Publication statistics
Pub. period:1995-2012
Pub. count:22
Number of co-authors:37
Co-authors
Number of publications with 3 favourite co-authors:
Raj M. Ratwani:5J. Malcolm McCurry:4Erik M. Altmann:3 Productive colleagues
J. Gregory Trafton's 3 most productive colleagues in number of publications:
Deborah Hix:46Dario D. Salvucci:23Erik M. Altmann:7
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J. Gregory Trafton
Publications by J. Gregory Trafton (bibliography)
Gartenberg, Daniel, Breslow, Leonard A., McCurry, J. Malcolm and Trafton, J. Gregory (2012): Time Pressure, Memory, and Task Knowledge Facilitate the Opportunism Heuristic in Dynamic Tasks. In: Proceedings of the Human Factors and Ergonomics Society 2012 Annual Meeting 2012. pp. 1025-1029.
“There are a variety of strategies that operators can utilize when performing a dynamic task, yet operator strategies are typically studied in a well-controlled environment that prevents the possibility of these strategies from interacting or competing with one another. In this study we investigated operator strategy use in a dynamic supervisory control task. We identified four possible strategies that the operator may use: scanning, opportunism, task knowledge, and memory. In order to determine the impact of time pressure on strategy use, we manipulated the speed of the vehicles. We found that as time pressure increased, operators shifted from a scanning strategy to a heuristic opportunistic strategy. We also found that when operators used task knowledge and memory they were more likely to be opportunistic.”
© All rights reserved Gartenberg et al. and/or Human Factors and Ergonomics Society
Ratwani, Raj M. and Trafton, J. Gregory (2011): A Real-Time Eye Tracking System for Predicting and Preventing Postcompletion Errors. In Human Computer Interaction, 26 (3) pp. 205-245.
“Procedural errors occur despite the user having the correct knowledge of how to perform a particular task. Previous research has mostly focused on preventing these errors by redesigning tasks to eliminate error prone steps. A different method of preventing errors, specifically postcompletion errors (e.g., forgetting to retrieve the original document from a photocopier), has been proposed by Ratwani, McCurry, and Trafton (2008), which uses theoretically motivated eye movement measures to predict when a user will make an error. The predictive value of the eye-movement-based model was examined and validated on two different tasks using a receiver-operating characteristic analysis. A real-time eye-tracking postcompletion error prediction system was then developed and tested; results demonstrate that the real-time system successfully predicts and prevents postcompletion errors before a user commits the error.”
© All rights reserved Ratwani and Trafton and/or Lawrence Erlbaum
Ratwani, Raj M., McCurry, J. Malcolm and Trafton, J. Gregory (2010): Single operator, multiple robots: an eye movement based theoretic model of operator situation awareness. In: Proceedings of the 5th ACM/IEEE International Conference on Human Robot Interaction 2010. pp. 235-242.
“For a single operator to effectively control multiple robots, operator situation awareness is a critical component of the human-robot system. There are three levels of situation awareness: perception, comprehension, and projection into the future [1]. We focus on the perception level to develop a theoretic model of the perceptual-cognitive processes underlying situation awareness. Eye movement measures were developed as indicators of cognitive processing and these measures were used to account for operator situation awareness on a supervisory control task. The eye movement based model emphasizes the importance of visual scanning and attention allocation as the cognitive processes that lead to operator situation awareness and the model lays the groundwork for real-time prediction of operator situation awareness.”
© All rights reserved Ratwani et al. and/or their publisher
Kriz, Sarah, Anderson, Gregory and Trafton, J. Gregory (2010): Robot-directed speech: using language to assess first-time users' conceptualizations of a robot. In: Proceedings of the 5th ACM/IEEE International Conference on Human Robot Interaction 2010. pp. 267-274.
“It is expected that in the near-future people will have daily natural language interactions with robots. However, we know very little about how users feel they should talk to robots, especially users who have never before interacted with a robot. The present study evaluated first-time users' expectations about a robot's cognitive and communicative capabilities by comparing robot-directed speech to the way in which participants talked to a human partner. The results indicate that participants spoke more loudly, raised their pitch, and hyperarticulated their messages when they spoke to the robot, suggesting that they viewed the robot as having low linguistic competence. However, utterances show that speakers often assumed that the robot had humanlike cognitive capabilities. The results suggest that while first-time users were concerned with the fragility of the robot's speech recognition system, they believed that the robot had extremely strong information processing capabilities.”
© All rights reserved Kriz et al. and/or their publisher
Chen, Jennifer M., Ratwani, Raj M. and Trafton, J. Gregory (2010): The Effect of Interruptions and Global Placekeeping on Postcompletion Error Rates. In: Proceedings of the Human Factors and Ergonomics Society 54th Annual Meeting 2010. pp. 463-467.
“A postcompletion error occurs when the final step of a task is omitted because the main goal of the task is thought to be completed (Byrne&Bovair, 1997). Postcompletion errors are more likely to occur after interruptions (Ratwani, McCurry&Trafton, 2008). Global placekeeping cues (Gray, 2000) allow a user to track their progress in a task and may be a method for reducing the rate of postcompletion errors. A computer-based procedural task with a postcompletion step was used in this experiment to determine how the interaction of global placekeeping cues with interruptions would affect postcompletion errors. These results suggest that global placekeeping cues reduce the postcompletion error rate after interruptions, but that global placekeeping does not completely eliminate postcompletion errors.”
© All rights reserved Chen et al. and/or HFES
Kriz, Sarah, Anderson, Gregory, Bugajska, Magdalena and Trafton, J. Gregory (2009): Robot-directed speech as a means of exploring conceptualizations of robots. In: Proceedings of the 4th ACM/IEEE International Conference on Human Robot Interaction 2009. pp. 271-272.
“Decades of research have shown that speakers adapt the way in which they speak to meet the needs of listeners, and that speech modifications can illuminate speakers' conceptualizations of their listeners' cognitive and communicative abilities. The present study extends this line of research into human-robot communication by analyzing the linguistic features of commands given to a robotic dog. The results indicate that males and females differed in the way in which they spoke to the robot, suggesting that there was not a uniform expectation of the robot's communicative capacities.”
© All rights reserved Kriz et al. and/or ACM Press
Jacobs, Allison M., Fransen, Benjamin, McCurry, J. Malcolm, Heckel, Frederick W. P., Wagner, Alan R. and Trafton, J. Gregory (2009): A preliminary system for recognizing boredom. In: Proceedings of the 4th ACM/IEEE International Conference on Human Robot Interaction 2009. pp. 299-300.
“A 3D optical flow tracking system was used to track participants as they watched a series of boring videos. The video stream of the participants was rated for boredom events. Ratings and head position data were combined to predict boredom events.”
© All rights reserved Jacobs et al. and/or ACM Press
Salvucci, Dario D., Monk, Christopher A. and Trafton, J. Gregory (2009): A Process-Model Account of Task Interruption and Resumption: When Does Encoding of the Problem State Occur?. In: Proceedings of the Human Factors and Ergonomics Society 53rd Annual Meeting 2009. pp. 799-803.
“Memory for goals theory (Altmann&Trafton, 2002) describes how people suspend and resume an interrupted task by encoding, or rehearsing, the current problem state at the point of interruption and recalling this state after the interruption. In this work we investigated the timing of the encoding process, attempting to determine the most likely strategies for when to perform encoding of interrupted problem state. We examined several candidate encoding strategies and developed computational cognitive models to represent each strategy, embedding the models into a larger model of behavior in a interruption-tracking task. Comparison of the model simulations with recent empirical data suggests that encoding of problem state occurs for a short time at the start of the interruption period and is performed concurrently with the interrupting task.”
© All rights reserved Salvucci et al. and/or their publisher
Ratwani, Raj M., McCurry, J. Malcolm and Trafton, J. Gregory (2008): Predicting postcompletion errors using eye movements. In: Proceedings of ACM CHI 2008 Conference on Human Factors in Computing Systems April 5-10, 2008. pp. 539-542.
“A postcompletion error is a distinct type of procedural error where one fails to complete the final step of a task. While redesigning interfaces and providing explicit cues have been shown to be effective in reducing the postcompletion error rate, these methods are not always feasible or well liked. This paper demonstrates how specific eye movement measures can be used to predict when a user will make a postcompletion error. We describe a real-time eye gaze system that provides cues to the user if and only if there is a high probability of the user making a postcompletion error.”
© All rights reserved Ratwani et al. and/or ACM Press
Trafton, J. Gregory, Bugajska, Magda D., Fransen, Benjamin R. and Ratwani, Raj M. (2008): Integrating vision and audition within a cognitive architecture to track conversations. In: Proceedings of the 3rd ACM/IEEE International Conference on Human Robot Interaction 2008. pp. 201-208.
“We describe a computational cognitive architecture for robots which we call ACT-R/E (ACT-R/Embodied). ACT-R/E is based on ACT-R [1, 2] but uses different visual, auditory, and movement modules. We describe a model that uses ACT-R/E to integrate visual and auditory information to perform conversation tracking in a dynamic environment. We also performed an empirical evaluation study which shows that people see our conversational tracking system as extremely natural.”
© All rights reserved Trafton et al. and/or ACM Press
Trickett, Susan Bell and Trafton, J. Gregory (2006): Toward a Comprehensive Model of Graph Comprehension: Making the Case for Spatial Cognition. In: Barker-Plummer, Dave, Cox, Richard and Swoboda, Nik (eds.) Diagrams 2006 - Diagrammatic Representation and Inference - 4th International Conference June 28-30, 2006, Stanford, CA, USA. pp. 286-300.
Trafton, J. Gregory, Schultz, Alan C., Perznowski, Dennis, Bugajska, Magdalena D., Adams, William, Cassimatis, Nicholas L. and Brock, Derek P. (2006): Children and robots learning to play hide and seek. In: Proceedings of the 1st ACM SIGCHI/SIGART Conference on Human-Robot Interaction 2006. pp. 242-249.
“How do children learn how to play hide and seek? At age 3-4, children do not typically have perspective taking ability, so their hiding ability should be extremely limited. We show through a case study that a 3 1/2 year old child can, in fact, play a credible game of hide and seek, even though she does not seem to have perspective taking ability. We propose that children are able to learn how to play hide and seek by learning the features and relations of objects (e.g., containment, under) and use that information to play a credible game of hide and seek. We model this hypothesis within the ACT-R cognitive architecture and put the model on a robot, which is able to mimic the child's hiding behavior. We also take the "hiding" model and use it as the basis for a "seeking" model. We suggest that using the same representations and procedures that a person uses allows better interaction between the human and robotic system.”
© All rights reserved Trafton et al. and/or ACM Press
Schultz, Alan C. and Trafton, J. Gregory (2005): Towards collaboration with robots in shared space: spatial perspective and frames of reference. In Interactions, 12 (2) pp. 22-24.
Trickett, Susan Bell and Trafton, J. Gregory (2004): Spatial Transformations in Graph Comprehension. In: Blackwell, Alan, Marriott, Kim and Shimojima, Atsushi (eds.) Diagrams 2004 - Diagrammatic Representation and Inference - Third International Conference March 22-24, 2004, Cambridge, UK. pp. 372-375.
Trafton, J. Gregory, Altmann, Erik M., Brock, Derek P. and Mintz, Farilee E. (2003): Preparing to resume an interrupted task: effects of prospective goal encoding and retrospective rehearsal. In International Journal of Human-Computer Studies, 58 (5) pp. 583-603.
“We examine people's strategic cognitive responses to being interrupted while
performing a task. Based on memory theory, we propose that resumption of a task
after interruption is facilitated by preparation during the interruption lag,
or the interval between an alert to a pending interruption (e.g. the phone
ringing) and the interruption proper (the ensuing conversation). To test this
proposal, we conducted an experiment in which participants in a Warning
condition received an 8-s interruption lag, and participants in an Immediate
condition received no interruption lag. Participants in the Warning condition
prepared more than participants in the Immediate condition, as measured by
verbal reports, and resumed the interrupted task more quickly. However,
Immediate participants resumed faster with practice, suggesting that people
adapt to particularly disruptive forms of interruption. The results support our
task analysis of interruption and our model of memory for goals, and suggest
further means for studying operator performance in dynamic task environments.”
© All rights reserved Trafton et al. and/or Academic Press
Altmann, Erik M. and Trafton, J. Gregory (2002): Memory for goals: an activation-based model. In Cognitive Science, 26 (1) pp. 39-83.
Altmann, Erik M. and Trafton, J. Gregory (2002): Erratum to "Memories for goals: An activation-based model"[Cognitive Science 26 (2002) 39-83]. In Cognitive Science, 26 (2) p. 233.
Bogacz, Sally and Trafton, J. Gregory (2002): Understanding Static and Dynamic Visualizations. In: Hegarty, Mary, Meyer, Bernd and Narayanan, N. Hari (eds.) Diagrams 2002 - Diagrammatic Representation and Inference - Second International Conference April 18-20, 2002, Callaway Gardens, GA, USA. pp. 347-349.
Trafton, J. Gregory, Marshall, Sandra P., Mintz, Farilee and Trickett, Susan Bell (2002): Extracting Explicit and Implict Information from Complex Visualizations. In: Hegarty, Mary, Meyer, Bernd and Narayanan, N. Hari (eds.) Diagrams 2002 - Diagrammatic Representation and Inference - Second International Conference April 18-20, 2002, Callaway Gardens, GA, USA. pp. 206-220.
Trafton, J. Gregory and Trickett, Susan B. (2001): Note-Taking as a Strategy for Self-Explanation and Problem Solving. In Human-Computer Interaction, 16 (1) pp. 1-38.
“We explore the effects of interfaces to take notes on problem solving and learning in a scientific discovery domain. In 2 experiments (1 correlational, 1 experimental), participants solved a series of 5 scientific reasoning problems in a computer environment. We provided some participants with access to an online notepad and found 3 main results: (a) Using the notepad helped participants solve the problems more accurately; (b) the benefits of using the notepad persisted after participants had stopped using it; and (c) participants who used the notepad for problem solving and self-explanation learned more, regardless of the type of notepad interface that was provided. Implications for learning systems with online notepads are discussed.”
© All rights reserved Trafton and Trickett and/or Taylor and Francis
Trafton, J. Gregory, Kirschenbaum, Susan S., Tsui, Ted L., Miyamoto, Robert T., Ballas, James and Raymond, Paula D. (2000): Turning Pictures Into Numbers: Extracting and Generating Information from Complex Visualizations. In International Journal of Human-Computer Studies, 53 (5) pp. 827-850.
“We present a study of complex visualization usage by expert meteorological forecasters. We performed a protocol analysis and examined the types of visualizations they examined. We present evidence for how experts are able to make use of complex visualizations. Our findings suggest that users of complex visualizations create qualitative mental models from which they can then generate quantitative information. In order to build their qualitative mental models, forecasters integrated information across multiple visualizations and extracted primarily qualitative information from visualizations in a goal-directed manner. We discuss both theoretical and practical implications of this study.”
© All rights reserved Trafton et al. and/or Academic Press
Brock, Derek, Hix, Deborah, Dievendorf, Lynn and Trafton, J. Gregory (1995): Extending the User Action Notation for Research in Individual Differences. In: Proceedings of the Human Factors and Ergonomics Society 39th Annual Meeting 1995. pp. 253-257.
“Software user interfaces that provide users with more than one device, such as a mouse and keyboard, for interactively performing tasks, are now commonplace. Concerns about how to represent individual differences in patterns of use and acquisition of skill in such interfaces led the authors to develop modifications to the standard format of the User Action Notation (UAN) that substantially augment the notation's expressive power. These extensions allow the reader of an interface specification to make meaningful comparisons between functionally equivalent interaction techniques and task performance strategies in interfaces supporting multiple input devices. Furthermore, they offer researchers a new methodology for analyzing the behavioral aspects of user interfaces. These modifications are documented and their benefits discussed.”
© All rights reserved Brock et al. and/or Human Factors Society
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