Publication statistics
Pub. period:1987-2012
Pub. count:44
Number of co-authors:55
Co-authors
Number of publications with 3 favourite co-authors:
Michael J. Schoelles:6Michael E. Atwood:6Bonnie E. John:6 Productive colleagues
Wayne D. Gray's 3 most productive colleagues in number of publications:
Fabio Paterno:118Elliot Soloway:77T. R. G. Green:70
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Wayne D. Gray
Personal Homepage:
http://www.rpi.edu/~graywCurrent place of employment:
Rensselaer Polytechnic Institute
Wayne Gray seeks to understand how goal-directed cognition is shaped by the accommodation of basic cognitive, perceptual, and motor operations to the cost-benefit structure of the designed task environment. These basic elements of integrated behavior, interactive routines, occur over a time span of 1/3 to 3 seconds and are typically beneath the level of our conscious awareness and deliberate control. Hence, non-deliberate forces that dynamically react to our task environment without our conscious awareness shape a large part of our mental life.
There is a basic and applied component to this research agenda. The Cognitive Science side focuses on the control of interactive behavior, resource allocation, dynamic decision-making, memory, attention, and motor movement. The Cognitive Engineering side can be characterized by the terms visual-analytics, human-computer interaction (HCI), cognitive workload, and human error. The two types of research feed into each other and are supported by a core of common techniques and methods including computational cognitive modeling, cognitive task analysis, and detailed collection and analysis of behaviors that take less than 1000 milliseconds to occur (e.g., eeg, keystrokes, mouse movements, and eye gaze).
Wayne earned his Ph.D. from U. C. Berkeley in 1979. His first position was with the U. S. Army Research Institute where he worked on tactical team training (at the Monterey Field Unit) and later on the application of artificial intelligence (AI) technology to training for air-defense systems (HAWK) (at ARI-HQ Alexandria, VA). He spent a post-doctoral year with Prof. John R. Anderson's lab at Carnegie Mellon University before joining the AI Laboratory of NYNEX' Science & Technology Division. At NYNEX he applied cognitive task analysis and cognitive modeling to the design and evaluation of interfaces for large, commercial telecommunications systems. His academic career began at Fordham University and then moved to George Mason University. He joined the Cognitive Science Department at Rensselaer Polytechnic Institute in 2002.
He is an active member of his professional communities. Dr. Gray is the Editor-in-Chief for topiCS, Topics in Cognitive Science, the newest journal of the Cognitive Science Society. He is a past Associate Editor for the Cognitive Science journal (2006-2008), the Cognitive Systems Research journal (2003-2008), the Human Factors journal (1998-2006), and ACM's Transactions on Computer-Human Interaction (1995-2003). He Chaired the Fourth International Conference on Cognitive Modeling (ICCM-2001) and co-Chaired the Cognitive Science Society Conference in 2002. He is the founding Chair of HFES' Human-Performance Modeling Technical Group (HPM-TG). In 2001 he was elected to a 6-yr term on the Board of Governors for the Cognitive Science Society where he served as Chair and member of the Executive Committee from 2003-2006.
Publications by Wayne D. Gray (bibliography)
John, Bonnie E., Patton, Evan W., Gray, Wayne D. and Morrison, Donald F. (2012): Tools for Predicting the Duration and Variability of Skilled: Performance without Skilled Performers. In: Proceedings of the Human Factors and Ergonomics Society 2012 Annual Meeting 2012. pp. 985-989.
“Many devices are designed to allow skilled users to complete routine tasks quickly, often within a specified amount of time. Predictive human performance modeling has long been able to predict the mean time to accomplish a task, making it possible to compare device designs before building them. However, estimates of the variability of performance are also important, especially in real-time, safety-critical tasks. Until recently, the human factors community lacked tools to predict the variability of skilled performance. In this paper, we describe a combination of theory-based tools (CogTool and SANLab) that address this critical gap and that can easily be used by human factors practitioners or system designers. We describe these tools, their integration, and provide a concrete example of their use in the context of entering the landing speed into the Boeing 777 Flight Management Computer (FMC) using the Control and Display Unit (CDU).”
© All rights reserved John et al. and/or Human Factors and Ergonomics Society
Hope, Ryan M., Wang, Ziheng, Wang, Zuoguan, Ji, Qiang and Gray, Wayne D. (2011): Workload Classification Across Subjects Using EEG. In: Proceedings of the Human Factors and Ergonomics Society 55th Annual Meeting 2011. pp. 202-206.
“EEG data has been used to discriminate levels of mental workload when classifiers are created for each subject, but the reliability of classifiers trained on multiple subjects has yet to be investigated. Artificial neural network and naive Bayesian classifiers were trained with data from single and multiple subjects and their ability to discriminate among three difficulty conditions was tested. When trained on data from multiple subjects, both types of classifiers poorly discriminated between the three levels. However, a novel model, the naive Bayesian classifier with a hidden node, performed nearly as well as the models trained and tested on individuals.”
© All rights reserved Hope et al. and/or HFES
Pfaff, Mark S., Allender, Laurel, Gray, Wayne D., McNeese, Michael D., Mendonca, David J. and Wright, Melanie C. (2010): Multidisciplinary Perspectives on Simulations and Games in Human Factors Research. In: Proceedings of the Human Factors and Ergonomics Society 54th Annual Meeting 2010. pp. 294-298.
“Much has been already been said about what simulations and games can provide that other research methodologies do not. But the complexity and richness of the results they afford in human factors research is matched by the complexity and cost of their conception, design, implementation, and validation. Though this may seem a daunting challenge to those considering such platforms for their own research, this panel aims to air the promises and pitfalls of simulations and games by sharing historical exemplars, lessons learned, and current issues in their use for human factors research. The panelists represent decades of experience in military, medical, and civilian research domains and have worked through abundant successes and failures in this area. Key issues of discussion will include cases which stand out as exemplary instances of using simulations and games in human factors research, particularly those that produced results that would have been unattainable by other methods, the challenges and constraints of participant pools (e.g. naïve subjects, access to domain experts, and suitable compromises), development of viable and engaging simulations (e.g., the problem of software written by grad students, for grad students), collection of accurate and meaningful data, and the generalizability of such game and simulation platforms as well as the adaptability of off-the-shelf solutions.”
© All rights reserved Pfaff et al. and/or HFES
Ralph, Jason, Gray, Wayne D. and Schoelles, Michael J. (2010): Squeezing the Balloon: Analyzing the Unpredictable Effects of Cognitive Workload. In: Proceedings of the Human Factors and Ergonomics Society 54th Annual Meeting 2010. pp. 299-303.
“Cognitive workload effects behavior like squeezing a balloon. If you squeeze at one place, it pops out at another, and it is hard to predict where it's going to pop out. Understanding workload requires understanding the control of cognition at the 1/3 to 3s-time span during which cognitive, perceptual, and motor operations become bound together into interactive routines. Interactive routines constitute unit tasks (3 to 30 s), and unit tasks constitute subtasks (30s to 3min). To reduce cognitive workload and overload, the Functional Resource Hypothesis maintains that an optimal allocation of interactive routines to task performance would be based on the functional resource of time not modality. Some of the implications of this hypothesis are investigated in an empirical study that varied memory load as well as the demands on the eyes, visual attention, auditory cognition, and motor operations. A microanalysis of the data revealed tradeoffs between groups in their pattern of resource allocation that were compatible with the Functional Resource Hypothesis and led to surprising behavioral effects.”
© All rights reserved Ralph et al. and/or HFES
Myers, Christopher W. and Gray, Wayne D. (2010): Visual scan adaptation during repeated visual search. In Journal of Vision, 10 (8) .
“There is no consensus as to how to characterize eye fixations during visual search. On the one hand, J. M. Wolfe, G. A. Alvarez, and T. S. Horowitz (2000) have described them as a haphazard sequence of fixations. On the other hand is research that shows systematic repetition of visual patterns when freely viewing a scene (T. Foulsham&G. Underwood, 2008; D. Noton&L. W. Stark, 1971a). Two experiments are reported that demonstrate the repetition and adaptation of visual scans during visual search, supporting an adaptive scanning hypothesis. When trials were repeated in a simple search task, visual scan similarity and search efficiency increased. These increments in similarity and efficiency demonstrate the systematic and adaptive nature of visual scans to the characteristics of the visual environment during search.”
© All rights reserved Myers and Gray and/or their publisher
Patton, Evan W. and Gray, Wayne D. (2010): SANLab-CM: A tool for incorporating stochastic operations into activity network modeling. In Behavior Research Methods, 42 (3) pp. 877-883.
“The Stochastic Activity Network Laboratory for Cognitive Modeling (SANLab-CM) is a new tool that incorporates stochastic operations into activity network modeling (Schweickert, Fisher,&Proctor, 2003). In this article, we discuss the core functionality of SANLab-CM and walk through a case study that expands a previously published single, static path model of telephone operators interacting with customers via a workstation (from Gray, John,&Atwood, 1993) into a stochastic model that generates 55 unique paths with different frequencies and a variety of qualitative properties. Without SANLab-CM, it would have been easy to mistake some of the more frequent critical paths as evidence for alternative strategies for task completion. With SANLab-CM, these critical paths can be shown to be simple emergent properties of variability in elementary cognitive, perceptual, and motor processes.”
© All rights reserved Patton and Gray and/or their publisher
Ralph, Jason, Gray, Wayne D. and Schoelles, Michael J. (2009): The Functional Resource Hypothesis as a Basis for Understanding Cognitive Workload in Immediate Interactive Behavior. In: Proceedings of the Human Factors and Ergonomics Society 53rd Annual Meeting 2009. pp. 404-408.
“Understanding workload requires understanding the control of cognition at the 1/3 to 3s time span during which cognitive, perceptual, and motor operations become bound together into interactive routines. Interactive routines constitute unit tasks (3 to 30 s), and unit tasks constitute subtasks (30s to 3min). To reduce cognitive workload and overload, the Functional Resource Hypothesis maintains that an optimal allocation of interactive routines to task performance would be based on the functional resource of time not modality. Some of the implications of this hypothesis are investigated in an empirical study that varied memory load as well as the demands on the eyes, visual attention, auditory cognition, and motor operations. A microanalysis of the data revealed tradeoffs between groups in their pattern of resource allocation that were compatible with the Functional Resource Hypothesis.”
© All rights reserved Ralph et al. and/or their publisher
Patton, Evan W., Gray, Wayne D. and Schoelles, Michael J. (2009): SANLab-CM The Stochastic Activity Network Laboratory for Cognitive Modeling. In: Proceedings of the Human Factors and Ergonomics Society 53rd Annual Meeting 2009. pp. 1654-1658.
“SANLab-CM is an activity network tool for the stochastic modeling of routine interactive behavior. Within the cognitive engineering community the best-known examples of activity networking modeling are the CPM-GOMS models of Project Ernestine (Gray, John,&Atwood, 1993). Project Ernestine showed that modeling the parallel use of cognitive, perceptual, and motor resources within an activity network formalism produces reliable and accurate predictions of expert performance times across alternative designs for the same task. SANLab-CM provides time predictions, but its essence is the prediction of procedural variability amidst strategic constancy: when expert human performers follow the same task strategy from trial to trial variability in the processing time of cognitive, perceptual, and motor resources is such as to produce different critical paths of performance and significantly different execution times. The stochastic component of SANLab-CM goes beyond current techniques to create a new means of assessing alternative designs based on the procedural variability expected in expert performance.”
© All rights reserved Patton et al. and/or their publisher
Neth, Hansjörg, Khemlani, Sangeet S. and Gray, Wayne D. (2008): Neth, H., Khemlani, S.S., & Gray, W.D. (2008). Feedback Design for the Control of a Dynamic Multitasking System: Dissociating Outcome Feedback from Control Feedback. In Human Factors, 50 (4) p. 643–651.
“Objective: We distinguish outcome feedback from control feedback to show that suboptimal performance in a dynamic multitasking system may be caused by limits inherent to the information provided rather than human resource limits. Background: Tardast is a paradigm for investigating human multitasking behavior, complex system management, and supervisory control. Prior research attributed the suboptimal performance of Tardast operators to poor strategic task management. Methods: We varied the nature of performance feedback in the Tardast paradigm to compare continuous, cumulative feedback (global feedback) on performance outcome with feedback limited to the most recent system state (local feedback). Results: Participants in both conditions improved with practice, but those with local feedback performed better than those with global feedback. An eye gaze analysis showed increased visual attention directed toward the feedback display in the local feedback condition. Conclusion: Predicting performance in the control of a dynamic multitasking system requires understanding the interactions between embodied cognition, the task being performed, and characteristics of performance feedback. In the current case, at least part of what had been diagnosed as a deficit caused by limited cognitive resources has been shown to be data limited. Application: Perfect outcome feedback can provide inadequate control feedback.Instances of suboptimal performance can be alleviated by better feedback design that takes into account the temporal dynamics of the human-system interaction.”
© All rights reserved Neth et al. and/or Human Factors Society
Chen, Jixu, Tong, Yan, Gray, Wayne D. and Ji, Qiang (2008): A robust 3D eye gaze tracking system using noise reduction. In: Räihä, Kari-Jouko and Duchowski, Andrew T. (eds.) ETRA 2008 - Proceedings of the Eye Tracking Research and Application Symposium March 26-28, 2008, Savannah, Georgia, USA. pp. 189-196.
Altmann, Erik M. and Gray, Wayne D. (2008): An integrated model of cognitive control in task switching. In Psychological Review, 115 (3) pp. 602-639.
“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 performance is proactive interference from old codes, which limits this access. Other memory processes are organized to overcome this interference, reproducing a wide range of behavioral phenomena as they operate. This cognitive-control model (CCM) accounts for switch cost and other well-known task-switching phenomena, and for effects like within-run slowing and error increase on which other theories are silent. CCM 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. ”
© All rights reserved Altmann and Gray and/or their publisher
Gray, Wayne D. (2008): Cognitive architectures: Choreographing the dance of mental operations with the task environments. In Human Factors, 50 (3) pp. 497-505.
“Objective: In this paper, I present the ideas and trends that have given rise to the use of cognitive architectures in human factors, provide a cognitive-engineering-oriented taxonomy of these architectures, and a snapshot of their use for cognitive engineering. Background: Architectures of cognition have had a long history in human factors but a brief past. The long history entails a 50 yr preamble, whereas the explosion of work in the current decade reflects the brief past. Understanding this history is key to understanding the current and future prospects for applying cognitive science theory to human factors practice. Method: The review defines three formative eras in cognitive engineering research; the 1950s, 1980s, and now. Results: In the first era the fledging fields of Cognitive Science and Human Factors emphasized characteristics of the dancer, the limited capacity or bounded rationality view of the mind, and the ballroom, the task environment. The second era emphasized the dance; i.e., the dynamic interaction between mental operations and task environment. The third era has seen the rise of cognitive architectures as tools for choreographing the dance of mental operations within the complex environments posed by human factors practice. Conclusions: Hybrid architectures present the best vector for introducing Cognitive Science theories into a renewed engineering-based Human Factors. Application: The taxonomy provided in the paper may provide guidance on when and whether to apply a cognitive science or a hybrid architecture to a human factors issue.
”
© All rights reserved Gray and/or Human Factors Society
Gray, Wayne D. (ed.) (2007): Integrated models of cognitive systems. New York, Oxford University Press
“[from the dust jacket] The field of cognitive modeling has progressed beyond modeling cognition in the context of simple laboratory tasks and begun to attack the problem of modeling it in more complex, realistic environments, such as those studied by researchers in the field of human factors. The problems that the cognitive modeling community is tackling focus on modeling certain problems of communication and control that arise when integrating with the external environment factors such as implicit and explicit knowledge, emotion, cognition, and the cognitive system. These problems must be solved in order to produce integrated cognitive models of moderately complex tasks. Architectures of cognition in these tasks focus on the control of a central system, which includes control of the central processor itself, initiation of functional processes, such as visual search and memory retrieval, and harvesting the results of these functional processes. Because the control of the central system is conceptually different from the internal control required by individual functional processes, a complete architecture of cognition must incorporate two types of theories of control: Type 1 theories of the structure, functionality, and operation of the controller, and type 2 theories of the internal control of functional processes, including how and what they communicate to the controller. This book presents the current state of the art for both types of theories, as well as contrasts among current approaches to human-performance models. It will be an important resource for professional and student researchers in cognitive science, cognitive-engineering, and human-factors.
”
© All rights reserved Gray and/or Oxford University Press
Liao, Wenhui, Zhang, Weihong, Zhu, Zhiwei, Ji, Qiang and Gray, Wayne D. (2006): Toward a decision-theoretic framework for affect recognition and user assistance. In International Journal of Human-Computer Studies, 64 (9) pp. 847-873.
“There is an increasing interest in developing intelligent human-computer interaction systems that can fulfill two functions -- recognizing user affective states and providing the user with timely and appropriate assistance. In this paper, we present a general unified decision-theoretic framework based on influence diagrams for simultaneously modeling user affect recognition and assistance. Affective state recognition is achieved through active probabilistic inference from the available multi modality sensory data. User assistance is automatically accomplished through a decision-making process that balances the benefits of keeping the user in productive affective states and the costs of performing user assistance. We discuss three theoretical issues within the framework, namely, user affect recognition, active sensory action selection, and user assistance. Validation of the proposed framework via a simulation study demonstrates its capability in efficient user affect recognition as well as timely and appropriate user assistance. Besides the theoretical contributions, we build a non-invasive real-time prototype system to recognize different user affective states (stress and fatigue) from four-modality user measurements, namely physical appearance features, physiological measures, user performance, and behavioral data. The affect recognition component of the prototype system is subsequently validated through a real-world study involving human subjects.”
© All rights reserved Liao et al. and/or Academic Press
Gray, Wayne D., Sims, Chris R., Fu, Wai-Tat and Schoelles, Michael J. (2006): The soft constraints hypothesis: A rational analysis approach to resource allocation for interactive behavior. In Psychological Review, 113 (3) pp. 461-482.
“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-R’s 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-millisecond level of analysis, mixtures of cognitive and perceptual-motor resources are adjusted based on their cost-benefit tradeoffs for interactive behavior.”
© All rights reserved Gray et al. and/or their publisher
Gray, Wayne D., Neth, Hansjörg and Schoelles, Michael J. (2006): The functional task environment. In: Kramer, Arthur F., Wiegman, Douglas A. and Kirlik, Alex (eds.). "Attention: From theory to practice". New York: Oxford University Presspp. 100-118
“[from the introduction] This chapter introduces the concept of the functional task environment (a brief definition is provided in the next section). This concept integrates disparate findings that show important differences between the physical task environment and the ways in which humans perceive, think about, and act on the physical world. The productivity of this concept will be judged by its success at motivating research that leads to the building of integrated models of cognitive systems (Gray, 2007). The functional task environment encompasses both blades of Newell and Simon’s scissors. Indeed, rather than the metaphor of the scissors, which suggests two structurally independent blades that are used to cut the mental world into small pieces, a metaphor for the functional task environment might be a laser beam that combines “an analysis of the structure of task environments” with “an analysis of the limits of rational adaptation” to provide a strong and focused light onto the operation of a cognitive system that is integrated with the world as well as with perception and action.”
© All rights reserved Gray et al. and/or Oxford University Press
Fu, Wai-Tat and Gray, Wayne D. (2006): Suboptimal tradeoffs in information seeking. In Cognitive Psychology, 52 (3) pp. 195-242.
“Explicit information-seeking actions are needed to evaluate alternative actions in problem-solving tasks. Information-seeking costs are often traded off against the utility of information. We present three experiments that show how subjects adapt to the cost and information structures of environments in a map-navigation task. We found that subjects often stabilize at suboptimal levels of performance. A Bayesian satisficing model (BSM) is proposed and implemented in the ACT-R architecture to predict information-seeking behavior. The BSM uses a local decision rule and a global Bayesian learning mechanism to decide when to stop seeking information. The model matched the human data well, suggesting that adaptation to cost and information structures can be achieved by a simple local decision rule. The local decision rule, however, often limits exploration of the environment and leads to suboptimal performance. We propose that suboptimal performance is an emergent property of the dynamic interactions between cognition and the environment.”
© All rights reserved Fu and Gray and/or their publisher
Gray, Wayne D., Schoelles, Michael J. and Myers, Christopher W. (2005): Profile before optimizing: a cognitive metrics approach to workload analysis. In: Proceedings of ACM CHI 2005 Conference on Human Factors in Computing Systems 2005. pp. 1411-1414.
“The Intelligence Analyst (IA) community will soon be the designated users of many new software tools. In the multitasking world of the IA, any one tool cannot be permitted to greedily consume cognitive resources. This situation requires a new approach to usability assessment; one that profiles the moment-by-moment demands placed on embodied cognition by a given software tool during task performance. The approach we have taken relies on families of cognitive models that interleave cognition, perception, and action at the 1/3 to 3 sec timescale. This is the level of analysis where embodied cognition forms interactive routines that adapt to the cost-benefit structure of the software tool. Our proof-of-concept is a model that performs a task that the IAs find challenging. From the trace of the model, we derive a cognitive metrics profile that pinpoints dynamic changes in workload demands on human cognitive, perceptual, or action systems.”
© All rights reserved Gray et al. and/or ACM Press
Gray, Wayne D. and Fu, Wai-Tat (2004): Soft constraints in interactive behavior: The case of ignoring perfect knowledge in-the-world for imperfect knowledge in-the-head. In Cognitive Science, 28 (3) pp. 359-382.
“Constraints and dependencies among the elements of embodied cognition form patterns or microstrategies of interactive behavior. Hard constraints determine which microstrategies are possible. Soft constraints determine which of the possible microstrategies are most likely to be selected. When selection is non-deliberate or automatic the least effort microstrategy is chosen. In calculating the effort required to execute a microstrategy each of the three types of operations, memory retrieval, perception, and action, are given equal weight; that is, perceptual-motor activity does not have a privileged status with respect to memory. Soft constraints can work contrary to the designer’s intentions by making the access of perfect knowledge in-the-world more effortful than the access of imperfect knowledge in-the-head. These implications of soft constraints are tested in two experiments. In experiment 1 we varied the perceptual-motor effort of accessing knowledge in-the-world as well as the 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. Soft constraints lead to a reliance on knowledge in-the-head even when the absolute difference in perceptual-motor versus memory retrieval effort is small, and even when relying on memory leads to a higher error rate and lower performance. We discuss the implications of soft constraints for routine interactive behavior, accounts of embodied cognition, and tool and interface design.”
© All rights reserved Gray and Fu and/or Ablex Publishing
Fu, Wai-Tat and Gray, Wayne D. (2004): Resolving the paradox of the active user: Stable suboptimal performance in interactive tasks. In Cognitive Science, 28 (6) pp. 901-935.
“This paper brings the intellectual tools of cognitive science to bear on resolving the “paradox of the active user” (Carroll&Rosson, 1987) – the persistent use of inefficient procedures in interactive tasks by experienced or even expert users when demonstrably more efficient procedures exist. The goal of this paper is to understand the roots of this paradox by finding regularities in these inefficient procedures. We examine three very different data sets. For each data set, we first satisfy ourselves that the preferred procedures used by some subjects are indeed less efficient than the recommended procedures. We then amass evidence, for each set, and conclude that when a preferred procedure is used instead of a more efficient, recommended procedure, the preferred procedure tends to have two major characteristics: (1) the preferred procedure is a well-practiced, generic procedure that is applicable either within the same task environment in different contexts or across different task environments, and (2) the preferred procedure is composed of interactive components that bring fast, incremental feedback on the external problem states. The support amassed for these characteristics leads to a new understanding of the paradox. In interactive tasks, people are biased towards the use of general procedures that start with interactive actions. These actions require much less cognitive effort as each action results in an immediate change to the external display that, in turn, cues the next action. Unfortunately for the users, the bias to use interactive unit tasks leads to a path that requires more effort in the long run. Our data suggest that interactive behavior is composed of a series of distributed choices; that is, people seldom make a once-and-for-all decision on procedures. Similar to what is observed in human choice behavior in many decision-making tasks, this series of biased selection of interactive unit tasks often leads to a stable sub-optimal level of performance.”
© All rights reserved Fu and Gray and/or Ablex Publishing
Gray, Wayne D. (2002): Simulated task environments: The role of high-fidelity simulations, scaled worlds, synthetic environments, and microworlds in basic and applied cognitive research. In Cognitive Science Quarterly, 2 (2) p. 205–227.
“Simulated task environments provide a setting that adds controlled complexity to experimental tasks performed by human subjects in laboratory research. Researchers whose problems are mostly applied may find that their problems are easier to study in a simulated task environment than in the actual task environment. Researchers whose theories have been nurtured in the simple environments of the typical laboratory study may find that adding controlled complexity will allow them to study how the theoretical constructs they have studied in isolation interact with other constructs in a more complex task environment. In this article I define a taxonomy and three dimensions of simulated task environments. The dimensions are based on viewing simulated task environments from the perspectives of the researcher, the task, and the participants. Research on complex systems is inherently complex. It is my hope that the terms and distinctions introduced in this article will further the scientific enterprise by enabling us to spend less time explaining our paradigms and more time communicating our results.”
© All rights reserved Gray and/or his/her publisher
Gray, Wayne D. and Fu, Wai-Tat (2001): Ignoring Perfect Knowledge In-the-World for Imperfect Knowledge In-the-Head. In: Beaudouin-Lafon, Michel and Jacob, Robert J. K. (eds.) Proceedings of the ACM CHI 2001 Human Factors in Computing Systems Conference March 31 - April 5, 2001, Seattle, Washington, USA. pp. 112-119.
“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.”
© All rights reserved Gray and Fu and/or ACM Press
Gray, Wayne D. (2000): The nature and processing of errors in interactive behavior. In Cognitive Science, 24 (2) pp. 205-248.
“Understanding the nature of errors in a simple, rule-based task – programming a VCR – required analyzing the interactions among human cognition, the artifact, and the task. This analysis was guided by least-effort principles and yielded a control structure that combined a device-task rule-hierarchy with display-based difference-reduction. A model based on this analysis was used to trace action protocols collected from participants as they programmed a simulated VCR. Trials that ended without success (the show was not correctly programmed) were interrogated to yield insights regarding problems in acquiring the control structure. For successful trials (the show was correctly programmed), steps that the model would make were categorized as matches to the model; steps that the model would not make were violations of the model. The model was able to trace the vast majority of correct keystrokes and yielded a business-as-usual account of the detection and correction of errors. Violations of the model fell into one of two fundamental categories. The model provided insights into certain subcategories of errors; whereas, regularities within other subcategories of error suggested limitations to the model. Although errors were rare when compared to the total number of correct actions, they were important. Problems with just 4% of the keypresses would have prevented two-thirds of the shows from being successfully recorded. A misprogrammed show is a minor annoyance to the user. However, devices with the approximate complexity of a VCR are ubiquitous and have found their way into emergency rooms, airplane cockpits, power plants, and so on. Errors of ignorance may be reduced by training; however, errors in the routine performance of skilled users can only be reduced by design.”
© All rights reserved Gray and/or Ablex Publishing
Gray, Wayne D. and Boehm-Davis, Deborah (2000): Milliseconds Matter: An introduction to microstrategies and to their use in describing and predicting interactive behavior. In Journal of Experimental Psychology: Applied, 6 (4) p. 322–335.
“Interactive behavior is constrained by the design of the artifacts available (such as a mouse and button) as well as by the ways in which elementary cognitive, perceptual, and motor operations can be combined. Any two basic activities, for example (a) moving to and (b) clicking on a button, can be combined to yield a limited number of microstrategies. The results of an experimental study suggest that alternative microstrategies can be deployed that shave milliseconds from routine interactive behavior. Data from a usability study are used to explore the potential of microstrategies for (a) bracketing the range of individual performance (b) profiling individual differences, and (c) diagnosing mismatches between expected and obtained performance. These two studies support the arguments that the microstrategies deployed can be sensitive to small features of an interface and that task analyses at the millisecond level can inform design.”
© All rights reserved Gray and Boehm-Davis and/or American Psychological Association
Gray, Wayne D., Palanque, Philippe A. and Paterno, Fabio (1999): Introduction to the Special Issue on Interface Issues and Designs for Safety-Critical Interactive Systems: When There is No Room for User Error. In ACM Computing Surveys (CSUR), 6 (4) pp. 309-310.
Gray, Wayne D. and Salzman, Marilyn C. (1998): Damaged Merchandise? A Review of Experiments That Compare Usability Evaluation Methods. In Human-Computer Interaction, 13 (3) pp. 203-261.
“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.”
© All rights reserved Gray and Salzman and/or Taylor and Francis
Gray, Wayne D. and Salzman, Marilyn C. (1998): Repairing Damaged Merchandise: A Rejoinder. In Human-Computer Interaction, 13 (3) pp. 325-335.
“Our goal in writing "Damaged Merchandise?" (DM) was not to have the last word on the subject but to raise an awareness within the human-computer interaction (HCI) community of issues that we felt had been too long ignored or neglected. On reading the 10 commentaries from distinguished members of the HCI community, we were pleased to see that they had joined the debate and broadened the discussion. Subsequently, we were some what torn by how to proceed. Our first thought was to respond point by point, commentary by commentary. However, we refrain from addressing many specific issues here, as a full discussion would involve an article at least as long as DM. Instead we focus on a few important themes that emerged throughout our article and the ensuing discussion: * What is usability, how do we measure it, and what do we need to know about our usability evaluation methods (UEMs)? * Why do we find ourselves where we are? * What is the role of experiments versus other empirical studies in HCI? Are there common issues in the design of empirical studies? * How do we judge the value of a study? * Where do we go from here?”
© All rights reserved Gray and Salzman and/or Taylor and Francis
Gray, Wayne D., Young, Richard M. and Kirschenbaum, Susan S. (1997): Introduction to This Special Issue on Cognitive Architectures and Human-Computer Interaction. In Human-Computer Interaction, 12 (4) pp. 301-309.
“This special issue was assembled by editors and contributors who believe that cognitive architectures provide the most important new contribution to a theoretical basis for HCI (human-computer interaction) since the publication of The Psychology of Human-Computer Interaction (Card, Moran,&Newell, 1983). In this introduction, we provide a brief overview of what cognitive architectures are and why we find them exciting. Then we introduce the four architectures represented by articles in this special issue.”
© All rights reserved Gray et al. and/or Taylor and Francis
Gray, Wayne D., Boehm-Davis, Deborah A. and Spohrer, James C. (eds.) Empirical Studies of Programmers - Sixth Workshop January 5-7, 1996, 1996, Alexandria, Virginia.
Kirschenbaum, Susan S., Gray, Wayne D. and Young, Richard M. (1996): Cognitive Architectures and HCI. In ACM SIGCHI Bulletin, 28 (2) pp. 18-21.
“The Cognitive Architectures and Human-Computer Interaction Workshop examined computational cognitive modeling approaches to human-computer interaction issues (HCI). The five major architectures and variations represented were briefly summarized. Participants compared approaches to a set of selected HCI problems and alternative solutions, and compared the strengths and weaknesses of the architectures. A list of additional issues was generated and discussed.”
© All rights reserved Kirschenbaum et al. and/or ACM Press
Boehm-Davis, Deborah A. and Gray, Wayne D. (1996): ESP6 (or, Snowbound during the great storm of '96): 6th Workshop on Empirical Studies of Programmers, Alexandria, Virginia, USA, Jan 5-7. In ACM SIGCHI Bulletin, 28 (3) pp. 42-43.
Gray, Wayne D., John, Bonnie E., Nardi, Bonnie A., Petre, Marion, Spohrer, James C. and Turner, Althea A. (1993): End-User Programming. In: Cook, Curtis, Scholtz, Jean and Spohrer, James C. (eds.) Empirical Studies of Programmers - Fifth Workshop December 3-15, 1993, 1993, Palo Alto, California. pp. 1-2.
“End-user programming involves the end user building new tools, not simply using an application. Hence, word processing is not an example of end-user programming while building style sheets for a word processor would be. Using communication software is not, writing a script for the communication software is. Using someone else's spreadsheet is not, building your own spreadsheet is. Using someone else's HyperCard stack is not, building your own is. Running someone else's cognitive model is not, building a cognitive model that fits your theory is. This definition includes both specialized software for experts (for example, Edmonds, O'Brien,&Bayley, 1993), semi-domain specialized software such as spreadsheets, as well as intendedly general purpose (but specialized anyway) software such as HyperCard. The two defining characteristics are: building software tools (what the end-user programming language, EPL, is used for) and characteristics of the user (whose main interest is in building a tool for which they, among possible others, will be a user). Hence, LISP could be considered an EPL for C programmers who use EMACS.”
© All rights reserved Gray et al. and/or Ablex Publishing
Gray, Wayne D., John, Bonnie E. and Atwood, Michael E. (1993): Project Ernestine: Validating a GOMS Analysis for Predicting and Explaining Real-World Task Performance. In Human-Computer Interaction, 8 (3) pp. 237-309.
“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.”
© All rights reserved Gray et al. and/or Taylor and Francis
Gray, Wayne D., Sabnani, Haresh and Kirschenbaum, Susan S. (1993): "Human Error," by James Reason. In International Journal of Man-Machine Studies, 39 (6) pp. 1051-1057.
Gray, Wayne D., Hefley, William and Murray, Dianne (eds.) International Workshop on Intelligent User Interfaces 1993 January 4-7, 1993, Orlando, Florida, USA.
Gray, Wayne D., Spohrer, James C. and Green, T. R. G. (1993): End-User Programming Language: The CHI'92 Workshop Report. In ACM SIGCHI Bulletin, 25 (2) pp. 46-50.
“The call for participation for the Workshop on End User Programming began with the following statement: "In the beginning, every user was a programmer. While that appeared to change forever in the 80's, the 90's are shaping up as the decade of macro-languages, scripting languages, authoring languages, dbase query languages, inter-application communication languages, and event languages. Programming in some form or another will become inescapable and again, every user will be a programmer. The 90's will be the decade of end-user programming." While many of our colleagues are working hard to build systems which automatically and intelligently adapt themselves to the needs of the user or which "program by example", a growing group of researchers and developers have become convinced that a large part of the 90's will be spent on a very different vision of computing. This is not to imply that we view these other efforts as either competitive or futile, on the contrary, we see them as trying to solve different problems and, sometimes, as complementary solutions to the same problem (see Kuhme, 1993 for an interesting proposal for a user-programmable adaptive interface).”
© All rights reserved Gray et al. and/or ACM Press
Gray, Wayne D., John, Bonnie E. and Atwood, Michael E. (1992): The Precis of Project Ernestine, or, An Overview of a Validation of GOMS. In: Bauersfeld, Penny, Bennett, John and Lynch, Gene (eds.) Proceedings of the ACM CHI 92 Human Factors in Computing Systems Conference June 3-7, 1992, Monterey, California. pp. 307-312.
Gray, Wayne D., Anderson, John R., Reiser, Brian J., Soloway, Elliot and Spohrer, James C. (1991): Tutors and Environments for Novice Programmers. In: Koenemann-Belliveau, Jurgen, Moher, Thomas G. and Robertson, Scott P. (eds.) Proceedings of the Fourth Annual Workshop on Empirical Studies of Programmers 1991, Norwood, New Jersey, USA. pp. 3-4.
Gray, Wayne D., John, Bonnie E., Stuart, Rory, Lawrence, Deborah and Atwood, Michael E. (1990): GOMS Meets the Phone Company: Analytic Modeling Applied to Real-World Problems. In: Diaper, Dan, Gilmore, David J., Cockton, Gilbert and Shackel, Brian (eds.) INTERACT 90 - 3rd IFIP International Conference on Human-Computer Interaction August 27-31, 1990, Cambridge, UK. pp. 29-34.
“GOMS analyses were used to interpret some perplexing data from a field evaluation of two telephone operator workstations. The new workstation is ergonomically superior to the old and is preferred by all who have used it. Despite these advantages telephone operators who use the new workstation are not faster than those who use the old but are, in fact, significantly slower. This bewildering result makes sense when seen with the aid of GOMS. With GOMS we can see that very few of the eliminated key-strokes or ergonomic advantages affect tasks that determine the operator's work time. Indeed, GOMS shows that some presumed procedural improvements have the contrary effect of increasing the time an operator spends handling a phone call. We concluded that if GOMS had been done early on, then the task, not the workstation, would have been redesigned.”
© All rights reserved Gray et al. and/or North-Holland
Gray, Wayne D., Atwood, Michael E., Olson, Judith S., John, Bonnie E. and Elkerton, Jay (1990): Real-Time GOMS: Comparative Modeling of a User-Nintendo Interaction. In: D., Woods, and E., Roth, (eds.) Proceedings of the Human Factors Society 34th Annual Meeting 1990, Santa Monica, USA. pp. 385-386.
Atwood, Michael E., Brooks, Ruven, Gray, Wayne D., Guindon, Raymonde and Mastaglio, Thomas W. (1989): Current Research in the Psychology of Programming. In: Proceedings of the Human Factors Society 33rd Annual Meeting 1989. pp. 242-244.
“Computer programming is one of the earliest topics addressed by studies of the human factors of computer systems and studies of how software systems are developed remain one of the most difficult areas of investigation. Early work in the psychology of programming focused on comparisons of time-sharing and batch modes, studies of programming team organization, studies of debugging, and investigations of the differences between novice and expert programmers. As new theories and experimental methodologies were developed, further areas were researched. This panel looks at current research in the psychology of computer programming. Topics include studies of programmer behavior, studies of software design, tools for programmers, and experimental methods. Audience members will have an opportunity to describe other areas of study.”
© All rights reserved Atwood et al. and/or Human Factors Society
Atwood, Michael E., Fischer, Gerhard, Gray, Wayne D. and Polson, Peter G. (1989): Theoretical Models for System Design. In: Proceedings of the Human Factors Society 33rd Annual Meeting 1989. pp. 278-280.
“In the history of human factors in computer systems, one of the most significant events of the past decade was the work on GOMS and keystroke models (cf. Card, Moran, and Newell, 1983). While a clear success in causing software developers to focus on the importance of interface design and attracting researchers to this areas, GOMS approaches have not significantly improved the quality of the systems that are developed. Why has this work, that has a great theoretical impact, had so little practical impact on existing systems? Is it that the GOMS formalism is not valid outside of laboratory contexts? Is it that it misses important aspects of behavior such as how people learn to use systems? Is it that GOMS was developed in the context of computer systems that are less powerful and interactive than we have today? Or, are there other reasons? In this panel, we argue that additional cognitive science approaches are needed to improve the quality of developed system. Dr. Gray extends this approach by reporting the first "real world": test of the GOMS-style of system modeling. Dr. Polson extends these models to how people learn to use systems. Dr. Fischer extends this style of research by focusing on cooperative, rather than passive computer systems. Audience members will have an opportunity to describe other approaches to developing theoretical models of system design.”
© All rights reserved Atwood et al. and/or Human Factors Society
Gray, Wayne D., Burns, Bart and Schooler, Lael (1989): The Usability of Intelligent Tutoring Systems. In: Proceedings of the Human Factors Society 33rd Annual Meeting 1989. pp. 1343-1347.
“Grace, the NYNEX COBOL tutor, is being built in a corporate environment following the philosophy of iterative design and test. Grace and the student interact in a mixed-initiative dialogue. Grace's side of the dialogue is controlled by a simulation based upon the ACT* theory of cognitive skill acquisition (Anderson, 1983, 1987b). This simulation is theory-driven and largely, but not completely, embodied in a production system architecture. The student-tutor dialogue is mediated by an interface whose design is empirically driven and embodied in a multi-media system of windows, text, hypertext, mouse gestures, menus, node selections, typing-in, and so. Construction of the simulation and the tutor interface are being tested and revised through a series of user trials. The trials are conducted at one of the sites at which the tutor will be used. Students participating in the trial are from the same population as our target audience.”
© All rights reserved Gray et al. and/or Human Factors Society
Gray, Wayne D. and Anderson, John R. (1987): Change-Episodes in Coding: When and How Do Programmers Change Their Code?. In: Olson, Gary M., Sheppard, Sylvia B. and Soloway, Elliot (eds.) Empirical Studies of Programmers - Second Workshop December 7-8 1987, 1987, Washington, DC. pp. 185-197.
“Any change in a programmer's code or intentions while coding constitutes a change-episode. Change-episodes include error detection and correction (including false positives) as well as stylistic, and tactical changes. In this study we examine change-episodes to determine what they can add to the study of the cognition of programming. We argue that change-episodes occur most often for constructs that allow the most variability (with variability defined by the language, the task, and the programmer's history). We predict and find that those constructs that are involved in the most change-episodes are those for which much planning is needed during coding. Similarly, we discuss two ways in which a goal can be changed in a change-episode. One involves relatively minor editing of a goal's subgoals, suggesting that much planning is local to the current goal. The other entails major transformations in the goal's structure. Finally, we find that change-episodes are initiated in one of three very distinct circumstances: as an interrupt to coding, a tag-along to another change-episode, or a byproduct of symbolic execution. Our findings support the distinction between inherent and planning subgoals (2,3) and the distinction between progressive and evaluative problem-solving activities (6).”
© All rights reserved Gray and Anderson and/or Ablex Publishing
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