Catalogue Search | MBRL
Are you sure you want to remove the book from the shelf?
{{itemTitle}}
84,523
result(s) for
"computer interaction"
Sort by:
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.
eBook
From tool to partner : the evolution of human-computer interaction
This is the first comprehensive history of human-computer interaction (HCI). Whether you are a user-experience professional or an academic researcher, whether you identify with computer science, human factors, information systems, information science, design, or communication, you can discover how your experiences fit into the expanding field of HCI. You can determine where to look for relevant information in other fields--and where you won't find it. This book describes the different fields that have participated in improving our digital tools. It is organized chronologically, describing major developments across fields in each period. Computer use has changed radically, but many underlying forces are constant. Technology has changed rapidly, human nature very little. An irresistible force meets an immovable object. The exponential rate of technological change gives us little time to react before technology moves on. Patterns and trajectories described in this book provide your best chance to anticipate what could come next. We have reached a turning point. Tools that we built for ourselves to use are increasingly influencing how we use them, in ways that are planned and sometimes unplanned. The book ends with issues worthy of consideration as we explore the new world that we and our digital partners are shaping.
Book
Persuasive technology : using computers to change what we think and do
Can computers change what you think and do?Can they motivate you to stop smoking, persuade you to buy insurance, or convince you to join the Army?\"Yes, they can,\" says Dr.B.J.Fogg, director of the Persuasive Technology Lab at Stanford University.
eBook
Research in the wild
The phrase \"in-the-wild\" is becoming popular again in the field of human-computer interaction (HCI), describing approaches to HCI research and accounts of user experience phenomena that differ from those derived from other lab-based methods. The phrase first came to the forefront 20-25 years ago when anthropologists Jean Lave, Lucy Suchman, and Ed Hutchins began writing about cognition being in-the-wild. Today, it is used more broadly to refer to research that seeks to understand new technology interventions in everyday living. A reason for its resurgence in contemporary HCI is an acknowledgment that so much technology is now embedded and used in our everyday lives. Researchers have begun following suit-decamping from their usability and living labs and moving into the wild; carrying out in-situ development and engagement, sampling experiences, and probing people in their homes and on the streets. The aim of this book is to examine what this new direction entails and what it means for HCI theory, practice, and design. The focus is on the insights, demands and concerns. But how does research in the wild differ from the other applied approaches in interaction design, such as contextual design, action research, or ethnography? What is added by labeling user research as being inthe- wild? One main difference is where the research starts and ends: unlike user-centered, and more specifically, ethnographic approaches which typically begin by observing existing practices and then suggesting general design implications or system requirements, in-the-wild approaches create and evaluate new technologies and experiences in situ. Moreover, novel technologies are often developed to augment people, places, and settings, without necessarily designing them for specific user needs. There has also been a shift in design thinking. Instead of developing solutions that fit in with existing practices, researchers are experimenting with new technological possibilities that can change and even disrupt behavior. Opportunities are created, interventions installed, and different ways of behaving are encouraged. A key concern is how people react, change and integrate these in their everyday lives. This book outlines the emergence and development of research in the wild. It is structured around a framework for conceptualizing and bringing together the different strands. It covers approaches, methods, case studies, and outcomes. Finally, it notes that there is more in the wild research in HCI than usability and other kinds of user studies in HCI and what the implications of this are for the field.
Book
Interacting with educational chatbots: A systematic review
Chatbots hold the promise of revolutionizing education by engaging learners, personalizing learning activities, supporting educators, and developing deep insight into learners’ behavior. However, there is a lack of studies that analyze the recent evidence-based chatbot-learner interaction design techniques applied in education. This study presents a systematic review of 36 papers to understand, compare, and reflect on recent attempts to utilize chatbots in education using seven dimensions: educational field, platform, design principles, the role of chatbots, interaction styles, evidence, and limitations. The results show that the chatbots were mainly designed on a web platform to teach computer science, language, general education, and a few other fields such as engineering and mathematics. Further, more than half of the chatbots were used as teaching agents, while more than a third were peer agents. Most of the chatbots used a predetermined conversational path, and more than a quarter utilized a personalized learning approach that catered to students’ learning needs, while other chatbots used experiential and collaborative learning besides other design principles. Moreover, more than a third of the chatbots were evaluated with experiments, and the results primarily point to improved learning and subjective satisfaction. Challenges and limitations include inadequate or insufficient dataset training and a lack of reliance on usability heuristics. Future studies should explore the effect of chatbot personality and localization on subjective satisfaction and learning effectiveness.
Journal Article
Crowdsourcing
Ever since the term \"crowdsourcing\" was coined in 2006 byWiredwriter Jeff Howe, group activities ranging from the creation of the Oxford English Dictionary to the choosing of new colors for M&Ms have been labeled with this most buzz-generating of media buzzwords. In this accessible but authoritative account, grounded in the empirical literature, Daren Brabham explains what crowdsourcing is, what it is not, and how it works. Crowdsourcing, Brabham tells us, is an online, distributed problem solving and production model that leverages the collective intelligence of online communities for specific purposes set forth by a crowdsourcing organization -- corporate, government, or volunteer. Uniquely, it combines a bottom-up, open, creative process with top-down organizational goals. Crowdsourcing is not open source production, which lacks the top-down component; it is not a market research survey that offers participants a short list of choices; and it is qualitatively different from predigital open innovation and collaborative production processes, which lacked the speed, reach, rich capability, and lowered barriers to entry enabled by the Internet. Brabham describes the intellectual roots of the idea of crowdsourcing in such concepts as collective intelligence, the wisdom of crowds, and distributed computing. He surveys the major issues in crowdsourcing, including crowd motivation, the misconception of the amateur participant, crowdfunding, and the danger of \"crowdsploitation\" of volunteer labor, citing real-world examples from Threadless, InnoCentive, and other organizations. And he considers the future of crowdsourcing in both theory and practice, describing its possible roles in journalism, governance, national security, and science and health.
eBook
Deep learning in vision-based static hand gesture recognition
Hand gesture for communication has proven effective for humans, and active research is ongoing in replicating the same success in computer vision systems. Human–computer interaction can be significantly improved from advances in systems that are capable of recognizing different hand gestures. In contrast to many earlier works, which consider the recognition of significantly differentiable hand gestures, and therefore often selecting a few gestures from the American Sign Language (ASL) for recognition, we propose applying deep learning to the problem of hand gesture recognition for the whole 24 hand gestures obtained from the Thomas Moeslund’s gesture recognition database. We show that more biologically inspired and deep neural networks such as convolutional neural network and stacked denoising autoencoder are capable of learning the complex hand gesture classification task with lower error rates. The considered networks are trained and tested on data obtained from the above-mentioned public database; results comparison is then made against earlier works in which only small subsets of the ASL hand gestures are considered for recognition.
Journal Article