Posted by: soniahs | November 1, 2010

Exam readings: Distributed cognition and visualizations

For today, here are two related papers on distributed cognition (the idea that our thinking processes are intimately tied up with our environments, rather than being just internal) and images. The first paper presents a framework for understanding visualizations as part of distributed cognition, and the second applies that framework to studying interactive visualizations.

Jiajie Zhang, and Donald. A. Norman. “Representations in Distributed Cognitive Tasks.” Cognitive Science 18(1): 87-122, 1994.

Summary: In this paper, the authors present their theory of distributed cognition to describe how people conceptualize and perform tasks. Tasks are modeled using both internal and external components to create “distributed” representations. There are three basic problems in this view: the distributed representation of information, interaction between internal and external representations, and the nature of external representations. They discuss the “representational effect:” how different representations of the same information can have different cognitive effects (e.g., Roman vs. Arabic numerals and ease of calculation.) At issue here is that there are both internal and external “rules” in all problem representations; some formats contain more explicit or more easily understood external “rules,” which makes it easier to mentally interact with them. They outline a methodology for representational analysis that breaks done representations into component parts (skipping over details of this.) While external representations are aids to memory, they have additional functions: structuring (internal) cognition and providing information that does not need to be internalized in order to form a mental representation (affordances), and changing the fundamental nature of tasks.

Comments: The authors’ model of cognition suggests that differences among external representations will influence internal representations, or how information is learned. Practical implications include applicability of their ideas to effective design of representations. Not sure I will apply their methodology to my work, but theoretical approach is useful.

Links to: Kostelnick & Hassett (take rhetorical, rather than cognitive, approach to representation, point out that efficiency is usually not the driving force behind design); Liu et al. (argument to apply these ideas to info visualization)

Zhicheng Liu, Nancy J. Nersessian, and John T. Stasko. “Distributed Cognition as a Theoretical Framework for Information Visualization.” IEEE Transactions on Visualization and Computer Graphics. 14.6 (2008): 1173-1180.

Summary: The authors suggest using distributed cognition as a framework for information visualization research (not well-developed enough to serve as theory at this point-lacks predictive, prescriptive aspects.) Distributed cognition holds that cognition arises from the interaction of the mind with objects in the environment, rather than as just internal symbol processing as in the traditional view of cognition. The mind works by building an internal representation of an object that coordinates all the viewer’s external observations of the object; bringing the internal and external representations into agreement. Using this framework, we can look at interaction with data representations as the “propagation of representation states in a cognitive system through coordination;” i.e., as the process of building mental models. The act of manipulation helps us understand things (e.g., Tetris.) The authors also discuss the importance of testing how info visualization systems work in practice to help create mental models, rather than testing just ease of use or how well people like using a particular visualization.

Comments: Includes a discussion of Zhang’s and Norman’s “Representations” paper, which I’m also reading. The authors mention importance of linking research in interactive visualization to current cognitive science and perception research. This paper suggests both that interactivity is a useful property for building understanding and that holistic evaluation of mental models is appropriate for evaluating such interactions; they mention “social visualization:” sharing visualizations over the Web for exploring data representations.

Links to: Zhang & Norman

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Responses

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