In this paper, we present an approach in the Multimodal Learning Analytics field. Within this approach, we have developed a tool to visualize and analyze eye movement data collected during learning sessions in online courses. The tool is named VAAD, an acronym for Visual Attention Analysis Dashboard. These eye movement data have been gathered using an eye-tracker and subsequently processed and visualized for interpretation. The purpose of the tool is to conduct a descriptive analysis of the data by facilitating its visualization, enabling the identification of differences and learning patterns among various learner populations. Additionally, it integrates a predictive module capable of anticipating learner activities during a learning session. Consequently, VAAD holds the potential to offer valuable insights into online learning behaviors from both descriptive and predictive perspectives.
@article{arxiv.2405.20091,
title = {VAAD: Visual Attention Analysis Dashboard applied to e-Learning},
author = {Miriam Navarro and Álvaro Becerra and Roberto Daza and Ruth Cobos and Aythami Morales and Julian Fierrez},
journal= {arXiv preprint arXiv:2405.20091},
year = {2024}
}
Comments
Published in IEEE Intl. Symposium on Computers in Education (SIIE) 2024