JOURNAL BROWSE
Search
Advanced SearchSearch Tips
A Structure of Personalized e-Learning System Using On/Off-line Mixed Estimations Based on Multiple-Choice Items
facebook(new window)  Pirnt(new window) E-mail(new window) Excel Download
 Title & Authors
A Structure of Personalized e-Learning System Using On/Off-line Mixed Estimations Based on Multiple-Choice Items
Oh, Yong-Sun;
  PDF(new window)
 Abstract
In this paper, we present a structure of personalized e-Learning system to study for a test formalized by uniform multiple-choice using on/off line mixed estimations as is the case of Driver :s License Test in Korea. Using the system a candidate can study toward the license through the Internet (and/or mobile instruments) within the personalized concept based on IRT(item response theory). The system accurately estimates user's ability parameter and dynamically offers optimal evaluation problems and learning contents according to the estimated ability so that the user can take possession of the license in shorter time. In order to establish the personalized e-Learning concepts, we build up 3 databases and 2 agents in this system. Content DB maintains learning contents for studying toward the license as the shape of objects separated by concept-unit. Item-bank DB manages items with their parameters such as difficulties, discriminations, and guessing factors, which are firmly related to the learning contents in Content DB through the concept of object parameters. User profile DB maintains users' status information, item responses, and ability parameters. With these DB formations, Interface agent processes user ID, password, status information, and various queries generated by learners. In addition, it hooks up user's item response with Selection & Feedback agent. On the other hand, Selection & Feedback agent offers problems and content objects according to the corresponding user's ability parameter, and re-estimates the ability parameter to activate dynamic personalized learning situation and so forth.
 Keywords
personalized e-Learning;on/off-line mixed estimation;IRT(item response theory);user ability parameter;item parameters;
 Language
English
 Cited by
1.
Instructional Planning in Online Universities in Korea: Considering Student Stressors and Demographic Variables,;;

International Journal of Contents, 2012. vol.8. 1, pp.1-9 crossref(new window)
1.
Instructional Planning in Online Universities in Korea: Considering Student Stressors and Demographic Variables, International Journal of Contents, 2012, 8, 1, 1  crossref(new windwow)
 References
1.
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)

2.
Yong-Sun Oh, "A Construction Method for Personalized e-Learning System Using Dynamic Estimations of Item Parameters and Examinees'Abilities," International Journal of Contents, Vol.4, No.2, Korea Contents Association, June 2008, pp. 19-23. crossref(new window)

3.
F.B.Baker and S.H.Kim, Item Response Theory - Parameter Estimation Techniques, 2nd ed., Marcel Dekker , Inc., New York, 2004

4.
Yong-Sun Oh, "Personalized E-Learning System for the Written Examination of Driver' License Test," to be registered in Korea Patent, application number 10-2008-0055787, June 13, 2008.

5.
Young-Hee Lee, "An Internet e-Learning System and its Learning Method," Korea Patent No. 10-0438466, 2004.

6.
Yong-Sun Oh and Jong-Tak Lee, "Educational Digital Content Which Applies Conceptual Object Branch Method and its Manipulation," Korea Patent No. 10-0442417, 2004.

7.
Mathilda du Toit, IRT from SSI: BILOG-MG, Scientific Software International, Inc., 2003.

8.
ADL(Advanced Distributed Learning), SCORM 2004 3rd ed. Content Aggregation Model (CAM) Ver. 1.0, Section 2.1 SCORM Content Model Components, Nov. 16, 2006.

9.
Chih-Ming Chen and Ling-Jiun 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)