Multimodal interactions and explainable AI for reflective physical and online learning: MiXai^learn workshop

Abstract

This half-day workshop discusses application of explainable AI and multimodal interactions with personal devices, tangible electronics and social robots for fostering reflective learning practices in physical and online learning scenarios. Reflective practices in education have been shown to improve student achievement and prepare students for a sustainable society. Still, learning activities that are across physical and online learning spaces make it difficult to assess reflection skills and support them comprehensively. Recent advances in robotics, sensors, machine learning and generative AI provide opportunities to create technologies to capture and analyze data in a hybrid format across physical and online spaces. The workshop aims to bring together experts from the fields of AI, learning analytics, sensing technologies, and learning sciences to discuss technologies for detecting, understanding, and predicting learning distributed in physical and online spaces, as well as to discuss what is pedagogically desirable, technically feasible, and ethically sound. As a technology context we will demonstrate the functionalities of the LA-ReflecT platform, which is being developed and used as part of this international collaboration. This workshop is important to the AIED community, particularly those developing technologies to capture learning in hybrid spaces or, more generally, complex multimodal student interactions.