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Learning Analytics for SNS-Integrated Virtual Learning Environment

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Data Mining and Big Data (DMBD 2017)

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 10387))

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Abstract

With the increasing interest of social media usage among the students, we are motivated to integrate this informal mode of socialized learning environment into the formal learning system to engage students for their learning activities. The existing Learning Analytics (LA) focused only on analyzing formal data obtained from controlled online learning environments and the social connections and learning experience of students are not analyzed. The expected output for this proposed work is a SNS-integrated Virtual Learning Environment (VLE) named Shelter which provides formal and informal learning for any subject domain area. User testing is conducted and both informal and formal data are stored and elicited from Shelter to investigate the impact of this data combination for more insightful LA results.

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Acknowledgments

This work is supported by funding of Fundamental Research Grant Scheme (FRGS), from the Ministry of Higher Learning Education (MOHE).

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Authors and Affiliations

  1. Faculty of Computing and Informatics, Multimedia University, Cyberjaya, Selangor, Malaysia

    Fang-Fang Chua, Chia-Ying Khor & Su-Cheng Haw

Authors
  1. Fang-Fang Chua
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  2. Chia-Ying Khor
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  3. Su-Cheng Haw
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Corresponding author

Correspondence to Fang-Fang Chua .

Editor information

Editors and Affiliations

  1. Peking University, Beijing, China

    Ying Tan

  2. Kyushu University, Fukuoka, Japan

    Hideyuki Takagi

  3. Southern University of Science and Technology, Shenzhen, China

    Yuhui Shi

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Chua, FF., Khor, CY., Haw, SC. (2017). Learning Analytics for SNS-Integrated Virtual Learning Environment. In: Tan, Y., Takagi, H., Shi, Y. (eds) Data Mining and Big Data. DMBD 2017. Lecture Notes in Computer Science(), vol 10387. Springer, Cham. https://doi.org/10.1007/978-3-319-61845-6_15

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  • DOI: https://doi.org/10.1007/978-3-319-61845-6_15

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-61844-9

  • Online ISBN: 978-3-319-61845-6

  • eBook Packages: Computer ScienceComputer Science (R0)

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