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

There is a growing interest in the research and use of multimodal data in learning analytics.
This paper presents a systematic literature review of multimodal learning analytics (MMLA) …

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 …

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

The digital age has introduced a host of new challenges and opportunities for the learning
sciences community. These challenges and opportunities are particularly abundant in …

Most research on learning technology uses clickstreams and questionnaires as their primary
source of quantitative data. This study presents the outcomes of a systematic literature …

Since the emergence of learning analytics (LA) in 2011 as a distinct field of research and
practice, multimodal learning analytics (MMLA), shares an interdisciplinary approach to …

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 …

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 …