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Applying Cluster Techniques of Data Mining to Analysis the Game-Based Digital Learning Work

  • Shu-Ling Shieh
  • Shu-Fen Chiou
  • Gwo-Haur Hwang
  • Ying-Chi Yeh
Conference paper
Part of the Lecture Notes in Electrical Engineering book series (LNEE, volume 253)

Abstract

Clustering is the most important task in unsupervised learning and applications is a major issue in cluster analysis. Digital learning, which arises in recent years, has become a trend of learning method in the future. The environment of digital learning may enable the learners work anytime and everywhere without the limitation of time and space. Another great improvement of digital learning is the ability of recording complete portfolio. These portfolios may be used to gain critical factors of learning if they are analyzed by data mining methods. Therefore, in this research will to analyze the records of students’ portfolios of game-based homework by using Clustering Algorithm Based on Histogram Threshold (HTCA) method of data mining. The HTCA method combines a hierarchical clustering method and Otsu’s method. The result indicates that the attributes or categories of impacting factors and to find conclusions of efficiency for the learning process.

Keywords

Data mining Clustering method Game-based digital learning 

Notes

Acknowledgments

This study is sponsored by the Science Council of Taiwan under the contract no. NSC 101-2221-E-275-006 and NSC99-2511-S-275-001-MY3.

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Copyright information

© Springer Science+Business Media Dordrecht 2013

Authors and Affiliations

  • Shu-Ling Shieh
    • 1
  • Shu-Fen Chiou
    • 2
  • Gwo-Haur Hwang
    • 1
  • Ying-Chi Yeh
    • 3
  1. 1.Department of Information Networking and System AdministrationLing Tung UniversityTaichungTaiwan
  2. 2.Department of Computer Science and EngineeringNational Chung-Hsing UniversityTaichungTaiwan
  3. 3.The Graduate Institute of Applied Information TechnologyLing Tung UniversityTaichungTaiwan

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