Wayne D. Gray

Basic objects in natural categories

Abstract Categorizations which humans make of the concrete world are not arbitrary but highly determined. In taxonomies of concrete objects, there is one level of abstraction at which the most basic category cuts are made. Basic categories are those which carry the most information, possess the highest category cue validity, and are, thus, the most differentiated from one another. The four experiments of Part I define basic objects by demonstrating that in taxonomies of common concrete nouns in English based on class inclusion, basic objects are the most inclusive categories whose members: (a) possess significant numbers of attributes in common, (b) have motor programs which are similar to one another, (c) have similar shapes, and (d) can be identified from averaged shapes of members of the class. The eight experiments of Part II explore implications of the structure of categories. Basic objects are shown to be the most inclusive categories for which a concrete image of the category as a whole can be formed, to be the first categorizations made during perception of the environment, to be the earliest categories sorted and earliest named by children, and to be the categories most codable, most coded, and most necessary in language.

Damaged merchandise? a review of experiments that compare usability evaluation methods

An interest in the design of interfaces has been a core topic for researchers and practitioners in the field of human-computer interaction (HCI); an interest in the design of experiments has not. To the extent that reliable and valid guidance for the former depends on the results of the latter, it is necessary that researchers and practitioners understand how small features of an experimental design can cast large shadows over the results and conclusions that can be drawn. In this review we examine the design of 5 experiments that compared usability evaluation methods (UEMs). Each has had an important influence on HCI thought and practice. Unfortunately, our examination shows that small problems in the way these experiments were designed and conducted call into serious question what we thought we knew regarding the efficacy of various UEMs. If the influence of these experiments were trivial, then such small problems could be safely ignored. Unfortunately, the outcomes of these experiments have been used to justify advice to practitioners regarding their choice of UEMs. Making such choices based on misleading or erroneous claims can be detrimental--compromising the quality and integrity of the evaluation, incurring unnecessary costs, or undermining the practitioners credibility within the design team. The experimental method is a potent vehicle that can help inform the choice of a UEM as well as help to address other HCI issues. However, to obtain the desired outcomes, close attention must be paid to experimental design.

Project ernestine: validating a GOMS analysis for predicting and explaining real-world task performance

Project Ernestine served a pragmatic as well as a scientific goal: to compare the worktimes of telephone company toll and assistance operators on two different workstations and to validate a GOMS analysis for predicting and explaining real-world performance. Contrary to expectations, GOMS predicted and the data confirmed that performance with the proposed workstation was slower than with the current one. Pragmatically, this increase in performance time translates into a cost of almost

The soft constraints hypothesis: A rational analysis approach to resource allocation for interactive behavior

2 million a year to NYNEX. Scientifically, the GOMS models predicted performance with exceptional accuracy. The empirical data provided us with three interesting results: proof that the new workstation was slower than the old one, evidence that this difference was not constant but varied with call category, and (in a trial that spanned 4 months and collected data on 72,450 phone calls) proof that performance on the new workstation stabilized after the first month. The GOMS models predicted the first two results and explained all three. In this article, we discuss the process and results of model building as well as the design and outcome of the field trial. We assess the accuracy of GOMS predictions and use the mechanisms of the models to explain the empirical results. Last, we demonstrate how the GOMS models can be used to guide the design of a new workstation and evaluate design decisions before they are implemented.

An Integrated Model of Cognitive Control in Task Switching.

Soft constraints hypothesis (SCH) is a rational analysis approach that holds that the mixture of perceptual-motor and cognitive resources allocated for interactive behavior is adjusted based on temporal cost-benefit tradeoffs. Alternative approaches maintain that cognitive resources are in some sense protected or conserved in that greater amounts of perceptual-motor effort will be expended to conserve lesser amounts of cognitive effort. One alternative, the minimum memory hypothesis (MMH), holds that people favor strategies that minimize the use of memory. SCH is compared with MMH across 3 experiments and with predictions of an Ideal Performer Model that uses ACT-Rs memory system in a reinforcement learning approach that maximizes expected utility by minimizing time. Model and data support the SCH view of resource allocation; at the under 1000-ms level of analysis, mixtures of cognitive and perceptual-motor resources are adjusted based on their cost-benefit tradeoffs for interactive behavior.

Forgetting to Remember: The Functional Relationship of Decay and Interference

A model of cognitive control in task switching is developed in which controlled performance depends on the system maintaining access to a code in episodic memory representing the most recently cued task. The main constraint on access to the current task code is proactive interference from old task codes. This interference and the mechanisms that contend with it reproduce a wide range of behavioral phenomena when simulated, including well-known task-switching effects, such as latency and error switch costs, and effects on which other theories are silent, such as with-run slowing and within-run error increase. The model generalizes across multiple task-switching procedures, suggesting that episodic task codes play an important role in keeping the cognitive system focused under a variety of performance constraints.

Transfer of Cognitive Skills

Functional decay theory proposes that decay and interference, historically viewed as competing accounts of forgetting, are instead functionally related. The theory posits that (a) when an attribute must be updated frequently in memory, its current value decays to prevent interference with later values, and (b) the decay rate adapts to the rate of memory updates. Behavioral predictions of the theory were tested in a task-switching paradigm in which memory for the current task had to be updated every few seconds, hundreds of times. Reaction times and error rates both increased gradually between updates, reflecting decay of memory for the current task. This performance decline was slower when updates were less frequent, reflecting a decrease in the decay rate following a decrease in the update rate. A candidate mechanism for controlled decay is proposed, the data are reconciled with practice effects, and implications for models of executive control are discussed.

Integrating perceptual and cognitive modeling for adaptive and intelligent human-computer interaction

Publisher Summary The cognitive science revolution has made impressive advances in the understanding of cognitive performance and the acquisition of cognitive skills. Based upon these successes, powerful theories are emerging that can predict when and how much transfer will occur. While these theories are diverse, their common denominator is the problem space hypothesis, with many of these theories using production systems as a tool for theory development and representation. This chapter describes the transfer of complex cognitive skills, such as text editing, with an emphasis on the relationship between transfer and learning. It presents the comparison of the cognitive science approach to transfer with the older verbal learning tradition. The chapter also presents a number of cognitive science concepts and methods that are important to the new study of transfer. The theoretical and practical goal of understanding the conditions of transfer of cognitive skills cannot go on in a vacuum. Before it can be possibly understood what is transferred, skilled performance must be understood and the way it is acquired.

The precis of Project Ernestine or an overview of a validation of GOMS

This paper describes technology and tools for intelligent human-computer interaction (IHCI) in which human cognitive, perceptual, motor and affective factors are modeled and used to adapt the H-C interface. IHCI emphasizes that human behavior encompasses both apparent human behavior and the hidden mental state behind behavioral performance. IHCI expands on the interpretation of human activities, known as W4 (what, where, when, who). While W4 only addresses the apparent perceptual aspect of human behavior the W5+ technology for IHCI described in this paper addresses also the why and how questions, whose solution requires recognizing specific cognitive states. IHCI integrates parsing and interpretation of nonverbal information with a computational cognitive model of the user which, in turn, feeds into processes that adapt the interface to enhance operator performance and provide for rational decision-making. The technology proposed is based on a general four-stage interactive framework, which moves from parsing the raw sensory-motor input, to interpreting the users motions and emotions, to building an understanding of the users current cognitive state. It then diagnoses various problems in the situation and adapts the interface appropriately. The interactive component of the system improves processing at each stage. Examples of perceptual, behavioral, and cognitive tools are described throughout the paper Adaptive and intelligent HCI are important for novel applications of computing, including ubiquitous and human-centered computing.

Suboptimal tradeoffs in information seeking.

INTRODUCTION Project Ernestine served a pragmatic as well as a scientific goal: to compare the worktimes of telephone company toll and assistance operators on two different workstations, and to test the validity of GOMSl models for predicting and explaining real-world performance. Contrary to expectations, GOMS predicted and the data confirmed, that performance with the proposed workstation was slower than with the current one, Pragmaticly, this increase in performance time translates into a cost of