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2014 | Buch

Reading and Interpreting Ethnography Kapitel lesen Erstes Kapitel lesen

Ways of Knowing in HCI

herausgegeben von: Judith S. Olson, Wendy A. Kellogg

Verlag: Springer New York

Enthalten in: Springer Professional "Wirtschaft+Technik" , Springer Professional "Technik" , Springer Professional "Wirtschaft"

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Über dieses Buch

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.

Inhaltsverzeichnis

Frontmatter
Reading and Interpreting Ethnography
Abstract
Ethnography is an approach to understanding cultural life that is founded on the researcher’s participation, with the goal of understanding not simply what people are doing, but how they experience what they do. The researcher participates in the life of the target people, both to serve as a stimulus (asking questions) that generates reactions and insights and to fully engage in the evolution and understanding of what is happening.
Paul Dourish
Curiosity, Creativity, and Surprise as Analytic Tools: Grounded Theory Method
Abstract
Grounded Theory Method offers a rigorous way to explore a domain, with an emphasis on discovering new insights, testing those insights, and building partial understandings into a broader theory of the domain. It begins with observations of a phenomenon for which no theory yet exists. Through layered coding of these observations and continual reexamination of the data, a theory emerges.
Michael Muller
Knowing by Doing: Action Research as an Approach to HCI
Abstract
Action research (AR) is an approach to research that involves engaging with a community to address a problem or a challenge and through this problem solving to develop scholarly knowledge. AR could involve any of a number of methods described in this book. Key to this type of research is that it includes the community participants as co-researchers throughout and that the result of the intervention be helpful and sustainable insofar as possible.
Gillian R. Hayes
Concepts, Values, and Methods for Technical Human–Computer Interaction Research
Abstract
Technical HCI research seeks to improve the world by expanding the set of things that can be done with computational systems. This chapter considers this work as invention—the creation of new things—contrasted with activities of discovery which are concerned more with understanding the world. We discuss the values, goals, and criteria for success in this approach. Technical HCI research includes both directly contributing to some human need and indirectly contributing by enabling other technical work with things like toolkits.
Scott E. Hudson, Jennifer Mankoff
Study, Build, Repeat: Using Online Communities as a Research Platform
Abstract
Research on online communities raises a number of challenges. It is difficult to get access to usage data, to users (to interview), and to the system itself to introduce new features (e.g., participation incentive mechanisms). One solution is for researchers to create an online community themselves. Although this provides more control and access, it also requires additional resources (e.g., for staff to maintain the community) and consideration of the needs of the user community after the research is completed.
Loren Terveen, Joseph A. Konstan, Cliff Lampe
Field Deployments: Knowing from Using in Context
Abstract
Researchers deploy systems, typically robust prototypes, to users in situ for a number of purposes: to assess changes in behavior, to gather feedback on how to improve the system, to influence the attitude of the population to adopt the final system in the future. Researchers collect both quantitative data (e.g., frequency of use) and qualitative data (e.g., observations and interviews about situations of use and attitudes), and thus, this method is associated with a number of other methods in this book.
Katie A. Siek, Gillian R. Hayes, Mark W. Newman, John C. Tang
Science and Design: The Implications of Different Forms of Accountability
Abstract
This chapter sets out to explicitly contrast scientific and design approaches to knowing. In both cases, practitioners create situations for people to engage, and the results may be of interest to the research community. Scientific researchers need to be able to defend the logic of each step of their process from hypothesis to test to theory. Design, in contrast, relies simply on the success of the artefacts it creates. This implies a great degree of methodological liberty, including the potential to create open-ended designs that occasion new and illuminating engagements with the world.
William Gaver
Research Through Design in HCI
Abstract
In Research through Design (RtD), researchers generate new knowledge by understanding the current state and then suggesting an improved future state in the form of a design. It involves deep reflection in iteratively understanding the people, problem, and context around a situation that researchers feel they can improve.
John Zimmerman, Jodi Forlizzi
Experimental Research in HCI
Abstract
In Experiments, researchers set up comparable situations in which they carefully manipulate variables and collect people’s behavior in each condition. Experiments are very effective in determining causation in controlled situations and complement techniques that investigate ongoing behavior in more natural settings. For example, experiments are excellent for determining whether increased audio quality reduces blood pressure of participants in a video conference, and can add important insights to the larger question of when people choose video conferences over audio-only ones.
Darren Gergle, Desney S. Tan
Survey Research in HCI
Abstract
Surveys, now commonplace on the Internet, allow researchers to make inferences about an entire population by gathering information from a small subset of the larger group. Surveys can gather insights about people’s attitudes, perceptions, intents, habits, awarenesses, experiences, and characteristics, at significant moments both in time and over time. Even though they are easy to administer, there is a wide gap between quick-and-dirty surveys and surveys that are properly planned, constructed, and analyzed.
Hendrik Müller, Aaron Sedley, Elizabeth Ferrall-Nunge
Crowdsourcing in HCI Research
Abstract
By recruiting large numbers of people online to perform small tasks, researchers can perform important assessments that are hard to obtain otherwise, at a very reasonable cost and speed. These tasks include assessing quality, reading characters that OCR readers can’t decipher, labeling photographs, and even answering questions in a survey. Care must be taken in using crowdsourcing, however, because some people “game” the system or simply misunderstand the task. However, there are techniques to minimize or detect questionable data.
Serge Egelman, Ed H. Chi, Steven Dow
Sensor Data Streams
Abstract
It is possible today to collect streams of data from sensors in the environment (e.g., on walls of buildings) or attached to individuals (e.g., badges that record location and with whom one is speaking). The data from these sensors allows researchers to trace people’s behavior with and without various technology interventions or incentives intended to change behavior. These traces can also be used inside technologies, for example to sense when it is a good time to interrupt a person with a message.
Stephen Voida, Donald J. Patterson, Shwetak N. Patel
Eye Tracking: A Brief Introduction
Abstract
Eye tracking is the process of measuring where eye gaze is focused to infer what someone is paying attention to and/or ignoring. The object of focus could be a digital display (e.g., on a phone, tablet or computer) or another person in a conversation, for example in face-to-face settings or in video conferences. Researchers measure what is looked at (point of gaze) and for how long (gaze duration), and the order in which gaze shifts.
Vidhya Navalpakkam, Elizabeth F. Churchill
Understanding User Behavior Through Log Data and Analysis
Abstract
HCI researchers are increasingly collecting rich behavioral traces of user interactions with online systems in situ at a scale not previously possible. These logs can be used to characterize user interactions with existing systems and compare different designs. Large-scale log studies give rise to new challenges in experimental design, data collection and interpretation, and ethics. The chapter discusses how to address these challenges using search engine logs, but the methods are applicable to other types of log data.
Susan Dumais, Robin Jeffries, Daniel M. Russell, Diane Tang, Jaime Teevan
Looking Back: Retrospective Study Methods for HCI
Abstract
Many people infer reasons for behavior without actually knowing. Two methods that can be used to actually gain insight into thought processes are the think-aloud protocol and retrospective cued recall. These two methods gather natural user behavior fairly unobtrusively over a period of time while allowing for some insight into what people are thinking as they are doing. These methods can be used to understand the reasons for tasks that require focused attention. In this chapter we illustrate these ideas in the domain of “searching on the Internet,” but these methods are broadly applicable.
Daniel M. Russell, Ed H. Chi
Agent Based Modeling to Inform the Design of Multiuser Systems
Abstract
Agent Based Modeling studies group activity by simulating the individuals in it and allowing group-level phenomena to emerge. It can be used to integrate theories to inform designs of technology for groups. Researchers use theories as the basis of the rules of how individuals behave (e.g., what motivates users to contribute to an online community). They can run virtual experiments by changing parameters of the model (e.g., the topical focus in an online community) to see what collective behaviors emerge.
Yuqing Ren, Robert E. Kraut
Social Network Analysis in HCI
Abstract
Social network analysis calculates and displays the relationships that exist among a collection of people, like those on a project, in an organization, or participating in a blog. From this analysis, the researcher can find key people, outliers, subgroups, and people who bridge subgroups. And, these analyses can reveal changes over time, for example, before and after a technology is introduced.
Derek L. Hansen, Marc A. Smith
Research Ethics and HCI
Abstract
The expansion of human–computer interaction (HCI) to every aspect of human activity creates new challenges to the core ethical mandates of doing no harm, maintaining respect for people who participate in our studies, and weighing the costs and benefits of research, making sure that they are distributed fairly over the population. Online research adds further complications. This chapter reviews the ethical challenges and helps researchers prepare their cases for the Institutional Review Board (IRB) approval.
Amy Bruckman
Epilogue
Abstract
Human-Computer Interaction has produced its third generation of researchers who represent an impressive array of academic disciplines. As we have seen, HCI’s methodological approaches are accordingly diverse, accommodating not only different ways of knowing, but reflecting a rich set of perspectives of what is worth knowing, when and why. Interactive and increasingly intelligent technologies touch every aspect of human life, and creating artifacts will always run the gamut from the artistic and inspirational to Fitt’s Law and psychomotor skills. In this final chapter, we look back at the ground we’ve covered, and forward to some of the emerging trends in HCI Ways of Knowing.
Wendy A. Kellogg, Judith S. Olson
Metadaten
Titel
Ways of Knowing in HCI
herausgegeben von
Judith S. Olson
Wendy A. Kellogg
Copyright-Jahr
2014
Verlag
Springer New York
Electronic ISBN
978-1-4939-0378-8
Print ISBN
978-1-4939-0377-1
DOI
https://doi.org/10.1007/978-1-4939-0378-8

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