Artificial Intelligence And Learning Environments

These essays explore cognitively oriented empirical trials that use AI programming as a modeling methodology and that can provide valuable insight into a variety of learning problems. New perspectives and techniques are shaping the field of computer-aided instruction. These essays explore cognitively oriented empirical trials that use AI programming as a modeling methodology and that can provide valuable insight into a variety of learning problems. Drawing on work in cognitive theory, plan-based program recognition, qualitative reasoning, and cognitive models of learning and teaching, this exciting research covers a wide range of alternatives to tutoring dialogues. Contents Artificial Intelligence and Learning Environments, William J. Clancey, Elliot Soloway * Cognitive Modeling and Intelligence Tutoring, John R. Anderson, C. Franklin Boyle, Albert T. Corbett, Matthew W. Lewis * Understanding and Debugging Novice Programs, W. Lewis Johnson * Causal Model Progressions as a Foundation for Intelligent Learning Environments, Barbara Y. White and John R. Frederiksen

As explored in this open access book, higher education in STEM fields is influenced by many factors, including education research, government and school policies, financial considerations, technology limitations, and acceptance of innovations by faculty and students. In 2018, Drs. Ryoo and Winkelmann explored the opportunities, challenges, and future research initiatives of innovative learning environments (ILEs) in higher education STEM disciplines in their pioneering project: eXploring the Future of Innovative Learning Environments (X-FILEs). Workshop participants evaluated four main ILE categories: personalized and adaptive learning, multimodal learning formats, cross/extended reality (XR), and artificial intelligence (AI) and machine learning (ML). This open access book gathers the perspectives expressed during the X-FILEs workshop and its follow-up activities. It is designed to help inform education policy makers, researchers, developers, and practitioners about the adoption and implementation of ILEs in higher education.

This work reports on research into intelligent systems, models, and architectures for educational computing applications. It covers a wide range of advanced information and communication and computational methods applied to education and training.

This book systematically reviews a broad range of cases in education that utilize cutting-edge AI technologies. Furthermore, it introduces readers to the latest findings on the scope of AI in education, so as to inspire researchers from non-technological fields (e.g. education, psychology and neuroscience) to solve education problems using the latest AI techniques. It also showcases a number of established AI systems and products that have been employed for education. Lastly, the book discusses how AI can offer an enabling technology for critical aspects of education, typically including the learner, content, strategy, tools and environment, and what breakthroughs and advances the future holds. The book provides an essential resource for researchers, students and industrial practitioners interested and engaged in the fields of AI and education. It also offers a convenient handbook for non-professional readers who need a primer on AI in education, and who want to gain a deeper understanding of emerging trends in this domain.

Artificial Intelligence in Education conference 2009 (AIED) is part of a series of biennial international conferences for top quality research in intelligent systems and cognitive science for educational computing applications. This title covers papers presented at the Artificial Intelligence in Education conference 2009 (AIED).

This volume will be the proceedings for the 9th International Conference on Artificial Intelligence in Education (AI-ED 1999). This is one of a series of international conferences in this area and it is designed to report on state of the art research in the field of AI in Education. This field is interdisciplinary and brings together researchers from the domains of computer science, cognitive science, education, psychology, linguistics, and engineering (to name a few). Researchers will contribute manuscripts to this volume, providing opportunities for cross-fertilization of information across disciplines that will lead to advances and new applications in the field. New computational technologies will be described that support learning, exploration, and collaboration. Technologies can support both the individual and small groups of individuals who work collaboratively to solve problems and learn new materials. New methodologies for supporting and documenting the learning process in both these situations are being developed and are described in this volume.

The nature of technology has changed since Artificial Intelligence in Education (AIED) was conceptualised as a research community and Interactive Learning Environments were initially developed. Technology is smaller, more mobile, networked, pervasive and often ubiquitous as well as being provided by the standard desktop PC. This creates the potential for technology supported learning wherever and whenever learners need and want it. However, in order to take advantage of this potential for greater flexibility we need to understand and model learners and the contexts with which they interact in a manner that enables us to design, deploy and evaluate technology to most effectively support learning across multiple locations, subjects and times. The AIED community has much to contribute to this endeavour. This publication contains papers, posters and tutorials from the 2007 Artificial Intelligence in Education conference in Los Angeles, CA, USA.

The increasingly pervasive use of digital technology has catapulted society into an interconnected world where the natural boundaries between humankind and machine, virtual and real, individual and community have become less perceptible. As individuals interact with different digital technologies, they must build a digital intelligence, which must be further cultivated as it is a key competency for the future of school and work. Digital intelligence includes understanding the mutual strengths between people and technology, as well as developing an awareness in the use of digital tools in order to avoid common threats such as cyberbullying, addiction to video games, techno-stress, and more. As adolescents continue to engage with virtual reality and 3D virtual worlds where the online and offline overlap and coincide, it is important to build this intelligence as well as utilize these technologies to promote successful learning. The Handbook of Research on Teaching With Virtual Environments and AI explores the new personalized educational opportunities that are available with digital technology and virtual environments that can be used within education. This book focuses on the use of these tools and how to navigate the use of new technologies such as AI and virtual environments for educational practices. While highlighting topics such as virtual worlds, game-based learning, intelligent tutoring, augmented reality, and more, this book is ideal for teachers, administrators, technologists, educational software developers, IT specialists, practitioners, researchers, academicians, and students interested in how virtual environments and AI are being implemented in teaching practices.