Part 1:Introduction 1. Introduction 1.1 Need of an Intelligent Tutoring System. 1.2 A Growing Field: Intelligent Tutoring System 1.3 Intelligent Tutoring System Architecture 2. Organization of Content of this Book Part 2 : Domain Modeling 2.1 Introduction to Domain Model 2.

2 The Epistemological Perspective of Domain Knowledge 2.3 Preliminary Research on Domain Model in ITS 2.4 Experiential (Tacit Domain Knowledge) 2.5 Experiential Knowledge Acquisition Approaches 2.5.1 Cognitive Map 2.5.2 Causal Map 2.

5.3 Self Q 2.5.4 Semi-Structured 2.6 Summary Part 3 : Pedagogy Modeling 3.1 Introduction to Pedagogy Model 3.2 Preliminary Research on Pedagogy Model in ITS 3.3 Path Sequencing of Learning Material in Learning Systems 3.

4 Impact of Emotion Capturing in Learning System 3.4.1 Emotion Recognition in Learning System 3.5 Summary Part 4: Building SeisTutor Intelligent Tutoring System for Experiential Learning Domain 4.1. Introduction 4.2. Seismic Data Interpretation: as a Experiential Learning Domain 4.

3. Development of Adaptive Domain Model 4.3.1. Phase 1: Tacit Knowledge Acquisition and Characterization 4.3.2. Phase 2: Knowledge Representation: Multilevel hierarchical model 4.

4. Summary Part 5: Pedagogy model for Building SeisTutor Intelligent Tutoring System. 5.1. Introduction 5.2. Workflow of SeisTutor 5.2.

1. Development of Custom-Tailored Curriculum 5.2.2. Development of Tutoring Strategy Recommendation 5.2.3. CNN based Emotion Recognition Model 5.

2.4. Development of Performance Analyzer Model 5.3. Summary Part 6: Execution of Developed Intelligent Tutoring System 6.1 Implementation of a System 6.2 Learner Interface Model 6.3 Domain Model 6.

4 Learner Model 6.5 Pedagogy Model 6.5.1 Performance Analyzer model 6.6 Learner Statistics 6.7 Learner Feedback 6.8 Summary Part 7: Assessment of Developed Intelligent Tutoring System 7.1 Overview 7.

2 Learner performance metrics 7.3 SeisTutor: a Comparative Analysis with Teachable, My-Moodle and Course-Builder Learning Management System 7.4 Summary Part 8: Analysis & Metrics 8.1 Critical analysis of Performance Metrics 8.2 Statistical Analysis of Learner Engagement 8.3 Learner Learning Analysis using Evaluation Model "Kirkpatrick" 8.4 Future Scope References.