Abstract: In the present world, ChatGPT has become a game-changing technology that gives students a creative approach to gaining knowledge, increasing their learning, and raising their academic standing. This narrative literature study aimed to discuss ChatGPT's advantages and disadvantages. Notwithstanding its many benefits, ChatGPT has drawbacks, including the possibility of academic dishonesty, false information, and excessive dependence on content produced by artificial intelligence. It can give precise and well-organized answers but lacks human intuition and critical thinking, which are necessary for more in-depth learning. Students should utilize it properly instead of completely replacing conventional teaching techniques and see it as an additional tool. Teachers should help pupils distinguish between trustworthy and untrustworthy material by integrating AI literacy into the curriculum. In order to control the use of AI in education, policymakers should also create moral standards and regulations. ChatGPT can remain a potent ally in contemporary education by encouraging ethical AI use and giving students the tools they need to succeed in an increasingly digital world.

Abstract: In the era of globalization, effective communication has become a fundamental requirement for individuals and organizations operating in an interconnected world. This narrative literature review aimed to establish a relationship between communication and the globalization era. Governments and policymakers should also take an active role in bridging communication gaps by improving access to digital infrastructure and promoting regulations that safeguard online interactions. Strengthening international cooperation on cybersecurity, data protection, and media literacy programs can help mitigate the negative impacts of digital communication. These efforts will contribute to a more equitable and responsible global communication landscape. By fostering digital literacy, intercultural understanding, and regulatory support, societies can harness the full potential of global communication while minimizing its challenges. A collaborative approach involving individuals, businesses, and governments is necessary to ensure that communication remains a force for positive global development.

Abstract: Integrating Learning Management Systems (LMS) in hybrid learning has revolutionized modern education by providing flexible, accessible, and efficient learning experiences. These platforms facilitate seamless communication between students and educators, enabling the delivery of digital content, real-time assessments, and interactive activities. With the growing demand for blended learning environments, LMS has become a fundamental tool for ensuring continuity and effectiveness in education. This review focused on highlighting LMS for hybrid learning as the new trend in today’s education. Regular assessments and feedback mechanisms should be established to identify areas for improvement in LMS platforms, ensuring that they remain aligned with the evolving needs of hybrid education. By implementing these recommendations, educational institutions can optimize the use of LMS in hybrid learning, ensuring a more effective, engaging, and inclusive learning experience for all students. As technology continues to evolve, the role of LMS in supporting hybrid learning will likely expand, necessitating ongoing research and adaptation to meet the changing needs of learners and educators.

Abstract:

ChatGPT has emerged as a transformative digital tool, revolutionizing how individuals interact with artificial intelligence. Its ability to process and generate human-like text has made it an invaluable asset in various fields, including education, business, and research. As a digital hero, ChatGPT enhances productivity, provides instant information, and assists users in problem-solving. The study aimed to explore the role of ChatGPT as a digital hero by analyzing its impact across various domains, including education, professional settings, and technological literacy. By examining its benefits and challenges, this research will provide a comprehensive understanding of how ChatGPT shapes the future of digital communication and problem-solving. ChatGPT has undeniably positioned itself as a "digital hero," revolutionizing communication, learning, and productivity. However, its limitations—such as ethical concerns, bias, and accuracy issues—necessitate ongoing development and responsible usage. With proper oversight and refinement, ChatGPT can continue to be a powerful AI companion in the digital age.

Abstract: Language is a fundamental component of human society, shaping how individuals communicate, interact, and perceive the world around them. This article review aimed to determine the relationship of language to society through the lens of young children. Language development in young children is an intricate process shaped by social interactions, socioeconomic factors, digital exposure, and cultural influences. By understanding how young children navigate language within society, caregivers and educators can foster environments that promote robust linguistic and cognitive growth. Future research should further explore the long-term effects of early social and linguistic experiences on children's overall academic and social success. Educators should incorporate culturally responsive teaching strategies that recognize and respect the linguistic diversity of their students. Schools should create an inclusive environment where children feel encouraged to use their home language while also developing proficiency in the dominant language of instruction. Additionally, policymakers should invest in early childhood education programs that provide equitable access to language learning resources, particularly for children from disadvantaged backgrounds. By implementing these strategies, society can foster a generation of young learners who are confident communicators and socially aware individuals.

Abstract: Artificial intelligence (AI) tools have become an essential part of modern education, transforming traditional learning methods and enhancing student engagement. These tools facilitate personalized learning, automate administrative tasks, and provide educators with valuable insights into student performance. This article review talked about the use of AI tools in the modern world of education. The integration of Artificial Intelligence tools in education is not merely a technological advancement but a necessity in today's modern world. By embracing AI, educational institutions can enhance learning experiences, streamline operations, and prepare students for a future where digital literacy is paramount. To fully harness AI’s potential, collaboration between policymakers, educators, and technology developers is essential. Establishing guidelines for ethical AI use, investing in teacher training programs, and ensuring data security are crucial steps toward responsible AI integration in education. Without proper regulation and oversight, AI may widen educational gaps instead of bridging them.

Abstract: Corpus analysis has become an essential methodology in linguistic research, providing critical insights into language use across large datasets. The development of various corpus analysis tools has greatly facilitated the exploration of textual data, allowing researchers to conduct sophisticated analyses of linguistic patterns and structures. This report offers a comprehensive overview of the most commonly used corpus analysis tools available today, with a focus on their functionality, applications, and suitability for beginner researchers. Additionally, this report discusses how these tools can provide crucial support to novice linguists in their corpus-based investigations, relieving them of the burden of complex tasks and offering user-friendly features. By introducing these tools and outlining their core capabilities, this report serves as a guide for those new to corpus analysis, providing reassurance and guidance, while also providing a foundation for further research and advanced linguistic exploration.

Abstract: Background/Objectives: Although specific language impairment (SLI) was thought to be a language impairment, recent studies suggest that it is also associated with domain-general and nonverbal deficits such as deficits in nonverbal working memory, visual short-term memory, executive functions, etc. This study aimed to examine if applied visual strategy when copying the Rey-Osterrieth complex figure (ROCF) correlates with language abilities in children with SLI. Methods: The sample consisted of 24 children diagnosed with SLI, divided into two groups based on the used strategy when copying ROCF. We used ROCF for the assessment of perceptual organization and planning, and Peabody Picture Vocabulary Test, Boston Naming Test, Token Test, Grammatical Judgment, The Children’s Grammar, and Global Articulation Test for the language measurement. One-way ANOVA with the Brown-Forsythe Test was used for statistical analysis. Results: The results indicate that children who used a more mature strategy when copying ROCF achieved better results on tests used to assess grammar and articulation status. Conclusions: These results support the conclusion that there are neurocognitive mechanisms underlying both grammatical deficits and visuospatial deficits The obtained results suggest the importance of examining visual and visuospatial functions in children with SLI and the need for more comprehensive treatment of those children.

Abstract: In this essay, I would like to explore the intersection of linguistic profiling, sociopolitical dynamics, and the future of Spanish in the United States, to emphasize the impact of contemporary immigration policies on language use among Hispanic communities. Specifically, I aim to examine how anti-immigrant rhetoric, intensified under the 2025 Trump administration’s policies, reinforces linguistic discrimination and creates a climate of fear for Spanish speakers and the use of their language in pubic. By analyzing the historical presence of Spanish in the U.S. and the challenges posed by linguistic profiling, I would like to highlight the erosion of linguistic rights and the broader consequences for social inequality. I will also consider the roles of schools and churches as spaces for language preservation and cultural expression, which are increasingly threatened by immigration enforcement measures. In advocating for sociolinguistic justice, this essay calls for policies that recognize and protect the linguistic rights of Spanish speakers, promoting multilingualism as a strength rather than a threat.

Abstract: This article reports on the first qualitative phase of an exploratory sequential mixed method (ESMM) research design focusing on EFL pronunciation instruction in Spanish primary schools. Firstly, it presents an analysis of the National Curriculum in light of recent policy changes and adaptations across seventeen Autonomous Communities (AACC) to assess coherence and the scaffolding of contents. Secondly, based on results from Focus Groups with eight instructors from five different schools and two different AACC, teachers' perceptions on EFL pronunciation teaching in the current curriculum change are examined according to two main strands, i.e., Curriculum Design and Development and Teacher Professional Development. The results reveal asymmetries in Curriculum Contents regarding specificity and teaching methodologies, as well as some conceptual inconsistencies and dispositions that seem to be leading to overregulation, particularly in relation to increased measures of public accountability. These appear to be heightening tensions that are causing a mismatch between the intended Curriculum and the instructor-experienced curriculum. Another key observation is that, in this scenario, the positive beliefs and attitudes of primary school teachers towards EFL pronunciation are insufficient for optimal teaching. Intervention measures and innovations are suggested to improve the situation, which may be extrapolated to other similar EFL contexts.

Abstract: The classification of newspaper articles into predefined categories is a key challenge in Natural Language Processing (NLP), particularly for underexplored languages like Sindhi, which present unique linguistic complexities. This study developed a custom-curated Sindhi newspaper dataset containing 6,156 articles categorized into entertainment, sports, and technology. Four deep learning models Convolutional Neural Networks (CNNs), Recurrent Neural Networks (RNNs), Long Short-Term Memory Networks (LSTMs), and a hybrid CNN-LSTM model were trained using optimized hyperparameters and evaluated using metrics such as accuracy, precision, and recall. The dataset underwent rigorous preprocessing, including tokenization and normalization, to enhance model performance. Each model was trained using an 80-20 train-test split, and early stopping was employed to mitigate overfitting. The CNN and hybrid models achieved the highest accuracy of 96%, effectively capturing spatial and sequential patterns. LSTM closely followed with 95.85%, while the RNN lagged at 67%, highlighting its limitations with long-term dependencies. These results underline the potential of hybrid architectures and advanced sequence models for text classification tasks in low-resource languages like Sindhi. Source Code: https://github.com/rajavavek/Multiclass-Classification-of-Sindhi-Newspaper-Article.

Abstract:

Throughout human history, understanding the fundamental nature of language has been a central concern of scholars and thinkers. Although substantial progress has been made in many areas of linguistics, a precise definition of language remains elusive. This study introduces new insights into the understanding of language and precisely describes its true nature. It formulates a simple universal model of language by applying a newly discovered law–the law of a trio linking thought, language, and reality. The study also illustrates how the law and model can be applied to address important linguistic issues, including the language skills, the universality of languages, the syntactic structure of complex sentences, and the acquisition of first and second languages. The identification of a triadic relationship linking thought, language, and reality is expected to resolve the conflicts between different theories of language, often referred to as theories of meaning. This discovery is expected to elevate linguistics to the same status as the natural sciences for the first time in its history.

Abstract: A multi–dimensional mathematical theory applied to texts belonging to classical Greek Literature spanning eight centuries reveals interesting connections between them. By studying words, sentences and interpunctions of texts, the theory defines deep–language parameters and linguistic communication channels. These mathematical entities are due to writer’s unconscious design and can reveal connections between texts far beyond writers’ awareness. The analysis, based on 3,225,839 words contained in 118,952 sentences, shows that ancient Greek writers, and their readers, were not significantly different from modern writers/readers. Their sentences were processed by an extended short–term memory, modelled with two independent processing units in series, just like modern readers. In a society in which people were used to memorize information more than modern people do, the ancient writers wrote almost exactly, mathematically speaking, as modern writers do and for readers of similar characteristics. Since meaning is not considered, any text of any alphabetical language can be studied exactly with the same mathematical/statistical tools and allows comparisons, regardless of different languages and epoch of writing.

Abstract: This research investigates linguistic hybridization in Armenia, Colombia, focusing on the usage of Spanish and English in public signage, particularly business names. Utilizing a quantitative methodology, we conducted a statistical analysis employing Chi-square tests to explore the rela-tionship between symbolic language choice and variables such as location and type of establish-ment. The results demonstrated a significant association between location and language choice (Χ² = 39.353, p < .001), revealing that commercial zones with high tourist traffic exhibited a pro-nounced preference for English (46.55%), reflecting branding strategies aimed at attracting a younger, cosmopolitan audience. Conversely, traditional sectors such as health services (74.24% in Spanish) and religious institutions (80% in Spanish) predominantly utilized Spanish, empha-sizing the community's need for accessible communication. Additionally, establishments in the most commercial area highlighted the presence of hybrid names, indicating a blending of lan-guages. Our findings suggest that the hybridization of English and Spanish serves as both a re-flection and reinforcement of cultural identity and social hierarchies, emphasizing the role of linguistic capital in shaping social dynamics within the urban landscape of Armenia, Colombia.

Abstract: This article reports on the development of a big data processing platform that uses hot words（politics, economy, military, culture and society） reflecting the national image as the search object and the key time points as the time domain of data resources. The platform crawls (in real time), continuously expands and dynamically monitors a corpus of mainstream media covering China in developed countries (including the United States, Britain, Germany, France and Japan) and in developing countries (such as Brazil, India and South Africa). In this study, the principles of platform development and operation and the software and hardware operating environment were determined.

Abstract: This article considers a different application of similar methods that have been used to reject the Sapir-Whorf Hypothesis and expounds the idea as a member of the cumulative proof against the theory. Rather than to explicitly include models of generative grammars, this model instead does not violate the ideas of Optimality Theory – and therein it preserves such qualities as freedom of analysis while retaining the idea of the pertinent constraints. However, it is suggestive of momentary disagreements with the Innateness Hypothesis.

Abstract: In the field of Natural Language Processing (NLP), Large Language Models (LLMs) have shown great potential in document-level event extraction tasks, but existing methods face challenges in the design of prompts. To address this issue, we propose an optimization strategy called "Definition-driven Document-level Event Extraction (DDEE)." By adjusting the length of the prompt and enhancing the clarity of heuristics, we have significantly improved the event extraction performance of LLMs. We used data balancing techniques to solve the long-tail effect problem, enhancing the model's generalization ability for event types. At the same time, we refined the prompt to ensure it is both concise and comprehensive, adapting to the sensitivity of LLMs to the style of prompts. In addition, the introduction of structured heuristic methods and strict limiting conditions has improved the precision of event and argument role extraction. These strategies not only solve the prompt engineering problems of LLMs in document-level event extraction but also promote the development of event extraction technology, providing new research perspectives for other tasks in the NLP field.

Abstract: Cognitive interventions vary in their level of structure, encompassing standardized and unstandardized tasks, person-centered tasks. Addressing semantic knowledge/semantic memory/semantics is important, mainly because its efficiency impacts other cognitive domains. Semantic tasks are commonly included in preventive and rehabilitation programs, typically as standardized tasks with pre-defined semantic referents. In contrast, person-centered approaches have introduced personally relevant semantics, allowing for expressive language to share thoughts and experiences. Although these approaches offer benefits beyond cognitive improvement, their lack of structure may pose challenges. Our CQ program blends structured activities with personally relevant semantics, aiming to harness the advantages of both methods. Additionally, in this review we discuss future challenges and directions in the field of semantic interventions.

Abstract: AI tools provide individualized learning experiences tailored to specific language learners' requirements. Artificial intelligence-driven programs can customize lessons, exercises, and feedback by evaluating a learner's progress and determining strengths and shortcomings. This individualized method aids students in concentrating on their areas of weakness, thus improving their total language competency. This narrative literature review aims to gather relevant literature discussing AI tools as supplementary support in aiding a learner's language acquisition. Relevant studies stated that there are a lot of chances to improve learning outcomes when AI tools are used in language acquisition. Teachers who want to give their students more resources and help should consider including these tools in their lessons. To preserve the interpersonal and cultural components of language learning, it is imperative to strike a balance between the application of AI and conventional teaching techniques. AI tools are always accessible, providing assistance to learners whenever needed. This is especially helpful for individuals with unpredictable schedules or restricted access to conventional language learning materials.

Abstract: The ability to decode words accurately at an early age strongly predicts reading competence later on. Decoding-challenged children may find it difficult to understand texts, which might impede their overall academic development. Strong word decoding skills accelerate the process of learning vocabulary and grammar rules in a variety of languages. The paper aimed to collect relevant literature regarding word decoding ability in the world of the language acquisition process. Policymakers and educators will be greatly impacted by realizing how crucial word decoding is to language learning. Providing targeted interventions for struggling readers, encouraging a positive reading culture, and explicitly teaching phonological and orthographic abilities are all essential components of effective reading education. Promoting decoding proficiency also requires making sure that people have access to excellent reading materials and tools. In order to enable learners to become great readers and communicators across linguistic and cultural boundaries, educators and policymakers should prioritize phonemic awareness from an early age and use effective teaching methodologies.