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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Wei Zang Fuzong Lin |
| Copyright Year | 2003 |
| Description | Author affiliation: Dept. of Comput. Sci. & Technol., Tsinghua Univ., Beijing, China (Wei Zang; Fuzong Lin) |
| Abstract | The analysis of teaching and learning in distance education is an active research topic in recent years. We propose a new method by introducing a machine learning algorithm called boosting to investigate this problem. The boosting algorithm can also be treated as a data mining method, trying to infer from a large amount of training data the essential factors and their relations which influence the students' academic successes. Based on the trained model it is possible to predict students' academic successes and assist them to adjust their learning behaviors. More importantly, these findings are of great importance to academic administrators and instructional developers to improve the teaching modes and online courseware design. |
| Sponsorship | New Jersey Inst. of Technol. Jersy Comm. on Higher Educ. sponsored by NJ I-TOWER program at NJIT IEEE North Jersy Section IEEE COMSOC North Jersey Chapter |
| Starting Page | 445 |
| Ending Page | 449 |
| File Size | 400054 |
| Page Count | 5 |
| File Format | |
| ISBN | 0780377249 |
| DOI | 10.1109/ITRE.2003.1270655 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2003-08-11 |
| Publisher Place | USA |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | Education Boosting Distance learning Training data Educational technology Machine learning algorithms Data mining Laboratories Intelligent systems Computer science |
| Content Type | Text |
| Resource Type | Article |
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