Machine Learning Paradigms

Chapter 1 Machine Learning Paradigms

Chapter 2 Using a Multi Module Model for Learning Analytics to Predict Learners’ Cognitive States and Provide Tailored Learning Pathways and Assessment

Chapter 3 Analytics for Student Engagement

Chapter 4 Assessing Self-regulation, a New Topic in Learning Analytics: Process of Information Objectification

Chapter 5 Learning Feedback Based on Dispositional Learning Analytics

Chapter 6 The Variability of the Reasons for Student Dropout in Distance Learning and the Prediction of Dropout-Prone Students

Chapter 7 An Architectural Perspective of Learning Analytics

Chapter 8 Multimodal Learning Analytics in a Laboratory Classroom

Chapter 10 Learning Analytics in Distance and Mobile Learning for Designing Personalised Software

Chapter 11 Optimizing Programming Language Learning Through Student Modeling in an Adaptive Web-Based Educational Environment