This book explores AI methodologies for the implementation of
affective states in intelligent learning environments. Divided into
four parts, Multimodal Affective Computing: Technologies and
Applications in Learning Environments begins with an overview
of Affective Computing and Intelligent Learning Environments, from
their fundamentals and essential theoretical support up to their
fusion and some successful practical applications. The basic
concepts of Affective Computing, Machine Learning, and Pattern
Recognition in Affective Computing, and Affective Learning
Environments are presented in a comprehensive and easy-to-read
manner. In the second part, a review on the emerging field of
Sentiment Analysis for Learning Environments is introduced,
including a systematic descriptive tour through topics such as
building resources for sentiment detection, methods for data
representation, designing and testing the classification models,
and model integration into a learning system. The methodologies
corresponding to Multimodal Recognition of Learning-Oriented
Emotions are presented in the third part of the book, where topics
such as building resources for emotion detection, methods for data
representation, multimodal recognition systems, and multimodal
emotion recognition in learning environments are presented. The
fourth and last part of the book is devoted to a wide application
field of the combination of methodologies, such as Automatic
Personality Recognition, dealing with issues such as building
resources for personality recognition, methods for data
representation, personality recognition models, and multimodal
personality recognition for affective computing. Â This book
can be very useful not only for beginners who are interested in
affective computing and intelligent learning environments, but also
for advanced and experts in the practice and developments of the
field. It complies an end-to-end treatment on these subjects,
especially with educational applications, making it easy for
researchers and students to get on track with fundamentals,
established methodologies, conventional evaluation protocols,
and the latest progress on these subjects.
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