Based on the formal concept of "knowledge structures" originally proposed by Jean-Claude Falmagne and Jean-Paul Doignon, this book contains descriptions of methodological developments and experimental investigations as well as applications for various knowledge domains. The authors address three main topics: * theoretical issues and extensions of Doignon & Falmagne's theory of knowledge structures; * empirical validations of specific problem types and knowledge domains, such as sentence comprehension, problem solving in chess, inductive reasoning, elementary mathematical reasoning, and others; and * application of knowledge structures in various contexts, including knowledge assessment, intelligent tutoring systems, and motor learning. Unlike most other approaches in the literature in cognitive psychology, this book provides both a rigorous mathematical formulation of knowledge-related psychological concepts and its empirical validation by experimental data.

The book describes up-to-date applications and relevant theoretical results. These applications come from various places, but the most important one, numerically speaking, is the internet based educational system ALEKS. The ALEKS system is bilingual English-Spanish and covers all of mathematics, from third grade to the end of high school, and chemistry. It is also widely used in higher education because US students are often poorly prepared when they reach the university level. The chapter by Taagepera and Arasasingham deals with the application of knowledge spaces, independent of ALEKS, to the teaching of college chemistry. The four chapters by Albert and his collaborators strive to give cognitive interpretations to the combinatoric structures obtained and used by the ALEKS system. The contribution by Eppstein is technical and develops means of searching the knowledge structure efficiently.

Knowledge Spaces offers a rigorous mathematical foundation for various practical systems of knowledge assessment, applied to real and simulated data. The systematic presentation extends research results to new situations, as well as describing how to build the knowledge structure in practice. The book also contains numerous examples and exercises and an extensive bibliography. This interdisciplinary representation of the theory of knowledge spaces will be of interest to mathematically oriented readers in computer science and combinatorics.

‘Global’ knowledge was constructed, communicated and contested during the long nineteenth century in numerous ways and places. This book focuses on the life-geographies, material practices and varied contributions to knowledge, be they medical or botanical, cartographic or cultural, of actors whose lives crisscrossed an increasingly connected world. Integrating detailed archival research with broader thematic and conceptual reflection, the individual case studies use local specificity to shed light on global structures and processes, revealing the latter to be lived and experienced phenomena rather than abstract historiographical categories. This volume makes an original and compelling contribution to a growing body of scholarship on the global history of knowledge. Given its wide geographic, disciplinary and thematic range this book will appeal to a broad readership including historical geographers and specialists in history of science and medicine, imperial history, museum studies, and book history.

This book explores the measurement of learning effectiveness and the optimization of knowledge retention by modeling the learning process and building the mathematical foundation of multi-space learning theory. Multi-space learning is defined in this book as a micro-process of human learning that can take place in more than one space, with the goal of effective learning and knowledge retention. This book models the learning process as a temporal sequence of concept learning, drawing on established principles and empirical evidence. It also introduces the matroid to strengthen the mathematical foundation of multi-space learning theory and applies the theory to vocabulary and mathematics learning, respectively. The results show that, for vocabulary learning, the method can be used to estimate the effectiveness of a single learning strategy, to detect the mutual interference that might exist between learning strategies, and to predict the optimal combination of strategies. In mathematical learning, it was found that timing is crucial in both first learning and second learning in scheduling optimization to maximize the intersection effective interval. The title will be of interest to researchers and students in a wide range of areas, including educational technology, learning sciences, mathematical applications, and mathematical psychology.

The present book is a result of a seven-year (1986-1992) national research program in cognitive science in Germany, presumably the first large scale cognitive science program there. Anchored in psychology, and therefore christened Wissenpsychologie (psychology of knowledge), it has found interdisciplinary resonance, especially in artificial intelligence and education. The research program brought together cognitive scientists from over twenty German universities and more than thirty single projects were funded. The program was initiated by Heinz Mandl and Hans Spada, the main goals of which were to investigate the acquisition of knowledge, the access to knowledge, and the modification and application of knowledge from a psychological perspective. Emphasis was placed on formalisms of knowledge representation and on the processes involved. In many of the projects this was combined with computer simulations. A final but equally important goal was the development of experimental paradigms and methods for data analysis that are especially suited to investigate knowledge based processes.The research program has had a major impact on cognitive psychology in Germany. Research groups were established at many universities and research equipment was provided. It also inspired a considerable number of young scientists to carry out cognitive research, employ modeling techniques from artificial intelligence for psychological theorizing, and construct intelligent tutoring systems for education. Close contacts with cognitive scientists in the U.S. have helped to firmly integrate the program with international research endeavours. Each year, one or two workshops were held. The present volume is the result of the final workshop which was held in September 1992. Selected results from seventeen projects are presented in this book. The volume is enriched by three guest scholars who agreed to participate in the final workshop and to comment on the chapters of the book.

This book explores next-generation artificial intelligence based on the symbiosis between humans, machines and nature, including the rules and emerging patterns of recognition, and the integration and optimization of various flows through cyberspace, physical space and social space. It unveils a reciprocal human-machine-nature symbiotic mechanism together with relevant rules on structuring and evolving reality, and also proposes a multi-dimensional space for modelling reality and managing the methodologies for exploring reality. As such it lays the foundation for the emerging research area cyber-physical-social intelligence. Inspiring researchers and university students to explore the development of intelligence and scientific methodology, it is intended for researchers and broad readers with a basic understanding of computer science and the natural sciences. Next-generation artificial intelligence will extend machine intelligence and human intelligence to cyber-physical-social intelligence rendered by various interactions in cyberspace, physical space and social space. With the transformational development of science and society, a multi-dimensional reality is emerging and evolving, leading to the generation and development of various spaces obeying different principles. A fundamental scientific challenge is uncovering the essential mechanisms and principles that structure and evolve the reality emerging and evolving along various dimensions. Meeting this challenge requires identifying the basic relations between humans, machines and nature in order to reveal the cyber-physical-social principles.