Towards error-free and personalized Web-based courses

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 analyzes the relationship between student learning time and 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 personalized make-up course or appropriate advanced courses for further study. All these can be done automatically without interfering the student learning and/or increasing the instructor working load In our design, all Web courses are dynamically assembled with selected course units.