Model-driven research in human-centric computing
|Model-driven research in human-centric computing|
|Published in||Proceedings - 2010 IEEE Symposium on Visual Languages and Human-Centric Computing, VL/HCC 2010|
|Keyword(s)||Component, HCI, Model-driven research (Extra: Complex equations, Component, Evolutionary dynamics, Group behavior, HCI, Human-centric, Information scent, Interactive system, Mix and match, Model driven approach, Model-driven, Model-driven research, Probabilistic models, Search system, Sensemaking, System development, User behaviors, Wikipedia, Behavioral research, Information theory, Mathematical operators, Web browsers, Mathematical models)|
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Model-driven research in human-centric computing is a 2010 conference paper written in English by Chi E.H. and published in Proceedings - 2010 IEEE Symposium on Visual Languages and Human-Centric Computing, VL/HCC 2010.
How can we build systems that enable users to mix and match tools together? How will we know whether we have done a good job in creating usable visual interactive systems that help users accomplish a wide variety of goals? How can people share the results of their explorations with each other, and for innovative tools to be remixed? Widely-used tools such as Web Browsers, Wikis, spreadsheets, and analytics environments like R all contain models of how people mix and combine operators and functionalities. In my own research, system developments are very much informed by models such as information scent, sensemaking, information theory, probabilistic models, and more recently, evolutionary dynamic models. These models have been used to understand a wide-variety of user behaviors in humancentric computing, from individuals interacting with a search system like MrTaggy.com to groups of people working on articles in Wikipedia. These models range in complexity from a simple set of assumptions to complex equations describing human and group behavior. In this talk, I will attempt to illustrate how a model-driven approach to answering the above questions should help to illuminate the path forward for Human-Centric Computing.
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