Affective Learning Environments

Ramón Zatarain Cabada, Héctor Manuel Cárdenas López and Hugo Jair Escalante
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Ramón Zatarain Cabada: Instituto Tecnológico de Culiacán
Héctor Manuel Cárdenas López: Instituto Tecnológico de Culiacán
Hugo Jair Escalante: Instituto Nacional de Astrofísica

Chapter Chapter 3 in Multimodal Affective Computing, 2023, pp 35-41 from Springer

Abstract: Abstract This chapter covers the application of affect, personality, emotion, and sentiment in learning environments. To begin, we examine the dynamics of teaching and learning, including the different parts of the learning process, how teachers can effectively teach a subject, how students can best learn it, and the various interactions that occur. Next, we explore the theoretical models that describe the role of affect in learning, including the various ways in which students learn a subject and how their emotions are related to this process. We also discuss different models created to describe this relationship and how they can be used to improve learning outcomes. Finally, we explore into affective learning environments, including affective instruction system design, computer-assisted instructor systems, intelligent tutoring systems, intelligent learning environments, and the integration of machine learning for affect prediction in intelligent learning environments. This chapter aims to contextualize the reader on subjects of the application of learning environments in the task of learning. In this chapter, we answer the following question: How can a tutoring system using affect recognition provide a student with a better learning experience?

Date: 2023
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Persistent link: https://EconPapers.repec.org/RePEc:spr:sprchp:978-3-031-32542-7_3

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DOI: 10.1007/978-3-031-32542-7_3

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