Towards a Gesture Recognition Model for Personalized Learning

DOI

10.2991/978-2-38476-408-2_27How to use a DOI?

Keywords

Gesture Recognition; Personalized Learning; Machine Learning; Educational Technology

Abstract

Personalizing the learning experience is increasingly important in a rapidly changing educational environment. This article presents a conceptual model that integrates gesture recognition into personalized learning environments by applying machine learning techniques. We propose that students’ gestures, as an important form of non-verbal communication, provide valuable information about the learning process, level of engagement, and depth of understanding. The model aims to use machine learning to recognize and interpret these gestures, thus dynamically adjusting educational content to the individual needs of students. This approach is expected to significantly improve engagement and understanding of learning.

This article delves into the theoretical foundations of gesture recognition combined with machine learning in educational settings and discusses the potential benefits of this integrated approach to creating responsive and adaptive learning experiences. It highlights how this innovative model helps bridge the gap between technology and personalized education and ensures a more engaging and effective learning process. Emphasis is placed on the conceptual development of the model, paving the way for future empirical and practical research in educational settings.

By harnessing the nuances of non-verbal cues through advanced machine learning algorithms, this model represents a transformative step towards a more intuitive, learner-centered educational experience. This opens new possibilities for educators to understand and respond to student needs in real time and represents a major advancement in the field of educational technology.

Copyright

© 2025 The Author(s)

Open Access

Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

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TY  - CONF
AU  - Tarik Touis
AU  - Ahmed El Khloufi
AU  - Souhaib Aammou
PY  - 2025
DA  - 2025/06/20
TI  - Towards a Gesture Recognition Model for Personalized Learning
BT  - Proceedings of the E-Learning and Smart Engineering Systems (ELSES 2024)
PB  - Atlantis Press
SP  - 367
EP  - 380
SN  - 2667-128X
UR  - https://doi.org/10.2991/978-2-38476-408-2_27
DO  - 10.2991/978-2-38476-408-2_27
ID  - Touis2025
ER  -