NDLI: A Remedial Supporting Based Learning Management System

Content Provider	IEEE Xplore Digital Library
Author	Po-Jen Chuang Chu-Sing Yang Ming-Chao Chiang
Copyright Year	2008
Description	Author affiliation: Dept. of Comput. Sci. & Eng., Nat. Sun Yat-sen Univ., Kaohsiung (Po-Jen Chuang)
Abstract	In this paper, we present a system for predicting the examination result, called automatic score prediction system (ASPS). ASPS builds on the lecture structure created by a teacher or a particular pedagogy a course content tree. Each examination sheet is then derived from this course content tree. Besides, each of the question items in an examination sheet belongs to either a section, a chapter, or a unit The difficulty and authority of the question items are determined by the weighted score. The main task of the system is in the classification of the testing results and in the provision of the learning curves and the remedial courses. The learning achievement and testing results can be summarized as a learning curve to the students. By analyzing the learning accomplishments, not only can ASPS predict the probabilistic result of the next examination, but it can also provide reviews or remedial lessons to the students. The main contributions of the ASPS system described herein are twofold: (1) the system can produce the learning curve based on the examination result, which would make it easy for the students and teachers to understand the learning results. (2) The system can provide the course contents to the students to help them review after the examination. Moreover, it provides suggestions for teaching on the not yet acquainted and confused contents.
Starting Page	488
Ending Page	493
File Size	160181
Page Count	6
File Format	PDF
ISBN	9780769531632
DOI	10.1109/ICIW.2008.110
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2008-06-08
Publisher Place	Greece
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Personalization Conference management Regression Application specific processors Regression analysis Learning Prediction Application software Learning systems Electronic learning Feedback Education Web and internet services Feedback System Score Classification Examination Testing
Content Type	Text
Resource Type	Article

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4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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