This textbook brings together both new and traditional research methods in Human Computer Interaction (HCI). Research methods include interviews and observations, ethnography, grounded theory and analysis of digital traces of behavior. Readers will gain an understanding of the type of knowledge each method provides, its disciplinary roots and how each contributes to understanding users, user behavior and the context of use. The background context, clear explanations and sample exercises make this an ideal textbook for graduate students, as well as a valuable reference for researchers and practitioners. 'It is an impressive collection in terms of the level of detail and variety.' (M. Sasikumar, ACM Computing Reviews #CR144066)

Many people find statistics confusing, and perhaps even more confusing given recent publicity about problems with traditional p-values and alternative statistical techniques including confidence intervals and Bayesian statistics. This book aims to help readers navigate this morass: to understand the debates, to be able to read and assess other people's statistical reports, and make appropriate choices when designing and analysing their own experiments, empirical studies, and other forms of quantitative data gathering.

Research Methods in Human-Computer Interaction is a comprehensive guide to performing research and is essential reading for both quantitative and qualitative methods. Since the first edition was published in 2009, the book has been adopted for use at leading universities around the world, including Harvard University, Carnegie-Mellon University, the University of Washington, the University of Toronto, HiOA (Norway), KTH (Sweden), Tel Aviv University (Israel), and many others. Chapters cover a broad range of topics relevant to the collection and analysis of HCI data, going beyond experimental design and surveys, to cover ethnography, diaries, physiological measurements, case studies, crowdsourcing, and other essential elements in the well-informed HCI researcher's toolkit. Continual technological evolution has led to an explosion of new techniques and a need for this updated 2nd edition, to reflect the most recent research in the field and newer trends in research methodology. This Research Methods in HCI revision contains updates throughout, including more detail on statistical tests, coding qualitative data, and data collection via mobile devices and sensors. Other new material covers performing research with children, older adults, and people with cognitive impairments. - Comprehensive and updated guide to the latest research methodologies and approaches, and now available in EPUB3 format (choose any of the ePub or Mobi formats after purchase of the eBook) - Expanded discussions of online datasets, crowdsourcing, statistical tests, coding qualitative data, laws and regulations relating to the use of human participants, and data collection via mobile devices and sensors - New material on performing research with children, older adults, and people with cognitive impairments, two new case studies from Google and Yahoo!, and techniques for expanding the influence of your research to reach non-researcher audiences, including software developers and policymakers

Theory is the bedrock of many sciences, providing a rigorous method to advance knowledge, through testing and falsifying hypotheses about observable phenomena. To begin with, the nascent field of HCI followed the scientific method borrowing theories from cognitive science to test theories about user performance at the interface. But HCI has emerged as an eclectic interdiscipline rather than a well-defined science. It now covers all aspects of human life, from birth to bereavement, through all manner of computing, from device ecologies to nano-technology. It comes as no surprise that the role of theory in HCI has also greatly expanded from the early days of scientific testing to include other functions such as describing, explaining, critiquing, and as the basis for generating new designs. The book charts the theoretical developments in HCI, both past and present, reflecting on how they have shaped the field. It explores both the rhetoric and the reality: how theories have been conceptualized, what was promised, how they have been used and which has made the most impact in the field -- and the reasons for this. Finally, it looks to the future and asks whether theory will continue to have a role, and, if so, what this might be. Table of Contents: Introduction / The Backdrop to HCI Theory / The Role and Contribution of Theory in HCI / Classical Theories / Modern Theories / Contemporary Theory / Discussion / Summary

Although it has influenced the field of Human-Computer Interaction (HCI) since its origins, humanistic HCI has come into its own since the early 2000s. In that time, it has made substantial contributions to HCI theory and methodologies and also had major influence in user experience (UX) design, aesthetic interaction, and emancipatory/social change-oriented approaches to HCI. This book reintroduces the humanities to a general HCI readership; characterizes its major epistemological and methodological commitments as well as forms of rigor; compares the scientific report vs. the humanistic essay as research products, while offering some practical advice for peer review; and focuses on two major topics where humanistic HCI has had particular influence in the field—user experience and aesthetics and emancipatory approaches to computing. This book argues for a more inclusive and broad reach for humanistic thought within the interdisciplinary field of HCI, and its lively and engaging style will invite readers into that project.

Esta enciclopedia presenta numerosas experiencias y discernimientos de profesionales de todo el mundo sobre discusiones y perspectivas de la la interacción hombre-computadoras

Edwin Hutchins combines his background as an anthropologist and an open ocean racing sailor and navigator in this account of how anthropological methods can be combined with cognitive theory to produce a new reading of cognitive science. His theoretical insights are grounded in an extended analysis of ship navigation—its computational basis, its historical roots, its social organization, and the details of its implementation in actual practice aboard large ships. The result is an unusual interdisciplinary approach to cognition in culturally constituted activities outside the laboratory—"in the wild." Hutchins examines a set of phenomena that have fallen in the cracks between the established disciplines of psychology and anthropology, bringing to light a new set of relationships between culture and cognition. The standard view is that culture affects the cognition of individuals. Hutchins argues instead that cultural activity systems have cognitive properties of their own that are different from the cognitive properties of the individuals who participate in them. Each action for bringing a large naval vessel into port, for example, is informed by culture: the navigation team can be seen as a cognitive and computational system. Introducing Navy life and work on the bridge, Hutchins makes a clear distinction between the cognitive properties of an individual and the cognitive properties of a system. In striking contrast to the usual laboratory tasks of research in cognitive science, he applies the principal metaphor of cognitive science—cognition as computation (adopting David Marr's paradigm)—to the navigation task. After comparing modern Western navigation with the method practiced in Micronesia, Hutchins explores the computational and cognitive properties of systems that are larger than an individual. He then turns to an analysis of learning or change in the organization of cognitive systems at several scales. Hutchins's conclusion illustrates the costs of ignoring the cultural nature of cognition, pointing to the ways in which contemporary cognitive science can be transformed by new meanings and interpretations. A Bradford Book

Over the past century, educational psychologists and researchers have posited many theories to explain how individuals learn, i.e. how they acquire, organize and deploy knowledge and skills. The 20th century can be considered the century of psychology on learning and related fields of interest (such as motivation, cognition, metacognition etc.) and it is fascinating to see the various mainstreams of learning, remembered and forgotten over the 20th century and note that basic assumptions of early theories survived several paradigm shifts of psychology and epistemology. Beyond folk psychology and its naïve theories of learning, psychological learning theories can be grouped into some basic categories, such as behaviorist learning theories, connectionist learning theories, cognitive learning theories, constructivist learning theories, and social learning theories. Learning theories are not limited to psychology and related fields of interest but rather we can find the topic of learning in various disciplines, such as philosophy and epistemology, education, information science, biology, and – as a result of the emergence of computer technologies – especially also in the field of computer sciences and artificial intelligence. As a consequence, machine learning struck a chord in the 1980s and became an important field of the learning sciences in general. As the learning sciences became more specialized and complex, the various fields of interest were widely spread and separated from each other; as a consequence, even presently, there is no comprehensive overview of the sciences of learning or the central theoretical concepts and vocabulary on which researchers rely. The Encyclopedia of the Sciences of Learning provides an up-to-date, broad and authoritative coverage of the specific terms mostly used in the sciences of learning and its related fields, including relevant areas of instruction, pedagogy, cognitive sciences, and especially machine learning and knowledge engineering. This modern compendium will be an indispensable source of information for scientists, educators, engineers, and technical staff active in all fields of learning. More specifically, the Encyclopedia provides fast access to the most relevant theoretical terms provides up-to-date, broad and authoritative coverage of the most important theories within the various fields of the learning sciences and adjacent sciences and communication technologies; supplies clear and precise explanations of the theoretical terms, cross-references to related entries and up-to-date references to important research and publications. The Encyclopedia also contains biographical entries of individuals who have substantially contributed to the sciences of learning; the entries are written by a distinguished panel of researchers in the various fields of the learning sciences.

How to be a great online searcher, demonstrated with step-by-step searches for answers to a series of intriguing questions (for example, “Is that plant poisonous?”). We all know how to look up something online by typing words into a search engine. We do this so often that we have made the most famous search engine a verb: we Google it—“Japan population” or “Nobel Peace Prize” or “poison ivy” or whatever we want to know. But knowing how to Google something doesn't make us search experts; there's much more we can do to access the massive collective knowledge available online. In The Joy of Search, Daniel Russell shows us how to be great online researchers. We don't have to be computer geeks or a scholar searching out obscure facts; we just need to know some basic methods. Russell demonstrates these methods with step-by-step searches for answers to a series of intriguing questions—from “what is the wrong side of a towel?” to “what is the most likely way you will die?” Along the way, readers will discover essential tools for effective online searches—and learn some fascinating facts and interesting stories. Russell explains how to frame search queries so they will yield information and describes the best ways to use such resources as Google Earth, Google Scholar, Wikipedia, and Wikimedia. He shows when to put search terms in double quotes, how to use the operator (*), why metadata is important, and how to triangulate information from multiple sources. By the end of this engaging journey of discovering, readers will have the definitive answer to why the best online searches involve more than typing a few words into Google.

Experiments help to understand human-computer interaction and to characterize the value of user interfaces. Yet, few intermediate guidelines exist on how to design, run, and report experiments. The present monograph presents such guidelines. We briefly argue why experiments are invaluable for advancing human-computer interaction beyond technical innovation. We then identify heuristics of doing good experiments, including how to build on existing work in devising hypotheses and selecting measures; how to craft challenging comparisons, rather than biased win-lose setups; how to design experiments so as to rule out alternative explanations; how to provide evidence for conclusions; and how to narrate findings. These heuristics are exemplified by excellent experiments in human-computer interaction.