An adaptive e-learning environment centred on learner's emotional behaviour

A. Kanimozhi, V. Raj
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引用次数: 10

Abstract

Recent trends in Information and Communication Technology, Web based learning environment attract the learner for anywhere and anytime learning such as e-learning environment. Many research says that the learner's active listening duration is 15 to 20 minutes and research on e-learning mainly focusing to offer an adaptive e-learning content with respect to the learner's profile and knowledge. This paper, we are mainly focused, how to engage the student in e-learning for longer duration. To keep the learner, in active listening mood, we have to recognize the learner mood and offer the adaptive learning content with respect to their mood, knowledge in the domain, profile and Learner history feedback. We focused to reveal the learner's emotional behavior, we have taken Facial feature emotion extraction, body gesture, movement and EEG — Bio signal approach for emotion prediction. The result was analyzed and it shows that bio-signal accurately predicting the learner's emotion. Finally, we have used the EEG approach for predicting the learner's emotional behavior while learning.
以学习者情绪行为为中心的适应性电子学习环境
随着信息通信技术的发展,以网络为基础的学习环境吸引着学习者随时随地学习,如电子学习环境。许多研究认为,学习者的主动听力持续时间为15 ~ 20分钟,而关于网络学习的研究主要集中在提供与学习者的个人资料和知识相适应的网络学习内容。本文主要研究如何使学生更持久地参与到网络学习中来。为了使学习者保持积极的倾听情绪,我们必须识别学习者的情绪,并根据他们的情绪、领域知识、个人资料和学习者历史反馈提供适应性的学习内容。为了揭示学习者的情绪行为,我们采用了面部特征情感提取、肢体动作、运动和脑电图-生物信号方法进行情绪预测。结果表明,生物信号能够准确地预测学习者的情绪。最后,我们使用脑电图方法来预测学习者在学习过程中的情绪行为。
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