Catálogo de publicaciones - libros

This study sought to address the problem of novices not being able to select the appropriate diagrams to suit given tasks. It investigated the usefulness of providing teaching sessions that involved active comparison of diagrams and review of lessons learnt following problem solving. Fifty-eight 8th grade participants were assigned to one of two instruction conditions. In both, traditional math classes were provided in which diagrams were used to explain how to solve math word problems. However, participants in the experimental group were additionally provided with sessions that required them to actively compare diagrams used, and consider and articulate the lessons they learnt from the problem solving exercises. The results showed that participants in the experimental condition subsequently constructed more appropriate diagrams in solving math word problems. In an assessment of conditional knowledge, these participants also provided more abstract and detailed descriptions about the uses of diagrams in problem solving.

As noted so eloquently by Lynch (1990), diagrams are critically important in science. Hegarty, Carpenter, and Just (1991) classified scientific diagrams into three categories: iconic, schematic, and charts and graphs. Iconic diagrams, such as photographs and line drawings, provide a depiction of concrete objects in which the spatial relations in the diagram are isomorphic to those in the referent object. Accurate representation of spatial relations can be critical, for example to distinguish the venomous coral snake from the similarly-colored non-venomous Arizona mountain king snake. In the life sciences, iconic representations help students understand the structure of objects that are not easily open to visual inspection. For example, side-by-side drawings of the stomachs of people and cows, with the parts labeled, would provide insight into why digestion works differently in these two taxa.

When done well, diagrams can support comprehension, inference, and learning. How about the case when learners create their own diagrams instead of just view them? Though novices typically enjoy and have some natural facility at creating spatial representations, they can easily create flawed representations. They need feedback to help them make their diagrammatic understanding more like that of experts. In this talk, I present three models of feedback. A global model where students simply see a correct diagram after they create their own; a social model where students receive feedback from one another while creating their diagrams; and, an automated model where the feedback is tightly coupled to the learner’s own diagram. I will describe the learning benefits of having students generate their own diagrams, and how different types of feedback help maximize those benefits.

In this tutorial, the attendees will gain an understanding of the main methods of measuring eye fixations on diagrams and how these data are coded and analyzed to make inferences about internal cognitive processes. This will enable attendees to better interpret and critically evaluate the results of studies that use this measure. It will also give them an introduction to the advantages of using eye fixation data and the effort involved in setting up an eye-tracking laboratory and analyzing eye fixation data. The tutorial will also identify problems in the analysis and interpretation of eye fixations that might lead to the development of new software tools for analyzing and interpreting this type of data.

Designers of information visualization and user interfaces must take account of culture in the design of metaphors, mental models, navigation, interaction, and appearance. Culture models define dimensions of difference and similarity among groups of people regarding signs, rituals, heroes/heroines, and values. Examples on the Web reveal these dimensions. Developers will increasingly need to take into account culture and other factors in development to better ensure usability, usefulness, and appeal.

This paper discusses the types of communicative signals that frequently appear in simple bar charts and how we exploit them as evidence in our system for inferring the intended message of an information graphic. Through a series of examples, we demonstrate the impact that various types of communicative signals, namely salience, captions and estimated perceptual task effort, have on the intended message inferred by our implemented system.

This experiment examines how, high and low mechanical and spatial abilities, learners understand an animation. Two variables were manipulated: the controllability of the animations and the task type of the learners to study the device. The comprehension test results indicated a positive effect of a fully controllable animation and also a positive effect of task type, when the attention of the learner is focused on the functional model and on local kinematics. The eye tracking data indicated that the learners attend more to the areas of the animations where a great amount of motion is involved along the causal chain of events. We show an effect of the controllability of the system and of the task type of the learner on the amount of eye fixations and on the number of transitions between areas that included the causal chain.

We present a method for constructing a teleological model of a drawing of a physical device through analogical transfer of the teleological model of the same device in an almost identical drawing. A source case, in this method, contains both a 2-D vector-graphics line drawing of a physical device and a teleological model of the device called a Drawing-Shape-Structure-Behavior-Function (DSSBF) model that relates shapes and spatial relations in the drawing to specifications of the structure, behavior and function of the device. Given an almost identical target 2-D vector-graphics line drawing as input, we describe how an agent may align the two drawings, and transfer the relevant structural, behavioral and functional elements over to the target drawing. We also describe how the DSSBF model of the source drawing guides the alignment of the two drawings. The Archytas system implements this method in domain of kinematic devices that convert translational motion into rotational motion, such as a piston and crankshaft device.

The intuitive properties of configurations of planar non-overlapping closed curves (boundaries) are presented as a pure boundary mathematics. The mathematics, which is not incorporated in any existing formalism, is constructed from first principles, that is, from empty space. When formulated as patternequations, boundary algebras map to elementary logic and to integer arithmetic.

Boundary logic is a formal diagrammatic system that combines Peirce’s Entitative Graphs with Spencer Brown’s Laws of Form. Its conceptual basis includes boundary forms composed of non-intersecting closed curves, void-substitution (deletion of irrelevant structure) as the primary mechanism of reduction, and spatial pattern-equations that define valid transformations. Pure boundary algebra, free of interpretation, is first briefly described, followed by a description of boundary logic. Then several new diagrammatic notations for logic derived from geometrical and topological transformation of boundary forms are presented. The algebra and an example proof of modus ponens is provided for textual, enclosure, graph, map, path and block based forms. These new diagrammatic languages for logic convert connectives into configurations of containment, connectivity, contact, conveyance, and concreteness.