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An AST-Based Collaborative Discussion Tool for the MOOC Environment

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Computer Supported Cooperative Work and Social Computing (ChineseCSCW 2022)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 1681))

Abstract

Online study becomes increasingly popular. Most existing massive open online course (MOOC) platforms provide a Community Question Answering (cQA) area where learners can seek for information, however, these cQA areas inevitably meet the following problems, such as low participation rate, insufficient contents and poor topic quality. Other online-learning websites equipped with the bullet screen achieve high interactivity by presenting history comments, but users who are watching the same course video with different progress cannot truly interact with each other. Therefore, it’s necessary to design a collaborative discussion tool which takes the advantages of both collaborative editing and the bullet screen. The present collaborative editing schemes focus on supporting instant interaction and reducing conflicts between real users while there is only one learner online is often the practical case in the MOOC environment. In this paper, we propose a simulated interaction solution which is adapted for the MOOC environment and based on the Address Space Transformation (AST) scheme to promote online study experience. Firstly, four interaction modes which simulate the collaboration between historical and real users are concluded according to applicable scenarios. Secondly, we propose a simulated interaction approach based on the AST scheme. Finally, taking the edX platform as an example, we implement a collaborative editing tool by using the approach mentioned above.

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Acknowledgements

This work was supported by the National Natural Science Foundation of China (NSFC) under Grant No. 62172106.

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Authors and Affiliations

  1. School of Computer Science, Fudan University, Shanghai, China

    Xinyue Yu & Tun Lu

  2. Shanghai Key Laboratory of Data Science, Fudan University, Shanghai, China

    Xinyue Yu & Tun Lu

Authors
  1. Xinyue Yu
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  2. Tun Lu
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Corresponding author

Correspondence to Tun Lu .

Editor information

Editors and Affiliations

  1. Shandong University, Jinan, China

    Yuqing Sun

  2. Fudan University, Shanghai, China

    Tun Lu

  3. Taiyuan University of Science and Technology, Taiyuan, China

    Yinzhang Guo

  4. Shanxi Datong University, Datong, China

    Xiaoxia Song

  5. Tongji University, Shanghai, China

    Hongfei Fan

  6. Guangdong University of Technology, Guangzhou, China

    Dongning Liu

  7. University of Shanghai for Science and Technology, Shanghai, China

    Liping Gao

  8. Tongji University, Shanghai, China

    Bowen Du

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Yu, X., Lu, T. (2023). An AST-Based Collaborative Discussion Tool for the MOOC Environment. In: Sun, Y., et al. Computer Supported Cooperative Work and Social Computing. ChineseCSCW 2022. Communications in Computer and Information Science, vol 1681. Springer, Singapore. https://doi.org/10.1007/978-981-99-2356-4_23

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  • DOI: https://doi.org/10.1007/978-981-99-2356-4_23

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  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-99-2355-7

  • Online ISBN: 978-981-99-2356-4

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