Cognitive psychologists have found the production systems class of computer simulation models to be one of the most direct ways to cast complex theories of human intelligence. There have been many scattered studies on production systems since they were first proposed as computational models of human problem-solving behavior by Allen Newell some twenty years ago, but this is the first book to focus exclusively on these important models of human cognition, collecting and giving many of the best examples of current research. In the first chapter, Robert Neches, Pat Langley, and David Klahr provide an overview of the fundamental issues involved in using production systems as a medium for theorizing about cognitive processes, emphasizing their theoretical power. The remaining chapters take up learning by doing and learning by understanding, discrimination learning, learning through incremental refinement, learning by chunking, procedural earning, and learning by composition. A model of cognitive development called BAIRN is described, and a final chapter reviews John Anderson's ACT theory and discusses how it can be used in intelligent tutoring systems, including one that teaches LISP programming skills. In addition to the editors, the contributors are Yuichiro Anzai (Hokkaido University, Japan), Paul Rosenbloom (Stanford) and Allen Newell (Carnegie-Mellon), Stellan Ohlsson (University of Pittsburgh), Clayton Lewis (University of Colorado, Boulder), Iain Wallace and Kevin Bluff (Deakon University, Australia), and John Anderson (Carnegie-Mellon). David Klahr is Professor and Head of the Department of Psychology at Carnegie-Mellon University. Pat Langley is Associate Professor, Department ofInformation and Computer Science, University of California, Irvine, and Robert Neches is Research Computer Scientist at University of Southern California Information Sciences Institute. "Production System Models of Learning and Development" is included in the series Computational Models of Cognition and Perception, edited by Jerome A. Feldman, Patrick J. Hayes, and David E.Rumelhart. A Bradford Book.

This book constitutes the refereed proceedings of the First International Conference on Adaptive Instructional Systems, AIS 2019, held in July 2019 as part of HCI International 2019 in Orlando, FL, USA. HCII 2019 received a total of 5029 submissions, of which 1275 papers and 209 posters were accepted for publication after a careful reviewing process. The 50 papers presented in this volume are organized in topical sections named: Adaptive Instruction Design and Authoring, Interoperability and Standardization in Adaptive Instructional Systems, Instructional Theories in Adaptive Instruction, Learner Assessment and Modelling, AI in Adaptive Instructional Systems, Conversational Tutors.

Adaptive Learning Environments (ALEs) can be viewed as the intersection of two traditionally distinct areas of research: instructional science and computer science. They encompass intelligent tutoring systems, interactive learning environments, and situated learning environments. There is increasing interest in effective instructional systems from education, industry, military and government sectors. Given recent advances in hardware architecture and reduction of hardware costs, the time is right to define the next steps in research and development of ALEs. This book is an outgrowth of the presentations and discussions that took place at the NATO Advanced Study Institute held at the University of Calgary in July 1990. It contains chapters from both researchers in instructional science and researchers in computer science on the following topics: - Systems and architectures for instruction - Representing curriculum and designing instructional tasks - Environments to support learning - Diagnosing students' learning and adjusting plans for instruction - Models of students' metacognition, motivation and learning strategies - Student-system interactions. The book containsintroductions/critiques of each pair of chapters, and a final chapter discusses the synthesis of instructional science and computer science.

The Cambridge Handbook of Computational Cognitive Sciences is a comprehensive reference for this rapidly developing and highly interdisciplinary field. Written with both newcomers and experts in mind, it provides an accessible introduction of paradigms, methodologies, approaches, and models, with ample detail and illustrated by examples. It should appeal to researchers and students working within the computational cognitive sciences, as well as those working in adjacent fields including philosophy, psychology, linguistics, anthropology, education, neuroscience, artificial intelligence, computer science, and more.

Although the ability to retain, process, and project prior experience onto future situations is indispensable, the human mind also possesses the ability to override experience and adapt to changing circumstances. Cognitive scientist Stellan Ohlsson analyzes three types of deep, non-monotonic cognitive change: creative insight, adaptation of cognitive skills by learning from errors, and conversion from one belief to another, incompatible belief. For each topic, Ohlsson summarizes past research, re-formulates the relevant research questions, and proposes information-processing mechanisms that answer those questions. The three theories are based on the principles of redistribution of activation, specialization of practical knowledge, and re-subsumption of declarative information. Ohlsson develops the implications of those mechanisms by scaling their effects with respect to time, complexity, and social interaction. The book ends with a unified theory of non-monotonic cognitive change that captures the abstract properties that the three types of change share.

This book is based on the workshop that kickstarted the NATO Science Committee Special Programme on Advanced Educational Technology. We invited the leaders in the field to attend this inaugural meeting and were delighted by the quality of the attendance, the papers delivered at the workshop and this book. Many of the authors have subsequently run other meetings funded by the Special Programme and have, or are in the process of, editing books which focus on particular topics. This book covers all the major themes in the area ranging from fundamental theoretical work to empirical studies of state of the art technological innovations. Tim O'Shea chaired the NATO Survey Group which planned the Programme and the subsequent Panel which disbursed funds in the first two years of the Programme. He would like to thank the other group and panel members, namely, Professor N Balacheff, Professor D Bjomer, Professor H Bouma, Professor P C Duchastel, Professor A Dias de Figueiredo, Dr D Jonassen and Professor T Liao. He would like to offer his special thanks to Dr L V da Cunha the NATO Programme Director for his unfailing support and patience. Eileen Scanlon was the Director of the Workshop which is the basis of this book. She offers heartfelt thanks to the contributors and to the following who provided practical help with the meeting or the production of this book: Mrs Pauline Adams, Dr Mike Baker, Mrs Kathy Evans, Mrs Patricia Roe, Mr Dave Perry and Ms Fiona Spensley.

An adjunct to the increased emphasis on developing students' critical thinking and higher order skills is the need for methods to monitor and evaluate these abilities. These papers provide insight into current techniques and examine possibilities for the future. The contributors to Diagnostic Monitoring of Skill and Knowledge Acquisition focus on two beliefs: that new kinds of tests and assessment methods are needed; and that instruction and learning can be improved by developing new assessment methods based on work in cognitive science.

Although computational modeling is now a widespread technique in cognitive science and in psychology, relatively little work in developmental psychology has used this technique. The approach is not entirely new, as a small group of researchers has attempted to create computational accounts of cognitive developmental phenomena since the inception of the technique. It should seem obvious that transition mechanisms -- or how the system progresses from one level of competence to the next -- ought to be the central question for investigation in cognitive developmental psychology. Yet, if one scans the literature of modern developmental studies, it appears that the question has been all but ignored. However, only recently have advances in computational technology enabled the researcher access to fully self-modifying computer languages capable of simulating cognitive change. By the beginning of the 1990s, increasing numbers of researchers in the cognitive sciences were of the opinion that the tools of mathematical modeling and computer simulation make theorizing about transition mechanisms both practical and beneficial -- by using both traditional symbolic computational systems and parallel distributed processing or connectionist approaches. Computational models make it possible to define the processes that lead to a system being transformed under environmental influence from one level of competence observed in children to the next most sophisticated level. By coding computational models into simulations of actual cognitive change, they become tangible entities that are accessible to systematic study. Unfortunately, little of what has been produced has been published in journals or books where many professionals would easily find them. Feeling that developmental psychologists should be exposed to this relatively new approach, a symposium was organized at the biennial meeting of the Society for Research in Child Development. The "cost of entry" was that speakers had to have a running computational model of a documented cognitive transition. Inspired by that conference, this volume is the first collection where each content chapter presents a fully implemented, self-modifying simulation of some aspect of cognitive development. Previous collections have tended to discuss general approaches -- less than fully implemented models -- or non self-modifying models. Along with introductory and review chapters, this volume presents a set of truly "developmental" computational models -- a collection that can inform the interested researcher as well as form the basis for graduate-level courses.