This comprehensive survey explored the evolving landscape of generative Artificial
Intelligence (AI), with a specific focus on the transformative impacts of Mixture of Experts …

This study presents the outcomes of a semi‐systematic literature review on the role of
learning theory in multimodal learning analytics (MMLA) research. Based on previous …

Multimodal Learning Analytics (MMLA) innovations are commonly aimed at supporting
learners in physical learning spaces through state-of-the-art sensing technologies and …

Simulation‐based learning provides students with unique opportunities to develop key
procedural and teamwork skills in close‐to‐authentic physical learning and training …

Higher education institutions are moving to design and implement teacher-facing learning
analytics (LA) dashboards with the hope that instructors can extract deep insights about …

Understanding and improving education are critical goals of learning analytics. However,
learning is not always mediated or aided by a digital system that can capture digital traces …

Multimodal Learning Analytics (MMLA) innovations make use of rapidly evolving sensing
and artificial intelligence algorithms to collect rich data about learning activities that unfold in …

Multimodal semantic understanding often has to deal with uncertainty, which means the
obtained messages tend to refer to multiple targets. Such uncertainty is problematic for our …

Embodied team learning is a form of group learning that occurs in co-located settings where
students need to interact with others while actively using resources in the physical learning …

In co-located situations, team members use a combination of verbal and visual signals to
communicate effectively, among which positional forms play a key role. The spatial patterns …