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    Chapter and Conference Paper

    Physiological Synchrony and Arousal as Indicators of Stress and Learning Performance in Embodied Collaborative Learning

    Advancements in sensing technologies, artificial intelligence (AI) and multimodal learning analytics (MMLA) are making it possible to model learners’ affective and physiological states. Physiological synchrony...

    Lixiang Yan, Roberto Martinez-Maldonado… in Artificial Intelligence in Education (2023)

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    Chapter and Conference Paper

    Analysing Verbal Communication in Embodied Team Learning Using Multimodal Data and Ordered Network Analysis

    In embodied team learning activities, students are expected to learn to collaborate with others while freely moving in a physical learning space to complete a shared goal. Students can thus interact in various...

    Linxuan Zhao, Yuanru Tan, Dragan Gašević… in Artificial Intelligence in Education (2023)

  3. No Access

    Chapter and Conference Paper

    Characterising Individual-Level Collaborative Learning Behaviours Using Ordered Network Analysis and Wearable Sensors

    Wearable positioning sensors are enabling unprecedented opportunities to model students’ procedural and social behaviours during collaborative learning tasks in physical learning spaces. Emerging work in this ...

    Lixiang Yan, Yuanru Tan, Zachari Swiecki… in Advances in Quantitative Ethnography (2023)