May the Forcing Functions be with You: The Stimulating World of AIED and ITS Research It is my pleasure to write the foreword for Advances in Intelligent Tutoring S- tems. This collection, with contributions from leading researchers in the field of artificial intelligence in education (AIED), constitutes an overview of the many challenging research problems that must be solved in order to build a truly intel- gent tutoring system (ITS). The book not only describes some of the approaches and techniques that have been explored to meet these challenges, but also some of the systems that have actually been built and deployed in this effort. As discussed in the Introduction (Chapter 1), the terms “AIED” and “ITS” are often used int- changeably, and there is a large overlap in the researchers devoted to exploring this common field. In this foreword, I will use the term “AIED” to refer to the - search area, and the term “ITS” to refer to the particular kind of system that AIED researchers build. It has often been said that AIED is “AI-complete” in that to produce a tutoring system as sophisticated and effective as a human tutor requires solving the entire gamut of artificial intelligence research (AI) problems.

This book is divided into three parts: machine learning and problem solving, machine teaching, and Real-world applications. Each of these areas is in some sense critical to the present and future credibility of AI as a discipline.

Building Intelligent Interactive Tutors discusses educational systems that assess a student's knowledge and are adaptive to a student's learning needs. The impact of computers has not been generally felt in education due to lack of hardware, teacher training, and sophisticated software. and because current instructional software is neither truly responsive to student needs nor flexible enough to emulate teaching. Dr. Woolf taps into 20 years of research on intelligent tutors to bring designers and developers a broad range of issues and methods that produce the best intelligent learning environments possible, whether for classroom or life-long learning. The book describes multidisciplinary approaches to using computers for teaching, reports on research, development, and real-world experiences, and discusses intelligent tutors, web-based learning systems, adaptive learning systems, intelligent agents and intelligent multimedia. It is recommended for professionals, graduate students, and others in computer science and educational technology who are developing online tutoring systems to support e-learning, and who want to build intelligence into the system. Combines both theory and practice to offer most in-depth and up-to-date treatment of intelligent tutoring systems available Presents powerful drivers of virtual teaching systems, including cognitive science, artificial intelligence, and the Internet Features algorithmic material that enables programmers and researchers to design building components and intelligent systems

The power and potential of current ITS technology is described here by the designers and builders of major ITS projects. The book illustrates how, in less than a decade, the field of Intelligent Tutoring Systems has advanced from experimental systems in universities to systems that perform practical, real-world tasks. Intelligent Tutoring Systems: Lessons Learned provides a first-hand, detailed account of how these systems were designed and built out of state-of-the-art technology. The essays build on the basic research foundations of the field and define the abilities and limitations of current knowledge. With this critical volume, teachers and industrial trainers have a realistic view of the future of their professions, and students, researchers, and professionals in AI, education, cognitive science, and psychology have both an introduction to the field and a comprehensive reference.

This book constitutes the refereed proceedings of the 9th International Conference on Intelligent Tutoring Systems, ITS 2008, held in Montreal, Canada, in June 2008. The 63 revised full papers and 61 poster papers presented together with abstracts of 5 keynote talks were carefully reviewed and selected from 207 submissions. The papers are organized in topical sections on emotion and affect, tutor evaluation, student modeling, machine learning, authoring tools , tutor feedback and intervention, data mining, e-learning and Web-based ITS, natural language techniques and dialogue, narrative tutors and games, semantic Web and ontology, cognitive models, and collaboration.

This is a collection of essays on issues related to the evolutionary design and the practical future of intelligent tutoring systems. Following in the tradition of Foundations of Intelligent Tutoring Systems and Intelligent Tutoring Systems: Lessons Learned, this volume examines some of the visions and near-term issues that have been further explored and better defined since those groundbreaking books first appeared. Questions addressed in this volume include: *How can knowledge bases generate explanations? *Will case-based reasoning techniques be worth pursuing in the ITS framework? *Will high performance skills be successfully taught in an ITS design? *Are there dimensions of ITS design which the research laboratories are ignoring, and ignoring at the customer's peril? Of particular importance to those engaged in research and development, this book will be of value to all who wish to apprise themselves of the advances being made in the rapidly evolving field of intelligent tutoring systems.

This volume explores advances in theory, research and technologies needed to advance the state of the art of intelligent tutoring systems (ITSs) for teams.