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Jagyeong Kim (2024). An investigation into revision pedagogy for translations students. Amid the changing landscape of the translation industry, revision competence is becoming increasingly important for translators, making it necessary to expand employability. However, revision education has yet to be incorporated into translator training and has received little attention in Korea compared to post-editing education. Against this background, this study investigated teaching methods in revision education for translation students by drawing on a literature review. Therefore, this study reviewed several aspects of revision education, including differentiation of revision competence from translation competence, the goal of revision education, shared experiences and student feedback on revision classes, and educational needs identified in survey-based studies. As a result, useful suggestions are derived in relation to theory, practice, and cooperative learning for revision education, highlighting the importance of revision pedagogy in translator education. (Ewha Womans University, Korea)

This study investigates the use of Computer-Assisted Interpreting (CAI) tools among interpreters in Korea to gain insights into their technological practices before, during, and after interpreting. To this end, the Korean Association of Translators and Interpreters (KATI) conducted a survey in February 2023, targeting 200 active conference interpreters. In the pre-interpreting phase, interpreters frequently use paper, laptop computers, and general office tools, while specialized glossary software is underused. During interpreting, tools were used differently for simultaneous and consecutive interpreting, in both online and offline settings. Pen and paper remain the most popular note-taking tools during consecutive interpreting. Subsequent to interpreting, the respondents organized glossaries, wrote transcripts, and monitored video and audio recordings using various tools. In this regard, respondents indicated the usefulness of voice recognition, specialized terminology, numerical conversions, and collaboration tools. To promote efficiency in the work environment for Korean interpreters, this study recommends developing CAI tools tailored for Korean users and improving relevant training.

This paper aims to investigate the handling of long sentences in Korean-to-English translation by human translators, large language models (LLMs), and neural machine translation (NMT). Using reliable human translations in the business reports genre as a reference, the article analyzes human, NMT, and LLM translations through three analytic phases: a quantitative comparison, a qualitative analysis, and retranslation after pre-editing. The analysis found that the sentence length in the original source texts negatively correlates with translation quality in MT outputs, and that NMT's tendency to preserve the original sentence boundary often led to omissions and incomplete translations. However, retranslation after pre-editing effectively fixed both issues. The findings in this article contribute to broadening the literature on machine translation by highlighting the need to focus on the linguistic characteristics of MT, exploring different translation tendencies of the LLM and NMT models, and enhancing the representativeness of test corpora.