• Title/Summary/Keyword: 자동 문제 출제 시스템

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e-Learning System Design and Implementation for Small Sized Cyber Lecturing (소형 사이버강좌를 위한 e-Learning시스템 설계 및 구현 사례)

  • Seo, Chang-Gab;Park, Sung-Kyou
    • Information Systems Review
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    • v.6 no.2
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    • pp.161-179
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    • 2004
  • The purpose of this study is to suggest practical experience to develop small sized e-Learning system. The system is designed to help lecturers can arrange interface, organize contents, submit examinations and assess learner's score with no professional computing skills. The system has three advantages. First, it reduced implementation period through the use of GUI. Second, it is ordered to be personalized to construct format of the whole interface. Third, it has operational convenience which can be implemented on PC based system. These personalized features are enabling Learning on Demand. Also, there is comparatively low cost and high effectiveness on e-Learning implementation which facilitating quick adoption of e-Learning in its lectures.

An Intelligent Marking System based on Semantic Kernel and Korean WordNet (의미커널과 한글 워드넷에 기반한 지능형 채점 시스템)

  • Cho Woojin;Oh Jungseok;Lee Jaeyoung;Kim Yu-Seop
    • The KIPS Transactions:PartA
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    • v.12A no.6 s.96
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    • pp.539-546
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    • 2005
  • Recently, as the number of Internet users are growing explosively, e-learning has been applied spread, as well as remote evaluation of intellectual capacity However, only the multiple choice and/or the objective tests have been applied to the e-learning, because of difficulty of natural language processing. For the intelligent marking of short-essay typed answer papers with rapidness and fairness, this work utilize heterogenous linguistic knowledges. Firstly, we construct the semantic kernel from un tagged corpus. Then the answer papers of students and instructors are transformed into the vector form. Finally, we evaluate the similarity between the papers by using the semantic kernel and decide whether the answer paper is correct or not, based on the similarity values. For the construction of the semantic kernel, we used latent semantic analysis based on the vector space model. Further we try to reduce the problem of information shortage, by integrating Korean Word Net. For the construction of the semantic kernel we collected 38,727 newspaper articles and extracted 75,175 indexed terms. In the experiment, about 0.894 correlation coefficient value, between the marking results from this system and the human instructors, was acquired.