We are quickly passing through the historical moment when people work in front of a single computer, dominated by a small CRT and focused on tasks involving only local information. Networked computers are becoming ubiquitous and are playing increasingly significant roles in our lives and in the basic infrastructures of science, business, and social interaction. For human-computer interaction to advance in the new millennium we need to better understand the emerging dynamic of interaction in which the focus task is no longer confined to the desktop but reaches into a complex networked world of information and computer-mediated interactions. We think the theory of distributed cognition has a special role to play in understanding interactions between people and technologies, for its focus has always been on whole environments: what we really do in them and how we coordinate our activity in them. Distributed cognition provides a radical reorientation of how to think about designing and supporting human-computer interaction. As a theory it is specifically tailored to understanding interactions among people and technologies. In this article we propose distributed cognition as a new foundation for human-computer interaction, sketch an integrated research framework, and use selections from our earlier work to suggest how this framework can provide new opportunities in the design of digital work materials.
We describe Pad++, a zoomable graphical sketchpad that we are exploring as an alternative to traditional window and icon-based interfaces. We discuss the motivation for Pad++, describe the implementation, and present prototype applications. In addition, we introduce an informational physics strategy for interface design and briefly contrast it with current design strategies. We envision a rich world of dynamic persistent informational entities that operate according to multiple physics specifically designed to provide cognitively facile access and serve as the basis for design of new computationally-based work materials. 1: INTRODUCTIONImagine a computer screen made of a sheet of a miraculous new material that is stretchable like rubber, but continues to display a crisp computer image, no matter what the sheet's size. Imagine that this sheet is very elastic and can stretch orders of magnitude more than rubber. Further, imagine that vast quantities of information are represented on the sheet, organized at different places and sizes. Everything you do on the computer is on this sheet. To access a piece of information you just stretch to the right part, and there it is.Imagine further that special lenses come with this sheet that let you look onto one part of the sheet while you have stretched another part. With these lenses, you can see and interact with many different pieces of data at the same time that would ordinarily be quite far apart. In addition, these lenses can filter the data in any way you would like, showing different representations of the same underlying data. The lenses can even filter out some of the data so that only relevant portions of the data appear.Imagine also new stretching mechanisms that provide alternatives to scaling objects purely geometrically. For example, instead of representing a page of text so small that it is unreadable, it might make more sense to present an abstraction of the text, perhaps just a title that is readable. Similarly, when stretching out a spreadsheet, instead of showing huge numbers, it might make more sense to show the computations from which the numbers were derived or a history of interaction with them.The beginnings of an interface like this sheet exists today in a program we call Pad++. We don't really stretch a huge rubber-like sheet, but we simulate it by zooming into the data. We use what we call portals to simulate lenses, and a notion we call semantic zooming to scale data in non-geometric ways. The user controls where they look on this vast data surface by panning and zooming. Portals are objects on the Pad++ data surface that can see anywhere on the surface, as well as filter data to represent it differently than it normally appears.Panning and zooming allow navigation through a large information space via direct manipulation. By tapping into people's natural spatial abilities, we hope to increase users' intuitive access to information. Conventional computer search techniques are also provided in Pad++, bridging traditional and new interface...
Computational notebooks combine code, visualizations, and text in a single document. Researchers, data analysts, and even journalists are rapidly adopting this new medium. We present three studies of how they are using notebooks to document and share exploratory data analyses. In the first, we analyzed over 1 million computational notebooks on GitHub, finding that one in four had no explanatory text but consisted entirely of visualizations or code. In a second study, we examined over 200 academic computational notebooks, finding that although the vast majority described methods, only a minority discussed reasoning or results. In a third study, we interviewed 15 academic data analysts, finding that most considered computational notebooks personal, exploratory, and messy. Importantly, they typically used other media to share analyses. These studies demonstrate a tension between exploration and explanation in constructing and sharing computational notebooks. We conclude with opportunities to encourage explanation in computational media without hindering exploration.
Being mobile influences not only the types of information people seek but also the ways they attempt to access it. Mobile contexts present challenges of changing location and social context, restricted time for information access, and the need to share attentional resources among concurrent activities. Understanding mobile information needs and associated interaction challenges is fundamental to improving designs for mobile phones and related devices. We conducted a two-week diary study to better understand mobile information needs and how they are addressed. Our study revealed that depending on the time and resources available, as well as the situational context, people use diverse and, at times, ingenious ways to obtain needed information. We summarize key findings and discuss design implications for mobile technology.
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