User Engagement (UE) is a complex concept to investigate. The purpose of this book is not to constrain UE to one perspective, but to offer a well-rounded appreciation for UE across various domains and disciplines. The text begins with two foundational chapters that describe theoretical and methodological approaches to user engagement; the remaining contributions examine UE from different disciplinary perspectives and across a range of computer-mediated environments, including social and communications media, online search, eLearning, games, and eHealth. The book concludes by bringing together the cross-disciplinary perspectives presented in each chapter and proposing an agenda for future research in this area. The book will appeal to established and emerging academic and industry researchers looking to pursue research and its challenges. This includes scholars at all levels with an interest in user engagement with digital media, from students to experienced researchers, and professionals in the fields of computer science, web technology, information science, museum studies, learning and health sciences, human-computer interaction, information architecture and design, and creative arts.

Connectionist modelling and neural network applications had become a major sub-field of cognitive science by the mid-1990s. In this ground-breaking book, originally published in 1995, leading connectionists shed light on current approaches to memory and language modelling at the time. The book is divided into four sections: Memory; Reading; Computation and statistics; Speech and audition. Each section is introduced and set in context by the editors, allowing a wide range of language and memory issues to be addressed in one volume. This authoritative advanced level book will still be of interest for all engaged in connectionist research and the related areas of cognitive science concerned with language and memory.

Connectionist modelling and neural network applications had become a major sub-field of cognitive science by the mid-1990s. In this ground-breaking book, originally published in 1995, leading connectionists shed light on current approaches to memory and language modelling at the time. The book is divided into four sections: Memory; Reading; Computation and statistics; Speech and audition. Each section is introduced and set in context by the editors, allowing a wide range of language and memory issues to be addressed in one volume. This authoritative advanced level book will still be of interest for all engaged in connectionist research and the related areas of cognitive science concerned with language and memory.

User Engagement (UE) is a complex concept to investigate. The purpose of this book is not to constrain UE to one perspective, but to offer a well-rounded appreciation for UE across various domains and disciplines. The text begins with two foundational chapters that describe theoretical and methodological approaches to user engagement; the remaining contributions examine UE from different disciplinary perspectives and across a range of computer-mediated environments, including social and communications media, online search, eLearning, games, and eHealth. The book concludes by bringing together the cross-disciplinary perspectives presented in each chapter and proposing an agenda for future research in this area. The book will appeal to established and emerging academic and industry researchers looking to pursue research and its challenges. This includes scholars at all levels with an interest in user engagement with digital media, from students to experienced researchers, and professionals in the fields of computer science, web technology, information science, museum studies, learning and health sciences, human-computer interaction, information architecture and design, and creative arts.

Human-Computer Interaction draws on the fields of computer science, psychology, cognitive science, and organisational and social sciences in order to understand how people use and experience interactive technology. Until now, researchers have been forced to return to the individual subjects to learn about research methods and how to adapt them to the particular challenges of HCI. This is the first book to provide a single resource through which a range of commonly used research methods in HCI are introduced. Chapters are authored by internationally leading HCI researchers who use examples from their own work to illustrate how the methods apply in an HCI context. Each chapter also contains key references to help researchers find out more about each method as it has been used in HCI. Topics covered include experimental design, use of eyetracking, qualitative research methods, cognitive modelling, how to develop new methodologies and writing up your research.

Each chapter of this book covers specific topics in statistical analysis, such as robust alternatives to t-tests or how to develop a questionnaire. They also address particular questions on these topics, which are commonly asked by human-computer interaction (HCI) researchers when planning or completing the analysis of their data. The book presents the current best practice in statistics, drawing on the state-of-the-art literature that is rarely presented in HCI. This is achieved by providing strong arguments that support good statistical analysis without relying on mathematical explanations. It additionally offers some philosophical underpinnings for statistics, so that readers can see how statistics fit with experimental design and the fundamental goal of discovering new HCI knowledge.

Each chapter of this book covers specific topics in statistical analysis, such as robust alternatives to t-tests or how to develop a questionnaire. They also address particular questions on these topics, which are commonly asked by human-computer interaction (HCI) researchers when planning or completing the analysis of their data. The book presents the current best practice in statistics, drawing on the state-of-the-art literature that is rarely presented in HCI. This is achieved by providing strong arguments that support good statistical analysis without relying on mathematical explanations. It additionally offers some philosophical underpinnings for statistics, so that readers can see how statistics fit with experimental design and the fundamental goal of discovering new HCI knowledge.