Title: Mining test results to personalise and refine web-based courses

Authors: Hui-Huang Hsu

Addresses: Department of Computer Science and Information Engineering, Tamkang University, Tamsui, Taipei Hsien, 25137, Taiwan, ROC

Abstract: Providing appropriate learning content to each student is a key to the success of a web-based distance learning system. Student test results can be an important feedback for the instructor to re-evaluate the course content. A Test Result Feedback (TRF) model that analyses the relationship between student learning time and the corresponding test result is developed. The model can give the instructor crucial information for course content refinement. It can also suggest the student with a personalised remedial course or appropriate advanced courses for further study. All these can be done automatically without interfering with the student|s learning and/or increasing the instructor|s working load. In our design, all web courses are dynamically assembled with selected course units.

Keywords: distance education; web mining; personalised courses; course refinement; TRF; test results feedback; feedback models; e-learning; electronic learning; online learning; appropriate learning content; distance learning.

DOI: 10.1504/IJASS.2010.034108

International Journal of Applied Systemic Studies, 2010 Vol.3 No.2, pp.183 - 191

Published online: 12 Jul 2010 *

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