This volume seeks to answer the question: "Can findings from cognitive science enhance the user-computer interaction process?" In so doing, it recognizes that user-computer interfaces (UCIs) are often essential parts of an information or decision support system -- and often critical components of software-intensive systems of all kinds. From the outset, the authors note that the design, prototyping, and evaluation of user-computer interfaces are part of larger systems and are therefore ideally designed, developed, and evaluated as part of a larger design and developmental process or "life cycle."
Thus, this book describes the process by which functional, nonfunctional, or display-oriented requirements are converted first into prototypes and then into working systems. While the process may at times seem almost mysterious, there is in fact a methodology that drives the process -- a methodology that is defined in terms of an adaptive life cycle. There are a number of steps or phases that comprise the standard life cycle, as well as methods, tools and techniques that permit each step to be taken. Describing the effort to implement this process to enhance user-computer interaction, this book presents a methodological approach that seeks to identify and apply findings from cognitive science to the design, prototyping, and evaluation of user-computer interfaces.

This volume seeks to answer the question: "Can findings from cognitive science enhance the user-computer interaction process?" In so doing, it recognizes that user-computer interfaces (UCIs) are often essential parts of an information or decision support system -- and often critical components of software-intensive systems of all kinds. From the outset, the authors note that the design, prototyping, and evaluation of user-computer interfaces are part of larger systems and are therefore ideally designed, developed, and evaluated as part of a larger design and developmental process or "life cycle." Thus, this book describes the process by which functional, nonfunctional, or display-oriented requirements are converted first into prototypes and then into working systems. While the process may at times seem almost mysterious, there is in fact a methodology that drives the process -- a methodology that is defined in terms of an adaptive life cycle. There are a number of steps or phases that comprise the standard life cycle, as well as methods, tools and techniques that permit each step to be taken. Describing the effort to implement this process to enhance user-computer interaction, this book presents a methodological approach that seeks to identify and apply findings from cognitive science to the design, prototyping, and evaluation of user-computer interfaces.

Knowledge-based systems are increasingly found in a wide variety of settings and this handbook has been written to meet a specific need in their widening use. While there have been many successful applications of knowledge-based systems, some applications have failed because they never received the corrective feedback that evaluation provides for keeping development focused on the users' needs in their actual working environment. This handbook provides a conceptual framework and compendium of methods for performing evaluations of knowledge-based systems during their development. Its focus is on the users' and subject matter experts' evaluation of the usefulness of the system, and not on the developers' testing of the adequacy of the programming code. The handbook permits evaluators to systematically answer the following kinds of questions: Does the knowledge-based system meet the users' task requirements? Is the system easy to use? Is the knowledge base logically consistent? Does it meet the required level of expertise? Does the system improve performance? The authors have produced a handbook that will serve two audiences: a tool that can be used to create knowledge-based systems (practitioners, developers, and evaluators) and a framework that will stimulate more research in the area (academic researchers and students). To accomplish this, the handbook is built around a conceptual framework that integrates the different types of evaluations into the system of development process. The kinds of questions that can be answered, and the methods available for answering them, will change throughout the system development life cycle. And throughout this process, one needs to know what can be done, and what can't. It is this dichotomy that addresses needs in both the practitioner and academic research audiences.

Knowledge-based systems are increasingly found in a wide variety of settings and this handbook has been written to meet a specific need in their widening use. While there have been many successful applications of knowledge-based systems, some applications have failed because they never received the corrective feedback that evaluation provides for keeping development focused on the users' needs in their actual working environment. This handbook provides a conceptual framework and compendium of methods for performing evaluations of knowledge-based systems during their development. Its focus is on the users' and subject matter experts' evaluation of the usefulness of the system, and not on the developers' testing of the adequacy of the programming code. The handbook permits evaluators to systematically answer the following kinds of questions: Does the knowledge-based system meet the users' task requirements? Is the system easy to use? Is the knowledge base logically consistent? Does it meet the required level of expertise? Does the system improve performance? The authors have produced a handbook that will serve two audiences: a tool that can be used to create knowledge-based systems (practitioners, developers, and evaluators) and a framework that will stimulate more research in the area (academic researchers and students). To accomplish this, the handbook is built around a conceptual framework that integrates the different types of evaluations into the system of development process. The kinds of questions that can be answered, and the methods available for answering them, will change throughout the system development life cycle. And throughout this process, one needs to know what can be done, and what can't. It is this dichotomy that addresses needs in both the practitioner and academic research audiences.