본 연구는 한국어를 모국어로 하는 학습자의 인도네시아어 쓰기 자료 를 분석하여 중간언어(interlanguage)에 나타나는 문법, 통사, 어휘 오류 의 유형과 원인을 규명하였다. 연구 대상은 사이버대학교 중급 수준의 학습자 67명이며, 동일 주제로 작성된 작문 과제를 기반으로 오류 분석 을 실시하였다. 오류는 문법적 오류(시제 부사, 전치사, 대명사), 통사적 오류(주어·대명사 오용, 어순, 부정문 구성), 어휘적 오류(철자, 날짜 표 현, 대소문자 표기)로 분류되었다. 오류의 주요 원인은 한국어 구조의 부 정확한 전이, 목표어 규칙의 불완전한 내면화, 음운·표기 습관 등으로 나 타났다. 특히 의미 충돌을 유발하는 시제 부사의 병치, 전치사 누락, 고 유명사의 소문자 표기 등은 중간언어 발달 특성을 반영한다. 분석 결과 는 반복적 피드백, 대조언어적 접근법, 자동화 기반 오류 진단 도구의 활 용 가능성을 시사한다. 본 연구는 온라인 외국어 교육 환경에서 중간언 어 분석이 가지는 이론적·실천적 가치에 주목하며, 향후 교수법 개선 및 학습자 맞춤형 교육 설계에 기여할 수 있다.

This paper reviews existing research on Critical Language Awareness (CLA) and argues that, despite its relevance to linguistic justice and democratic citizenship, CLA research and pedagogy remain underdeveloped in the Korean educational context. Drawing on sociolinguistics, critical discourse analysis, and other related fields, it explores potential directions for integrating CLA into language education in thematic areas: linguistic forms and functions, language as a social practice, semiotic landscapes, multilingual hierarchies, and narrative identities. Rather than presenting empirical findings, this study offers an exploratory framework intended to stimulate scholarly and pedagogical dialogue on CLA in Korea, emphasizing its role in enabling learners to critically examine dominant language ideologies, recognize sociopolitical dimensions of language use, and reflect on their linguistic identities.

The purpose of this study is to investigate the language attitude and perception of multilingual education for children of old overseas Chinese in Korea. To this end, three old overseas Chinese from different backgrounds were selected as participants in the study, and in-depth interviews were conducted according to the qualitative narrative research method. As a result of the study, the participants still maintained an affection and positive attitude toward Chinese even after living in Korea for a long time, and showed a willingness to protect the traditional Chinese culture. However, as generations changed and people gradually became familiar with Korean society, there has been a tendency to increase the use of Korean and decrease the use of Chinese in daily life. While Korean was perceived as a language that could be acquired naturally through everyday exposure without formal instruction, Chinese was not acquired as sufficiently as expected due to the limitations of the learning and use environment. Although participants recognized the necessity of English education, their actual engagement with it remained relatively limited.

This study investigates how the term burnout was framed, transformed, and made to function in Korean public discourse from 2010 to 2024. Drawing on 9,206 news articles retrieved from the BigKinds database, the research applies an integrated analytical framework combining Entman’s (1993) four framing functions with Leventhal’s Common-Sense Model (CSM) of illness representation. Five dominant frames —medicalisation, individualisation, normalisation, risk framing, and metaphorisation— were identified through quantitative content analysis and qualitative coding with MAXQDA 2024 (qualitative and mixed-methods analysis software). Results show a marked shift from a medicalised frame in Period 1 (2010-2015) to an increasingly normalised frame in Period 3 (2021-2024), indicating a recontextualisation of burnout from an individual pathological condition to a shared everyday experience. Statistical analyses, including chi-square tests, interrupted time series analysis, and keyword network mapping, reveal significant temporal changes in frame distribution, functional complexity, and co-occurrence patterns. The framing functions were found to systematically structure CSM dimensions, shaping public perceptions of identity, causation, temporality, consequences, and controllability. These findings demonstrate that the reframing of burnout reflects not only shifts in linguistic representation but also broader socio-cultural and political reconfigurations, with implications for health communication, organisational policy, and public health strategies.

This study explored how adult speakers mediate triadic interactions involving young children and generative AI (GPT), focusing on discourse strategies and meaning negotiation. Four five-year-old children and their primary caregivers, acting as adult interlocutors, participated in structured GPT-based sessions. The adults actively interpreted, reformulated, and scaffoldedﾠthe children's utterances and the GPT's responses. Through inductive transcript analysis, nine caregiver strategies were identified and categorized into three functional domains: information adjustment (e.g., summarizing, rephrasing), meaning expansion (e.g., repetition, interpretation), and discourse organization (e.g., scaffolding, framing). These strategies shaped interactional flow and enabled meaningful participation by the children. Rather than functioning as a neutral tool, GPT acted as a quasi-participant whose outputs required adult mediation to be developmentally appropriate. The findings position adult speakers as co-constructors of meaning, aligning with Vygotsky's zone of proximal development, Bruner's language acquisition support system, and Gumperz's contextualization theory. This study underscores the socially situated nature of child-AI interaction and argues that the developmental value of generative AI depends not on its autonomous functionality but on the interpretive work of responsive adults. The findings hold implications for designing AI-mediated educational discourse and enhancing language socialization in early childhood.

This study evaluates how three AI models—ChatGPT, DeepSeek, and Clova X—detect and respond to gender-biased expressions in Korean. Clova X exhibited the highest accuracy in identifying discriminatory language, followed by ChatGPT, while DeepSeek performed the poorest. While terms like “kimchi girl” and “doenjang girl” were correctly recognized, phrases such as “female doctor” and “maiden work” were often misinterpreted. ChatGPT and DeepSeek occasionally provided inaccurate definitions, raising concerns about misinformation. Interestingly, DeepSeek performed best when interpreting sexist proverbs, although the overall differences across models were minor. All three models generally succeeded in recognizing biased expressions in conversational contexts, but DeepSeek struggled with non-standard sentence formats, leading to delays or missing responses. These results reveal current limitations in generative AI’s ability to process culturally specific and nuanced language. This study emphasized the need to incorporate more diverse Korean language data and up-to-date linguistic research in AI training. As generative AI tools become more integrated into everyday communication, improving their ability to detect and respond to gender biases is crucial for fostering fair and responsible language technologies.

Written examination for driver’s license certification plays a critical role in promoting road safety by assessing the applicants' understanding of traffic laws and safe driving practices. However, concerns have emerged regarding structural biases in multiple-choice question (MCQ) formats, such as disproportionate answer placement and leading linguistic cues, which may allow test-takers to guess the correct answers without substantive legal knowledge. To address these problems, this paper proposes a prompt-driven evaluation framework that integrates structural item analysis with response simulations using a large language model (LLM). First, we conducted a quantitative analysis of 1,000 items to assess formal biases in the answer positions and option lengths. Subsequently, GPT-based simulations were performed under four distinct prompt conditions: (1) safety-oriented reasoning without access to legal knowledge, (2) safety-oriented reasoning with random choices for knowledge-based questions, (3) performance-oriented reasoning using all available knowledge, and (4) a random-guessing baseline model to simulate non-inferential choice behavior. The results revealed notable variations in item difficulty and prompt sensitivity, particularly when safety-related keywords influence answer selection, irrespective of legal accuracy. The proposed framework enables a pretest diagnosis of potential biases in the MCQ design and provides a practical tool for enhancing the fairness and validity of traffic law assessments. By improving the quality control of item banks, this approach contributes to the development of more reliable knowledge-based testing systems that better support public road safety.

본 연구는 K-POP 음률을 기반한 개사 언어치료 활동이 학령기 경계선 지능 아동 대상으로 언어발달에 미치는 영향에 대해 탐색적 연구를 진행하 였다. 이와 관련하여 K-POP 노래를 선정하고 중재 활동 목표를 설정하여 학령기 경계선 지능 아동 3명을 대상으로 주 2회 50분씩 사전 및 사후 검사 를 포함하여 총 20회기의 K-POP 음률 개사 언어치료 활동을 실시하였다. 그 결과, 중재 프로그램 이후 아동의 어휘 능력, 구문 이해 능력, 상위 언어 능력의 유의한 차이는 없으나, 아동의 수용 및 표현 어휘, 구문 이해, 상위 언어를 평가한 표준화검사의 원점수가 향상하는 경향을 보였다. 본 연구의 내용이 추후 K-POP을 활용한 언어치료 중재 프로그램 개발의 기초자료로 활용되길 기대한다.

최근 몇 년간 힙합 문화가 중국 전역에 빠르게 확산되면서, 민남어 랩은 점차 대표적인 지역 음악 표현 형식으로 자리 잡아 학계의 주목을 받고 있다. 본토 정체성과 문화적 정체성을 강화하 기 위해 점점 더 많은 래퍼들이 지역 방언을 활용한 창작을 시도하고 있으며, 그중 민남어는 복잡 한 성조 체계, 풍부한 어휘 구조, 강한 문화적 특성을 바탕으로 힙합 음악과 결합하면서 독특한 언어 미학과 표현 방식을 형성해왔다. 본 연구는 민남어 랩의 대표적 작품 여섯 곡—<少年家>, <放蕩不羈>, <保險櫃>, <少年ㄟ安啦>, <Gang電仔>, <大丈夫>—을 분석 대상으로 삼아, 텍스트 분 석, 사례 분석 및 비교 분석 방법을 통해 음운 특성, 어휘 사용, 통사 구조, 문화적 표상 등 네 가지 측면에서 민남어가 현대 공연 맥락 속에서 어떻게 언어적으로 구현되고 있는지를 체계적으로 고찰하였다. 연구 결과, 민남어 랩의 언어 표현에서 독창성은 다음 다섯 가지 측면에서 두드러지 게 나타난다. 첫째, 성조 체계가 곡의 리듬 형성에 결정적 역할을 하며, 둘째, 비음 발음이 청각 적 표현력을 강화한다. 셋째, 음운 변화가 언어의 운율감을 높이며, 넷째, 독특한 한자 표기 방식 이 더 깊은 감정 전달을 가능하게 한다. 다섯째, 생략과 도치 등의 문장 구조는 리듬적 긴장감과 감정 표현을 극대화한다. 본 연구는 민남어와 랩 음악의 결합이라는 기존 연구의 공백을 일정 부 분 보완하였을 뿐 아니라, 음악 텍스트에서 중국어 방언의 언어적 기능과 문화적 의미를 탐구하는 데 있어 언어학적 시야와 학제 간 연구 방법을 제공한다는 점에서 의의를 지닌다. 이는 중국 방언 문화의 생동감 있는 전승과 창조적 계승을 촉진하는 새로운 문화적 실천의 가능성을 제시한다.

This study examine the manner by which media characteristics are reflected in text formation by-, focusing on book advertising on Instagram. By analyzing book advertising, i.e., a type of advertising text on Instagram, from a text-linguistic perspective, this study examines the textual characteristics of Instagram advertising texts and compares them with book advertisements in other media to identify the unique media characteristics of Instagram. Book advertising on Instagram can be categorized into three types: traditional, hide, and fan page. Differences in the structural characteristics and composition of linguistic and visual symbols are observed in each type. Compared with book advertisements in print and video media, the reversal technique due to page-type image exposure, direct exposure to the advertisement target, and intuitive advertisement-content organization can be regarded as examples that reflect the characteristics of Instagram as a medium. In particular, the structure of book advertisements comprising [thumbnail > text > conclusion] reveals the characteristics of the medium the most significantly. Additionally, various aspects such as the linear organization of verbal and visual symbols and hierarchical and complementary relationships, are observed, which are regarded as the characteristics of book advertisements on Instagram.

This study examines the signs of 83 Korean restaurants operating in Berlin as of January 2025 and discusses the following from the perspective of the language landscape: First, in which characters are these signs written? Second, in what language is the term ʺKorean restaurantʺ stated? Third, in which language is the store name written? Fourth, do other design considerations exists? The result shows that those who operate Korean restaurants in Berlin tend to display signs primarily in Roman letters instead of highlighting Hangul, which is still considered an unfamiliar character to Germans to avoid creating an overly heterogeneous language landscape. But the result of more comprehensive examination shows that the Korean restaurants in Berlin tend to display their identity and characteristics as Koreans. These research results can be used as reference material to gauge the lifestyle of Korean immigrants in the present Germany, beyond a simple discussion of the language landscape.

이 글은 인문학의 학문적 자산으로서 ‘하늘의 언어와 하늘의 역사’ 자료를 환 기하고 그에 대한 자료 접근력과 관점의 다양화 모색을 펼친 서술이다. 하늘이 궁극의 존재라는 점을 잘 알지만 우리 역사 속에서 어떤 구체성으로 묘사되었 고 그리고 어떠한 언설로 표출되어 왔는지를 학술적으로 접근하는 개관적 시도 이다. 이에 천지인 삼재관과 지저세계관의 유입 문제를 통해 전통적 하늘관을 동서비교 관점에서 들여다보고, 수평과 수직의 공간 우주론을 대비하여 고대 하 늘 인식의 구조를 드러내며, 한국 고대인이 묘사한 수직 하늘 공간론이 신라 선 덕왕릉의 사천왕-제석천주 모형으로 또는 불교적 수요 9층천설의 황룡사 구층 탑으로 구현되는 면모를 짚어보았다. 그러나 조선시대 성리학 사회에서 하도·낙 서의 수비주의적 도식학이 만개하면서 하늘과의 교통이 상실되는 문화상을 읽 게 되고, 그에 무관하지 않은 궁극론 측면에서 척도의 혼란과 한달 시간학의 부 재 현상을 함께 논의하였다. 이를 통해 수천년 한자시대에서 근대 한글시대를 구가하는 우리 시대에 하늘의 언어와 역사 현장을 논의하는 하늘 논장 곧 학문 적 천론의 활성화가 필요함을 역설하고자 하였다.

This study investigates contact-induced grammatical change with specific emphasis on the prefinal imperfectives –ang and -ag in Swahili. Strategies for marking tense and aspect in Swahili and Bantu languages have been analyzed in a number of books, book chapters and articles. Despite the incontrovertible upsurge in the use of prefinal imperfectives, particularly in communicative interactions amongst the youth in urban settings, investigations into this phenomenon are scarce. Based on naturally occurring data obtained in Nairobi, Kenya and observations and interpretations, this study attempts to analyze the morphosyntactic and semantic features of prefinal imperfectives –ang and -ag in Swahili. First, background information conducive to understanding this grammatical change is provided. This includes the standardization of Swahili and its impact on present-day Swahili, strategies to mark tense and aspect in Swahili and other Bantu languages, semantic features of imperfectivity in Swahili, the prominent roles of mimesis in acquiring a second language in contact situations, the S-curve of language change and its applicability, and the disadvantages of prescriptive grammar rules. All these key concepts and topics are interrelated, and less researched topics must be included to systemically and clearly explain language change. Accordingly, this study is designed to enhance our understanding regarding one of the aspects of grammatical change from both synchronic and diachronic perspectives.

This study presents a novel methodology for analyzing disease relationships from a network perspective using Large Language Model (LLM) embeddings. We constructed a disease network based on 4,489 diseases from the International Classification of Diseases (ICD-11) using OpenAI’s text-embedding-3-small model. Network analysis revealed that diseases exhibit small-world characteristics with a high clustering coefficient (0.435) and form 16 major communities. Notably, mental health-related diseases showed high centrality in the network, and a clear inverse relationship was observed between community size and internal density. The embedding-based relationship analysis revealed meaningful patterns of disease relationships, suggesting the potential of this methodology as a novel tool for studying disease associations. Results suggest that mental health conditions play a more central role in disease relationships than previously recognized, and disease communities show distinct organizational patterns. This approach shows promise as a valuable tool for exploring large-scale disease relationships and generating new research hypotheses.

생성형 인공지능의 급속한 발전은 사회 전반에 광범위한 영향을 미치며, 일상생활을 포함한 다양한 분야 에 활용되고 있다. 본 연구에서는 인공지능 기술의 발전 동향을 대규모 언어모델(Large Language Models, LLM)을 중심으로 살펴보고 생성형 인공지능 기반 솔루션이 정치 및 공공 부문의 효율성과 서비스 최적화 에 기여하고 있음을 확인하였다. 본 연구는 미국, 싱가포르, 인도 등의 사례분석을 통해 인공지능 도구가 선거의 확장성과 시민과의 상호작용 개선에 역할 할 수 있다는 것을 주장한다. 동시에, 대규모 언어모델의 실사용 과정에서 제기되는 편향성, 허위정보 확산, 규제 공백 등의 쟁점들을 고찰할 필요가 있음을 지적한 다. 요컨대, 생성형 인공지능은 민주주의 발전과 공공서비스 증진에 대한 가능성을 제공하지만, 기술의 지속 가능하고 적실한 활용을 위해 투명성, 공정성과 책임성을 고려한 사용이 요구된다.