Multimodal learning analytics (MMLA), which has become increasingly popular, can help
provide an accurate understanding of learning processes. However, it is still unclear how …

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 …

The first workshop on Multimodal Learning Analytics took place in 2012 at the International
Conference of Multimodal Interaction in Santa Monica, California. Since then researchers …

Learning Design, as a field of research, provides practitioners with guidelines towards more
effective teaching and learning. In parallel, observational methods (manual or automated) …

Learning analytics (LA) and lesson observations are two approaches frequently used to
study teaching and learning processes. In both cases, in order to extract meaningful data …

The proliferation of educational technologies has generated unprecedented volumes of
diverse, multimodal learner data, offering rich insights into learning processes and …

Physiological sensors can be used to detect changes in the emotional state of users with
affective computing. This has lately been applied in the educational domain, aimed to better …

In a world bursting with new information, ideas, opportunities, and technological
advancements, it is time to rethink how continuous learning shapes our future. Amidst the …

Observational data can be used to illuminate different areas of teaching and learning
process and enrich Learning Analytics data. Majority of lesson observation tools provide …

This chapter describes a physiology-aware learning analytics framework that is aimed to
collect and analyze physiological data of learners. A pedagogical agent detecting learner's …