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Affective Learning with an EEG Approach
Bin Hu
School of Information Science and Engineering
Lanzhou University, China, and
Department of Computing, Birmingham City University, UK
binhu@lzu.edu.cn
People's moods heavily influence their way of communicating and their acting
and productivity, which also plays a crucial role in learning process. Affective
learning is an important aspect of education. Emotions of learners need to be rec-
ognized and interpreted so as to motivate learners and deepen their learning, and
this is a prerequisite in e-learning. Normally, affective learning has been inves-
tigating some technologies to understand learners' emotions through detecting
their face, voice and eyes motion, etc.
Our research focuses on how to enhance interactive learning between learners
and tutors, and understand learners' emotions through an EEG approach. We
have developed an e-learning environment and recorded EEG signals of learners
while they are surfing in the website. We presented an ontology based model
for analyzing learners' alpha wave (a component of EEG signals) to infer the
meaning of its representation, then to understand learners' emotions in learning
process. The outcomes of the research can contribute to evaluation of e-learning
systems and deepen understanding of learners' emotions in learning process.
