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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.
*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.
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Hugh Burns, Carol A. Luckhardt, Hugh Burns, James W. Parlett, Carol L. Redfield
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