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Computer Science - Information Systems and Applications | Advances in Intelligent Tutoring Systems

Advances in Intelligent Tutoring Systems

Nkambou, Roger, Mizoguchi, Riichiro, Bourdeau, Jacqueline (Eds.)

2010, XXII, 510 p.

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  • Presents recent results in intelligent tutoring systems
  • Written by leading experts in this field State-of-the-Art book
The idea for this book on Intelligent Tutoring Systems (ITS) was sparked by the success of the ITS’08 international conference. The number of presentations and their quality bore witness to the vitality and maturity of the field, and the enthusiasm of the participants held out a promise of sustainability and innovative research. Long life to ITS research! The book is divided into five parts. The introductory chapters to these parts, which summarize foundations, developments, strengths and weaknesses in each of the areas covered, are addressed to all readers. For those who want more in-depth knowledge, we give the floor to researchers who present their work, their results, and their view of what the future holds. It is our hope that all readers will find the book informative and thought-provoking.

Content Level » Research

Keywords » Artificial Intelligence in Education - Computational Intelligence - E-learning - Emotion - Intellignet Tutoring - Simulation - knowledge - learning - modeling - natural language - ontology

Related subjects » Artificial Intelligence - Computational Intelligence and Complexity - Information Systems and Applications

Table of contents 

Introduction: What Are Intelligent Tutoring Systems, and Why This Book?.- Introduction: What Are Intelligent Tutoring Systems, and Why This Book?.- I: Domain Modeling.- Modeling the Domain: An Introduction to the Expert Module.- Rule-Based Cognitive Modeling for Intelligent Tutoring Systems.- Modeling Domains and Students with Constraint-Based Modeling.- Building Intelligent Tutoring Systems for Ill-Defined Domains.- A Survey of Domain Ontology Engineering: Methods and Tools.- II: Tutor Modeling and Learning Environments.- Modeling Tutoring Knowledge.- Decision-Making in Cognitive Tutoring Systems.- Tutorial Dialog in Natural Language.- Affective Tutors: Automatic Detection of and Response to Student Emotion.- Ontology-Based Formal Modeling of the Pedagogical World: Tutor Modeling.- Using Drawings in Knowledge Modeling and Simulation for Science Teaching.- III: Student Modeling.- Student Modeling.- Bayesian Student Modeling.- Open Learner Models.- Mining Data for Student Models.- Managing Learner’s Affective States in Intelligent Tutoring Systems.- IV: ITS Authoring and Applications.- Building Intelligent Tutoring Systems: An Overview.- Authoring Problem-Solving Tutors: A Comparison between ASTUS and CTAT.- Open Content Authoring Tools.- The Andes Physics Tutoring System: An Experiment in Freedom.- V: Social, Cultural and Privacy Issues.- Computer Supported Collaborative Learning and Intelligent Tutoring Systems.- Preserving Learners’ Privacy.- Infusing Cultural Awareness into Intelligent Tutoring Systems for a Globalized World.

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