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Big Data Visualization:

Application in Visualizing Learning Activities

  • Conference paper
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Information Science and Applications (ICISA) 2016

Part of the book series: Lecture Notes in Electrical Engineering ((LNEE,volume 376))

Abstract

Information visualization helps users quickly identify interesting and significant events and patterns from data that are otherwise too detailed or complex to discern. For instance, rich content and convenience provided by social networks allow students to exchange ideas and collaborate. In this context, students are interested in exploring learning activities of other students without having to read through lots of textual contents. Students tend to have the interest of finding information concerning their majors, contents of the subjects and their co-learners. However, with the huge amount of information available, it is difficult to identify relevant information for the users. In this paper, we highlight challenges and opportunities in the visualization of big data and learning activities on social network and present a new method of visualizing learning activities of students on social networks. The method allows students to view trends in content and activities near them and around the world. A new application is developed based on the method and is evaluated. The results show that students find it fun and easy to explore learning activities of their peers.

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Author information

Authors and Affiliations

  1. School of Business/IT, James Cook University Australia, Singapore Campus, Singapore, Singapore

    Nguyen Thanh Tam & Insu Song

Authors
  1. Nguyen Thanh Tam
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  2. Insu Song
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Corresponding author

Correspondence to Insu Song .

Editor information

Editors and Affiliations

  1. Kyonggi University, iCatse Kyonggi University, Seongnam-si, Kyonggi-do, Korea (Republic of)

    Kuinam J. Kim

  2. Chair of IEEE CS STCOS, IBM T.J.Watson Research Center Chair of IEEE CS STCOS, Yorktown Heights, New York, USA

    Nikolai Joukov

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Tam, N.T., Song, I. (2016). Big Data Visualization:. In: Kim, K., Joukov, N. (eds) Information Science and Applications (ICISA) 2016. Lecture Notes in Electrical Engineering, vol 376. Springer, Singapore. https://doi.org/10.1007/978-981-10-0557-2_40

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  • DOI: https://doi.org/10.1007/978-981-10-0557-2_40

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  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-10-0556-5

  • Online ISBN: 978-981-10-0557-2

  • eBook Packages: EngineeringEngineering (R0)

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