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

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Information Technology Convergence

Part of the book series: Lecture Notes in Electrical Engineering ((LNEE,volume 253))

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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.

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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.

Author information

Authors and Affiliations

  1. Department of Information Networking and System Administration, Ling Tung University, Taichung, Taiwan

    Shu-Ling Shieh & Gwo-Haur Hwang

  2. Department of Computer Science and Engineering, National Chung-Hsing University, Taichung, Taiwan

    Shu-Fen Chiou

  3. The Graduate Institute of Applied Information Technology, Ling Tung University, Taichung, Taiwan

    Ying-Chi Yeh

Authors
  1. Shu-Ling Shieh
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  2. Shu-Fen Chiou
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  3. Gwo-Haur Hwang
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  4. Ying-Chi Yeh
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Corresponding author

Correspondence to Shu-Ling Shieh .

Editor information

Editors and Affiliations

  1. Department of Computer Science and Engineering, Seoul University of Science & and Technology (SeoulTech), Seoul, Korea, Republic of (South Korea)

    James J. (Jong Hyuk) Park

  2. Dept. Information & Communication Engineering, Fukuoka Institute of Technology Fac. Information Engineering, Fukuoka, Japan

    Leonard Barolli

  3. Departament De Llenguatges I Sistemes Informàtics, Universitat Politècnica De Catalunya, Barcelona, Spain

    Fatos Xhafa

  4. Humanitas College, Kyung Hee University, Seoul, Korea, Republic of (South Korea)

    Hwa-Young Jeong

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Shieh, SL., Chiou, SF., Hwang, GH., Yeh, YC. (2013). Applying Cluster Techniques of Data Mining to Analysis the Game-Based Digital Learning Work. In: Park, J., Barolli, L., Xhafa, F., Jeong, HY. (eds) Information Technology Convergence. Lecture Notes in Electrical Engineering, vol 253. Springer, Dordrecht. https://doi.org/10.1007/978-94-007-6996-0_48

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  • DOI: https://doi.org/10.1007/978-94-007-6996-0_48

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  • Publisher Name: Springer, Dordrecht

  • Print ISBN: 978-94-007-6995-3

  • Online ISBN: 978-94-007-6996-0

  • eBook Packages: EngineeringEngineering (R0)

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