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This study examines the translation patterns and strategies used by ChatGPT when translating English passive constructions into Korean. English frequently employs passive structures as an important grammatical and discourse device, whereas Korean systematically prioritizes active or topic-oriented expressions. Because of this structural difference, translating English passives into Korean often requires strategic restructuring. This study analyzes how ChatGPT translates various types of English passive constructions, including agentive, agentless, progressive, dative and other complex passive forms. The findings show that ChatGPT does not simply preserve the passive structure of the source text. Instead, it adopts diverse strategies such as passive maintenance, active conversion, impersonalization, and syntactic restructuring. These strategies are selected according to contextual and linguistic factors in Korean. The results suggest that ChatGPT tends to prioritize functional equivalence and naturalness in Korean rather than strict structural correspondence with the English source text.

This study investigates the translation of culturally loaded color terms in Dream of Red Mansions, focusing on the Korean complete translation by Choi Yong-cheol and Ko Min-hee. Expressions such as yuebai (moon-white) and qiuxiang (autumn fragrance) exemplify “culture-specific items” that extend beyond chromatic reference to embody cultural imagery, social hierarchy, and aesthetic philosophy. Through systematic textual analysis and comparative case studies, the research examines how the translators negotiated the challenges posed by these terms. Findings reveal that the translation does not rely on a single, rigid principle but instead deploys a dynamic spectrum of aspects oriented toward functional equivalence and hierarchical treatment of cultural imagery. Four primary aspects-image substitution, semantic attenuation, explanatory full translation, and domestically adapted simplification-are flexibly applied and cross-combined. These approaches collectively enhance narrative fluency and reader accessibility, while compensatory techniques in key aesthetic passages partially reproduce the artistic essence of the original. Nevertheless, simplification and cultural amalgamation inevitably result in losses in metaphorical depth, precision of characterization, and the integrity of the aesthetic system. The study concludes that the translation of culture-specific items in literary texts constitutes a dynamic negotiation between cultural fidelity and reader reception, as well as between preservation of literariness and narrative efficiency. By offering micro-level evidence from East Asian interlingual practice, this research contributes empirical perspectives and methodological references to the study of Chinese classical literature in translation and the broader discourse on culturally loaded vocabulary.

This study explores the development, thematic patterns, and research gaps in AI-related interpreting studies in Korea. Drawing on content analysis, it examines 27 journal articles published since 2022, when AI-related discussions began to emerge visibly in Korean interpreting studies. The articles were classified into six thematic categories according to their primary research focus. The findings show a sharp increase in publications in 2025, suggesting that AI has moved from a peripheral technological issue to a significant research agenda in the field. The largest share of studies focused on AI-based interpreter education and instructional design, followed by research on interpreters’ professionalism, roles, and ethics in the AI era. Overall, Korean scholarship has tended to treat AI less as a direct substitute for human interpreters than as a tool for supporting interpreter education and interpreting performance. This tendency indicates that Korean interpreting studies have engaged with AI primarily through pedagogical adaptation, performance support, and professional redefinition, rather than through direct testing of replacement potential. The study concludes by identifying current limitations and proposing directions for future research, including empirical validation of educational applications, more refined quality comparisons, and closer examination of service acceptance and institutional implementation.

This study explores the complex sensibilities in the poetry of T. S. Eliot, focusing on The Waste Land and Four Quartets, to examine how modernist techniques represent the fragmentation of modern consciousness. Adopting a qualitative textual analysis grounded in close reading and interpretive literary analysis, the study investigates how Eliot’s poetic strategies function within a modernist framework. Eliot’s work reflects the breakdown of unified sensibility and reveals an ongoing effort to reconcile intellectual thought with emotional experience. Through rapid associative shifts, ambiguity, paradox, and wit, he constructs a poetic language that embodies the discontinuity of modern life. His poetry is further characterized by dense symbolism, thematic compression, and extensive intertextual references, enabling the juxtaposition of diverse temporal, cultural, and spiritual dimensions within a single framework. While portraying fragmentation, Eliot simultaneously seeks coherence by integrating disparate elements. His concept of “pure” and “impure” poetry highlights the coexistence of philosophical depth and everyday experience. Moreover, his use of ambiguity and structural complexity invites active reader participation, encouraging multiple interpretations rather than fixed meanings. Pedagogically, Eliot’s poetry is valuable in EFL contexts, as it fosters close reading, critical thinking, and interpretive skills. By engaging with his texts, learners can better understand how poetic language conveys complex human experiences in modern literature.

Given that communicative competence plays a critical role in multinational military operations, effective instructional approaches that promote practical language use have become increasingly important in military English education. This study investigates how speaking activities implemented in an EFL military English instruction by analyzing various functions of comprehensible output and how such output processes emerge during classroom interaction. The study draws on Littlewood’s communicative continuum as a pedagogical framework and examines classroom interaction from the perspective of Swain’s Comprehensible Output Hypothesis. For this study fourteen military English learners participated in three-month intensive English course engaging in speaking activities and completed perception questionnaires. A mixed-method approach was employed using triangulated data from classroom observation logs, instructor reflective journals, and learner perception questionnaires. The findings indicate that structured speaking activities tended to promote grammatical accuracy, while authentic communicative activities encouraged fluency and meaning negotiation. Through repeated task engagement, learners noticed linguistic gaps, tested alternative forms, and gradually refined their spoken output. Pedagogically, these findings highlight the value of communicative speaking activities in fostering speaking development through multiple comprehensible output functions.

With the rapid development of generative AI, ChatGPT has been increasingly applied to translation tasks. However, translating classical poetry remains challenging because it demands both semantic accuracy and stylistic reproduction. This study investigates ChatGPT’s performance in translating elegiac poems in Romance of the Three Kingdoms. Using human translation as a reference, it compares outputs generated under literal and poetry-oriented prompts. A multidimensional framework combining automated and human evaluation is adopted. Cosine similarity, BERTScore, and chrF2 are used to assess semantic and formal alignment, while human evaluators rate fidelity, metaphorical expression, style, and overall acceptability. The findings indicate that poetry-oriented prompts improve the translations to a certain extent, but still fail to reproduce the subtle expressiveness achieved by human translation. The study proposes a practical framework for evaluating small-sample classical poetry translation and offers empirical insight into ChatGPT’s applicability to this task.