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.
From novice to expert: tools and techniques to make your learning faster, deeper, and stronger. Time to master the most important meta-skill of all: learning. Too bad you didn’t have this book years ago! Scientifically-proven, step-by-step methods for effective absorption, retention, and comprehension. Rapid Knowledge Acquisition & Synthesis is a collection of the very best methods to get ahead of the typical learning curve. You’ll learn how to create an environment for information absorption at shocking speeds. From scientifically-validated tips to best practices of some of the world’s smartest polymaths, you’ll get it all. Faster, deeper, stronger. Directly from one of self-education's thought leaders. Peter Hollins has studied psychology and peak human performance for over a dozen years and is a bestselling author. He has worked with a multitude of individuals to unlock their potential and path towards success. His writing draws on his academic, coaching, and research experience. Clear guidelines for every stage of the learning process. •The most common obstacles of learning and how to overcome them. •Single loop learning, double loop learning, and how to fundamentally change your comprehension mindset. •Best practices for reading, note-taking, absorbing knowledge, and making things stick inside your brain. •The most strategic questions to ask that will make information become memorable and 3d. •Dual coding, REM sleep, shifting locations, the efficacy of variety, and catching your own blind spots. Unlock the most important meta-skill of all: learning. Make yourself recession-proof, upgrade-proof, competition-proof, absent-minded-proof, and stagnant-proof.
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.
Media-didactics have recently become more firmly grounded on cognitive theory, with an increasing concern for the internal processes of knowledge representation and acquisition. With this cognitive aspect in mind, an international group of researchers held a meeting in Tübingen, Federal Republic of Germany, to present and discuss the theoretical approaches to and empirical investigations of knowledge acquisition from text and pictures. This volume contains the revised contributions resulting from that meeting.
This book presents a practical view of the knowledge acquisition process, its methodologies and techniques, in order to enable readers to develop expert systems knowledge bases more effectively. It strikes a balance between presenting (1) summaries of research in the field of knowledge acquisition and (2) methodologies and techniques that have been applied and tested on numerous programs in various contexts. Written for novice knowledge engineers or others tasked with acquiring knowledge for the systematic development of expert systems. The presentation of the material does not presume a background in either computer science or artificial intelligence.
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.
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.
Promoting organizational knowledge is an important consideration for any business looking toward the future. Understanding the dynamics of knowledge-intensive organizations is a crucial first step in establishing a strong knowledge base for any organization. Organizational Knowledge Dynamics: Managing Knowledge Creation, Acquisition, Sharing, and Transformation introduces the idea that organizational knowledge is composed of three knowledge fields: cognitive knowledge, emotional knowledge, and spiritual knowledge. This book is useful for graduate students, researchers, and practitioners in knowledge management, intellectual capital, human resources management, change management, and strategic management.
Building an expert system involves eliciting, analyzing, and interpreting the knowledge that a human expert uses when solving problems. Expe rience has shown that this process of "knowledge acquisition" is both difficult and time consuming and is often a major bottleneck in the production of expert systems. Unfortunately, an adequate theoretical basis for knowledge acquisition has not yet been established. This re quires a classification of knowledge domains and problem-solving tasks and an improved understanding of the relationship between knowledge structures in human and machine. In the meantime, expert system builders need access to information about the techniques currently being employed and their effectiveness in different applications. The aim of this book, therefore, is to draw on the experience of AI scientists, cognitive psychologists, and knowledge engineers in discussing particular acquisition techniques and providing practical advice on their application. Each chapter provides a detailed description of a particular technique or methodology applied within a selected task domain. The relative strengths and weaknesses of the tech nique are summarized at the end of each chapter with some suggested guidelines for its use. We hope that this book will not only serve as a practical handbook for expert system builders, but also be of interest to AI and cognitive scientists who are seeking to develop a theory of knowledge acquisition for expert systems.
