SCORM 기반의 e-Learning 시스템에서 적응형 학습자 수준 판단 기법
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e-Learning system is defined as concept that includes experience of scholarship, data for teaching and education organization that can be implemented by skill or instrument of electronic shape. Now, it is difficult for most e-Learning system to share other system and contents because contents depend on specific system. Therefore, we need e-Learning standardization. Actually, SCORM have admitted as standardization of the part of e-Learning. In this thesis, the method that estimates level of learners by tracking their learning activity was proposed by SCORM based e-Learning system. We proposed a new method that combines tracking function in SCORM and Item Response Theory for estimating learners' level effectively. At the proposed method, in the case of small population, we estimated learners' level using difficulty assigned by tutor to improve problem of Item Response Theory that decreases reliability with small population, and in the case of sufficient population, we estimated learners' level using difficulty that apply Item Response Theory. At the point that applies Item Response Theory, if there is difficulty gap between assigned by tutor and estimated by Item Response Theory, we proposed adaptive method that changed it was proposed adaptive method that change difficulty assigned by tutor to difficulty estimated by Item Response Theory. For proving effects of proposed method, we collected learners' response by making out SCORM based course for judgment of level. we analyzed chang of the level of difficulty that Item Response Theory estimates as the changing of the number of learner. At the result of an experiment, in the case that the size of population is small, it is impossibility that estimates a correct level of difficulty by Item Response Theory. Later, a learner level estimation method that was proposed from this thesis will enhance effects of study by applying at the study course recommending system, and it is able to increase learner's ability more and more.