This study aims to demonstrate the integration of character education with content and language integrated learning (CLIL) and evaluate its effects on the English language learning and character development of young learners who use EFL. Eight participants received character-integrated CLIL instruction over 16 class sessions. Employing a mixed-method approach, this study collected qualitative data primarily through observations, interviews, portfolios, self-assessments, and peerassessments, complemented by quantitative data from English tests and questionnaires. Findings revealed that character-integrated CLIL significantly enhanced learners’ oral language skills, confidence, and engagement in learning English. Additionally, it facilitated simultaneous development of language proficiency and subject knowledge, while promoting acquisition of positive character traits. The learner-centered environment supported by teacher scaffolding and authentic materials allowed learners to apply their knowledge to real-life situations. These results provide educators with a model for effectively integrating character education into language learning. They also highlight the broader potential of CLIL to foster holistic learner development.

This study explored how teachers could provide support to enhance students’ out-ofclass mobile-assisted language learning (MALL) engagement. We interviewed five Korean English teachers who used Class Card, a focal technology of this study, for their students’ self-directed vocabulary learning. Additionally, students of the interviewed teachers completed a survey on their perceptions of teacher support and MALL engagement. This study has three major findings. First, the teachers adopted either a proactive or a passive approach to promoting students’ out-of-class MALL engagement, which was influenced by their beliefs about whether teachers or students should be responsible for learning beyond the classroom. Second, all teachers provided orientation and behavioral support to enhance out-of-class MALL engagement, although the consistency and intensity in providing this support varied between proactive and passive teachers. Finally, students who perceived higher levels of teacher support reported greater out-of-class MALL engagement. We discuss the importance of classroom-based teacher support to enhance MALL engagement beyond the classroom as pedagogical implications.

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.

본 연구의 목적은 외국인 학부생의 한국어능력시험(TOPIK) 중급 취득 을 목표로 하는 한국어 집중 수업의 명암을 확인하고 이를 바탕으로 학 부 유학생 대상 한국어 교육과정 개발 및 운영의 문제점을 고찰하는 데 에 있다. 이를 위해 특정 대학에서 24-2학기에 실시한 8주 300시간의 집중 이수 한국어 수업을 관찰하고 학생과 교수자 대상의 설문조사 및 성적 자료와 문서 등의 데이터를 분석하여 교육과정 운영 사례를 기술하 였다. 분석 결과, 학생들은 집중 이수 수업이 TOPIK 준비에 긍정적인 영향을 미친다고 인식하는 반면 과도한 수업 시간과 학습 분량 및 잦은 평가에 대한 피로감을 상당히 느끼는 것으로 나타났으며 교수자 또한 집 중 이수 수업의 부정적인 측면에 더욱 주목하는 것으로 나타났다.

The results of data visualisation and analysis of relevant literature on China Knowledge Network (CNKI) with CiteSpace show that China's overall research in the field of emergency language services presents the characteristics of strong interdisciplinarity and practice orientation, and plays an important role in the new crown epidemic. However, the research on language demand in specific scenarios is slightly insufficient, and the systematic construction of talent training system still needs to be improved. Based on the results of the visualisation analysis and the current situation of small language demand and small language education in central Zhejiang, the construction of the emergency small language service talent training system in central Zhejiang requires the establishment of a government-school-enterprise synergistic training model. The government should strengthen policy support and resource integration, while enterprises and social organisations take responsibility for standard setting and technological innovation, and colleges and universities need to strengthen language proficiency and professional knowledge course design. Individual strength requires recognition by society as a whole through the qualification system. In addition, the characteristics of the new era of information technology should be incorporated to promote the concept of small language services through the integration of technologies such as the Internet, big data and artificial intelligence.

Purpose: This study aims to examine the effect of 'debate education using generative artificial intelligence (AI)' on 'debate efficacy' targeting elementary school students in the 5th and 6th grades. Through this, we aim to provide valuable information on debate classes using generative AI to field teachers and researchers in debate-related studies. This study aimed to provide students with a positive communication experience by allowing them to articulate their arguments, engage with peers, and persuade others. Additionally, it sought to serve as a foundation for fostering students' collaborative communication skills and digital language literacy. Furthermore, in alignment with the introduction of the “Media” domain in the 2022 Revised Korean Language Education Curriculum, this study aimed to offer pedagogical implications for teachers regarding debate education using generative AI. Lastly, it sought to expand the scope of Korean language education by preparing students to actively adapt to the rapidly evolving communication environment of the future society. Methods: To achieve this, a triangulation study combining quantitative and qualitative research methods was conducted. The quantitative research compared and analyzed the pre-post debate self-efficacy of the participants, while the qualitative research explored the effects of debate classes using generative AI by analyzing portfolios generated by the participants. Descriptive statistics and the Wilcoxon signed-rank test were used to analyze quantitative data. As some of the response data from the participants did not satisfy the assumption of normality, the pre-and post-test changes in debate efficacy among the participants were analyzed using a nonparametric Wilcoxon signed- rank test (p<.05). The reliability of this study was verified through Cronbach’s ⍺ value. Portfolio analysis was employed for the qualitative data analysis. Results: The “Debate Self-Efficacy” of the participants was measured pre- and post-intervention using the Wilcoxon Signed-Rank Test. The results showed a significant improvement in all subcomponents of debate self-efficacy, including Emotional Self-Efficacy, Cognitive Self-Efficacy, and Social Self-Efficacy. In particular, significant improvements were observed in the components of Emotional Self-Efficacy, namely ‘expectation,’ ‘persistence,’ and ‘emotion regulation.’ Furthermore, the analysis of portfolios composed of activity sheets developed for this study revealed that engaging in debate activities using Generative AI positively enhanced the debate self-efficacy of the participants. Conclusion: This study demonstrates through action research and empirical analysis that Korean language debate classes utilizing generative AI are effective in enhancing students' debate efficacy. This study hopes to serve as a stepping stone for fostering Inclusivity and enhancing Communication Competence among learners, thereby contributing to the strengthening of their Debate Self-Efficacy. Furthermore, it is expected that this research will contribute to the activation of Debate Education Using Generative AI in school.

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.

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.

본 연구는 한국어교육 분야의 기존 메타버스 관련 개별 연구를 혼합연 구의 방법으로 종합적으로 분석하고 수업 모형 개발을 통해 구체적인 교 육 방안을 제시하는 데 목적이 있다. 이를 위해 먼저 일차 선정된 한국 어교육 분야의 학술지 논문 및 학위논문 52편을 대상으로 통합 요소를 도출하고, 양적·질적·혼합적 방법으로 결과를 통합하였다. 먼저 양적 통 합 결과 교육 분야에서 많이 활용되는 플랫폼, 학습자 대상 및 숙달도 수준의 경향성을 확인할 수 있었다. 다음으로 혼합적 통합 결과 메타버 스 활용 수업에 대한 인식과 기대, 몰입감 및 실재감과 관련된 의견을 통합할 수 있었다. 마지막으로 질적 통합 결과 기존 연구에서 제안한 수 업 모형 사례를 분석하고 교육 방안과 방향성 내용을 통합하였다. 이를 바탕으로 본 연구에서는 메타버스 활용 모듈식 한국어 수업 모형을 제안 하였다. 이 모형은 지식 중심, 상호작용 중심, 수행 중심 모듈로 구분되 며 수업 환경이나 학습자에 따라 적용할 수 있도록 구성되어 효용성이 높다는 점에서 의의가 있다.

This study aims to collect and analyze Common European Framework of Reference for Languages (CEFR)-related research in Korean language education to identify emerging trends. It examines 28 academic articles published in Korea from 2020 to 2024, using text mining and language network analysis methods. Term Frequency (TF) and Term Frequency-Inverse Document Frequency (TF-IDF) analyses revealed that studies on curriculum design and application in Korean language education appeared with high frequency. Semantic network analysis identified key research directions, such as comparing proficiency level systems in Korean curricula, proposing “mediation” activities based on CEFR, and evaluating CEFR as an assessment tool. Latent Dirichlet Allocation (LDA) topic modeling categorized the studies into three groups: (1) research directly analyzing CEFR, (2) research applying CEFR to overseas Korean language curriculum design, and (3) research comparing existing Korean curricula with CEFR. This study is significant as the first to analyze CEFR-related research trends in Korean language education. By employing objective data analysis tools such as text mining, it enhances the reliability of findings and provides valuable insights into recent research trends.

최근 ChatGPT로 대표되는 인공지능의 급격한 발전은 인공지능 에 대한 낙관과 비관이 엇갈리는 가운데 기독교 선교가 새롭고도 실제적 인 방향을 모색해야 할 필요성을 제기했다. 이를 위해 본 연구는 행위자 -네트워크 이론을 주요 이론적 틀로 활용하여 인공지능을 단순한 도구가 아닌 인간과 상호작용하는 행위자로 인식한다. 이러한 관점에서 현재 인공지능 기술의 최전선에 있는 거대 언어 모델의 기술적 특성과 작동원리를 상세히 분석하여 인공지능이 인간과 맺는 관계에 주목한다. 이러한 이해를 토대로 인공지능과의 선교적 접점을 모색하기 위한 방안은 첫째, 인공지능을 선교 현장으로 인식하는 것, 둘째, 인간에게만 주어진 선교적 삶을 사는 것. 셋째, 인공지능을 선교사역의 협력자로 받아들이는 것, 넷째, 오픈소스 거대 언어 모델을 활용한 선교적 목적의 인공지능을 개발하는 것이다. 본 연구는 인공지능 시대의 기독교 선교 가 단순히 인공지능을 도구로 활용하는 차원을 넘어, 인공지능과의 협력적 관계를 통해 새로운 선교의 지평을 열어가야 함을 제안한다. 이는 데이비드 보쉬가 주장한 것처럼, 선교는 각 시대의 변화에 따라 새로운 패러다임으로 변화되어야 한다는 관점에 기반한다.

본 연구는 생성형 AI(GPTs)를 활용하여 한국어 학습자를 위한 인접쌍 생성 챗봇을 개발하고, GPTs가 생성한 사과 화행 인접쌍 전략을 분석하 는 데 초점을 맞추었다. GPTs의 대화 생성을 통해 사과 화행에 대한 인 접쌍의 전략 유형을 담화완성형 테스트(DCT)를 기반으로 다양한 상황별 로 도출하고, 인접쌍을 연구하였다. 연구 결과, 공적·사적 상황, 친밀도, 사회적 지위 등의 사회적 변인이 GPTs의 인접쌍 생성에 영향을 미침을 확인하였다. 특히, 공적 상황에서는 문제 해결 중심의 대안 제시 전략이 주로 사용되었으며, 사적이면서 사회적 지위 차이가 있는 상황에서는 상 대방의 체면을 회복시키는 이해 전략이 두드러졌다. 본 연구는 GPT 기반 인공지능 챗봇을 활용하여 학습자들이 실제 대화 상황에서 사용할 수 있는 전 략적 도구를 제공할 수 있는 기반을 마련하였다는 데 의의가 있다.

This study investigated the relationship between changes in language learning beliefs and English proficiency among 41 Korean university students who participated in a short-term English program. Participants’ beliefs were assessed using the Beliefs About Language Learning Inventory (BALLI), and their proficiency was measured using the Test of English for International Communication (TOEIC). Frequency analysis, descriptive statistics, paired-sample t-tests, and correlation analysis were employed to analyze the data. The study found significant improvements in both listening and reading scores, and changes in beliefs varied with proficiency gains. Students with higher proficiency gains demonstrated improved confidence and self-efficacy, and decreased instrumental motivation, whereas those with lower gains exhibited minimal changes in beliefs. Correlation analysis revealed that belief shifts, such as reduced selfconsciousness and increased integrative motivation, were positively related to proficiency gains. These findings suggest the dynamic nature of learners’ beliefs and their potential impact on language learning outcomes, highlighting the importance of addressing belief systems in English language education.

Research on teaching of Chinese characters has seen a relatively late start in international Chinese language education. Since there is little experience in teaching handwritten characters in previous Chinese as a foreign language instruction, the theory and practice of Chinese character teaching for non-native speakers have developed gradually. The latest Chinese Proficiency Grading Standards for International Chinese Language Education list the Handwritten Chinese Character List as a separate item, strengthening the guiding position of the separation of character recognition and writing principle in teaching Chinese characters. It also allows us to re-examine the issue of handwritten instruction in teaching Chinese characters to those learning Chinese as a foreign language. This paper examines issues in Chinese character teaching based on the theory of Chinese character formation, focusing on three levels of mastery: whole character, component, and stroke. The component teaching method has gained a high level of attention in recent pedagogical circles, and this method offers both advantages and disadvantages. Stroke instruction, often overlooked, is also essential for mastering handwritten Chinese characters. Stroke instruction goes beyond merely practicing basic strokes and their order and emphasizes understanding of the logic behind stroke writing.

This study aims to analyze the correlation between the digital literacy competency and the TPACK (Technological Pedagogical And Content Knowledge) of Korean language teachers. By measuring both the digital literacy competency and the TPACK of Korean language teachers, the study analyzes the correlation between these two variables. To this end, the digital literacy competency of Korean language teachers was divided into ‘technical, cognitive, and socialjustice aspects’ for investigation. The results showed that cognitive digital literacy was the highest competency, while technical digital literacy was the lowest. TPACK was further divided into TK (Technological Knowledge), TCK (Technoligical Contenet Knowledge), TPK (Technoligical Pedagogical Knowledge) and TPCK for measurement, revealing that teachers scored the lowest on TK and the highest on TPK. The analysis revealed a strong correlation between technical digital literacy and TPACK, suggesting that enhancing technical competencies should be prioritized. Furthermore, based on the finding that teaching experience in Korean language education does not influence digital literacy and TPACK, it is believed that practice-oriented teacher training focused on integrating digital tools and technologies could enhance teachers’ digital literacy competencies.

정보 기술이 교육에서 지속적으로 응용됨에 따라 ‘혼합형’ 수업 교육 모델이 대학 교의 개방 교육에 점차 융합되고 있다. 중국의 많은 대학교들은 시대의 조류를 따라 현대 정보 기술과 원격 개방 교육의 결합을 통해 온라인 핵심 과정, 온라인 학습 공 간, 온라인 교수진, 온라인 학습 서비스, 온라인 학습 평가, 온라인 교수 관리 등을 중심으로 한 ‘혼합형’ 교수 모델을 구축하고 있다. 본 연구는 중국 개방대학의 ‘응용 한국어’ 전공 교재 편찬에서 나타나는 특징을 분석하였다. 특히, 대학생을 중심으로 한 인터넷 플랫폼을 활용한 자율 학습을 강조하는 하는 교재 편찬 사고방식을 바탕으로, 온라인 교육 시대에 적합한 교재의 내용 및 디자인 방안을 논의하였다. 연구는 한국어 발음, 전문 용어, 한국어 문법 및 문법 프로젝트, 평가 방안 등 교재 편찬에 있어 중요한 요소들을 살펴보고, 각 항목 별로 제시되는 편찬 순서를 구체적으로 소 개하였다.

This study aims to explore the linguistic and cultural characteristics of Busan’s old downtown. To achieve this, the linguistic landscapes of three major traditional markets—Gukje Market, Bupyeong Kkangtong Market, and Jagalchi Market—were collected and analyzed as representative commercial spaces of this area. The key findings are as follows: First, Hangeul was the most frequently used script type across all three markets and appeared in the largest font size, reflecting a general preference for Hangeul and the Korean language regardless of business type. Second, store names consisting of four to five syllables were the most common. Third, Gukje Market displayed varied linguistic landscapes across its streets, with the street adjacent to Gwangbok-dong exhibiting the most linguistic diversity. Fourth, the temporary stall signs in Bupyeong Kkangtong Market’s night market exhibited the greatest linguistic variety, showcasing a broad range of languages. Fifth, in Jagalchi Market, where the proportion of foreign tourists is relatively high, signs were predominantly in Hangeul, but menus were provided in multiple languages to accommodate linguistic diversity among visitors. Finally, the use of regional dialects and various regional names in store signage reflected Busan’s local identity and migration-driven history.

This study analyzes the language identity of a 1.5 generation Korean woman in her 30s through a qualitative research method, focusing on her journey of seeking a stable sense of belonging, and reveals its sociocultural implications. The research participant is a woman in her 30s who moved to Germany, with her family in her early teens. She chose, maintained, and strengthened her sense of belonging between Korean and German in the following ways. First, the participant held German citizenship but did not consider herself to have citizenship rights. Second, she perceived people who spoke Korean well as attractive and wanted to connect with Korea. Third, the participant utilized her Korean language skills to position herself as marked German. This study is significant in that it explores the process by which a 1.5 generation Korean woman constructs her language identities, builds a sense of belonging, and shapes her meaning of existence, thereby contributing to a deeper understanding of the various aspects of Korean diaspora.