Language Context Research Articles

Learning to write Scots: a school ethnography of Scots literacy development

ABSTRACT Scots is one of three indigenous languages in Scotland, alongside English and Gaelic, spoken by 1.5 million people (National Records of Scotland 2011). Historically, Scots was excluded from formal education, but since the launch of a Scots qualification in 2014, the language is now taught in a growing number of schools. Findings from a school-university research partnership into the use of Scots show that lack of a standardised orthography, lack of exposure to written Scots, teacher attitudes, and lack of confidence in writing Scots are factors that influence Scots literacy development. This research was undertaken in 2018–2019, at Banff Academy in North-East Scotland, where Scots is spoken by approximately 50% of pupils. I used Participatory Action Research and Linguistic Ethnography (Creese 2010; Shaw, Copland, and Snell 2015) as a method and theoretical framework to explore attitudes towards Scots, set within a broader language policy framework. Data from ethnographic interviews with pupils, teachers and Scots language experts suggests that innovative pedagogical approaches can stimulate students to develop positive language attitudes and language awareness and that improving language attitudes can influence linguistic behaviours. These approaches to creative language teaching could be applicable in other regional or minority language contexts.

Юридический язык средневековых русских купчих на землю XIV–XV вв.

This article aims to examine the history of the emergence of legal terms and expressions used in the drafting of land deeds in Russian territories during the XIV–XV centuries. The content of land deeds from this period indicates that over the centuries in medieval Russia, a distinct legal language was formed through which transactions for the sale and purchase of land were formalized. Analyzing the terminology and speech patterns used in the drafting of land deeds not only allows for a deeper understanding of our ancestors’ perceptions of the sequence of actions accompanying the process of land alienation through sale and purchase but also traces the transformation of certain commonly used words from Old Russian and Old Church Slavonic into legal terms. The findings of the study suggest that the legal language of medieval Russian land deeds was shaped by the oral practice of concluding real estate transactions predominantly based on the lexicon and linguistic expressions of the Old Russian language. In conclusion, the study of the legal language of medieval Russian land deeds sheds light on the evolution of legal terminology and linguistic practices in the region. The incorporation of traditional linguistic elements into legal discourse underscores the importance of historical context in understanding legal language. Moving forward, continued research into the linguistic and legal aspects of medieval land deeds will contribute to our understanding of the legal history of Russia and its linguistic heritage.

ChineseEEG: A Chinese Linguistic Corpora EEG Dataset for Semantic Alignment and Neural Decoding

An Electroencephalography (EEG) dataset utilizing rich text stimuli can advance the understanding of how the brain encodes semantic information and contribute to semantic decoding in brain-computer interface (BCI). Addressing the scarcity of EEG datasets featuring Chinese linguistic stimuli, we present the ChineseEEG dataset, a high-density EEG dataset complemented by simultaneous eye-tracking recordings. This dataset was compiled while 10 participants silently read approximately 13 hours of Chinese text from two well-known novels. This dataset provides long-duration EEG recordings, along with pre-processed EEG sensor-level data and semantic embeddings of reading materials extracted by a pre-trained natural language processing (NLP) model. As a pilot EEG dataset derived from natural Chinese linguistic stimuli, ChineseEEG can significantly support research across neuroscience, NLP, and linguistics. It establishes a benchmark dataset for Chinese semantic decoding, aids in the development of BCIs, and facilitates the exploration of alignment between large language models and human cognitive processes. It can also aid research into the brain’s mechanisms of language processing within the context of the Chinese natural language.

Investigating Teachers’ Attitudes towards the Incorporation of Global Education within the English as a Foreign Language (EFL) Context “Ticket to English” textbook as a case study

This study examines the investigation of the integration of global education within the Moroccan English as a Foreign Language (EFL) context, focusing on the attitudes and perceptions of EFL teachers toward the inclusion of global issues and values in secondary public school textbooks. Utilizing a quantitative research methodology, the study employs surveys and questionnaires to gather insights from a carefully selected participant pool. The findings reveal a spectrum of perspectives among teachers, with some emphasizing that integrating global values enhances learners' global awareness and fosters global citizenship. In contrast, others express concerns that such inclusions may aim to assimilate learners into a homogeneous global culture, potentially suppressing local and national identities. Notably, the study underscores the perception that global education is viewed by some as ideologically driven rather than educationally motivated, prompting critical reflections on the underlying principles guiding these integrations and their alignment with broader educational goals. This article contributes valuable insights for curriculum development and pedagogical considerations in the context of global education in Morocco's EFL classrooms.

Exploring the Influence of Socio-Cultural Factors on Teacher Development in the Saudi EFL Setting

This research article explores the complex relationship between socio-cultural factors and teacher development within the English as a Foreign Language (EFL) context in Saudi Arabia. Acknowledging the pivotal role of teacher growth in enhancing language education, the study seeks to unravel the influence of socio-cultural elements on the professional development of EFL educators in the unique Saudi Arabian educational landscape. Through the lens of qualitative research, this investigation employs in-depth interviews with 10 Saudi teachers actively engaged in teaching English at the university level. The thematic analysis method was chosen for its suitability in identifying patterns and recurring themes within the qualitative data, allowing for a comprehensive exploration of the socio-cultural dynamics influencing teacher development. Themes such as societal perceptions of the teaching profession, the influence of traditional teacher-development approaches, group learning, community support, cultural sensitivity, and Islamic values emerge as crucial elements shaping the participants’ experiences. The study highlights the intricate ways in which cultural norms and societal expectations interact with teachers’ professional journeys, impacting their teaching methodologies, beliefs, and overall development. The findings offer valuable insights for educators, policymakers, and researchers seeking to enhance teacher development programs within diverse cultural and linguistic contexts.

COMPARATIVE EFFECTIVENESS OF RULE-BASED AND MACHINE LEARNING METHODS IN SENTIMENT ANALYSIS OF KAZAKH LANGUAGE TEXTS

Sentiment analysis is increasingly pivotal in natural language processing (NLP), crucial for deciphering public opinions across diverse sectors. This research conducts a comparative examination of rule-based and machine learning (ML) methods in sentiment analysis, specifically targeting the Kazakh language. Given the Kazakh language's limited exposure in computational linguistics, the study meticulously evaluates datasets from news articles, literature, and Amazon product reviews, aiming to compare the efficiency, adaptability, and overall performance of these distinct approaches. Employing a detailed set of evaluation metrics such as accuracy, precision, recall, and computational efficiency, the study provides a comprehensive analysis of the strengths and limitations of rule-based techniques versus ML models like Logistic Regression, Multinomial Naive Bayes, Decision Trees, Random Forest, and XGBoost. The findings suggest rule-based methods excel in identifying nuanced emotional expressions within literary texts, while ML models demonstrate superior adaptability and robustness, particularly effective in handling the linguistic variations found in news and reviews. Despite the strengths identified, the study also reveals significant limitations of the rule-based approach, especially in broader contexts beyond literary analysis. This highlights an imperative for future research to integrate sentiment dictionaries or domain-specific lexicons that cater to a wider array of linguistic styles, potentially enhancing sentiment analysis tools' applicability in Kazakh and similar less-studied languages. This investigation contributes significantly to the sentiment analysis discourse, offering invaluable insights for both researchers and practitioners by elucidating the complexities of applying NLP technologies across diverse linguistic landscapes, thus advancing the understanding and methodologies of sentiment analysis in the Kazakh language context.

Verbal Symbols Support Concrete but Enable Abstract Concept Formation: Evidence From Brain‐Constrained Deep Neural Networks

AbstractConcrete symbols (e.g., sun, run) can be learned in the context of objects and actions, thereby grounding their meaning in the world. However, it is controversial whether a comparable avenue to semantic learning exists for abstract symbols (e.g., democracy). When we simulated the putative brain mechanisms of conceptual/semantic grounding using brain‐constrained deep neural networks, the learning of instances of concrete concepts outside of language contexts led to robust neural circuits generating substantial and prolonged activations. In contrast, the learning of instances of abstract concepts yielded much reduced and only short‐lived activity. Crucially, when conceptual instances were learned in the context of wordforms, circuit activations became robust and long‐lasting for both concrete and abstract meanings. These results indicate that, although the neural correlates of concrete conceptual representations can be built from grounding experiences alone, abstract concept formation at the neurobiological level is enabled by and requires the correlated presence of linguistic forms.

A data-driven approach to aligning academic offerings with industry needs for business and economy in Slovenia

ABSTRACT The success of graduates and their employability hinge on a crucial alignment between the skills and competencies sought by employers and those possessed by job seekers. This study delves into the extent to which the competencies cultivated in the curricula of selected Slovenian universities align with the ever-evolving requirements of the Slovenian labour market. Employing a combination of LLaMA-2-7B-chat, a generative language model, and the multilingual Sentence Transformer, a contextual language model, we identify skill gaps and pinpoint the most in-demand competencies that align with those generated by the faculty. This data-driven approach offers a roadmap for confirming the relevance and enhancing the university curricula, thus fostering a stronger connection between education and employment as well as improving the labour market efficiency.

Neural Machine Translation for Low-Resource Languages from a Chinese-centric Perspective: A Survey

Machine translation—the automatic transformation of one natural language (source language) into another (target language) through computational means—occupies a central role in computational linguistics and stands as a cornerstone of research within the field of Natural Language Processing (NLP). In recent years, the prominence of Neural Machine Translation (NMT) has grown exponentially, offering an advanced framework for machine translation research. It is noted for its superior translation performance, especially when tackling the challenges posed by low-resource language pairs that suffer from a limited corpus of data resources. This article offers an exhaustive exploration of the historical trajectory and advancements in NMT, accompanied by an analysis of the underlying foundational concepts. It subsequently provides a concise demarcation of the unique characteristics associated with low-resource languages and presents a succinct review of pertinent translation models and their applications, specifically within the context of languages with low-resources. Moreover, this article delves deeply into machine translation techniques, highlighting approaches tailored for Chinese-centric low-resource languages. Ultimately, it anticipates upcoming research directions in the realm of low-resource language translation.

The effect of positive emotion on foreign language teacher engagement and well-being: A cross-cultural comparison

Foreign language teaching enjoyment (FLTE) has recently been introduced as a broad positive emotion experienced by foreign language (FL) teachers, despite obstacles embedded in FL teaching. However, identifying its psychological outcomes – and the cultural specificity of these outcomes – has received scant research attention across different contexts. The present cross-cultural study aims to investigate whether teachers’ FLTE can predict and influence engagement and well-being in the English as a foreign language (EFL) context of Iran and China. A series of structural equation models (SEMs) indicated that EFL teachers’ FLTE affected their work engagement and well-being in both Iranian and Chinese samples, with structural invariance tests confirming the group-level differences between Iranian and Chinese EFL teachers in the light of FLTE outcomes. The study provides insight into the positive outcomes of positive emotions in FL teaching as framed by the lens of positive psychology. In addition, a rare non-Western cross-cultural comparison contributes to the ongoing discussions in literature regarding the influence of cultural contexts on the experience and outcome manifestation of positive emotions.

The Contrastive and Referential Function of Specific Classifiers in Xiamen Southern Min—Evidence from a Cognitive Experimental Study

Southern Min is generally known for not using classifiers [CL] for expressing definiteness/indefiniteness as it is associated with the bare classifier construction [CL N]. This paper offers evidence from Xiamen Southern Min (XSM) that the use of a specific classifier vs. the general classifier é contributes to referentiality in an alternative way by supporting object identification as it is due to the semantic specificity present in specific classifiers and absent in the general classifier. In a dialogic cognitive experiment adapted from the “Hidden color-chips” task (Enfield and Bohnemeyer 2001), 18 participants had to manipulate their addressees’ attention toward various objects situated in their immediate physical space through language as well as deictic gestures. The objects were associated with different specific classifiers or with the general classifier, and they were arranged according to the factors of (a) distance from speaker, (b) visibility for speaker, and (c) uniqueness (adjacency of similar items). The results show, among other things, that there is a higher tendency to use the specific CL in the [demonstrative CL N] construction if adjacent similar objects [−unique] are too far away from the speaker for clear identification by a demonstrative or a pointing gesture. This is seen as a last-resort strategy for creating contrast. Further corroboration comes from the use of specific classifiers in later mentions after the general CL failed to achieve clear identification. These findings can be situated in the broader context of other languages with classifiers in contrastive function (Thai, Vietnamese, and Ponapean) and they show the relevance of using dialogic texts for modeling classifier selection in contrast to narrative texts. Finally, dialogic contexts may serve as bridging contexts for grammaticalization from numeral classifiers to definiteness markers.

L2 pragmatic development by early teenagers in study abroad and foreign language settings: a focus on pragmatic markers

ABSTRACT Second Language Pragmatics (L2 pragmatics) research focused on the study abroad (SA) context points out the benefits of this context for second language (L2) pragmatic development while also illustrating the non-linearity of this development, as it is shaped by different contextual factors and individual differences. Nevertheless, this research has primarily focused on adult learners, and little is known about how children and adolescents learn L2 pragmatics in SA. The present study investigates how pragmatic markers (PMs) develop in young English language learners in two learning contexts: SA and at home (AH). More particularly, the study examines differences in the frequency and type of PMs across these contexts. Thirty-four Catalan/Spanish girls aged 12, learning English at home (n = 16) and in an SA context in Ireland (n = 18), participated in the study. Participants were interviewed before and after their SA experience, and the results revealed no statistically significant differences from pre- to post-test in the AH group, with only one observed in the SA group. Only one significant difference was found between the two groups in favour of the SA group. Hence, the study sheds more light on the complexity entailed in the phenomenon of L2 pragmatic development during SA.

Promoting students as partners in a pilot study involving undergraduate students and instructors in Spanish as a foreign language courses

Through the student-as-partners (SaP) framework, this paper explores how this can enhance undergraduate Spanish as a foreign language flipped classroom courses and promote student engagement and satisfaction. Traditionally, higher education courses are designed and developed by faculty members; however, our pilot project proposed collaboration between students and instructors in the design and implementation of course activities. This paper explores the model’s effects and outcomes through four surveys administered at the end of the academic year. Each survey included key factors related to the learning experience: student enjoyment, emotional support, relatedness to peers, feedback from/for students, and content-related support. Collectively, these perspectives were used to reflect on the feedback provided, which helped us achieve our objective: the creation of teaching and learning resources to engage future cohorts and increase student retention. Although this model is presented in the foreign language context, it is transferable to any discipline.

Rhetorical strategies in Chinese and English talk show humor: a comparative analysis.

Humor is a kind of cognitive psychology activity, and it is diverse among individuals. One of the main characteristics of talk shows is to produce humorous discourse to make the audience laugh; however, rare studies have made a deeper comparative investigation on the rhetorical strategies in different language humorous utterances. Therefore, the current study adopted a mixed method of sequential explanatory design to identify the types of rhetorical strategies in the monolog verbal humor of Chinese and English talk shows, examine their similarities and differences. Two hundred monolog samples from 2016 to 2022, which consisted of 100 monologs of Chinese talk shows (CTS) and 100 monologs of English talk shows (ETS), were downloaded from the internet as language corpus. Berger's theory was adopted to identify the types of rhetorical strategies. Based on the obtained findings, this study found that both language talk show hosts use a variety type of rhetorical strategies to produce humorous discourse. The comparison of similarities and differences revealed that the most frequently used rhetorical strategies in both talk shows were almost similar (e.g., satire, exaggeration, facetiousness, and ridicule), but the percentage of usage of these various rhetorical strategies in both talk shows was slightly different. Interestingly, misunderstanding occurred 20 times in CTS but was not found in ETS. Meanwhile, simile and personification were used more often in ETS. Conclusively, this study contributes valuable insights on the use of different types of rhetorical strategies to create verbal humor in different language contexts.

Growth Mindset in Vocabulary Learning from Reading in a Foreign Language Context

Growth Mindset in Vocabulary Learning from Reading in a Foreign Language Context

Minority language happiness: The link between social inclusion, well-being, and speaking a regional language in the northern Netherlands

Belonging to groups is often based on shared features between members and is associated with higher levels of (social) well-being. One especially strong marker of one's group membership is language. In linguistics, most research about group membership and well-being focuses on migrants and refugees. However, very little research has focused on the link between speaking a regional language and well-being. This is surprising, as regional languages index a strong shared in-group identity that could lead to exclusion of those who do not speak them. As a first empirical step, this paper reports on the association between regional language use (specifically, of Frisian and Low Saxon) and social well-being. We distributed a language background questionnaire to participants of the Lifelines cohort, a multigenerational cohort study comprising data from 167,729 participants living in the north of the Netherlands. In both language contexts (Frisian in Fryslân, and Low Saxon in Groningen and Drenthe), those using the regional language half of the time or more were found to have significantly more social contacts. They also experienced higher levels of social embeddedness than those who did not know or did not frequently use the regional language. The higher degree of social embeddedness for frequent regional language users was most strongly present in rural areas. Furthermore, we found that frequent users of Frisian living in Fryslân had higher levels of social embeddedness in rural areas than frequent users of Low Saxon living in Groningen or Drenthe. No effect was found for more overt measures of social well-being such as loneliness or life satisfaction. While our results confirm an association between regional language speaking and some indices of social functioning on a large scale, they cannot uncover a causal relationship between the two. We discuss how longitudinal studies and interviews in future studies may inform us further about the relation between regional language use and social well-being.

Examining The Foundations Of Academic Books: A Longmanian Analysis Of The Oxford Eap Elementary/A2 Student Book

This article delves into the analysis of the Oxford EAP Elementary/A2 Student Book using the analytical framework developed by M.H. Longman. The focus lies on comprehending the structure, content, and learning objectives embedded within the textbook. Through the Longmanian framework, various aspects such as clarity, consistency, relevance to learning objectives, variation in material presentation, and student engagement are evaluated. The analysis aims to provide insights into how the book is designed and utilized in educational contexts, thereby enhancing its effectiveness in supporting student learning at the Elementary/A2 level in academic language contexts. Additionally, the integration of language skills and academic skills within the book is explored to assess its role in preparing students for success in English-speaking academic environments at university level.

Deteksi Cyberbullying Menggunakan BERT dan Bi-LSTM

Cyberbullying is a digital problem that is not a new phenomenon. This existed before the advent of social networks, and cyberbullying has a wide impact, including a person's mental and physiological conditions such as sadness, anxiety and depression. The main objective of this research is to develop an effective cyberbullying detection system using natural language processing techniques. The method used in this research includes the application of the BERT (Bi-Directional Encoder Representations from Transformers) and Bi-LSTM (Bi-Directional Long Short-Term Memory) models as a deep learning approach to analyze text and detect cyberbullying behavior. This approach allows the system to understand complex language contexts and capture patterns that traditional methods may find difficult to identify. Testing was carried out using a dataset that included various types of Indonesian language texts containing cyber bullying acts. The research results show that the combination of BERT and Bi-LSTM is able to provide superior detection performance with a high accuracy rate of 90% and the ability to identify variations of cyber bullying. This research makes a significant contribution to efforts to protect individuals from the negative impacts of cyber bullying through the development of a sophisticated and adaptive detection system.

Incidental Vocabulary Learning in a Postcolonial English Second Language Context

This study investigated the incidental English second-language (ESL) vocabulary development of 125 science university students over two years, as well as their productive vocabulary knowledge in relation to academic achievement. The study was conducted in Ghana, a typical postcolonial ESL country in West Africa. Results showed that productive knowledge of vocabulary at the 2000, 3000, and 5000-word levels was not mastered in academic year one. In spite of the poorly resourced educational context with limited print exposure, students’ longitudinal incidental vocabulary growth at the 3000-word level and academic word level was significant. Academic achievement was significantly predicted by word knowledge at these two levels. The study contributes to our understanding of incidental vocabulary learning in a “natural” ESL context, without language interventions. Given the predict ive factor of vocabulary knowledge on academic achievement, the integration of vocabulary instruction into the curriculum and establishm ent of required vocabulary thresholds seems warranted.

Exploring the Impact of Online Teaching Factors on International Students’ Control-Value Appraisals and Achievement Emotions in a Foreign Language Context

Drawing upon Pekrun’s (2006) control–value theory of achievement emotions, the present study explores the relations between online teaching factors (i.e., teachers’ information and communications technology (ICT) competence and provision of structure) and students’ control–value appraisals and achievement emotions (i.e., enjoyment, boredom, and anxiety) in an online foreign language learning context. Data were collected through semi-structured interviews with 12 international students and 6 teachers who were involved in a Chinese foreign language course delivered online during the coronavirus pandemic. Results from the thematic analysis showed that both students’ and teachers’ positive evaluations of teachers’ ICT competence and provision of structure were associated with students’ increased control beliefs and intrinsic value, but not necessarily with utility value. According to the participants, the two increased appraisals related to students’ greater enjoyment and reduced feelings of boredom and anxiety during the online language learning process. Findings are discussed in light of the role of online teaching factors in shaping students’ appraisals and emotional experiences in online environments, particularly during the coronavirus pandemic.