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Over the last decade there has been a significant growth in interest in aspects of people's experience with technologies under headings such as user experience, aesthetics, affect, fun, reflection, and enjoyment. In more recent years critical theory has begun to make a small but important impact at CHI conferences and other HCI publications. It is arguable that a relationship between critical theory and experience would benefit HCI research and practice as it has benefited other areas of research in the humanities and social sciences. However, in the history of ideas experience and critical theory have not always made good bedfellows, sometimes complementing each other, sometimes resisting each other. This workshop will explore the ways in which HCI might benefit from a constructive dialogue between critical theory and experience in questions of design and evaluation.
"SIGDOC is the Association for Computing Machinery's Special Interest Group (SIG) on the Design of Communication (DOC). Until 2003, SIGDOC focused on documentation for hardware and software. With the shift in focus from systems to computer documentation to the design of communication, SIGDOC has better positioned itself to emphasize the potentials, practices, and problems of multiple kinds of communication technologies, such as Web applications, user interfaces, and online and print documentation."
"Human-Centered Informatics (HCI) is the intersection of the cultural, the social, the cognitive, and the aesthetic with computing and information technology. It encompasses a huge range of issues, theories, technologies, designs, tools, environments and human experiences in knowledge work, recreation and leisure activity, teaching and learning, and the potpourri of everyday life. The series will publish state-of-the-art syntheses, case studies, and tutorials in key areas. It will share the focus of leading international conferences in HCI."
in list: For Teaching
"Why is it so common to use parametric tests such as the T-test or ANOVA instead of non-paramtric counterparts? Kaptein, Nass, & Markopoulos (2010) suggest it is because HCI researchers know that non-parametric tests lack power. This means they are worried that the non-parametric tests will fail to find a test where one exists. They also suggest it is because there aren't handy non-parametric tests which let you do analysis of factorial designs. So what's a researcher to do?"
links to press release on Stanford study and PNAS for the study
Welcome to the Communication Between Humans and Interactive Media Lab, located in the Communication Department at Stanford University.
Our laboratory focuses on uncovering fundamental relationships between humans and interactive media. We are interested both in advancing the overall understanding of human psychology and in exploring the practical implications of our discoveries.
Clifford Nass is currently the Thomas M. Storke Professor at Stanford University; he has been a professor at Stanford since 1986. ...Nass's research focuses on (laboratory and field) experimental studies of social-psychological aspects of human-interactive media interaction. Specifically, Nass discovered that people use the same rules and heuristics when interacting with technology as they do when interacting with other people. This approach is called the "Computers are Social Actors" (CASA) paradigm or "The Media Equation" (media equals real life).
Conference on Information and Knowledge Management -
Proceeding of the 2008 ACM workshop on Research advances in large digital book repositories
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The challenge of personal computing became manifest at an opportune time. The broad project of cognitive science, which incorporated cognitive psychology, artificial intelligence, linguistics, cognitive anthropology, and the philosophy of mind, had formed at the end of the 1970s. Part of the programme of cognitive science was to articulate systematic and scientifically-informed applications to be known as "cognitive engineering". Thus, at just the point when personal computing presented the practical need for HCI, cognitive science presented people, concepts, skills, and a vision for addressing such needs. HCI was one of the first examples of cognitive engineering.
Other historically fortuitous developments contributed to establishment of HCI. Software engineering, mired in unmanageable software complexity in the 1970s, was starting to focus on nonfunctional requirements, including usability and maintainability, and on non-linear software development processes that relied heavily on testing. Computer graphics and information retrieval had emerged in the 1970s, and rapidly came to recognize that interactive systems were the key to progressing beyond early achievements. All these threads of development in computer science pointed to the same conclusion: The way forward for computing entailed understanding and better empowering users.
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One of the most significant achievements of HCI is its evolving model of the integration of science and practice. Initially this model was articulated as a reciprocal relation between cognitive science and cognitive engineering. Later, it ambitiously incorporated a diverse science foundation, notably Activity Theory, distributed cognition, and ethnomethodology, and a culturally embedded conception of human activity, including the activities of design and technology development. Currently, the model is incorporating design practices and research across a broad spectrum. In these developments, HCI provides a blueprint for a mutual relation between science and practice that is unprecedented.
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Although ethnography has become a common approach in HCI research and design, considerable confusion still attends both ethnographic practice and the criteria by which it should be evaluated in HCI. Often, ethnography is seen as an approach to field investigation that can generate requirements for systems development; by that token, the major evaluative criterion for an ethnographic study is the implications it can provide for design. Exploring the nature of ethnographic inquiry, this paper suggests that "implications for design" may not be the best metric for evaluation and may, indeed, fail to capture the value of ethnographic investigations.
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One of those chapters is titled Keys and Keyboards and was written by James Lewis, Kathleen Potosnak and Regis Magyar. It considers virtually every imaginable factor involved in designing keyboards, and, by drawing from experimental studies, provides recommendations for each of them. Ever since I read this chapter a couple of years ago, I've been meaning to summarise some of their conclusions and to consider them in the context of modern keyboard design.
My fundamental interest lies in the marriage of AI and human-computer interaction. I seek to use AI techniques to make computing systems easier to use. Current interfaces require users to learn to speak the language of the system in order to do their work
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