Predicting postcompletion errors using eye movements

Ratwani, Raj M.; McCurry, J. Malcolm; Trafton, J. Gregory

doi:10.1145/1357054.1357141

Cited by 25 publications

(36 citation statements)

References 9 publications

(14 reference statements)

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“…Real-time feedback systems based on various online measures of cognitive process have been used in several domains [26,27,34,35].…”

Section: Improving Operator Situation Awarenessmentioning

confidence: 99%

Single operator, multiple robots: An eye movement based theoretic model of operator situation awareness

Ratwani¹,

McCurry²,

Trafton³

2010

2010 5th ACM/IEEE International Conference on Human-Robot Interaction (HRI)

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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.

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“…Real-time feedback systems based on various online measures of cognitive process have been used in several domains [26,27,34,35].…”

Section: Improving Operator Situation Awarenessmentioning

confidence: 99%

Single operator, multiple robots: An eye movement based theoretic model of operator situation awareness

Ratwani¹,

McCurry²,

Trafton³

2010

2010 5th ACM/IEEE International Conference on Human-Robot Interaction (HRI)

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“…DFA is a linear technique that will provide an indicator of the importance of each predictor. DFA was used on the dataset from Ratwani et al. (2008) and on the data from this experiment to compare the relative importance of each the predictors across tasks.…”

Section: Methodsmentioning

confidence: 99%

“…We sought to address these issues in two ways. To determine the robustness of the logistic regression model and the set of predictors, the logistic regression model from Ratwani et al. (2008) was applied to a new task to see how well the model could account for postcompletion errors on that task.…”

Section: Introductionmentioning

confidence: 99%

A Generalized Model for Predicting Postcompletion Errors

Ratwani¹,

Trafton²

2010

Topics in Cognitive Science

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A postcompletion error is a type of procedural error that occurs after the main goal of a task has been accomplished. There is a strong theoretical foundation accounting for postcompletion errors (Altmann & Trafton, 2002;Byrne & Bovair, 1997). This theoretical foundation has been leveraged to develop a logistic regression model of postcompletion errors based on reaction time and eye movement measures (Ratwani, McCurry, & Trafton, 2008). This study further develops and extends this predictive model by (a) validating the model and the general set of predictors on a new task to test the robustness of the model, and (b) determining which specific theoretical components are most important to postcompletion error prediction.

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“…For example, previous research has shown that an individual's mental effort correlates with pupil size [48,49] and heart rate variability [50]. Furthermore, eye gaze analysis can be used to assess where an individual is allocating attention (or failing to attend to), and therefore be employed to provide alerts and prevent errors in real time [51,52]. Lastly, key-logging can be used as a secondary measure of workload and means of measuring operator "percent busy time," when the operator is actively engaged in a task, which impacts user performance on a task (i.e., when utilization exceeds 70 %, operator performance decreases) [53].…”

Section: A-tasc Predictive Modelmentioning

confidence: 99%

Modeling User Behaviors to Enable Context-Aware Proactive Decision Support

Newsom

Mittu

Livingston

et al. 2016

Advances in Computer Vision and Pattern Recognition

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The problem of automatically recognizing a user's operational context, the implications of its shifting properties, and reacting in a dynamic manner are at the core of mission intelligence and decision making. Environments such as the OZONE Widget Framework (http://www.owfgoss.org) (OWF) provide the foundation for capturing the objectives, actions, and activities of both the mission analyst and the decision maker. By utilizing a "context container" that envelops an OZONE Application, we hypothesize that both user action and intent can be used to characterize user context with respect to operational modality (strategic, tactical, opportunistic, or random). As the analyst moves from one operational modality to another, we propose that information visualization techniques should adapt and present data and analysis pertinent to the new modality and to the trend of the shift. As a system captures the analyst's actions and decisions in response to the new visualizations, the context container has the opportunity to assess the analyst's perception of the information value, risk, uncertainty, prioritization, projection, and insight with respect to the current context stage. This paper will describe a conceptual architecture for an adaptive work environment for inferring user behavior and interaction within the OZONE framework, in order to provide the decision B. Newsom

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Predicting postcompletion errors using eye movements

Cited by 25 publications

References 9 publications

Single operator, multiple robots: An eye movement based theoretic model of operator situation awareness

Single operator, multiple robots: An eye movement based theoretic model of operator situation awareness

A Generalized Model for Predicting Postcompletion Errors

Modeling User Behaviors to Enable Context-Aware Proactive Decision Support

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