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 data have the potential to explore emerging learning practices that extend
human cognitive capacities. A critical issue stretching in many multimodal learning analytics …

Learning outcomes are the result of interactions between intraindividual factors, such as
prior knowledge, emotions, and motivation; as well as the contextual factors in which the …

This chapter is an introduction to the use of multiple modalities of learning trace data to
better understand and feedback learning processes that occur both in digital and face-to …

Abstract Motion-Based Learning Technologies (MBLT) offer a promising approach for
integrating play and problem-solving behaviour within children's learning. The proliferation …

Multimodal learning analytics (MMLA) has increasingly been a topic of discussion within the
learning analytics community. The Society of Learning Analytics Research is home to the …

Abstract The goal of Learning Analytics is to understand and improve learning. However,
learning does not always occur through or mediated by a technological system that can …

Using data to generate a deeper understanding of collaborative learning is not new, but
automatically analyzing log data has enabled new means of identifying key indicators of …

The metaverse entails modes of interactivity that hold enormous potential for education in
various contexts and domains. The metaverse represents a convergence of technologies …

" Automated scoring engines [...] require a careful balancing of the contributions of
technology, NLP, psychometrics, artificial intelligence, and the learning sciences. The …