VAAD: Visual Attention Analysis Dashboard applied to e-Learning
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arXiv
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| Main Authors: | , , , , , |
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| Format: | Preprint |
| Published: |
2024
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| _version_ | 1866929480582299648 |
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| author | Navarro, Miriam Becerra, Álvaro Daza, Roberto Cobos, Ruth Morales, Aythami Fierrez, Julian |
| author_facet | Navarro, Miriam Becerra, Álvaro Daza, Roberto Cobos, Ruth Morales, Aythami Fierrez, Julian |
| contents | 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. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2405_20091 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | VAAD: Visual Attention Analysis Dashboard applied to e-Learning Navarro, Miriam Becerra, Álvaro Daza, Roberto Cobos, Ruth Morales, Aythami Fierrez, Julian Computer Vision and Pattern Recognition Human-Computer Interaction Machine Learning 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. |
| title | VAAD: Visual Attention Analysis Dashboard applied to e-Learning |
| topic | Computer Vision and Pattern Recognition Human-Computer Interaction Machine Learning |
| url | https://arxiv.org/abs/2405.20091 |