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.

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.

Learning Issues for Intelligent Tutoring Systems arrays the most current and exciting research in this dynamic and growing area of cognitive science. The various contributions address the design and use of instructional systems as well as the important theoretical and practical questions involved in implementing knowledge-based systems. This book offers complete and up-to-date reviews of the major research programs in computer-aided instruction and intelligent tutoring systems. Learning Issues for Intelligent Tutoring Systems is an important and useful introduction to this rapidly changing field.

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 proceedings of the 14th International Conference on Intelligent Tutoring Systems, IST 2018, held in Montreal, Canada, in June 2018. The 26 full papers and 22 short papers presented in this volume were carefully reviewed and selected from 120 submissions. In the back matter of the volume 20 poster papers and 6 doctoral consortium papers are included. They deal with the use of advanced computer technologies and interdisciplinary research for enabling, supporting and enhancing human learning.

Modern education has increased its reach through ICT tools and techniques. To manage educational data with the help of modern artificial intelligence, data and web mining techniques on dedicated cloud or grid platforms for educational institutes can be used. By utilizing data science techniques to manage educational data, the safekeeping, delivery, and use of knowledge can be increased for better quality education. Utilizing Educational Data Mining Techniques for Improved Learning: Emerging Research and Opportunities is a critical scholarly resource that explores data mining and management techniques that promote the improvement and optimization of educational data systems. The book intends to provide new models, platforms, tools, and protocols in data science for educational data analysis and introduces innovative hybrid system models dedicated to data science. Including topics such as automatic assessment, educational analytics, and machine learning, this book is essential for IT specialists, data analysts, computer engineers, education professionals, administrators, policymakers, researchers, academicians, and technology experts.

This book explores the intersection of tutoring and intelligent tutoring systems. The process of tutoring has a long history within learning settings, and this effective method has led to attempts to automate the process via intelligent tutoring system research areas. Intelligent Tutoring Systems (ITS) are increasingly being used in a wide range of educational settings to enhance student learning. They are also used frequently as platforms for research on educational psychology and artificial intelligence. ITS can assess a wide variety of learner characteristics and adapt instruction according to principles of learning. Their effectiveness allegedly derives from their ability to provide detailed guidance to learners and to adapt promptly to individual learner's needs that are tracked at a fine grained level. Examples of such tutoring technologies include writing environments for guided inquiry learning, environments for collaborative problem solving or discussion, natural language processing and dialogue in tutoring systems, modeling and shaping affective states, interactive simulations of complex systems, ill-defined domains, and adaptive educational games. At their core, these systems rely on our basic knowledge of effective human tutoring. This book starts with a presentation of learning frameworks related to tutoring and ITS. This is followed by examples of best practices of tutoring and learning strategies by implementing within specific ITS. Finally, it presents examples for evaluating the effectiveness of tutoring systems.

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 collection of essays -- each of which treats an integral aspect of the field -- defines several key concepts and their interrelationships, outlines basic research issues, and discusses near-term applications projects. The book examines three foundations of ITSs in detail -- expert, student diagnostic, and instructional or curricular knowledge -- and describes: * How they are embodied in computer-assisted instructional environments * How these systems accrue the advantages of advanced computer interface technologies * How ITSs will emerge in the real world of complex problem solving * How researchers must learn to evaluate the effectiveness and overall quality of these dynamic systems in a world where machine tutoring may one day be taken for granted. Justine Wise Polier (1903-1987) was educated at Bryn Mawr, Radcliffe, and Barnard. She earned her law degree from Yale Law School where she was editor of the Yale Law Journal. In 1935, she was appointed Justice of the Family Court where she sat for 38 years. Judge Polier took a leave from the bench in 1941 when she was appointed special advisor to Eleanor Roosevelt at the Office of Civilian Defense in Washington. She also served as Chairman of the Committee on Mental Health for New York. Judge Polier was a founder and president of the Wiltwyck School; vice president of the Citizens Committee for Children of N.Y.; vice president of the American Jewish Congress; Delegate to the White House Conferences on Children and on Education. Judge Polier was a member of the Institute of Judicial Administration, American Bar Association. She was on the editorial board of the International Juridical Association and was awarded the 1964 Isaac Ray Award by the American Psychiatric Association for "contributions to the improvement of the relations of Law and Psychiatry." Following her retirement from the bench, she served as the director of the Juvenile Judge division of the Children's Defense Fund. During her illustrious career, Judge Polier was the recipient of numerous awards including: the Citation for Distinguished Service to the City of New York, 1973; the Human Services Award from the New York and Bronx Mental Health Association, 1973; the Eleanor Roosevelt Humanitarian Award from the Board of Directors of Wiltwyck School, 1975. Judge Polier also published numerous reports and several books including: Everyone's Children, Nobody's Child; Back to What Woodshed?; A View from the Bench; and The Rule of Law and the Role of Psychiatry.

This book presents the refereed proceedings of the Third International Conference on Intelligent Tutoring Systems, ITS '96, held in Montreal, Canada, in June 1996. The book contains 69 revised papers selected from a total of 128 submissions; also included are six invited papers from well-known speakers. All in all, the book reflects the state-of-the-art in the area. In particular the following topics are covered: advising systems, ITS architectures, cognitive models, design issues, empirical studies, formal models, learning environments, real-world applications, software tools for tutoring, student modelling, teaching and learning strategies, and multimedia and WWW.