Multimodal Learning Experience for Deliberate Practice

Multimodal Learning Experience for Deliberate Practice

Di Mitri, Daniele (DIPF - Leibniz Institute for Research and Information in Education)
Schneider, Jan (DIPF - Leibniz Institute for Research and Information in Education)
Limbu, B.H. (TU Delft Web Information Systems)
Mat Sanusi, Khaleel Asyraaf (TH Köln)
Klemke, Roland (TH Köln)

Giannakos, Michail (editor)
Spikol, Daniel (editor)
Di Mitri, Daniele (editor)
Sharma, Kshitij (editor)
Ochoa, Xavier (editor)
Hammad, Rawad (editor)

2022

While digital education technologies have improved to make educational resources more available, the modes of interaction they implement remain largely unnatural for the learner. Modern sensor-enabled computer systems allow extending human-computer interfaces for multimodal communication. Advances in Artificial Intelligence allow interpreting the data collected from multimodal and multi-sensor devices. These insights can be used to support deliberate practice with personalised feedback and adaptation through Multimodal Learning Experiences (MLX). This chapter elaborates on the approaches, architectures, and methodologies in five different use cases that use multimodal learning analytics applications for deliberate practice.

http://resolver.tudelft.nl/uuid:08db8793-fafa-407d-8fbe-036a83be573e

https://doi.org/10.1007/978-3-031-08076-0_8

Springer, Cham

2023-07-01

978-3-031-08075-3

The Multimodal Learning Analytics Handbook

Green Open Access added to TU Delft Institutional Repository 'You share, we take care!' - Taverne project https://www.openaccess.nl/en/you-share-we-take-care Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public.

Institutional Repository

book chapter

© 2022 Daniele Di Mitri, Jan Schneider, B.H. Limbu, Khaleel Asyraaf Mat Sanusi, Roland Klemke