• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2018.11a
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• pp.289-291
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• 2018

본 발표는 대한민국 선원의 의사소통 역량 및 글로벌 역량 강화를 위해 해수부에서 실시한 "선상 의사소통능력 강화방안" 사업을 통해 개발된 한국형 해사영어 커리큘럼의 수립 과정과 그에 따른 컨텐츠 제작 과정을 공유하고, 향후 개발 방향을 모색하기 위함이다. 따라서 본 발표를 통해 커리큘럼을 수립을 위한 선행 연구 과정(국제해사기구, 국제민간항공기구 및 국제항로표지협회 등의 국제 가이드라인 검토 및 분석, 특수목적영어 교육훈련기법 외), 교육 커리큘럼 수립(IMO 해사영어모델코스 및 표준해사통신용어 분석 및 재편성), 교육 컨텐츠 구성(실제 선사 유관 자료의 수집 및 데이터베이스 구축), 교육 훈련 교재 개발(교재, 학생용 워크북, 교사용 워크북, 음원) 등의 과정을 순차적으로 소개하고, 이에 대한 결과물을 공유하며, 향후 발전 방향을 제안하고자 한다.

• Journal of the Korean Society for Aviation and Aeronautics
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• v.28 no.4
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• pp.102-116
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• 2020

The existence of appropriate teaching materials in foreign language is very essential especially if it is related to safety. Among them, the importance of textbooks is more emphasized because there is no suitable education or curriculum for EPTA (English proficiency test of aviation). A good textbook not only presents the right direction to study but also provides an efficient way to learn. This research exploded how well textbooks for EPTA are organized and analyzed current pilots' responses whether the textbooks are suitable for preparing EPTA through the questionnaire. The conclusion drawn is that textbooks for EPTA should be designed to encourage current and pre-pilots to learn how to communicate with controllers efficiently and briefly, and also should provide proper guide lines for preparing EPTA.

• The Journal of the Convergence on Culture Technology
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• v.7 no.2
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• pp.427-436
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• 2021

The purpose of this study is to implement a machine learning language model that learns literary texts. Literary texts have an important characteristic that pairs of question-and-answer are not frequently clearly distinguished. Also, literary texts consist of pronouns, figurative expressions, soliloquies, etc. They hinder the necessity of machine learning using literary texts by making it difficult to learn algorithms. Algorithms that learn literary texts can show more human-friendly interactions than algorithms that learn general sentences. For this goal, this paper proposes three text correction tasks that must be preceded in researches using literary texts for machine learning language model: pronoun processing, dialogue pair expansion, and data amplification. Learning data for artificial intelligence should have clear meanings to facilitate machine learning and to ensure high effectiveness. The introduction of special genres of texts such as literature into natural language processing research is expected not only to expand the learning area of machine learning, but to show a new language learning method.