Search Results (189)

This study proposes a framework that leverages natural language processing and unsupervised machine learning techniques to measure, identify, and classify examinees’ writing strategies. The framework integrates three categories of writing strategies (text complexity, evidence use, and argument structure) to identify the characteristics of examinees’ writing. Additionally, a measurement model is used to calibrate examinees’ writing proficiency. An empirical example is presented to demonstrate the performance of the framework. The data comprise 430 Grade 8 examinees’ responses to English Language Arts (ELA) assessments in the United States. Using K-means clustering, distinct patterns were identified in each category. The one-parameter logistic measurement model was applied to estimate examinees’ writing proficiency. Analyses revealed significant effects of text complexity and evidence use on writing proficiency, while argument structure was not significant. This study has implications for writing instruction and assessment design that highlight the point that effective writing is not simply a matter of isolated skill acquisition, but rather the coordinated implementation of complementary strategies, a finding that supports cognitive developmental theories of writing. Full article

Effective language processing relies on pattern detection. Spanish monolinguals predict verb tense through stress–suffix associations: a stressed first syllable signals present tense, while an unstressed first syllable signals past tense. Low-proficiency second language (L2) Spanish learners struggle to detect these associations, and we investigated whether they benefit from game-based training. We examined the effects of four variables on their ability to detect stress–suffix associations: three linguistic variables—verbs’ lexical stress (oxytones/paroxytones), first-syllable structure (consonant–vowel, CV/consonant–vowel–consonant, CVC), and phonotactic probability—and one learner variable—working memory (WM) span. Beginner English learners of Spanish played a digital game focused on stress–suffix associations for 10 days and completed a Spanish proficiency test (Lextale-Esp), a Spanish background and use questionnaire, and a Corsi WM task. The results revealed moderate gains in the acquisition of stress–suffix associations. Accuracy gains were observed for CV verbs and oxytones, and overall reaction times (RTs) decreased with gameplay. Higher-WM learners were more accurate and slower than lower-WM learners in all verb-type conditions. Our findings suggest that prosody influences word activation and that digital gaming can help learners attend to L2 inflectional morphology. Full article

Interest in language-learning motivation has been growing recently, particularly in multilingual contexts where individuals acquire additional languages beyond English. Despite increasing the focus on multilingualism within second-language acquisition (SLA) research, less research focuses on the motivational dynamics of multilingual learners in learning languages other than English (LOTE). Addressing this gap, the present study investigates the complex motivational factors influencing multilingual university students in learning French as an additional language and LOTE within the Belgian context. The participants consisted of 121 multilingual university students who were learning French as an additional language and LOTE. Data were collected through questionnaire and semi-structured interviews, and analyzed using a combination of quantitative and qualitative methods to provide a comprehensive understanding of learners’ motivational profile. Findings revealed that multilingual learners’ motivation is multifaceted and dynamic, shaped by a combination of intrinsic interests (e.g., cultural appreciation and personal growth), extrinsic goals (e.g., academic and career aspirations), integrative motives, and prior language-learning experiences. The study also sheds light on the overlapping and evolving nature of motivational patterns and provides nuanced insights into LOTE learning motivation within multilingual settings. Full article

The rapid development of online media has significantly facilitated the public’s information consumption, knowledge acquisition, and opinion exchange. However, it has also led to more violent conflicts in online discussions. Therefore, controversy detection becomes important for computational and social sciences. Previous research on detection methods has primarily focused on larger datasets and more complex computational models but has rarely examined the underlying mechanisms of conflict, particularly the psychological motivations behind them. In this paper, we propose a lightweight and language-independent method for controversy detection by introducing two novel psychological features: ascending gradient (AG) and tier ascending gradient (TAG). These features capture psychological signals in user interactions—specifically, the patterns where controversial comments generate disproportionate replies or replies outperform parent comments in likes. We develop these features based on the theory of the backfire effect in ideological conflict and demonstrate their consistent effectiveness across models and platforms. Compared with structural, interaction, and text-based features, AG and TAG show higher importance scores and better generalizability. Extensive experiments on Chinese and English platforms (Reddit, Toutiao, and Sina) confirm the robustness of our features across languages and algorithms. Moreover, the features exhibit strong performance even when applied to early-stage data or limited “one-page” scenarios, supporting their utility for early controversy detection. Our work highlights a new psychological perspective on conflict behavior in online discussions and bridges behavioral patterns and computational modeling. Full article

This study investigates L3 Spanish perception patterns among L1 Korean–L2 English bilinguals with varying L3 proficiency levels, aiming to test the applicability of traditional L2 perceptual models in multilingual contexts. We conducted two experiments: a cross-linguistic discrimination task and a cross-language identification task. Results revealed unexpected outcomes unique to multilingual contexts. Participants had difficulty reliably discriminating between cross-linguistic categories and showed little improvement over time. Similarly, they did not demonstrate progress in categorizing sounds specific to each language. The absence of a clear correlation between proficiency levels and the ability to discriminate and categorize sounds suggests that input distribution and language-specific activation may play more critical roles in L3 perception, consistent with the distributional learning approach. We argue that phoneme distributions from all three languages likely occupy a shared perceptual space. When a specific language is activated, the relevant phoneme distributions become dominant, while others are suppressed. This selective activation, while not crucial in traditional L1 and L2 studies, is critical in L3 contexts, like the one examined here, where managing multiple phonemic systems complicates discrimination and categorization. These findings underscore the need for theoretical adjustments in multilingual phonetic acquisition models and highlight the complexities of language processing in multilingual settings. Full article

This study explores how Danish student teachers notice teaching quality when engaging with video-enhanced campus teaching and the research-based observation manual PLATO. Despite the limited tradition of using systematic observation tools in Danish teacher education, this intervention study investigates how student teachers from three subject-didactical courses (Danish, English, and Mathematics) engage with the PLATO criteria during group discussions on classroom video clips. Teacher noticing is conceptualized as a set of interrelated competencies—observing, interpreting, deciding, and acting—across four phases of teaching practice. Through qualitative content analysis of the group discussions, this study reveals varying degrees of engagement with PLATO, ranging from strategic and superficial use to nuanced, criteria-based interpretations. While some student teachers struggle with the manual’s language and purpose, others demonstrate meaningful integration of PLATO with didactical theory. This study concludes that bridging the gap between international quality frameworks and national didactical traditions requires thoughtful integration and openness to diverse conceptualizations of teaching quality. The findings highlight the importance of how the work with video and teacher noticing is framed, modeled and scaffolded in teacher education to support student teachers’ acquisition of teacher noticing and the language of teaching quality. Full article

Introduction: Combat sport athletes are exposed to repetitive head impacts yet also develop distinct performance-related brain adaptations. Electroencephalography (EEG) provides millisecond-level insight into both processes; however, findings are dispersed across decades of heterogeneous studies. This mechanistic review consolidates and interprets EEG evidence to elucidate how participation in combat sports shapes brain function and to identify research gaps that impede clinical translation. Methods: A structured search was conducted in March 2025 across PubMed/MEDLINE, Scopus, Cochrane Library, ResearchGate, Google Scholar, and related databases for English-language clinical studies published between January 1980 and March 2025. Eligible studies recorded raw resting or task-related EEG in athletes engaged in boxing, wrestling, judo, karate, taekwondo, kickboxing, or mixed martial arts. Titles, abstracts, and full texts were independently screened by two reviewers. Twenty-three studies, encompassing approximately 650 combat sport athletes and 430 controls, met the inclusion criteria and were included in the qualitative synthesis. Results: Early visual EEG and perfusion studies linked prolonged competitive exposure in professional boxers to focal hypoperfusion and low-frequency slowing. More recent quantitative studies refined these findings: across boxing, wrestling, and kickboxing cohorts, chronic participation was associated with reduced alpha and theta power, excess slow-wave activity, and disrupted small-world network topology—alterations that often preceded cognitive or structural impairments. In contrast, elite athletes in karate, fencing, and kickboxing consistently demonstrated neural efficiency patterns, including elevated resting alpha power, reduced task-related event-related desynchronization (ERD), and streamlined cortico-muscular coupling during cognitive and motor tasks. Acute bouts elicited transient increases in frontal–occipital delta and high beta power proportional to head impact count and cortisol elevation, while brief judo chokes triggered short-lived slow-wave bursts without lasting dysfunction. Methodological heterogeneity—including variations in channel count (1 to 64), reference schemes, and frequency band definitions—limited cross-study comparability. Conclusions: EEG effectively captures both the adverse effects of repetitive head trauma and the cortical adaptations associated with high-level combat sport training, underscoring its potential as a rapid, portable tool for brain monitoring. Standardizing acquisition protocols, integrating EEG into longitudinal multimodal studies, and establishing sex- and age-specific normative data are essential for translating these insights into practical applications in concussion management, performance monitoring, and regulatory policy. Full article

This article presents acoustic data on coarticulatory vowel nasalization from the productions of twelve L1 Korean speakers and of fourteen Korean learners of L2 English. The dataset includes eight monosyllabic target words embedded in eight carrier sentences, each repeated four times per speaker. Half of the words contain a nasal coda such as p*am in Korean and bomb in English and the other half a nasal onset such as mat in Korean and mob in English. These were produced under varied prosodic conditions, including three phrase positions and two focus conditions, enabling analysis of prosodic effects on vowel nasalization across languages along with individual speaker variation. The accompanying CSV files provide acoustic measurements such as nasal consonant duration, A1-P0, and normalized A1-P0 at multiple timepoints within the vowel. While theoretical implications have been discussed in two published studies, the full dataset is published here. By making these data publicly available, we aim to promote broad reuse and encourage further research at the intersection of prosody, phonetics, and second language acquisition—ultimately advancing our understanding of how phonetic patterns emerge, transfer, and vary across languages and learners. Full article

Deep, potent silences sometimes underlie thoughts of suicide. This paper presents a personal reflection of silence as a form of expression, and examines how engaging in expressive arts activities may reveal and help in processing feelings of distress and thoughts of suicide. There is an additional layer of hegemony that the use of words adds to discussions of suicidality, which makes these discussions inaccessible to many of the disenfranchised, including people from a refugee background for whom English is not a first language. But, for those struggling with speaking the (English) language in the first place, at what level of language acquisition can they be deemed fit to express and accurately represent their thoughts and ideas about suicide? Does their silence count? And so, by tackling this dilemma, this paper seeks to examine alternative ways of expression that do not heavily rely on words. It explores how, in our undertaking of suicidality studies creatively, we may embody and dignify the ways of the marginalised that have been devalued by a colonialist or interventionist agenda. The paper is an exercise in re-writing their experiences from the critical consciousness of coloniality. It is a disassembling of the control, domination, and exploitation that words can have. It is an attempt to shift the source and profile of knowledge about suicide from those who wield the power and privilege of words to those who live in the margins, shielded by silence. Full article

The development of artificial intelligence has revolutionized language learning approaches with AI-assisted language applications (AiLAs) like Grammarly, Siri, and ChatGPT 3.5, offering self-paced learning, tailored feedback, and increased engagement. There is, however, not much understanding about AI’s precise effects on perceived English learning improvements among students, as the majority of current research concentrates on the fact that AI is generally regarded as a language support tool. This study investigates the relation between students’ beliefs of using AiLA in terms of duration, frequency, familiarity, and user satisfaction to improve their learning of English. Fifty-five (55) undergraduate students between the ages of 21 and 24 participated in the survey. The results showed that the duration of use and perceived English learning improvements had a moderate positive relationship, indicating that extensive use of AiLA aids in language acquisition. Frequency of use, however, had little effect, suggesting that frequent use of AiLA may not be enough. There was a small and statistically insignificant correlation between students’ perceived English learning improvement and their familiarity with AiLA. Additionally, there was a minimal to no significant correlation between user pleasure and perceived improvements in English learning, indicating that enjoyment of AiLA is not closely related to the use of the tools. These findings demonstrate that AiLA needs to be systematically incorporated into instruction, with a focus on interactive and adaptable features rather than passive engagement. To maximize language acquisition, developers should improve AI-driven feedback and adaptive learning pathways, while educators should integrate AiLA into collaborative learning. Full article

Word games are of great importance in the acquisition of vocabulary and letter recognition among children, usually between the ages of 3 and 13, boosting their memory, word retention, spelling, and cognition. Despite the importance of these games, little attention has been paid to the development of word games for low-resource or highly morphologically constructed languages. This study develops an Advanced Cubic-oriented Game (ACG) model by using a character-level N-gram technique and statistics, commonly known as the matching letter game, wherein a player forms words using a given number of cubes with letters on each of its sides. The main objective of this study is to find out the optimal number of letter cubes while maintaining the overall coverage. Comprehensive experiments on 12 datasets (from low-resource and high-resource languages) incorporating morphological features were conducted to form 3–5-letter words using 7–8 cubes and a special case of forming 6–7-letter words using 8–9 cubes. Experimental evaluations show that the ACG model achieved reasonably high results in terms of average total coverage, with 89.5% for 3–5-letter words using eight cubes and 79.7% for 6–7-letter words using nine cubes over 12 datasets. The ACG model obtained over 90% coverage for Uzbek, Turkish, English, Slovenian, Spanish, French, and Malaysian when constructing 3–5-letter words using eight cubes. Full article

Artificial intelligence (AI) in education has become increasingly common in higher education, particularly in learning English as a second language (ESL). ChatGPT is a conversational AI model frequently used to support language acquisition by creating personalized, interactive learning experiences. This narrative review explored the impact of ChatGPT on ESL in higher education within the past three years. It employed a qualitative literature review using EBSCOhost, ERIC, and JSTOR databases. A total of 29 peer-reviewed articles published between 2023 and 2025 were selected for review. The Scale for the Assessment of Narrative Review Articles (SANRA) was applied as an assessment tool for quality and reliability. The results indicated that ChatGPT enhances learning outcomes in ESL by helping students improve their writing skills, grammar proficiency, and speaking fluency. Moreover, it fostered student engagement due to its personalized feedback and accessible learning resources. There were, however, concerns about plagiarism, factual errors, and dependency on AI tools. Although ChatGPT and similar models present promising opportunities and benefits in ESL education, there is a need for structured implementation and ethical guidance. Full article

Artificial Intelligence (AI) and deep learning models have revolutionized diagnosis, prognostication, and treatment planning by extracting complex patterns from medical images, enabling more accurate, personalized, and timely clinical decisions. Despite its promise, challenges such as image heterogeneity across different centers, variability in acquisition protocols and scanners, and sensitivity to artifacts hinder the reliability and clinical integration of deep learning models. Addressing these issues is critical for ensuring accurate and practical AI-powered neuroimaging applications. We reviewed and summarized the strategies for improving the robustness and generalizability of deep learning models for the segmentation and classification of neuroimages. This review follows a structured protocol, comprehensively searching Google Scholar, PubMed, and Scopus for studies on neuroimaging, task-specific applications, and model attributes. Peer-reviewed, English-language studies on brain imaging were included. The extracted data were analyzed to evaluate the implementation and effectiveness of these techniques. The study identifies key strategies to enhance deep learning in neuroimaging, including regularization, data augmentation, transfer learning, and uncertainty estimation. These approaches address major challenges such as data variability and domain shifts, improving model robustness and ensuring consistent performance across diverse clinical settings. The technical strategies summarized in this review can enhance the robustness and generalizability of deep learning models for segmentation and classification to improve their reliability for real-world clinical practice. Full article

In recent years, the topic of language teacher motivation has garnered significant attention within the realm of language teacher psychology. Researchers have delved into various aspects, including teachers’ commitments to the teaching career, teachers’ teaching motivation, and teachers’ professional development motivation. Nevertheless, the motivation of English as a Foreign Language (EFL) teachers to engage in ongoing in-service learning, particularly the pursuit of a Master of Education (Ed.M.) degree, has received comparatively less scrutiny. To bridge this gap, the present study adopted Boshier’s Education Participation Scale (EPS) and Liu’s seven-dimensional motivation framework to explore the motivation of 529 Chinese EFL teachers in their quest for an Ed.M. degree. Utilizing Exploratory Structural Equation Modeling (ESEM), the analysis revealed seven types of key motivation: cognitive interest, social responsibility, academic information acquisition, academic achievement acquisition, school context, rival demand, and significant others. An examination of differences in EFL teacher motivation in terms of gender and school type showed that male teachers perceived significantly higher levels of cognitive interest and rival demand than female teachers did. And, teachers in regular schools reported significantly higher levels of significant others than those in key schools. We propose some future directions for EFL teacher motivation research. Full article

This study explores the effectiveness of Technology-Assisted Vocabulary Learning (TAVL) using student-created video learning materials within a tertiary-level English as a Foreign Language (EFL) flipped classroom. By leveraging the flipped classroom model, which allocates classroom time for interactive activities and shifts instructional content delivery outside of class, the research investigates how student-produced videos can enhance vocabulary acquisition and retention. Conducted with 47 university students from a Translation and Translation Studies course, the study aims to fill a gap in empirical evidence regarding this innovative approach. Quantitative analysis revealed that students who created and utilized videos (Group 1) showed the highest improvement in vocabulary scores, followed by those who only used the videos (Group 2), with the control group relying on traditional teacher-led methods showing the least improvement. Qualitative feedback highlighted that video creators experienced deeper engagement and better vocabulary retention, while users appreciated the videos’ visual and auditory elements but faced challenges with vocabulary overload. The findings suggest that incorporating student-created videos into the curriculum fosters a dynamic and collaborative learning environment, offering practical implications for enhancing vocabulary instruction through technology-enhanced pedagogical practices. Future research should focus on optimizing video production processes and integrating these methods with traditional teaching for comprehensive vocabulary learning. Full article