Table of Contents
Table of Contents
Preface
Chapter 1. A Case Based Reasoning Framework to Structure a Knowledge Base in Intelligent Tutoring Systems
Joice Barbosa Mendes, Isabela Neves Drummond and Alexandre Carlos BrandĂŁo Ramos (Federal University of Itajuba, UNIFEI, Brazil)
Chapter 2. Intelligent Tutoring Systems in the Medical Domain: Fostering Self-Regulatory Skills in Problem-Solving
Poitras, E., Lajoie, S. P., Jarrell, A., Doleck, T., and Naismith, L. (University of Utah, Utah, USA, and others)
Chapter 3. Predictive Student Action Model for Procedural Training in 3D Virtual Environments
Diego Riofrio-Luzcando and Jaime RamĂrez (Universidad PolitĂ©cnica de Madrid, Spain)
Chapter 4. Intelligent Automated Assessment and Tutoring: A Pairing of an Intelligent Tutoring System with an Automated Assessment Engine for U.S. Navy Shiphandling Training
Alan D. Koenig, John J. Lee and Elizabeth O. Bratt (CRESST/University of California, Los Angeles, California, USA, and others)
Chapter 5. EEG-Based User Performance Prediction Using Random Forest in a Dynamic Learning Environment
Gustavo A. Lujan-Moreno, Robert Atkinson and George Runger (Arizona State University, Arizona, USA)
Chapter 6. Opportunities from Usability Design for Improving Intelligent Tutoring Systems
Rehman Chughtai, Shasha Zhang and Scotty D. Craig (Arizona State University, Arizona, USA)
Chapter 7. Intelligent Tutoring Systems for Literacy: Existing Technologies and Continuing Challenges
Matthew E. Jacovina and Danielle S. McNamara (Arizona State University, Arizona, USA)
Chapter 8. Comparing Learning Outcomes and Implementation Factors from Student-Managed vs. Teacher-Managed Intelligent Tutoring Systems
Kausalai (Kay) Wijekumar, Bonnie J.F. Meyer, Karen R. Harris, Steve Graham, and Andrea Beerwinkle (Texas A&M University, Texas, USA, and others)
Index