http://chineseinput.net/에서 pinyin(병음)방식으로 중국어를 변환할 수 있습니다.
변환된 중국어를 복사하여 사용하시면 됩니다.
이신은 한국외국어대학교 외국어교육연구소 2020 외국어교육연구 Vol.34 No.2
With the rise of globalization in the academic community, individual L2 writers face new challenges in the course of becoming a member of their discourse community while also developing English academic writing skills. Stemming from these challenges surrounding L2 academic writing, the present study explores EFL graduate students’ construction of academic writer identity during their Ph.D. program. The clues that reveal writer's identity construction in the writing (Matsuda & Tardy, 2007; Tardy & Matsuda, 2009) and the selves framework that categorizes writer identities into different types of selves (Clark & Ivanič, 1997; Ivanič & Camps, 2001) were used to observe how L2 advanced writers' academic identities are embedded in the research papers. The results showed that L2 graduate students employed clues extensively throughout the papers by using various linguistic features and source citations appropriately with the disciplinary conventions. The patterns of students' use of clues changed as the semester passed by and reflected their construction and development of academic writer identities. The study further provided limitations and suggestions for the next steps of writer identity research.
이신은,박영호,임선영,허재희 한국정보과학회 2017 데이타베이스 연구 Vol.33 No.2
기존의 영어교육은 학습자에 대한 이해와 학습 환경을 배제한 채, 획일적이고 고정된 콘텐츠의 주입식 교육이 되어왔다. 학습자는 현재 상황과 무관한 콘텐츠를 학습할 때 체험적인 학습 대신 암기 학습을 할 수밖에 없고, 자신이 좋아하지 않는 콘텐츠들을 제공받았을 때 학습에 대한 흥미와 욕구가 급격히 감소한다. 본 논문에서는 이러한 문제를 해결하기 위해, 상황인지 기술과 추천 기술을 적용함으로써 학습자의 상황에 동적으로 대응하며 학습자가 좋아할 만한 콘텐츠를 선택적으로 제공하는 새로운 영어 학습 시스템을 제안한다. 제안한 시스템의 추천 모듈에 기존의 알고리즘들을 적용해보고, 실험을 통하여 정확도가 높은 알고리즘과 최적의 설정 값을 제시하였다. 제시한 알고리즘과 설정 값을 시스템에 적용하여 학습 체감률을 높임으로써, 학습의 효과를 향상시킬 수 있다. Existing English learning system provides inflexible and ordinary content without understanding learners and learning environment. English learners have limited opportunity to learn English sentence which is appropriate for their daily lives. Due to the context-irrelevance of English learning system, English learners must learn each sentence by rote. Moreover, they tend to lose the interest and desire for learning when they receive uninteresting content. In this paper, we propose context-aware recommender system for English language learning to solve these problems. The system is based on the two technologies; context-aware technology which provides learning contents that corresponding to the current situation of English learners and recommender technology that selectively provides user-preferable learning contents. We enumerate the imputation algorithms which are applicable to the system. Also, we investigate the most accurate algorithm and optimal setting value through the experiment. We apply those settings to the system in order to experience situational learning in consideration of the user-preference. Therefore, our proposed system enables to increase the efficiency of English learning.