• DocumentCode
    721376
  • Title

    VisMOOC: Visualizing video clickstream data from Massive Open Online Courses

  • Author

    Conglei Shi ; Siwei Fu ; Qing Chen ; Huamin Qu

  • Author_Institution
    Hong Kong Univ. of Sci. & Technol., Hong Kong, China
  • fYear
    2015
  • fDate
    14-17 April 2015
  • Firstpage
    159
  • Lastpage
    166
  • Abstract
    Massive Open Online Courses (MOOCs) platforms are becoming increasingly popular in recent years. With thousands of students watching course videos, enormous amounts of clickstream data are produced and recorded by the MOOCs platforms for each course. Such large-scale data provide a great opportunity for instructors and educational analysts to gain insight into online learning behaviors on an unprecedented scale. Nevertheless, the growing scale and unique characteristics of the data also pose a special challenge for effective data analysis. In this paper, we introduce VisMOOC, a visual analytic system to help analyze user learning behaviors by using video clickstream data from MOOC platforms. We work closely with the instructors of two Coursera courses to understand the data and collect task analysis requirements. A complete user-centered design process is further employed to design and develop VisMOOC. It includes three main linked views: the List View to show an overview of the clickstream differences among course videos, the Content-based View to show temporal variations in the total number of each type of click action along the video timeline, the Dashboard View to show various statistical information such as demographic information and temporal information. We conduct two case studies with the instructors to demonstrate the usefulness of VisMOOC and discuss new findings on learning behaviors.
  • Keywords
    behavioural sciences; computer aided instruction; data visualisation; distance learning; educational courses; user centred design; video signal processing; Coursera courses; MOOC platforms; VisMOOC; click action; content-based view; course videos; dashboard view; data analysis; demographic information; large-scale data; linked views; list view; massive open online courses; online learning behaviors; statistical information; task analysis requirements; temporal information; temporal variations; user learning behaviors; user-centered design process; video clickstream data visualization; video timeline; visual analytic system; Data visualization; Education; Image color analysis; Interviews; Streaming media; Visual analytics;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Visualization Symposium (PacificVis), 2015 IEEE Pacific
  • Conference_Location
    Hangzhou
  • Type

    conf

  • DOI
    10.1109/PACIFICVIS.2015.7156373
  • Filename
    7156373