This study explores the phenomenon of third-person self-reference (illeism) in the Indonesian and Korean languages, focusing on gender-based patterns in everyday interactions. While prior research has largely focused on literary works and the speech of public figures, this study explores illeism among everyday speakers with gender as a key influence. Comparing the two communities enhances our understanding of possible differences in the language use of illeism. A total of 64 participants were sampled: 40 Indonesians (20 males and 20 females) and 24 Koreans (12 males and 12 females). Using both quantitative and qualitative designs, data were collected via an online questionnaire using DCT (a discourse-completion task) with five social scenarios followed by an open-ended question for each scenario to elicit the reasoning behind the use of illeism. The responses were then analyzed thematically. The results show that Indonesian females use illeism more than males, while Korean respondents show balanced usage across genders. Four factors seem to influence illeism: context of formality and naturalness, emphasis on social roles, politeness and affection, and social distance.

Despite the growing interest in the role of first language (L1) in English-medium instruction (EMI) contexts, few studies have examined how L1 instruction influences learners’ writing beliefs, motivation, and perceptions of instructional languages. This study investigates the effects of genre-based L1 writing instruction on core writing beliefs among Korean university students in relation to their motivational orientations and perceptions of Koreans’ role within a broader EMI context. A mixed-methods approach was employed, combining questionnaire data from 140 university students with eight semi-structured interviews. The results showed that following the writing instruction, students’ beliefs about key writing skills shifted, with greater emphasis placed on textual structure and logical organization. Alongside these changes, both intrinsic and extrinsic writing motivation increased by the end of the course. Notably, extrinsic motivation was strongly correlated with students’ perceptions of the instructional languages (English and Korean). Qualitative findings further highlighted the importance of meaningful L1 writing experiences and the role of English as a disciplinary language in engineering education. These findings underscore the pedagogical and policy relevance of strategically incorporating L1 instruction to enhance the effectiveness of EMI in higher education.

This study examined the 2022 Revised National Curriculum of Korea and Englishrelated policy documents through a critical discourse analytic lens, with particular focus on how language ideologies surrounding English education are discursively constructed and legitimised. The analysis demonstrates that the curriculum operates as a site of relegitimation and stabilisation in which English is discursively rearticulated as necessary, desirable, and governable under conditions of reform. Through intersecting discourses of future uncertainty, global communication, competency-based education, and inclusion, the curriculum constructs English as adaptive linguistic capital for an unpredictable future, moralises it as a marker of ethical global citizenship, and renders it measurable through standardised curricular technologies. In doing so, the policy stabilises standard language ideology while presenting itself as progressive, internationalised, and inclusive. This configuration exemplifies how reform discourse enables continuity in language ideology and linguistic stratification under the guise of innovation. These findings suggest that educational reforms frequently reproduce dominant ideologies through recontextualisation rather than transformation.

본 연구는 직원 리뷰 텍스트에 나타난 언어적 변화가 조직 평판 하락을 선행적으로 예측할 수 있는지 를 실증적으로 검증한다. ‘언어가 먼저 변한다’는 핵심 가설에 기반하여, 본 연구는 한국 상장기업을 대상 으로 한 대규모 직원 리뷰 데이터를 회사–월 단위 패널로 구성하고, 특정 시점의 언어적 및 정량적 정보만을 활용해 이후 시점의 조직 평판 하락 위험을 예측하는 조기경보 시스템(Early Warning System, EWS)을 구축하였다. 이는 조직 평판 변화가 이미 발생한 이후 이를 설명하는 기존 접근을 넘어, 변화 이전 단계에서 나타나는 미세한 언어 신호에 주목한다는 점에서 차별성을 갖는다. 분석은 자연어처리 기 반 언어 지표와 전통적 정량 지표를 결합한 예측 모형을 중심으로 수행되었다. 언어 지표는 리뷰 텍스트 에 내재된 시간적 지향성, 정서적 태도, 책임 귀인 방식과 같은 심리·인지적 특성을 포착하도록 설계되었 으며, 이를 통해 구성원의 기대 변화와 인식 전환을 조기에 감지하고자 하였다. 분석 결과, 특정 시점에서 관찰되는 언어적 패턴의 변화는 이후 시점의 조직 평판 하락 가능성과 일관되게 연결되는 것으로 나타났 다. 특히 미래에 대한 과도한 기대 표현, 체념적 태도를 반영하는 언어, 그리고 문제의 원인을 외부로 지속 적으로 귀인하는 언어는 평판 하락 위험을 조기에 포착하는 핵심 신호로 기능하였다. 이러한 예측 관계는 조직 고유의 특성을 통제한 이후에도 유지되어, 언어 기반 조기경보 모델의 일반화 가능성을 시사한다. 본 연구는 조직 진단과 평판 관리 연구에 있어, 재무 지표나 평점 변화와 같은 사후적 지표 중심의 접근을 넘어 언어적 신호를 활용한 선제적 예측의 가능성을 제시한다. 실무적으로는 HR 및 조직 담당자들이 직 원 리뷰 텍스트를 단순 만족도 측정이 아닌 위험 감지 도구로 활용할 수 있는 이론적·방법론적 기반을 제공한다.

study aims to explore the language attitudes toward the regional language and the identity as community members among Korean Language Learners(KLLs) who have migrated and reside in Jeonnam. It is important to pay attention to KLLs as community members, considering they communicate with speech community members who use the regional language. Therefore, in-depth interviews were conducted with six KLLs residing in Jeonnam to examine their language attitudes and identities. Analysis revealed that the KLLs exhibited a neutral attitude toward regional language, perceiving them as natural and commonplace. They positively accepted and used these dialects within their regional community. Furthermore, during the early stages of migration, learners experienced a lack of community belonging due to their unfamiliarity with regional language and insufficient language proficiency. However, through the process of striving to belong to the regional community, they began to unconsciously use the regional language, demonstrating that they employ the same linguistic resources as community members.

This study investigates the discursive construction of diasporic Korean identities across generations using a sociocultural narrative discourse approach. Combining interpretative phenomenological analysis with Braun and Clarke’s (2006) thematic framework, it examines interviews and public discourse materials to explore how language functions as both a symbolic resource and a medium of social practice. The findings reveal a generational shift from heritage-oriented identity maintenance to processes of identity reconstruction and negotiation. While earlier generations emphasize collective belonging through linguistic continuity and shared cultural memories, later generations reinterpret Korean as a resource for self-expression, relational positioning, and social recognition within multicultural contexts. In this sense, language does not operate as a marker of ethnic purity but as an interactive site where identities are negotiated, reconfigured, and performed. Theoretically, this study contributes to diasporic identity research by foregrounding performative subjectivity and demonstrating how language mediates identity construction across both generational and sociocultural contexts.

This study examines the language ideologies of Korean university students learning Hungarian in the context of South Korea’s “Critical Foreign Language” policy. Adopting Critical Discourse Analysis, this study analyzes how learners discursively construct and justify their language choices beyond personal interest or aptitude. The findings show that Hungarian is recurrently categorized as an “uncommon language,” most often through the everyday labels such as “special language” and “minor language,” which are not used in their institutional or linguistic senses but are re-semantized in learners’ talk. Within the special language discourse, scarcity is capitalized as an advantage and differentiation, whereas within the minor language discourse, it simultaneously indexes marginality and limited visibility. This ambivalent meaning of scarcity is further extended into competitive positioning against “others” who choose mainstream languages. Importantly, such strategic framing shapes learners’ normative orientations in learning; Hungarian is treated as a language that must be mastered to a high level and put to use, leading learners to link proficiency with future career trajectories. This study highlights how policy categories are reinterpreted and internalized in learner discourse, showing that foreign language learning functions as a socially situated practice organized by value, competition, and future-oriented imaginaries.

This study examines gender differences in language use in online shopping reviews through an analysis of five-star reviews posted on the fashion platform Musinsa. Focusing on reviews of a single unisex sneaker product, a corpus of 977 reviews by male users and 998 reviews by female users were compiled and analyzed. This study used morphological analysis and frequency-based methods to compare high-frequency vocabulary, part-of-speech distributions, abbreviated forms, loanwords, original-language expressions, sentence-ending forms (haeyo-che and hasipsio-che), and symbolic language such as emoticons. The findings show that male users tend to use verbs and nouns directly related to functions and outcomes, whereas female users more frequently employ adjectives and adverbs expressing aesthetics, emotions, and overall impressions. Although the use of hybrid abbreviations and emoticons differed significantly by gender, sentence-ending forms also showed a statistically significant association with gender. These results suggest that gender does not rigidly determine the overall stylistic structure of review discourse but influences language use by shaping evaluative focus, emotional marking, and rhetorical emphasis in positive reviews.

Through an intertextual analysis of policy documents, this study examines how language ability has been constructed as a key technology in Korean migration policy. Drawing on Foucault’s concept of governmentality and critical discourse analysis, this paper treats policy texts not as neutral administrative instruments but as discursive practices that legitimize language assessment as a condition of eligibility, integration, and citizenship. Focusing on documents related to Korean language testing, naturalization requirements, and social integration programs, this analysis highlights how recurring discourses on standardization, social order, and risk management have bee mobilized to acclimatize language evaluation. Rather than reporting the empirical outcomes of language testing, this study offers a critical reading of policy discourse, showing how language ability is framed as an objective and technical criterion, while obscuring its political and normative implications. This study contributes to the sociolinguistic and critical language policy research by illuminating how language assessment operates as a powerful mechanism for selection and governance in contemporary migration regimes.

기존 비디오 게임은 사전 정의된 스크립트와 정적인 캐릭터 관계 모델로 인해 상호작용 과 몰입감에 한계가 있다. 최근 대규모 언어 모델(LLM)이 대안으로 떠올랐으나, 생성된 서 사와 게임 내부 데이터가 단절되는 문제가 여전히 존재한다. 이에 본 연구는 Unity 엔진, LLM, 게임 서버 플랫폼을 통합하여 캐릭터 데이터가 서사를 생성하고, 그 결과가 다시 데 이터베이스에 반영되는 '순환형 동적 스토리텔링 시스템'을 제안한다. 실험 결과, 캐릭터 성 향에 따른 차별화된 서사 생성 및 관계도의 실시간 DB 동기화를 확인하였다. 본 시스템은 기존 스크립트의 경직성을 극복하고 무한히 확장 가능한 개인화된 게임 경험을 제공한다.

The application of machine learning in concrete technology has expanded rapidly, yet its reliability is often constrained by limited experimental data, heterogeneous testing conditions, and inconsistencies across published studies. This study investigates the integration of machine learning and synthetic data augmentation to predict the compressive strength of concrete incorporating biochar as a partial replacement for cement. An experimental dataset was compiled from peer-reviewed journal articles indexed in Web of Science, focusing on biochar-modified concrete mixtures. Input variables included cement content, fine and coarse aggregates, biochar dosage, water to binder ratio, superplasticizer content, and curing age, with compressive strength as the target variable. Extreme Gradient Boosting was adopted due to its strong performance on nonlinear tabular data. Model performance was evaluated using the mean absolute error (MAE), mean squared error (MSE), and coefficient of determination (R²), alongside five-fold cross-validation. Hyperparameter optimization was performed using Optuna. To address data scarcity, a synthetic dataset of 1000 samples was generated using ChatGPT. the large language model approach relied solely on natural language prompts. Only feature definitions and the target variable were provided, without exposing the original data or implementing data generation algorithms. Three modeling strategies were examined. First, model trained and tested solely on experimental data achieved a testing R² of approximately 0.91. Second, model trained on synthetic data and evaluated exclusively on experimental data showed reduced generalization, achieving a testing R² of about 0.42, indicating pronounced domain shift effects. Third, synthetic and experimental data were combined through data augmentation and jointly modeled, a testing R² of 0.93 was achieved. The result showed that the use of LLMs for augmentation improved the performance of the model.

국제적 조직 환경에서 언어는 단순한 의사소통 수단을 넘어, 개인의 심리적 경험과 경력 기회를 결정짓는 전략 적 자원으로 기능한다. 본 연구는 다국적기업(MNE) 자회사 직원의 외국어 능력이 상대적 박탈감과 문화적응 스 트레스에 어떠한 영향을 미치는지를 실증적으로 검증하였다. 이를 위해 한국에 진출한 11개국 49개 MNE 자회 사에서 근무하는 한국인 직원 456명을 대상으로 설문조사를 실시하고, 다층모형 분석을 수행하였다. 분석 결과, 외국어 능력은 상대적 박탈감을 낮추는 한편, 상대적 박탈감은 문화적응 스트레스를 증가시키는 것으로 나타났다. 또한, 외국어 능력은 문화적응 스트레스를 직접적으로 감소시키는 동시에, 상대적 박탈감을 매개로 간접적인 영 향을 미쳐 부분 매개 효과를 확인하였다. 본 연구는 외국어 능력이 단순한 의사소통 도구를 넘어 조직 내 심리사 회적 경험과 문화적응 과정에 미치는 핵심적 역할을 통합적으로 설명하며, 글로벌 조직에서 현지 직원의 역량 개 발 및 심리적 웰빙 관리 전략 수립에 유의미한 시사점을 제공한다.

본 연구는 인공지능(AI) 기반 말하기 연습이 외국어로서의 한국어 (KFL) 학습자의 말하기 불안감과 정서적 발달에 미치는 영향을 분석함으 로써, AI 도구가 학습자의 정서적 요인에 미치는 교육적 의미를 탐색하 였다. 양적·질적 혼합연구 방법을 사용하여 설문조사 결과와 심층 인터 뷰 자료를 종합적으로 분석하였다. 통계분석 결과, 전반적으로 말하기 불 안이 감소하는 경향을 보였으나, 통계적으로 유의한 차이는 한 문항에서 만 확인되었다. 그러나, 질적 분석에서는 인터뷰에 참가한 모든 학습자가 AI와의 상호작용을 통해 말하기에 대한 자신감과 편안함이 향상되었다고 보고하였으며, 이는 AI 기반 연습 환경이 학습자에게 심리적 안정감과 언어 사용의 부담 완화라는 긍정적 경험을 제공했음을 보여준다. AI 기 반 말하기 연습은 완전한 의사소통 능력의 습득을 대체하기보다는, 학습 자가 인간과의 실제 상호작용으로 나아가기 위한 초기 단계의 스캐폴드 역할을 수행하는 것으로 이해할 수 있다. 연구의 한계로는 소규모 표본, 짧은 개입 기간, 그리고 연구 결과의 일반화 가능성 제한이 있다.

This study examines the ideological dynamics surrounding South Korea’s 2019 Bilingual Special Zone policy, a short-lived initiative to promote Korean–Chinese bilingual education in selected Seoul districts. It is guided by a single research questions: What underlying ideologies can be identified in the discourses surrounding the 2019 Bilingual Special Zone policy in South Korea? Drawing on a corpus-assisted critical discourse analysis of policy documents and newspaper articles, this study employs text-mining to identify salient lexical patterns and recurrent framings and applies critical discourse analysis to interpret how these linguistic choices construct particular understandings of language, identity, and security. The findings reveal that while governmental texts frames bilingual education as an instrument of globalization and urban competitiveness media and residents’ discourses often invoked nationalist and securitization ideologies, portraying Chinese language education and Chaoxianzu communities as potential threats. Thus, the policy’s eventual withdrawal is understood as an administrative failure and the outcome of these ideological struggles. By foregrounding how public reactions are shaped by broader linguistic and geopolitical hierarchies, this study contributes to critical language policy scholarship and offers insights for designing more participatory and context-sensitive multilingual policies.

The primary purpose of this study is to critically examine ethical challenges arising from integrating AI into language education. While tools such as large language models, machine translation, automated writing feedback, and speech recognition offer gains in personalization, language development, and efficiency, their rapid adoption raises several ethical concerns. Six challenges are discussed: data privacy and security, academic integrity, overreliance on AI, algorithmic bias, and widening educational divides tied to access and digital literacy. Drawing on recent empirical findings and theoretical insights, this paper also underscores risks such as the erosion of critical thinking, challenges to academic honesty, exclusion of diverse linguistic identities, and exacerbation of inequities. To address these challenges, the study proposes a multi-faceted framework comprising robust data protection, bias-aware language practice, human-AI collaboration, process-oriented instruction, and teacher training. These measures aim to foster a responsible and ethical approach to AI use, ensuring that AI supports equitable, inclusive, and effective language learning and teaching while preserving the inherently social and humanistic nature of language education.

This study develops a generative AI-based system for automatically generating scholarly topic descriptions within the OpenAlex database and evaluates its performance. Although OpenAlex provides concise topic descriptions, they lack contextual richness and informational coverage, limiting researchers’ ability to quickly grasp the semantic relevance of each topic. To address this issue, this study generated new descriptions for a total of 4,516 topics by utilizing metadata attributes—topic_id, topic_name, description, and keywords—and compared them with the original descriptions. Multiple large language models (LLMs), including GPT, LLaMA, and Mistral, were employed, and a consistent prompt-engineering scheme was designed to ensure the reproducibility of model comparison. A standardized evaluation framework integrating quantitative and qualitative indicators was proposed. Quantitative evaluation included keyword-based Precision, Recall, and F1 scores, ROUGE-L, Specter2 embedding-based cosine similarity, and BERTScore. Qualitative evaluation was conducted using LLM-based pairwise comparison, assessing Relevance, Coverage, and Clarity, with relative rankings determined through the Elo rating system. Furthermore, the Friedman test and Wilcoxon signed-rank test were applied to verify statistical significance. Experimental results revealed distinctive strengths and weaknesses across models, providing a benchmarking foundation for improving automated content generation in scholarly databases such as OpenAlex. The proposed evaluation framework also offers a reproducible and consistent basis for assessing various generative models, contributing to both academic research and practical system development.

본 연구는 『표준 한국어』 교재에 다문화 교육 요소가 어떻게 반영되어 있는지를 분석하는 데 목적을 두었다. 분석 대상은 초등 및 중·고등용 본 문 교재, 익힘책, 교사용 지도서 등 총 12권이며, 각 단원의 주제, 학습 활동 구성, 문화·삽화·사진 등의 제시 자료를 중심으로 다문화 관련 요소 의 제시 양상을 검토하였다. 분석 기준은 조영달(2010)의 세 범주(정체 성, 문화 다양성, 사회 정의)를 1차 틀로 설정하였으며, 이를 통해 단원 별 문화 내용의 범주화와 제시 방식의 특성을 도출하였다. 분석 결과, 문 화 다양성 요소는 비교적 자주 나타난 반면, 정체성 형성이나 사회 정의 와 관련된 요소는 제한적으로 제시되었고, 외국 문화 소개는 정보 전달 수준에 머무르는 경향이 확인되었다. 이러한 결과를 바탕으로, 향후 교재 개발에서 다문화 교육의 핵심 목표를 보다 체계적으로 반영하고, 학습자 의 문화 감수성과 비판적 사고를 촉진할 수 있는 학습활동 구성이 필요 함을 제안한다.

본 연구는 고령중국어 학습자의 신체적, 인지적, 사회·환경적 및 고령자 외국어 학 습의 방면에서 학습자의 특성과 심리요인을 분석하고, 설문과 인터뷰를 통한 중국어 학습자의 학습현황을 통하여 수업설계의 기초가 되도록 하였다. 또한 수업설계의 활 용도를 검증하기 위하여 실제 수업을 진행하고 분석을 실시하였다. 다만 설문과 인 터뷰인원의 제한성으로 인해 연구의 한계성이 존재하지만 수업에서 학습자의 심리를 고려한 수업은 학습의 지속성과 학습자의 소속감을 향상시킨다는 긍정적인 결론을 도출하였다. 중국어 학습이 언어기능향상의 목적 외에도 고령학습자에게 노년기를 함께 보낼 수 있는 상호 보완적인 기능을 담당할 수 있도록 하는 것에 본 연구의 의 의를 두고자 한다.

This study examines the development of Korean language education in Sri Lanka from secondary to tertiary levels and identifies key institutional challenges. Korean has recently been introduced as a high school subject and added to the university entrance examination, yet systematic academic research remains limited in the local educational context. Using document analysis and field-based inquiry, the study investigates the expansion and implementation of Korean language programs. Data come from statistics by the National Institute of Education, a survey of 123 secondary school teachers, and interviews with university instructors. The analysis covers curricula at the secondary and upper-secondary levels as well as programs in five universities that offer Korean courses. Findings show persistent structural issues, including insufficiently qualified and understaffed teachers, curriculum inconsistencies, limited instructional materials, and a lack of specialized institutions and research infrastructure. The study proposes a teacher-qualification framework, mentoring-based training, localized textbooks, and the expansion of university-level Korean majors.

This study examines linguistic variation in Korean spoken by the first generation of Korean immigrants to the United States (1903–1924), a group that marked the beginning of Korean-American history. While some studies have explored the language of contemporary Korean Americans, limited prior research has addressed the Korean language of these early immigrants. Around 1975, second-generation Korean American Sonia Shinn Sunoo conducted a large-scale oral history project, interviewing early Korean immigrants. Among the collected recordings, more than 40 participants used Korean for their interviews. Despite their historical and linguistic value, these recordings do not appear to have been used for linguistic research. Analysis reveals that early immigrants’ Korean reflects the regional dialects of early twentieth-century Korea and extensive English lexical borrowing. Rather than showing large-scale lexical changes influenced by Japanese in Korea during the same period, their speech demonstrates a strong English influence. This study highlights the sociolinguistic and historical significance of the early Korean immigrants' language use and calls for further scholarly attention to this valuable linguistic heritage.