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
한국의학교육학회 Korean Journal of Medical Education Korean Journal of Medical Education 제31권 제1호
발행연도
2019.1
수록면
1 - 9 (9page)

이용수

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

초록· 키워드

오류제보하기
Purpose: This study investigated the relationship between the item response time (iRT) and classic item analysis indicators obtained from computer-based test (CBT) results and deduce students’ problem-solving behavior using the relationship. Methods: We retrospectively analyzed the results of the Comprehensive Basic Medical Sciences Examination conducted for 5 years by a CBT system in Dankook University College of Medicine. iRT is defined as the time spent to answer the question. The discrimination index and the difficulty level were used to analyze the items using classical test theory (CTT). The relationship of iRT and the CTT were investigated using a correlation analysis. An analysis of variance was performed to identify the difference between iRT and difficulty level. A regression analysis was conducted to examine the effect of the difficulty index and discrimination index on iRT. Results: iRT increases with increasing difficulty index, and iRT tends to decrease with increasing discrimination index. The students’ effort is increased when they solve difficult items but reduced when they are confronted with items with a high discrimination. The students’ test effort represented by iRT was properly maintained when the items have a ‘desirable’ difficulty and a ‘good’ discrimination. Conclusion: The results of our study show that an adequate degree of item difficulty and discrimination is required to increase students’ motivation. It might be inferred that with the combination of CTT and iRT, we can gain insights about the quality of the examination and test behaviors of the students, which can provide us with more powerful tools to improve them.

목차

등록된 정보가 없습니다.

참고문헌 (15)

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