Artificial Intelligence and Tutoring Systems: Computational and Cognitive Approaches to the Communication of Knowledge focuses on the cognitive approaches, methodologies, principles, and concepts involved in the communication of knowledge. The publication first elaborates on knowledge communication systems, basic issues, and tutorial dialogues. Concerns cover natural reasoning and tutorial dialogues, shift from local strategies to multiple mental models, domain knowledge, pedagogical knowledge, implicit versus explicit encoding of knowledge, knowledge communication, and practical and theoretical implications. The text then examines interactive simulations, existing CAI traditions, and learning environments. The manuscript elaborates on knowledge communication, didactics, and diagnosis. Topics include knowledge presentation and communication, pedagogical contexts, target levels of didactic operations, behavioral and epistemic diagnosis, and aspects of diagnostic experience. The publication is a dependable reference for researchers interested in the computational and cognitive approaches to the communication of knowledge.

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 volume constitutes the proceedings of the 17th International Conference on Intelligent Tutoring Systems, ITS 2021, held in Athens, Greece, in June 2021. Due to COVID-19 pandemic the conference was held virtually. The 22 full papers, 22 short papers and 18 other papers presented in this volume were carefully reviewed and selected from 87 submissions. Conforming to the current move of education, work and leisure online, the title of ITS 2021 was “Intelligent Tutoring Systems in an online world”. Its objective was to present academic and research achievements of computer and cognitive sciences, artificial intelligence, and, due to its recent emergence, specifically, deep learning in tutoring and education

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

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 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.