We investigated retroactive transfer when users alternate between different interfaces. Retroactive transfer is the influence of a newly learned interface on users' performance with a previously learned interface. In an interview study, participants described their experiences when alternating between different interfaces, e.g. different operating systems, devices or techniques. Negative retroactive transfer related to text entry was the most frequently reported incident. We then reported a laboratory experiment that investigated the impact of similarity between two abstract keyboard layouts, and the number of alternations between them, on retroactive interference. Results indicated that even small changes in the interference interface produced a significant performance drop for the entire previously learned interface. The amplitude of this performance drop decreases with the number of alternations. We suggest that retroactive transfer should receive more attention in HCI, as the ubiquitous nature of interactions across applications and systems requires users to increasingly alternate between similar interfaces.

This paper describes a novel real-time 3D gaze estimation system. The system consists of two cameras and two IR light sources. There are three novelties in this method. First, in our system, two IR lights are mounted near the centers of the stereo cameras, respectively. Based on this specific configuration, the 3D position of the corneal center can be simply derived by the 3D reconstruction technique. Then, after extracting the 3D position of the "virtual pupil" correctly, the optical axis of the eye can be obtained directly by connecting the "virtual pupil" with the corneal center. Second, we systematically analyze the noise in our 3D gaze estimation algorithm and propose an effective constraint to reduce this noise. Third, to estimate the user-dependent parameters (i.e. the constraint parameters and the eye parameters), a simple calibration method is proposed by gazing at four positions on the screen. Experimental results show that our system can accurately estimate and track eye gaze under natural head movement.

Despite extensive research, it is still difficult to produce effective interactive layouts for large graphs. Dense layout and occlusion make food webs, ontologies, and social networks difficult to understand and interact with. We propose a new interactive Visual Analytics component called TreePlus that is based on a tree-style layout. TreePlus reveals the missing graph structure with visualization and interaction while maintaining good readability. To support exploration of the local structure of the graph and gathering of information from the extensive reading of labels, we use a guiding metaphor of "Plant a seed and watch it grow." It allows users to start with a node and expand the graph as needed, which complements the classic overview techniques that can be effective at (but often limited to) revealing clusters. We describe our design goals, describe the interface, and report on a controlled user study with 28 participants comparing TreePlus with a traditional graph interface for six tasks. In general, the advantage of TreePlus over the traditional interface increased as the density of the displayed data increased. Participants also reported higher levels of confidence in their answers with TreePlus and most of them preferred TreePlus.

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 user's motions and emotions, to building an understanding of the user's 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.

Memory can be internal or external - knowledge in-the-world or knowledge in-the-head. Making needed information available in an interface may seem the perfect alternative to relying on imperfect memory. However, the rational analysis framework (Anderson, 1990) suggests that least-effort tradeoffs may lead to imperfect performance even when perfect knowledge in-the-world is readily available. The implications of rational analysis for interactive behavior are investigated in two experiments. In experiment 1 we varied the perceptual-motor effort of accessing knowledge in-the-world as well as the cognitive effort of retrieving items from memory. In experiment 2 we replicated one of the experiment 1 conditions to collect eye movement data. The results suggest that milliseconds matter. Least-effort tradeoffs are adopted even when the absolute difference in effort between a perceptual-motor versus a memory strategy is small, and even when adopting a memory strategy results in a higher error rate and lower performance.

Software is increasingly being used to control safety-critical systems. Much research since Levesons fundamental article Software Safety: Why, What, and How (ACM Computing Surveys 18, 2 (1986), pp. 125163) has focused on ways to reduce or avoid software failures. However, the reliability of even the best-engineered software can be undermined by its user interface. Indeed, interface design for safety-critical interactive systems poses special challenges to the human-computer interaction community. This special issue addresses the challenge of analyzing, designing, and building reliable and usable safety-critical interactive systems. From a pragmatic point of view a safety-critical system is a system for which the cost of a failure is more important than the cost of developing the system. Safety-critical interactive systems add the human dimension to a software system by putting control into the hands of a human operator. Prominent examples of such control systems include nuclear power plants, railways systems, airplane cockpits, and military systems. Recent years have seen much effort put into the reengineering of the control system that is well represented in this special issueair traffic control. When compared to office automation systems, human-computer interac-tion for safety-critical interactive systems is both familiar and different. For instance, the management of a functionality like undo, that can be seen as a usability issue in an office automation system, can become a critical functionality when the user interacts with a safety-critical system. The three articles in this special issue provide three snapshots for how human-computer interaction issues play out in the broader field of safety-critical interactive systems. In the first article, Is Paper Safer? The Role of Flight Strips in Air Traffic Control, Wendy Mackay provides a detailed ethnographic study on how air traffic controllers work. As in Mackays article, the case study entails en-route air traffic control. An important contribution of this article is a method for an integrated analysis of three important methods of this field: task performance, analysis of user deviation and consequent hazard, and cooperation among users. Each of the three articles deals with the analysis and design phases of safety-critical interactive systems. If changes are to be made to large, complex, safety-critical control systems, the changes must be made early in the development lifecycle, where redesign in response to identified problems is feasible.This special issue arose from a CHI98 Workshop organized by Palanque and Paterno´ (“Designing User Interfaces for Safety-Critical Systems”, SIGCHI Bulletin 30, 4 ). The three articles included in this special issue were selected from more than a score of papers received. The editors thank and acknowledge their debt to the many qualified external reviewers from several countries who have helped select and improve (through their comments) the contributions in this special issue.

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 practitioner's 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.

published version is slightly different Gray, W. D., & Salzman, M. C. (1998). Repairing damaged merchandise: A

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 $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.

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 $2.4 million dollars a year to NYNEX. Scientificly, the GOMS models predicted performance with exceptional accuracy.