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Emotions recognition in an intelligent elearning environment

机译:智能学习环境中的情绪识别

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摘要

For the purpose of improving the quality in Elearning process and overcoming the limitations of the current online educational environments, we propose to take into consideration the emotional states of students during Elearning sessions. Our objective is to ensure the ability of emotional intelligence: Emotion Recognition, in an eLearning environment. Thus, we present an architecture of Emotionally Intelligent Elearning System (EIES). Within the development of a computational probabilistic model of emotions, we proposed a Bayesian Network (BN) model to deal with emotions in Elearning environments and handle the uncertain nature of emotion recognition process. In a second phase, we focus on the incorporation of the emotion recognition in the Elearning systems by developing a simulation of EIES based on the BN model, able to predict the students' affects. Consequently, we reached positive and promising results related to the fact that simulated EIES based on the BN model of emotions predicts correctly the student's emotion when an event occurs during an Elearning session.
机译:为了提高在线学习过程的质量并克服当前在线教育环境的局限性,我们建议考虑在线学习课程中学生的情绪状态。我们的目标是确保情绪智力的能力:在电子学习环境中的情绪识别。因此,我们提出了情感智能电子学习系统(EIES)的体系结构。在开发情感计算概率模型的过程中,我们提出了一种贝叶斯网络(Bayesian Network,BN)模型来处理电子学习环境中的情感并处理情感识别过程的不确定性。在第二阶段,我们致力于通过基于BN模型的EIES仿真来预测学生的情感,从而将情感识别整合到电子学习系统中。因此,我们获得了积极而有希望的结果,这一事实与基于情感的BN模型的模拟EIES在电子学习会话期间发生事件时正确预测学生的情感这一事实有关。

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