Mining Test Results to Personalise and Refine Web-Based Courses
學年 98
學期 2
出版（發表）日期 2010-07-01
作品名稱 Mining Test Results to Personalise and Refine Web-Based Courses
作品名稱（其他語言）
著者 Hsu, Hui-Huang
單位 淡江大學資訊工程學系
出版者 Olney: Inderscience Enterprises
著錄名稱、卷期、頁數 International Journal of Applied Systemic Studies 3(2), pp.183-191
摘要 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.
關鍵字 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
語言 en
ISSN 1751-0589; 1751-0597
期刊性質 國外
收錄於 EI
產學合作
通訊作者 Hsu, Hui-Huang
審稿制度 是
國別 GBR
公開徵稿
出版型式 紙本
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