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E-raamat: Affective Feedback in Intelligent Tutoring Systems: A Practical Approach

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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.
1 Introduction 1(4)
References
2(3)
2 Feedback and Affectivity in Intelligent Tutoring Systems 5(22)
2.1 Intelligent Tutoring Systems
5(4)
2.1.1 Intelligent Tutoring System Architecture
7(2)
2.2 Affective Feedback in Learning Environment
9(7)
2.2.1 Feedback in Learning
10(2)
2.2.2 Affective Interaction Between Tutor and Student
12(4)
2.3 Affective Feedback in Intelligent Tutoring Systems
16(2)
2.4 Motivation Assessment
18(3)
2.5 Summary
21(1)
References
21(6)
3 A Model for Providing Affective Feedback 27(20)
3.1 Ontology Conceptual Design
27(10)
3.1.1 Glossary of Concepts
28(1)
3.1.2 Taxonomy
28(2)
3.1.3 Relations
30(1)
3.1.4 Dictionary of Concepts
30(3)
3.1.5 Ontology's Quantitative Evaluation
33(2)
3.1.6 Ontology's Qualitative Evaluation
35(2)
3.2 Affective Feedback Model
37(4)
3.2.1 Exploratory Study of the Characteristics of Feedback
37(4)
3.3 Context-Free Grammar
41(2)
3.4 Setting Affective Dataset of Phrases
43(1)
3.5 Summary
44(1)
References
45(2)
4 Implementation of the Affective Feedback Model 47(12)
4.1 TIPOO
47(3)
4.1.1 TIPOO Views
48(1)
4.1.2 TIPOO Models
48(1)
4.1.3 TIPOO Controllers
49(1)
4.2 Affective Feedback System
50(5)
4.2.1 Architecture
52(3)
4.3 Integration of the Affective Feedback System in a Intelligent Tutoring System
55(1)
4.4 Summary
55(2)
References
57(2)
5 The Impact of the Affective Feedback on Student Motivation to Learn 59(18)
5.1 Instrument
59(1)
5.2 Analysis of the Relationship Between Motivation to Learn and Some Aspects of Student Profile
60(6)
5.2.1 Experimental Design
61(1)
5.2.2 General Results
62(1)
5.2.3 Gender Analysis
62(2)
5.2.4 Academic Performance Analysis
64(2)
5.3 Relationship Between Motivation to Learn and Personality
66(3)
5.3.1 Experimental Design
66(1)
5.3.2 General Results
67(1)
5.3.3 Personality Analysis
68(1)
5.4 Motivation in Prior and Post Interaction with the System
69(2)
5.4.1 Experimental Design
69(1)
5.4.2 Results
70(1)
5.5 Affective Feedback Versus Non-affective Feedback
71(3)
5.5.1 Experimental Design
71(1)
5.5.2 Results
72(2)
5.6 Summary of the Findings
74(1)
References
74(3)
6 Impact and Applicability of the Affective Feedback 77(6)
6.1 Theoretical Implications
77(2)
6.2 Practical Implications
79(1)
6.3 Limitations
80(1)
References
81(2)
7 Conclusions 83