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Machine Learning Paradigms

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Cover of 'Machine Learning Paradigms'

Table of Contents

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    Book Overview
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    Chapter 1 Machine Learning Paradigms
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    Chapter 2 Using a Multi Module Model for Learning Analytics to Predict Learners’ Cognitive States and Provide Tailored Learning Pathways and Assessment
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    Chapter 3 Analytics for Student Engagement
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    Chapter 4 Assessing Self-regulation, a New Topic in Learning Analytics: Process of Information Objectification
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    Chapter 5 Learning Feedback Based on Dispositional Learning Analytics
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    Chapter 6 The Variability of the Reasons for Student Dropout in Distance Learning and the Prediction of Dropout-Prone Students
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    Chapter 7 An Architectural Perspective of Learning Analytics
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    Chapter 8 Multimodal Learning Analytics in a Laboratory Classroom
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    Chapter 9 Dashboards for Computer-Supported Collaborative Learning
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    Chapter 10 Learning Analytics in Distance and Mobile Learning for Designing Personalised Software
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    Chapter 11 Optimizing Programming Language Learning Through Student Modeling in an Adaptive Web-Based Educational Environment
Attention for Chapter 6: The Variability of the Reasons for Student Dropout in Distance Learning and the Prediction of Dropout-Prone Students
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