메뉴 건너뛰기
.. 내서재 .. 알림
소속 기관/학교 인증
인증하면 논문, 학술자료 등을  무료로 열람할 수 있어요.
한국대학교, 누리자동차, 시립도서관 등 나의 기관을 확인해보세요
(국내 대학 90% 이상 구독 중)
로그인 회원가입 고객센터 ENG
주제분류

추천
검색

논문 기본 정보

자료유형
학술저널
저자정보
저널정보
한국멀티미디어언어교육학회 멀티미디어 언어교육 멀티미디어 언어교육 제10권 제2호
발행연도
2007.1
수록면
70 - 97 (28page)

이용수

표지
📌
연구주제
📖
연구배경
🔬
연구방법
🏆
연구결과
AI에게 요청하기
추천
검색

초록· 키워드

오류제보하기
This study describes an "emic" view (i.e., students’ own voice) on the effectiveness of two different types of peer response (i.e., electronic and traditional modes) in returnee writing class context. In order to analyze how the participants of each mode changed their perception toward the peer response, a questionnaire for each mode was given to them at the beginning and ending stages of this research. For more detailed information on the participants' perception towards peer response, an interview was administered at the end of the research. In addition, this study investigates the actual revisions produced by returnee participants. The participants engaged in peer response sessions and exchanged their written peer feedback. The two mode classes followed the same peer response procedures, but the electronic class performed their assigned tasks on blogs. 1) the completed survey items revealed the following: the participants in both modes made progress in perception of peer response; 2) items 2 and 6 were found to be significantly different between electriric and traditional mode. Considering the results, it can beassumed that blogs encourage students to integrate the comments of peers to complete their writings and are effective tools in writing and editing. The student's interviews also indicated that each mode had its own specialties and advantages and can serve as a supplementary medium for effective peer response. After more thorough examination of the actual revision examples, it was reasonable to deduce that there was no notable difference in the quality of the results of utilizing electronic and traditional mode feedback.

목차

등록된 정보가 없습니다.

참고문헌 (1)

참고문헌 신청

함께 읽어보면 좋을 논문

논문 유사도에 따라 DBpia 가 추천하는 논문입니다. 함께 보면 좋을 연관 논문을 확인해보세요!

이 논문의 저자 정보

최근 본 자료

전체보기

댓글(0)

0