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A Construction Method for Personalized e-Learning System Using Dynamic Estimations of Item Parameters and Examinees` Abilities
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 Title & Authors
A Construction Method for Personalized e-Learning System Using Dynamic Estimations of Item Parameters and Examinees` Abilities
Oh, Yong-Sun;
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This paper presents a novel method to construct a personalized e-Learning system based on dynamic estimations of item parameters and learners` abilities, where the learning content objects are of the same intrinsic quality or homogeneously distributed and the estimations are carried out using IRT(Item Response Theory). The system dynamically connects the test and the corresponding learning procedures. Test results are directly applied to estimate examinee`s ability and are used to modify the item parameters and the difficulties of learning content objects during the learning procedure is being operated. We define the learning unit `Node` as an amount of learning objects operated so that new parameters can be re-estimated. There are various content objects in a Node and the parameters estimated at the end of current Node are directly applied to the next Node. We offer the most appropriate learning Node for a person`s ability throughout the estimation processes of IRT. As a result, this scheme improves learning efficiency in web-base e-Learning environments offering the most appropriate learning objects and items to the individual students according to their estimated abilities. This scheme can be applied to any e-Learning subject having homogeneous learning objects and unidimensional test items. In order to construct the system, we present an operation scenario using the proposed system architecture with the essential databases and agents.
Personalized e-Leaning;dynamic estimation;IRT;Node;item parameter;ability parameter;
 Cited by
A Structure of Personalized e-Learning System Using On/Off-line Mixed Estimations Based on Multiple-Choice Items, International Journal of Contents, 2009, 5, 1, 51  crossref(new windwow)
M. Balabanovic and Y. Shoham, “Fab: Content-based, Collaborative Recommendation,” Commun. Of the ACM, Vol. 40, No. 3, 1997, pp. 66-72. crossref(new window)

E. Leung, Q. Li, and Y. T. Zhuang, “Media-Based Presentation with Personalization in a Web-Based eLearning System,” Lecture Notes in Computer Science, Vol. 3818, Springer 2005, pp. 160-171.

C. M. Chen, H. M. Lee, and Y. H. Chen, “Personalized e-Learning System Using Item Response Theory,” Computers & Education, Vol. 44, 2005, pp. 237-255. crossref(new window)

C. M. Chen and L. J. Duh, “Personalized Web-Based Tutoring System Based on Fuzzy Item Response Theory,” Expert Systems with Applications, Vol. 34, 2008, pp. 2298-2315. crossref(new window)

Yong-Sun Oh, "Educational Digital Content Which Applies Conceptual Object Branch Method, and its Manipulation," Korea Patent No.10-0442417, 2004.

Mathilda du Toit, IRT from SSI: BILOG-MG, Scientific Software International, Inc., 2003.

F. B. Baker and S. H. Kim, Item Response Theory – Parameter Estimation Techniques, 2nd ed., Marcel Dekker, Inc., 2004.

ADL(Advanced Distributed Learning), SCORM 2004 3rd ed. Content Aggregation Model(CAM) Ver.1.0, Section2.1 SCORM Content Model Components, Nov. 16, 2006.

Yong-Sun Oh, "Personalized e-Learning System for the Written Examination of Driver's License Test," applied for Korea Patent, June 20, 2008.