantu family’s West-Coastal Bantu branch. Starting out from a robust dataset comprising over 4000 lexical items collected through fieldwork and existing descriptions, the Comparative Method is used to distinguish changes in noun class morphology due to regular sound shifts from those emerging from analogical reanalysis and levelling. The comparative study shows a systematic reduction and reorganization of the inherited Proto-Bantu noun class system, notably the loss of classes 12/13 and 19 across all languages, variable retention and loss of classes 7/8 and 11, and complex patterns of reshuffling involving classes 5, 9/10, and 1/2. Key innovations, potentially reinforcing lexicon-based hypotheses of phylogenetic subgrouping within Kwilu-Ngounie, include the development of a class 7 allomorphy conditioned by stem-initial segments in the B50 languages and the emergence of vocalic prefixes restricted to the B60 and B70 languages. Full article

The cognitive core of human beings is closely connected to the concept of animacy, which significantly influences their memory, vision, and complex language comprehension. While animacy is reflected in language through subtle constraints on verbs and adjectives, it is also acquired and honed through non-linguistic experiences. In the same vein, we suggest that the limited capacity of LLMs to grasp natural language, particularly in relation to animacy, stems from the fact that these models are trained solely on textual data. Hence, the question this paper aims to answer arises: Can LLMs, in their digital wisdom, process animacy in a similar way to what humans would do? We then propose a systematic analysis via prompting approaches. In particular, we probe different LLMs using controlled lexical contrasts (animate vs. inanimate nouns) and narrative contexts in which typically inanimate entities behave as animate. Results reveal that, although LLMs have been trained predominantly on textual data, they exhibit human-like behavior when faced with typical animate and inanimate entities in alignment with earlier studies, specifically on seven LLMs selected from three major families—OpenAI (GPT-3.5, GPT-4), Meta (Llama2 7B, 13B, 70B), and Mistral (Mistral-7B, Mixtral). GPT models generally achieve the most consistent and human-like performance, and in some tasks, such as sentence plausibility and acceptability judgments, even surpass human baselines. Moreover, although to a lesser degree, the other models also assume comparable results. Hence, LLMs can adapt to understand unconventional situations by recognising oddities as animated without needing to interface with unspoken cognitive triggers humans rely on to break down animations. Full article

The role of attention has been shown to be essential in second language (L2) learning. However, the impact of different learning conditions on attention and learning outcomes remains underdeveloped, particularly through the application of eye-tracking technology. This study aims to evaluate the effect of intentional learning conditions (i.e., data-driven learning) on vocabulary learning and attentional allocations. Twenty-six intermediate English L2 learners participated in the study to learn the usage of four artificial attributive adjectives in noun phrases (NPs). Learning outcomes were analysed to assess the types of knowledge developed, shedding light on the role of attention and the conscious processing of word usage. Eye-tracking data, collected using Eyelink 1000 plus, investigated gaze patterns and the allocation of attentional sources when applying the learned usage of adjectives. The results indicate that fixation stability and regression movements significantly differ under the impact of intentional learning conditions. Post-test results also indicate a shift in attention from the target adjectives to the associated nouns. These findings underscore the critical role of attention and highlight the influence of learning conditions on L2 vocabulary learning, providing practical implications and empirical validation for L2 educators and researchers aiming to enhance vocabulary instruction through intentional learning strategies. Full article

Despite the growing number of bilinguals worldwide, research on how bilingualism influences grammatical development in children with learning disabilities remains limited. This may be due to challenges in assessing language in these children, given the heterogeneity of their disabilities, lack of appropriate tools, and variability in language background and exposure common in bilingual populations. This pilot study investigates grammatical abilities in bilingual versus monolingual children with Down syndrome using the LITMUS Sentence Repetition Task, specifically designed for bilingual populations. Sentence repetition tasks are widely used for assessing grammar in neurotypical children and children with language impairments and are part of many omnibus language assessments. Ten children with Down syndrome aged 5–8 were recruited: five bilingual, speakers of British English and various home languages, and five monolingual, age- and language-matched. Both groups produced a high proportion of ungrammatical repetitions, with more omissions of verbs than nouns, function words than content words, and significant difficulties producing complex structures such as relative clauses, wh-questions, and passives. However, qualitative analyses showed that bilingual children speaking morphologically rich home languages (e.g., Polish, Greek) appeared to have fewer difficulties with some function words (e.g., prepositions) and were able to produce complex structures like passives and wh-questions, unlike their monolingual peers. Although the small sample limits generalisability, two insights emerge: First, sentence repetition may be of limited use in assessing expressive grammar in children with Down syndrome due to frequent ungrammatical responses. Second, while both groups showed similar challenges, bilingualism—especially with richly inflected home languages—may support specific grammatical skills. These findings support existing evidence that bilingualism does not hinder grammatical development in children with Down syndrome and suggest that parents should not avoid dual-language input. Further research is needed to determine whether bilingualism confers specific benefits in grammatical morpheme use and complex syntactic constructions. Full article

Background/Objectives: Verbs are considered to be more abstract than nouns, as they represent actions, states, and events, which are less tangible, more flexible in their meaning and thus less univocally specified. It has been suggested that children acquire abstract concepts based on their linguistic contexts of use, making use of semantic and syntactic cues. By contrast, according to theories of embodied cognition, conceptual knowledge is based on physical and perceptual interaction with the world. The present study investigates whether the verbal and the visual modality produce similar or different results in the processes of construction and reactivation of novel verbs, corresponding to new compositional abstract concepts, in children of different ages. In Experiment 1, the acquisition of the concept was determined based on the quality of verbal explanation; in Experiment 2, participants were asked to decide whether a visual representation fitted the concept or not. Thus, response modality could be either explicit or implicit, and either congruent or incongruent with respect to learning modality. Methods: In Experiment 1, 100 children from grade 1 to 5 were asked to explain the meaning of verbs introduced via verbal or visual instances. In Experiment 2, 15 children aged 8 to 10 had to judge pictures as (not) being examples of previously verbally or visually presented novel verbs. Results: The results of Experiment 1 show more accurate explanations after verbal presentation across all grades. In Experiment 2, verbal presentation was no longer associated with more accurate matching responses, but rather with slower decision times. Conclusions: Modality congruence, explicitness and linguistic (semantic and syntactic) factors were all shown to play a role, which is discussed in a developmental perspective. Full article

Large language models (LLMs) are increasingly applied to specialized domains like medical education, necessitating tailored approaches to evaluate structured responses such as SBAR (Situation, Background, Assessment, Recommendation). This study developed an evaluation tool for nursing student responses using LLMs, focusing on word-based learning and assessment methods to align automated scoring with expert evaluations. We propose a three-stage biasing approach: (1) integrating reference answers into the training corpus; (2) incorporating high-scoring student responses; (3) applying domain-critical token weighting through Weighted Noun Embeddings to enhance similarity measurements. By assigning higher weights to critical medical nouns and lower weights to less relevant terms, the embeddings prioritize domain-specific terminology. Employing Word2Vec and FastText models trained on general conversation, medical, and reference answer corpora alongside Sentence-BERT for comparison, our results demonstrate that biasing with reference answers, high-scoring responses, and weighted embeddings improves alignment with human evaluations. Word-based models, particularly after biasing, effectively distinguish high-performing responses from lower ones, as evidenced by increased cosine similarity differences. These findings validate that the proposed methodology enhances the precision and objectivity of evaluating descriptive answers, offering a practical solution for educational settings where fairness and consistency are paramount. Full article

In this article, we tested some specific claims made in the literature on relative distances among European languages and among Chinese dialects, suggesting that some language varieties within the Sinitic family traditionally called dialects are, in fact, more linguistically distant from one another than some European varieties that are traditionally called languages. More generally, we examined whether distances among varieties within and across European language families were larger than those within and across Sinitic language varieties. To this end, we computed lexico-phonetic as well as syntactic distance measures for comparable language materials in six Germanic, five Romance and six Slavic languages, as well as for six Mandarin and nine non-Mandarin (‘southern’) Chinese varieties. Lexico-phonetic distances were expressed as the length-normalized MPI-weighted Levenshtein distances computed on the 100 most frequently used nouns in the 32 language varieties. Syntactic distance was implemented as the (complement of) the Pearson correlation coefficient found for the PoS trigram frequencies established for a parallel corpus of the same four texts translated into each of the 32 languages. The lexico-phonetic distances proved to be relatively large and of approximately equal magnitude in the Germanic, Slavic and non-Mandarin Chinese language varieties. However, the lexico-phonetic distances among the Romance and Mandarin languages were considerably smaller, but of similar magnitude. Cantonese (Guangzhou dialect) was lexico-phonetically as distant from Standard Mandarin (Beijing dialect) as European language pairs such as Portuguese–Italian, Portuguese–Romanian and Dutch–German. Syntactically, however, the differences among the Sinitic varieties were about ten times smaller than the differences among the European languages, both within and across the families—which provides some justification for the Chinese tradition of calling the Sinitic varieties dialects of the same language. Full article