Affective Feedback in Intelligent Tutoring Systems: A Practical Approach (Human-Computer Interaction Series)

Affective components are as important as cognitive components in tutoring assisted learning process. Feedback from tutors is essential in keeping students motivated. Affectivity and motivation are also significant in computer-based tutoring systems. However, several educational frameworks do not include this kind of interaction between students and tutoring systems. In those cases, the students learning interest and motivation to learn could be negatively affected, and student profits from the system could be impoverished. This is why tutoring systems need to provide direct and affective interaction with students; it can encourage them and increase the motivation to learn.

This book introduces a broad range of topics in affective learning in computer-based systems. The text offers a deep conceptual background, covering relevant concepts of affectivity, feedback and motivational components in learning environments. It describes the design of a proposed model for providing affective feedback, the mathematical validation of the conceptual model and its implementation. Moreover, it presents an analysis of the impact of the affective feedback on student motivation to learn. Finally, the book offers research perspectives of the impact and applicability of the affective feedback in computer-based tutoring environments.

Affective Feedback in Intelligent Tutoring Systems can be used by human tutors who want to include motivational and affective elements in the learning process, researchers in Human-Computer Interaction and Education and by software developers who want to develop learning systems using these elements.

Affective components are as important as cognitive components in tutoring assisted learning process. Feedback from tutors is essential in keeping students motivated. Affectivity and motivation are also significant in computer-based tutoring systems. However, several educational frameworks do not include this kind of interaction between students and tutoring systems. In those cases, the students learning interest and motivation to learn could be negatively affected, and student profits from the system could be impoverished. This is why tutoring systems need to provide direct and affective interaction with students; it can encourage them and increase the motivation to learn.

This book introduces a broad range of topics in affective learning in computer-based systems. The text offers a deep conceptual background, covering relevant concepts of affectivity, feedback and motivational components in learning environments. It describes the design of a proposed model for providing affective feedback, the mathematical validation of the conceptual model and its implementation. Moreover, it presents an analysis of the impact of the affective feedback on student motivation to learn. Finally, the book offers research perspectives of the impact and applicability of the affective feedback in computer-based tutoring environments.

Affective Feedback in Intelligent Tutoring Systems can be used by human tutors who want to include motivational and affective elements in the learning process, researchers in Human-Computer Interaction and Education and by software developers who want to develop learning systems using these elements.