Peter C.-H. Cheng

Modeling the Effect of Task and Graphical Representation on Response Latency in a Graph Reading Task

We report an investigation into the processes involved in a common graph-reading task using two types of Cartesian graph. We describe an experiment and eye movement study, the results of which show that optimal scan paths assumed in the task analysis approximate the detailed sequences of saccades made by individuals. The research demonstrates the computational inequivalence of two sets of informationally equivalent graphs and illustrates how the computational advantages of a representation outweigh factors such as user unfamiliarity. We describe two models, using the ACT rational perceptual motor (ACT-R/PM) cognitive architecture, that replicate the pattern of observed response latencies and the complex scan paths revealed by the eye movement study. Finally, we outline three guidelines for designers of visual displays: Designers should (a) consider how different quantities are encoded within any chosen representational format, (b) consider the full range of alternative varieties of a given task, and (c) balance the cost of familiarization with the computational advantages of less familiar representations. Actual or potential applications of this research include informing the design and selection of appropriate visual displays and illustrating the practice and utility of task analysis, eye tracking, and cognitive modeling for understanding interactive tasks with external representations.

Theory and Application of Diagrams

This presentation will address the representation of geospatial information in the context of group work. The focus is on visual representations that mediate between human collaborators who are participating in a joint reasoning process, within a place and/or space-based problem context. The perspective developed for addressing the challenges involved builds upon the cognitive-semiotic approach outlined in How Maps Work, extending it to consider the issues that underlie creation of maps and related diagrams that work in a group work context. This context requires representations that depict not only geospatial information but also individual perspectives on that information, the process of negotiation among those perspectives, and the behaviors (work) of individuals participating in that negotiation. M . An d e rson , P. Ch e n g, an d V. Haarsl e v (E d s. ) : D i agram s 2000, LNAI 1889, p . 1, 2000. c

Cognitive Science Approaches To UnderstandingDiagrammatic Representations

Through a wide variety of approaches cognitive sciencehas given us various important insights into thenature of diagrammatic representations. This papersurveys the findings, issues and approaches todiagrammatic representations in cognitive science. Important current issues that are highlighted include:the relation between the parts of the representationalsystem that are internal to the mind and in externalvisual media that presents the diagram; the use ofmultiple representations which is typical of realcontexts of diagram use; the benefits of diagrams interms of (i) computational offloading, (ii)re-representation and (iii) graphical constraining.

Unlocking conceptual learning in mathematics and science with effective representational systems

There are provided a solidifying material used for radioactive waste which comprises a latent hydraulic material, an ultra-fine powder substance and a dispersing agent, and a process for the solidification of radioactive wastes which comprises kneading the above solidifying material with a cure stimulating agent, radioactive waste and, as occasion demands, water, and then curing the mixture by aging. Since the solidifying material of the present invention has excellent properties such as large treating capacity, excellent water resistance and large compressive strength, not only temporary storage but also permanent storage of radioactive wastes can be made.

Scientific Discovery With Law-Encoding Diagrams

This article introduces the concept of law-encoding diagrams (LEDs) and presents the argument that they have had a role in scientific discovery that has not been previously recognized. An LED is a representation that correctly encodes the underlying relations of a law, or a system of simultaneous laws, in the structure of a diagram by the means of geometric, topological, and spatial constraints, such that the instantiation of a particular diagram represents a single instance of the phenomena or a particular case of the law(s). Examples of LEDs in the history of science are discussed, and the benefits of using LEDs in discovery are considered. LEDs are distinguished from other forms of diagrammatic representation. Previous work on the computational modeling of diagrammatic law induction is reinterpreted in terms of the search for diagrammatic constraints of LEDs. A general characterization of the role of LEDs in discovery is considered, and a framework for classifying processes of discovery based on LEDs i...

Probably Good Diagrams for Learning: Representational Epistemic Recodification of Probability Theory

The representational epistemic approach to the design of visual displays and notation systems advocates encoding the fundamental conceptual structure of a knowledge domain directly in the structure of a representational system. It is claimed that representations so designed will benefit from greater semantic transparency, which enhances comprehension and ease of learning, and plastic generativity, which makes the meaningful manipulation of the representation easier and less error prone. Epistemic principles for encoding fundamental conceptual structures directly in representational schemes are described. The diagrammatic recodification of probability theory is undertaken to demonstrate how the fundamental conceptual structure of a knowledge domain can be analyzed, how the identified conceptual structure may be encoded in a representational system, and the cognitive benefits that follow. An experiment shows the new probability space diagrams are superior to the conventional approach for learning this conceptually challenging topic.

Attention Design: Eight issues to consider

In HCI research there is a body of work concerned with the development of systems capable of reasoning about users’ attention and how this might be most effectively guided for specific applications. We present eight issues relevant to this endeavour: What is attention? How can attention be measured? How do graphical displays interact with attention? How do knowledge, performance and attention interact? What is working memory? How does doing two things at a time affect attention? What is the effect of artificial feedback loops on attention? Do attentional processes differ across tasks? For each issue we present design implications for developing attention–aware systems, and present a general discussion focussing on the dynamic nature of attention, tasks (number, nature and variety), level of processing, nature of the display, and validity of measures. In conclusion, we emphasise the need to adopt a dynamic view of attention and suggest that attention is a more complex phenomenon than some designers may have realised; however, embracing the multi-faceted nature of attention provides a range of design opportunities yet to be explored.

Interactive Law Encoding Diagrams for learning and instruction

Abstract Law Encoding Diagrams (LEDs) appear to be effective for learning and instruction, because they make the underlying relations of a domain more readily accessible than do traditional representations. Two systems of interactive computer based LEDs are described. The empirical evaluation of one system is reviewed. The potential of LEDs is analysed in terms of how they support different classes of activities that can be done with notation systems ( Kaput, 1992 ). Implementing LEDs as interactive computer based representations alleviates some of the potential difficulties of using them for learning. Strategies for effective learning with LEDs are discussed.

Why Diagrams Are (Sometimes) Six Times Easier than Words: Benefits beyond Locational Indexing

By building computational models, Larkin and Simon (1987) showed that the effects of locational indexing give an explanation of ’Why a diagam is (sometimes) worth ten thousand words’, to quote the title of their seminal paper. This paper reports an experiment in which participants solved three versions of Larkin and Simon’s simple pulley system problem with varying complexity. Participants used a diagrammatic, tabular or sentential representation, which had different degrees of spatial indexing of information. Solutions with the diagrams were up to six times easier than informationally equivalent sentential representations. Contrary to predictions derived from the idea of locational indexing, the tabular representation was not better overall than sentential representation and the proportional advantage of the diagrammatic representation over the others did not increase with problem complexity. This suggests that the advantage of diagrams goes beyond the effects that locational indexing has on the processes of searching for items of information and the recognition of applicable rules. A possible explanation resides in the specific problem solving strategies that the participants may have been using, which depended on the structure of the representations and the extent to which they supported solution path recognition and planning.

Opening the Information Bottleneck in Complex Scheduling Problems with a Novel Representation: STARK Diagrams

This paper addresses the design of representational systems for complex knowledge rich problems, focussing on scheduling in particular. Multiple tables are ubiquitous in representations of schedule information, but they impose large cognitive demands and inhibit the comprehension of high-level patterns. The application and evaluation of representational design principles in the development of STARK diagrams, a novel system for scheduling problems, is reported. STARK diagrams integrate conceptual dimensions, principal relations and individual cases into a single diagrammatic structure. An experiment compared performance on STARK diagrams and a conventional representation with features typical of current commercial scheduling software interfaces. Subjects using the STARK diagram performed better at improving an examination schedule by minimising constraint violations. This provides support for the validity and utility of the design principles.