Niederhauser, Mario

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Niederhauser
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Mario
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Niederhauser, Mario

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    Publikation
    Logible: Detecting, Analyzing and Visualizing Behavior Sequences for Investigating Learning Behavior
    (International Society of the Learning Sciences, 2021) Ruf, Alessia; Jäger, Joscha; Niederhauser, Mario; Zahn, Carmen; Opwis, Klaus; Wichmann, Astrid; Hoppe, H. Ulrich; Rummel, Nikol [in: General Proceedings of the 1st Annual Meeting of the International Society of the Learning Sciences 2021]
    Logible is a highly sensitive web-based interactive tool that automatically detects behavior sequences from raw log files. It further analyzes and visualizes sequences and allows for comparisons of behavior data between different experimental conditions without the use of other software. Logible was developed based on an iterative, exploratory, and rule-based method devised to find meaningful sequences from 92 data sets of students who learned individually or collaboratively with an enhanced video-based environment. The tool is customizable and thus enables researchers to investigate learning behavior with various kinds of sequentially logged interaction data (from web-based video environments, online learning platforms etc.).
    04B - Beitrag Konferenzschrift
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    Publikation
    Introducing a new approach for investigating learning behavior
    (International Society of the Learning Sciences, 2021) Ruf, Alessia; Niederhauser, Mario; Jäger, Joscha; Zahn, Carmen; Opwis, Klaus; Hmelo-Silver, Cindy; de Wever, Bram; Oshima, Jun [in: 14th International Conference on Computer-Supported Collaborative Learning – CSCL 2021]
    The potential of learners’ video interactions to understand learning behavior has been recognized in previous research. However, little research has yet been conducted on enhanced video-based environments using behavior sequence analyses. Hence, we developed Logible, a sensitive, web-based tool to detect and analyze meaningful behavior sequences of learners interacting with such environments. The tool is based on an iterative method. With Logible we were able to visualize learning behavior and emphasize differences in experimental conditions.
    04B - Beitrag Konferenzschrift
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