It is well recognized that knowledge acquisition is the critical bottleneck of knowledge engineering. This book presents three major approaches of current research in this field, namely the psychological approach, the artificial intelligence approach and the software engineering approach. Special attention is paid to the most recent advances in knowledge acquisition research, especially those made by Chinese computer scientists. A special chapter is devoted to its applications in other fields, e.g. language analysis, software engineering, computer-aided instruction, etc., which were done in China.

This is the first book to provide a step-by-step guide to the methods and practical aspects of acquiring, modelling, storing and sharing knowledge. The reader is led through 47 steps from the inception of a project to its conclusion. Each is described in terms of reasons, required resources, activities, and solutions to common problems. In addition, each step has a checklist which tracks the key items that should be achieved.

Currently, both fields are moving towards an integrated approach using machine learning techniques to automate knowledge acquisition from experts, and knowledge acquisition techniques to guide and assist the learning process.

This book discusses emerging trends in the field of managing knowledge work due to technological innovations. The book is organized in 3 sections. The first section, entitled "Managing Knowledge, Projects and Networks", discusses knowledge processes and their use, reuse or generation in the context of an organization. The second section, entitled "Managing Knowledge using Social Media", focuses on factors influencing adoption and usage, the role of social media in managing knowledge, and factors that influence employees' acceptance and participation. The third section brings into discussion new approaches and technologies for acquiring knowledge. The book will be useful to both academics engaged in research in knowledge management and practitioners who are considering or implementing strategies for managing one of their most important resources.

Exemplar-Based Knowledge Acquisition: A Unified Approach to Concept Representation, Classification, and Learning covers the fundamental issues in cognitive science and the technology for solving real problems. This text contains six chapters and begins with a description of the rationale for the design of Protos Approach, its construction and performance. The succeeding chapters discuss how the Protos approach meets the requirements of representing concepts, using them for classification, and acquiring them from available training. These chapters also deal with the design and implementation of Protos. These topics are followed by a presentation of examples of the application of Protos to audiology and evaluate its performance. The final chapters survey related work in the areas of case-based reasoning and automated knowledge acquisition and the contributions of Protos approach. This book will be of great value to psychologists, psychiatrists, and researchers in the field of artificial intelligence.

In 1963 an initial attempt was made in my The Psychology of Meaningful Verbal Learning to present a cognitive theory of meaningful as opposed to rote verbal learning. It was based on the proposition that the acquisition and retention of knowl edge (particularly of verbal knowledge as, for example, in school, or subject-matter learning) is the product of an active, integrative, interactional process between instructional material (subject matter) and relevant ideas in the leamer's cognitive structure to which the new ideas are relatable in particular ways. This book is a full-scale revision of my 1963 monograph, The Psychology of Meaningful Verbal Learning, in the sense that it addresses the major aforementioned and hitherto unmet goals by providing for an expansion, clarification, differentiation, and sharper focusing of the principal psychological variables and processes involved in meaningful learning and retention, i.e., for their interrelationships and interactions leading to the generation of new meanings in the individual learner. The preparation of this new monograph was largely necessitated by the virtual collapse of the neobe havioristic theoretical orientation to learning during the previous forty years; and by the meteoric rise in the seventies and beyond of constructivist approaches to learning theory.

This book provides the first comprehensive literature review on the acquisition and retention of complex skills in High Reliability Organizations. Based on this review, it introduces a theoretical model of how skill and knowledge acquisition for complex tasks is accomplished and shows how this model can be used to derive training methods and instructional techniques. Successful acquisition and retention of complex technical skills within High Reliability Organizations requires a full understanding of the learning process, knowledge structure, and skill requirements associated with the effective operation and management of technology. For researchers and for organizations, the understanding of these processes is vital for designing training programs as well as for reducing errors with severe consequences for human lives and the environment. Until now, only theoretical fragments exist on this topic, and only a very limited number of publications actually address complex tasks in vocational/occupational settings. “The Acquisition of Knowledge and Skills for Task Work and Teamwork to Control Complex Technical Systems ” uses its literature overview and theoretical model to formulate training principles, that can be used to develop training experiments for further empirical investigations as well as training methods for applied organizational contexts.

The Acquisition of Strategic Knowledge deals with the automation of the acquisition of strategic knowledge and describes a knowledge acquisition program called ASK, which elicits strategic knowledge from domain experts and puts it in operational form. This book explores the dynamics of intelligent systems and how the components of knowledge systems (including a human expert) interact to produce intelligence. Emphasis is placed on how to represent knowledge that experts require to make decisions about actions. The move toward abstract tasks and how tasks are solved are discussed, along with their implications for knowledge acquisition, particularly the acquisition of expert strategies. This book is comprised of eight chapters and begins with an overview of the knowledge acquisition problem for strategic knowledge, as well as the relevance of strategic knowledge to artificial intelligence. The next chapter describes a dialog session between the ASK knowledge acquisition assistant and the user (""the expert""). The discussion then turns to software architecture with which to represent strategic knowledge; design and implementation of an assistant for acquiring strategic knowledge; and approaches to knowledge acquisition. Two applications of the ASK system are considered: to evaluate the usability of the elicitation technique with real users and to test the adequacy of the strategy rule representation upon which the approach is dependent. The scope of ASK, its sources of power, and its underlying assumptions are also outlined. This monograph will be a valuable resource for knowledge systems designers and those interested in artificial intelligence and expert systems.

The subject of this book is the analysis and processing of structural or quantitative data with emphasis on classification methods, new algorithms as well as applications in various fields related to data analysis and classification. The book presents the state of the art in world-wide research and application of methods from the fields indicated above and consists of survey papers as well as research papers.

There are many reasons to be curious about the way people learn, and the past several decades have seen an explosion of research that has important implications for individual learning, schooling, workforce training, and policy. In 2000, How People Learn: Brain, Mind, Experience, and School: Expanded Edition was published and its influence has been wide and deep. The report summarized insights on the nature of learning in school-aged children; described principles for the design of effective learning environments; and provided examples of how that could be implemented in the classroom. Since then, researchers have continued to investigate the nature of learning and have generated new findings related to the neurological processes involved in learning, individual and cultural variability related to learning, and educational technologies. In addition to expanding scientific understanding of the mechanisms of learning and how the brain adapts throughout the lifespan, there have been important discoveries about influences on learning, particularly sociocultural factors and the structure of learning environments. How People Learn II: Learners, Contexts, and Cultures provides a much-needed update incorporating insights gained from this research over the past decade. The book expands on the foundation laid out in the 2000 report and takes an in-depth look at the constellation of influences that affect individual learning. How People Learn II will become an indispensable resource to understand learning throughout the lifespan for educators of students and adults.