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Construction on Learning Analytics Object for Sharing and Interoperation of Educational Big Data

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Current Developments in Web Based Learning (ICWL 2015)

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 9584))

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Abstract

Educational Big Data (EBD) come from various types of Educational Systems such as LMS, CMS, ITS, SLS, and MOOCs. How to share and interoperate Educational Big Data for Learning Analytics (LA) has garnered a lot of research attention. In the paper, we probe into the process of Learning Analytics, outline the dataflow of EBD, define the Learning Analytics Object, and propose a new data format model for the Learning Analytics object to actualize the sharing and interoperability of Learning Analytics.

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Acknowledgments

This work was supported by the 2014 Shanghai Pujiang Program (Grant 14PJC034) and the 2014 Shanghai “Technology Innovation Action Plan” Project (Grant 14511109300).

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Authors and Affiliations

  1. East China Normal University, 3663 Zhongshan Road (N.), Shanghai, China

    Yonghe Wu & Wei Zhong

  2. East China Normal University, 500 Dongchuan Road, Shanghai, China

    Chun Zhou & Xiaoling Ma

Authors
  1. Yonghe Wu
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  2. Wei Zhong
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  3. Chun Zhou
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  4. Xiaoling Ma
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Corresponding author

Correspondence to Yonghe Wu .

Editor information

Editors and Affiliations

  1. University of Macau, Macau, China

    Zhiguo Gong

  2. The University of Hong Kong, Hong Kong, China

    Dickson K. W. Chiu

  3. The Hong Kong Polytechnic University, Hong Kong, China

    Di Zou

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© 2016 Springer International Publishing Switzerland

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Wu, Y., Zhong, W., Zhou, C., Ma, X. (2016). Construction on Learning Analytics Object for Sharing and Interoperation of Educational Big Data. In: Gong, Z., Chiu, D., Zou, D. (eds) Current Developments in Web Based Learning. ICWL 2015. Lecture Notes in Computer Science(), vol 9584. Springer, Cham. https://doi.org/10.1007/978-3-319-32865-2_20

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  • DOI: https://doi.org/10.1007/978-3-319-32865-2_20

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-32864-5

  • Online ISBN: 978-3-319-32865-2

  • eBook Packages: Computer ScienceComputer Science (R0)

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