Research Methods In Human Computer Interaction
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Research Methods in Human-Computer Interaction
Continual technological evolution has led to an explosion of new techniques in Human-Computer Interaction (HCI) research. Research Methods in Human-Computer Interaction is a thoroughly comprehensive guide to performing research and is essential reading for both quantitative and qualitative methods. 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, time diaries, physiological measurements, case studies, and other essential elements in the well-informed HCI researcher's toolkit. “This book is a must read for anyone in the field of Human-Computer Interaction. The multi-disciplinarian approach, housed in the reality of the technological world today, makes for a practical and informative guide for user interface designers, software and hardware engineers and anyone doing user research.” Dr. Mary Czerwinski, Research Area Manager, Microsoft Research, USA “Research Methods in HCI is an excellent read for practitioners and students alike. It discusses all the must-know theory, provides detailed instructions on how to carry out the research, and offers great examples. I loved it!” Professor Vanessa Evers, Professor, Human Computer Studies Lab, University of Amsterdam, the Netherlands "The book is superb: comprehensive, clear, and engaging! This is a one-stop HCI methods reference library. If you can only buy one HCI methods book, this is the one!" Dr. Clare-Marie Karat, IBM TJ Watson Research, USA, and recipient of the 2009 ACM SIGCHI Lifetime Service Award “A much needed and very useful book, covering important HCI research methods overlooked in standard research methods texts.” Professor Gilbert Cockton, School of Design, Northumbria University, United Kingdom
Research Methods in Human-Computer Interaction
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
Modern Statistical Methods for HCI
This book critically reflects on current statistical methods used in Human-Computer Interaction (HCI) and introduces a number of novel methods to the reader. Covering many techniques and approaches for exploratory data analysis including effect and power calculations, experimental design, event history analysis, non-parametric testing and Bayesian inference; the research contained in this book discusses how to communicate statistical results fairly, as well as presenting a general set of recommendations for authors and reviewers to improve the quality of statistical analysis in HCI. Each chapter presents [R] code for running analyses on HCI examples and explains how the results can be interpreted. Modern Statistical Methods for HCI is aimed at researchers and graduate students who have some knowledge of “traditional” null hypothesis significance testing, but who wish to improve their practice by using techniques which have recently emerged from statistics and related fields. This book critically evaluates current practices within the field and supports a less rigid, procedural view of statistics in favour of fair statistical communication.