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Analyzing the Students’ Achievements of Taiwan Web-based Mathematics Competition by Data Mining
PROCEEDINGS

, Dept. of Industrial Technology Education, National Kaohsiung Normal University, Taiwan ; , Faculty of Computer Science and Automation, Ilmenau University of Technology, Germany ; , Dept. of Mathematics, National Kaohsiung Normal University, Taiwan

E-Learn: World Conference on E-Learning in Corporate, Government, Healthcare, and Higher Education, in Las Vegas, Nevada, USA ISBN 978-1-880094-66-2 Publisher: Association for the Advancement of Computing in Education (AACE), San Diego, CA

Abstract

Experts from three different fields will cooperate to explore this study, including e-learning experts from Taiwan; data mining experts from Canada, and Artificial Intelligence experts from Germany. Through this new analysis technique (data mining), new discoveries can be concluded in the field of web-based mathematics competition. Researchers try to explore these relations between different students’ portfolios and achievements of Taiwan Web-based Mathematics Competition. These findings will provide valuable information for instructors, researchers and government. In particular, optimal learning conditions in- and outside the learning scenario can be explored.

Citation

Chiang, F.K., Knauf, R. & Tso, T.C. (2008). Analyzing the Students’ Achievements of Taiwan Web-based Mathematics Competition by Data Mining. In C. Bonk, M. Lee & T. Reynolds (Eds.), Proceedings of E-Learn 2008--World Conference on E-Learning in Corporate, Government, Healthcare, and Higher Education (pp. 2560-2565). Las Vegas, Nevada, USA: Association for the Advancement of Computing in Education (AACE). Retrieved December 9, 2019 from .

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