David Peebles

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.

The effect of Gestalt laws of perceptual organization on the comprehension of three-variable bar and line graphs

Objective: We report three experiments investigating the ability of undergraduate college students to comprehend 2 × 2 “interaction” graphs from two-way factorial research designs. Background: Factorial research designs are an invaluable research tool widely used in all branches of the natural and social sciences, and the teaching of such designs lies at the core of many college curricula. Such data can be represented in bar or line graph form. Previous studies have shown, however, that people interpret these two graphical forms differently. Method: In Experiment 1, participants were required to interpret interaction data in either bar or line graphs while thinking aloud. Verbal protocol analysis revealed that line graph users were significantly more likely to misinterpret the data or fail to interpret the graph altogether. Results: The patterns of errors line graph users made were interpreted as arising from the operation of Gestalt principles of perceptual organization, and this interpretation was used to develop two modified versions of the line graph, which were then tested in two further experiments. One of the modifications resulted in a significant improvement in performance. Conclusion: Results of the three experiments support the proposed explanation and demonstrate the effects (both positive and negative) of Gestalt principles of perceptual organization on graph comprehension. Application: We propose that our new design provides a more balanced representation of the data than the standard line graph for nonexpert users to comprehend the full range of relationships in two-way factorial research designs and may therefore be considered a more appropriate representation for use in educational and other nonexpert contexts.

The effect of emergent features on judgments of quantity in configural and separable displays.

Two experiments investigated effects of emergent features on perceptual judgments of comparative magnitude in three diagrammatic representations: kiviat charts, bar graphs, and line graphs. Experiment 1 required participants to compare individual values; whereas in Experiment 2 participants had to integrate several values to produce a global comparison. In Experiment 1, emergent features of the diagrams resulted in significant distortions of magnitude judgments, each related to a common geometric illusion. Emergent features are also widely believed to underlie the general superiority of configural displays, such as kiviat charts, for tasks requiring the integration of information. Experiment 2 tested the extent of this benefit using diagrams with a wide range of values. Contrary to the results of previous studies, the configural display produced the poorest performance compared to the more separable displays. Moreover, the pattern of responses suggests that kiviat users switched from an integration strategy to a sequential one depending on the shape of the diagram. The experiments demonstrate the powerful interaction between emergent visual properties and cognition and reveal limits to the benefits of configural displays for integration tasks.

Beyond Single-Level Accounts: The Role of Cognitive Architectures in Cognitive Scientific Explanation

We consider approaches to explanation within the cognitive sciences that begin with Marrs computational level (e.g., purely Bayesian accounts of cognitive phenomena) or Marrs implementational level (e.g., reductionist accounts of cognitive phenomena based only on neural-level evidence) and argue that each is subject to fundamental limitations which impair their ability to provide adequate explanations of cognitive phenomena. For this reason, it is argued, explanation cannot proceed at either level without tight coupling to the algorithmic and representation level. Even at this level, however, we argue that additional constraints relating to the decomposition of the cognitive system into a set of interacting subfunctions (i.e., a cognitive architecture) are required. Integrated cognitive architectures that permit abstract specification of the functions of components and that make contact with the neural level provide a powerful bridge for linking the algorithmic and representational level to both the computational level and the implementational level.

Spaces or Scenes: Map-based Orientation in Urban Environments

Abstract Two experiments examined peoples strategies when orienting with a map in outdoor scenes within unfamiliar urban environments. We investigated how the 3D visual scene and the 2D layout geometry influenced peoples choices of features when matching the scene and the map, and studied the problems they encountered when doing so. Results support previous evidence that in geographically realistic contexts, visible salient landmarks bias people away from using optimal geometry-matching strategies. This implies that prediction of orientation difficulty merely from analysing the spatial layout (e.g., with space syntax isovist measures) may be highly problematic. Implications for future map design are discussed.

Thirty Years After Marr's Vision: Levels of Analysis in Cognitive Science.

Thirty years after the publication of Marrs seminal book Vision (Marr, 1982) the papers in this topic consider the contemporary status of his influential conception of three distinct levels of analysis for information-processing systems, and in particular the role of the algorithmic and representational level with its cognitive-level concepts. This level has (either implicitly or explicitly) been downplayed or eliminated both by reductionist neuroscience approaches from below that seek to account for behavior from the implementation level and by Bayesian approaches from above that seek to account for behavior in purely computational-level terms.

Modelling dynamic decision making with the ACT-R cognitive architecture

Modelling Dynamic Decision Making with the ACT-R Cognitive Architecture This paper describes a model of dynamic decision making in the Dynamic Stocks and Flows (DSF) task, developed using the ACT-R cognitive architecture. This task is a simple simulation of a water tank in which the water level must be kept constant whilst the inflow and outflow changes at varying rates. The basic functions of the model are based around three steps. Firstly, the model predicts the water level in the next cycle by adding the current water level to the predicted net inflow of water. Secondly, based on this projection, the net outflow of the water is adjusted to bring the water level back to the target. Thirdly, the predicted net inflow of water is adjusted to improve its accuracy in the future. If the prediction has overestimated net inflow then it is reduced, if it has underestimated net inflow it is increased. The model was entered into a model comparison competition—the Dynamic Stocks and Flows Challenge—to model human performance on four conditions of the DSF task and then subject the model to testing on five unseen transfer conditions. The model reproduced the main features of the development data reasonably well but did not reproduce human performance well under the transfer conditions. This suggests that the principles underlying human performance across the different conditions differ considerably despite their apparent similarity. Further lessons for the future development of our model and model comparison challenges are considered.

Editorial: Macrocognition: The science and engineering of sociotechnical work systems

1 The Applied Cognition & Cognitive Engineering Research Group, University of Huddersfield, Huddersfield, UK, 2 Florida Institute for Human and Machine Cognition, Ocala, FL, USA, Defence Science and Technology Laboratory (Dstl), Porton Down, UK, 4 TNO Netherlands Organisation for Applied Scientific Research, Soesterberg, Netherlands, 5 Trimetis Ltd., Bristol, UK, College of Human Medicine, Michigan State University, East Lansing, MI, USA

On the relation between Marr’s levels: a response to Blokpoel (2017)

Blokpoel reminds us of the importance of consistency of function across Marrs levels, but we argue that the approach to ensuring consistency that he advocates-a strict relation through exact implementation of the higher level function at the lower level-is unnecessarily restrictive. We show that it forces overcomplication of the computational level (by requiring it to incorporate concerns from lower levels) and results in the sacrifice of the distinct responsibilities associated with each level. We propose an alternative, no less rigorous, potential characterization of the relation between levels.

An innovative virtual reality training tool for orthognathic surgery

Virtual reality (VR) surgery using Oculus Rift and Leap Motion devices is a multi-sensory, holistic surgical training experience. A multimedia combination including 360° videos, three-dimensional interaction, and stereoscopic videos in VR has been developed to enable trainees to experience a realistic surgery environment. The innovation allows trainees to interact with the individual components of the maxillofacial anatomy and apply surgical instruments while watching close-up stereoscopic three-dimensional videos of the surgery. In this study, a novel training tool for Le Fort I osteotomy based on immersive virtual reality (iVR) was developed and validated. Seven consultant oral and maxillofacial surgeons evaluated the application for face and content validity. Using a structured assessment process, the surgeons commented on the content of the developed training tool, its realism and usability, and the applicability of VR surgery for orthognathic surgical training. The results confirmed the clinical applicability of VR for delivering training in orthognathic surgery. Modifications were suggested to improve the user experience and interactions with the surgical instruments. This training tool is ready for testing with surgical trainees.