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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...
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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...
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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 ...