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

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

Multimodal learning analytics (MMLA) research for building collaboration quality estimation
models has shown significant progress. However, the generalizability of such models is …

Abstract Currently, Big Data Analytics help educators better analyze students and monitor
their progress and likelihood of success. The online learning experience applies to the …

Multimodal Learning Analytics (MMLA) researchers are progressively employing machine
learning (ML) techniques to develop predictive models to improve learning and teaching …

The smart classrooms of the future will use different software, devices and wearables as an
integral part of the learning process. These educational applications generate a large …

Digital transformation has resulted in the availability of more data in higher quality and
business models aiming at exploiting them, both on the level of individual enterprises and …

Multimodal Learning Analytics (MMLA) systems integrate diverse data to provide real-time
insights into student learning, yet their design faces the challenge of limited established …

In the past decade, the applications of big data and learning analytics in education have
made significant headways resulting in new opportunities for educational research …

Abstract When MultiModal Learning Analytics (MMLA) are applied in authentic educational
scenarios, multiple stakeholders (such as teachers, researchers and developers) often …