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    Exploring Massive Open Online Course (MOOC) forum data is challenging. This study introduces iForum, an interactive visual analytics system designed to uncover temporal patterns in MOOC discussions for course improvement.

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    Area of Science:

    • Educational Technology
    • Data Visualization
    • Human-Computer Interaction

    Background:

    • Massive Open Online Courses (MOOCs) generate extensive discussion forum data.
    • Analyzing this complex, heterogeneous data is crucial for course enhancement but presents significant challenges due to the dynamic interactions between users, posts, and threads.

    Purpose of the Study:

    • To present the design study of iForum, an interactive visual analytics system.
    • To enable effective discovery and understanding of temporal patterns within MOOC forum data.

    Main Methods:

    • An iterative design study involving three domain experts (one MOOC instructor, two teaching assistants) over one year.
    • Development of novel visualization designs to represent posts, users, and threads at multiple scales.
    • A case study using iForum with field experts on real MOOC forum data from a JAVA programming course.

    Main Results:

    • iForum provides novel visualizations for exploring interconnected aspects of MOOC forums (posts, users, threads).
    • The system facilitates the discovery of temporal patterns at different granularities.
    • A case study demonstrated the system's effectiveness and usefulness in analyzing real-world MOOC data.

    Conclusions:

    • iForum offers a valuable tool for instructional staff to gain insights from MOOC forum data.
    • The system aids in understanding user interactions and discussion dynamics over time.
    • iForum supports data-driven course improvement and preparation for future iterations.