Journal of the Korea Society of Computer and Information (한국컴퓨터정보학회논문지)

Korean Society of Computer Information (한국컴퓨터정보학회)
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An Ontology-Based Method for Calculating the Difficulty of a Learning Content

온톨로지 기반 학습 콘텐츠의 난이도 계산 방법

  • Park, Jae-Wook (Dept. of Computer Science and Engineering, Dongguk University-Seoul) ;
  • Park, Mee-Hwa (Dept. of Computer Science and Engineering, Dongguk University-Seoul) ;
  • Lee, Yong-Kyu (Dept. of Computer Science and Engineering, Dongguk University-Seoul)
  • 박재욱 (동국대학교 컴퓨터공학과-서울) ;
  • 박미화 (동국대학교 컴퓨터공학과-서울) ;
  • 이용규 (동국대학교 컴퓨터공학과-서울)
  • Received : 2010.12.24
  • Accepted : 2011.01.08
  • Published : 2011.02.28
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Abstract

Much research has been conducted on the e-learning systems for recommending a learning content to a student based on the difficulty of it. The difficulty is one of the most important factors for selecting a learning content. In the existing learning content recommendation systems, the difficulty of a learning content is determined by the creator. Therefore, it is not easy to apply a standard rule to the difficulty as it is determined by a subjective method. In this paper, we propose an ontology-based method for determining the difficulty of a learning content in order to provide an objective measurement. Previously, ontologies and knowledge maps have been used to recommend a learning content. However, their methods have the same problem because the difficulty is also determined by the creator. In this research, we use an ontology representing the IS-A relationships between words. The difficulty of a learning content is the sum of the weighted path lengths of the words in the learning content. By using this kind of difficulty, we can provide an objective measurement and recommend the proper learning content most suitable for the student's current level.

이러닝 시스템에서 난이도를 이용한 학습추천 시스템 설계에 관한 연구가 활발히 진행 중이다. 난이도는 학습자의 수준에 맞는 후행학습을 추천하는데 매우 중요한 요소임에도 불구하고 현행 난이도 기반 학습 추천시스템은 각 학습 콘텐츠의 제작자가 주관적으로 정한 난이도를 적용함으로써 정확한 후행 학습 콘텐츠를 추천하기가 어렵다. 본 논문에서는 객관적인 난이도 지표를 제공하기 위하여 온톨로지에 기반한 새로운 학습콘텐츠 난이도 계산 방법을 제안한다. 기존 온톨로지나 지식맵을 이용한 난이도 계산 방법들은 선행학습과 후행학습 또는 주제간의 선후 관계를 표현하고 이를 이용하여 난이도를 계산하였으나, 이 방법들도 콘텐츠 작성자의 주관적인 판단에 의해 후행학습이 결정된다는 문제점이있다. 본 논문에서는 이를 해결하기 위하여 콘텐츠를 구성하는 단어들의 상하위 관계 및 심화도를 나타내는 온톨로지를 이용하여 단어들 간 온토로지의 경로상의 거리로 난이도를 계산한다. 이를 통하여 학습자에게 보다 객관적인 난이도 정보를 제공하고 학습자 수준에 가장 적합한 후행학습 콘텐츠를 추천할 수 있다.

Keywords

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