Hasil untuk "Language acquisition"

Yan Xiao

Aliyeva Dilsado

This article provides an in-depth exploration of the multifaceted process of teaching English as a second language (TESL). Delving into the intricacies of language acquisition and pedagogical methodologies, the article offers insights into the challenges and innovations in TESL. With a focus on fostering effective communication skills and cultural understanding, the discussion encompasses the role of technology, cultural sensitivity, and the evolving landscape of TESL. The article concludes by emphasizing the pivotal role of TESL in promoting global communication and cultural exchange.

C. Doughty, Jessica Williams

M. Tomasello

S. Pinker

D. Slobin

These two volumes contain 16 chapters together with an editorial introduction. One of the papers in Volume II is also by Slobin and he is coauthor of the chapter on Turkish in Volume I. Volume I is oriented towards the acquisition of specific languages (namely, English, German, Hebrew, Japanese, Kaluli, Polish, Romance [with special reference to French], Samoan, Turkish, American Sign language), whereas the second focuses on theoretical issues. MacWhinney's paper in the second volume adds Hungarian to the list of languages from which the data are drawn. It should be obvious that this is an important collection since nothing of this scope and type exists. It is the culmination of some 15 years of research on language acquisition motivated largely by Slobin's notion of the operating principles which guide language acquisition. The contributors address themselves to a common set of issues and sum up the research that has been done on particular languages. At the same time, however, these volumes draw our attention to how few languages we have adequate acquisitional data for. One useful function of this collection is thus to identify lacunae in the literature and to isolate particular problems that require elucidation from a particular type of data. There are still many aspects of acquisition for which we have no data, even in relatively well-investigated languages like English and French. At the moment, cross-linguistic comparison can be realistically carried out for only a handful of constructions and/or categories, for example, passives, locative prepositions, relative clauses. And even for features that have been extensively studied, there is often little agreement across different studies. The subsystems chosen for cross-linguistic comparison are generally biased towards the typological distinctions made within Indo-European languages. Thus, not surprisingly, there have been no comparative studies of children's acquisition of switch reference systems, as far as I know. The evidence presented from languages like Japanese, Samoan, and Kaluli indicate too how biased our notions are of what children's language is like. Linguistics generally refer to the early stages of child language as telegraphic because much that would have to be present in the presumed adult equivalent has not been expressed. However, in other languages ellipsis is the norm. As Ochs (808) points out, in Samoan the relative nonexpression of major constituents is a sign of competence, since the presence of a subject or object would represent a marked strategy of expression. In English, however, telegraphic speech is indicative of incompetence. In still other cases, like Turkish, child speech is not telegraphic because children acquire most of the inflectional system by 2 years of age or earlier. Although utterances are short

R. Dekeyser

R. Gardner, W. Lambert

M. Imai, S. Kita

Domen Vreš, Tjaša Arčon, Timotej Petrič et al.

Large language models (LLMs) have become an essential tool for natural language processing and artificial intelligence in general. Current open-source models are primarily trained on English texts, resulting in poorer performance on less-resourced languages and cultures. We present a set of methodological approaches necessary for the successful adaptation of an LLM to a less-resourced language, and demonstrate them using the Slovene language. We present GaMS3-12B, a generative model for Slovene with 12 billion parameters, and demonstrate that it is the best-performing open-source model for Slovene within its parameter range. We adapted the model to the Slovene language using three-stage continual pre-training of the Gemma 3 model, followed by two-stage supervised fine-tuning (SFT). We trained the model on a combination of 140B Slovene, English, Bosnian, Serbian, and Croatian pretraining tokens, and over 200 thousand English and Slovene SFT examples. We evaluate GaMS3-12B on the Slovenian-LLM-Eval datasets, English-to-Slovene translation, and the Slovene LLM arena. We show that the described model outperforms 12B Gemma 3 across all three scenarios and performs comparably to much larger commercial GPT-4o in the Slovene LLM arena, achieving a win rate of over 60 %.

Marit Westergaard, N. Mitrofanova, Roksolana Mykhaylyk et al.

Ben Ambridge, E. Kidd, C. Rowland et al.

ABSTRACT This review article presents evidence for the claim that frequency effects are pervasive in children's first language acquisition, and hence constitute a phenomenon that any successful account must explain. The article is organized around four key domains of research: children's acquisition of single words, inflectional morphology, simple syntactic constructions, and more advanced constructions. In presenting this evidence, we develop five theses. (i) There exist different types of frequency effect, from effects at the level of concrete lexical strings to effects at the level of abstract cues to thematic-role assignment, as well as effects of both token and type, and absolute and relative, frequency. High-frequency forms are (ii) early acquired and (iii) prevent errors in contexts where they are the target, but also (iv) cause errors in contexts in which a competing lower-frequency form is the target. (v) Frequency effects interact with other factors (e.g. serial position, utterance length), and the patterning of these interactions is generally informative with regard to the nature of the learning mechanism. We conclude by arguing that any successful account of language acquisition, from whatever theoretical standpoint, must be frequency sensitive to the extent that it can explain the effects documented in this review, and outline some types of account that do and do not meet this criterion.

S. Gass, Alison Mackey

Rubia Truppel, Anderson D’Oliveira, Laura Canale et al.

This review investigates and analyzes the state of the art on scientific evidence related to educational interventions to improve air quality indoors and outdoors through a mapping review. The review followed proposed guidelines for mapping reviews in environmental sciences and the steps described in the Template for a Mapping Study Protocol. The search was conducted in PubMed, Web of Science, Embase, Cinahl, and Google Scholar with no language restrictions, and was completed in January 2025. Three filters were applied: search, selection with inclusion and exclusion criteria (PECOS strategy), and data extraction. Two independent reviewers assessed article eligibility, and disagreements were resolved by a third researcher. Twenty-four studies that met the eligibility criteria were included. Five research questions were answered. Studies published between 1977 and 2024 were included, totaling 7289 participants aged 12 to 85. The geographic distribution was concentrated in China (five studies) and the United States (four studies), followed by South Korea, India, Australia, and other countries, with fewer publications. The methodological predominance was experimental studies; observational studies were also analyzed, although less frequently. The period with the greatest increase in the number of publications was between 2020 and 2024. The educational methods most commonly used in the studies were lectures and the delivery of information leaflets. Particulate matter with diameters of 2.5 μm and 10 μm (PM_2.5 and PM₁₀) were the most widely investigated pollutants in the studies. From our analyses, it was observed that the educational interventions to improve air quality, adopted in the selected studies, resulted in the acquisition of knowledge about the environmental effects and the importance of individual actions. The changes in behavior included the adoption of more sustainable practices and an improvement in air quality in the environment, with a significant reduction in pollutant emissions. We conclude that interventions through environmental education demonstrate great potential to improve air quality. Based on the mapped evidence, governments and global policymakers can use this information to develop new strategies or improve existing ones to reduce air pollution in affected environments and regions.

I Made Agus Wirawan, Ketut Paramarta

One of the main goals of today's technology is to create a connected environment between humans and technological devices to perform daily physical activities. However, users with speech disorders cannot use this application. Loss of verbal communication can be caused by injuries and neurodegenerative diseases that affect motor production, speech articulation, and language comprehension. To overcome this problem, Brain-Computer Interfaces (BCI) use EEG signals as assistive technology to provide a new communication channel for individuals who cannot communicate due to loss of motor control. Of the several BCI studies that use EEG signals, no studies have studied Balinese characters. As a first step, this study examines the acquisition of EEG signal data for Balinese character recognition. There are several stages in obtaining EEG signal data for Balinese character spelling imagination in this study: preparation of research documents, preparation of stimulus media, submission of ethical permits, determination of participants, recording process, data presentation, and publication of datasets. The result datasets from this study are in the form of raw data, and data was analyzed for 18 Balinese and 6 vowel characters, both spelling and imagined.

Józef Jarosz

The content of the review is a discussion of the anthology „Zagadnienia lingwistyczne w dydaktyce szkolnej i uniwersyteckiej” edited by Tomasz Kurdyła and Beata Ziajka. It begins with a general description of the objectives, theoretical foundations and methodological solutions of Polish paedolinguistics, using selected publications as examples. This field of research, established on the borderline between linguistics and didactics, already has a tradition in the scientific literature and its scientific output includes not only empirical analyses but also theoretical publications describing the tasks and methodological foundations. The anthology is made up of eleven academic essays whose problems can be located in the fields of paedolinguistics, educational linguistics and language didactics. Although the contributions are characterized by different research interests and methodological diversity, the focus on linguistic problems in a didactic context gives all of them a common thematic framework. The contributions address the acquisition of linguistic competences both in school education (in the areas of word formation, onomastics, grammatical terminology and pupils with language disorders) and at university level (word formation, text type analysis). Four essays are dedicated to selected aspects of communication: the categories of sender and receiver, non-verbal communication, barriers and obstacles in communication and successful communication. One article analyses the text-linguistic competence of teachers. Finally, the thesis formulated in the article topic is substantiated and analysed in more detail. The analysis of linguistic components in curricula at all levels of education is necessary due to changing social and civilisational circumstances and can be useful for two target groups. Learners find consistent terminology and desired progress in textbooks, students are provided with the latest theories that can be applied in their theses. Teachers benefit from the results of the research by fulfilling the postulates and thus optimizing the teaching and learning process through innovations.

Qihao Yang, Xuelin Wang, Jiale Chen et al.

Language acquisition is vital to revealing the nature of human language intelligence and has recently emerged as a promising perspective for improving the interpretability of large language models (LLMs). However, it is ethically and practically infeasible to conduct experiments that require controlling human learners' language inputs. This poses challenges for the verifiability and scalability of language acquisition modeling, particularly in Chinese second language acquisition (SLA). While LLMs provide a controllable and reproducible alternative, a systematic benchmark to support phase-wise modeling and assessment is still lacking. In this paper, we present HSKBenchmark, the first benchmark for staged modeling and writing assessment of LLMs in Chinese SLA. It covers HSK levels 3 to 6 and includes authentic textbooks with 6.76 million tokens, 16K synthetic instruction samples, 30 test topics, and a linguistically grounded evaluation system. To simulate human learning trajectories, we introduce a curriculum-tuning framework that trains models from beginner to advanced levels. An evaluation system is created to examine level-based grammar coverage, writing errors, lexical and syntactic complexity, and holistic scoring. We also build HSKAgent, fine-tuned on 10K learner compositions. Extensive experimental results demonstrate that HSKBenchmark not only models Chinese SLA effectively, but also serves as a reliable benchmark for dynamic writing assessment in LLMs. Our fine-tuned LLMs have writing performance on par with advanced human learners and exhibit human-like acquisition characteristics. The HSKBenchmark, HSKAgent, and checkpoints serve as foundational tools and resources, with the potential to pave the way for future research on language acquisition modeling and LLMs interpretability. Code and data are publicly available at: https://github.com/CharlesYang030/HSKB.

Jeffrey S. Bowers, Jeff Mitchell

According to Futrell and Mahowald [arXiv:2501.17047], both infants and language models (LMs) find attested languages easier to learn than impossible languages that have unnatural structures. We review the literature and show that LMs often learn attested and many impossible languages equally well. Difficult to learn impossible languages are simply more complex (or random). LMs are missing human inductive biases that support language acquisition.

Yurie Koga, Shunsuke Kando, Yusuke Miyao

This paper investigates whether the Critical Period (CP) effects in human language acquisition are observed in self-supervised speech models (S3Ms). CP effects refer to greater difficulty in acquiring a second language (L2) with delayed L2 exposure onset, and greater retention of their first language (L1) with delayed L1 exposure offset. While previous work has studied these effects using textual language models, their presence in speech models remains underexplored despite the central role of spoken language in human language acquisition. We train S3Ms with varying L2 training onsets and L1 training offsets on child-directed speech and evaluate their phone discrimination performance. We find that S3Ms do not exhibit clear evidence of either CP effects in terms of phonological acquisition. Notably, models with delayed L2 exposure onset tend to perform better on L2 and delayed L1 exposure offset leads to L1 forgetting.

Glenn Stockwell

This introduction to the special issue examines the integration of ChatGPT and similar generative AI technologies in language teaching and learning. It examines the rapid evolution of AI tools since 2022, with particular focus on their applications in educational settings and the mixed responses they have generated among educators and learners. While some educators embrace these tools for their potential to automate and enhance instructional tasks, others express concern over issues such as academic integrity, accuracy, and potential job displacement. This special issue explores various perspectives on the use of ChatGPT, including its benefits in providing non-judgmental feedback, aiding material creation, and enhancing language practice, alongside challenges like ethical use, student over-reliance, and the evolving digital literacy demands for both teachers and students. The collection of articles in this special issue seeks to balance the hype with practical insights and offers a framework for understanding the nuanced impacts of generative AI on second language education.