This study explores the user experience (UX) of students on e-learning platforms, emphasizing emotional expression and satisfaction. It enhances existing research by applying usability tests and surveys to assess the emotional impact of online learning. The study's novelty lies in its focus on emotional expression, which, along with cognitive issues and engagement, significantly affects satisfaction and learning outcomes. It compares the effectiveness of a real-time face and eye recognition method (MIORA) with a retrospective questionnaire (SAM) for measuring emotional responses. Results indicate that the real-time method is more accurate and reliable, capturing transient emotional states with machine learning. Unlike retrospective assessments, which are prone to memory biases, the real-time method provides immediate, objective data for dynamic understanding and instant feedback. These insights are crucial for improving e-learning platform design, enhancing user engagement, and enabling real-time adaptations, leading to more effective and satisfactory online learning environments.

User Experience and Emotion on E-learning Platforms: An Experiment

Luca Giraldi
First
;
2025-01-01

Abstract

This study explores the user experience (UX) of students on e-learning platforms, emphasizing emotional expression and satisfaction. It enhances existing research by applying usability tests and surveys to assess the emotional impact of online learning. The study's novelty lies in its focus on emotional expression, which, along with cognitive issues and engagement, significantly affects satisfaction and learning outcomes. It compares the effectiveness of a real-time face and eye recognition method (MIORA) with a retrospective questionnaire (SAM) for measuring emotional responses. Results indicate that the real-time method is more accurate and reliable, capturing transient emotional states with machine learning. Unlike retrospective assessments, which are prone to memory biases, the real-time method provides immediate, objective data for dynamic understanding and instant feedback. These insights are crucial for improving e-learning platform design, enhancing user engagement, and enabling real-time adaptations, leading to more effective and satisfactory online learning environments.
2025
1
36
https://www.tandfonline.com/doi/full/10.1080/13803611.2025.2501530
E-learning platforms, user behaviour, user experience, emotions recognition, non-invasive tools
Luca Giraldi, Marta Giovannetti, Elena Cedrola
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/2318/2071210
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