Pub Date : 2020-06-01DOI: 10.1177/1555343419881563
A. R. Panganiban, G. Matthews, Michael D. Long
Human–Machine teaming is a very near term standard for many occupational settings and still requires considerations for the design of autonomous teammates (ATs). Transparency of system processes is important for human–machine interaction and reliance but standards for its implementation are still being explored. Embedding social cues is a potential design approach, which may capture the social benefits of a team environment, yet vary with task setting. The current study examined the manipulation of transparency of benevolent intent from an AT within a piloting task requiring suppression of enemy defenses. Specifically, the benevolent AT maintained task communication as in a neutral condition, but included messages of support and awareness of errors. Benevolent communication reduced reported workload and increased reported team collaboration, indicating that this team intent was beneficial. In addition, trust and acceptance of the AT were rated higher by individuals tasked with depending on the system to protect them from missile threats. The need for information from ATs is beneficial, however may vary depending on team type.
{"title":"Transparency in Autonomous Teammates","authors":"A. R. Panganiban, G. Matthews, Michael D. Long","doi":"10.1177/1555343419881563","DOIUrl":"https://doi.org/10.1177/1555343419881563","url":null,"abstract":"Human–Machine teaming is a very near term standard for many occupational settings and still requires considerations for the design of autonomous teammates (ATs). Transparency of system processes is important for human–machine interaction and reliance but standards for its implementation are still being explored. Embedding social cues is a potential design approach, which may capture the social benefits of a team environment, yet vary with task setting. The current study examined the manipulation of transparency of benevolent intent from an AT within a piloting task requiring suppression of enemy defenses. Specifically, the benevolent AT maintained task communication as in a neutral condition, but included messages of support and awareness of errors. Benevolent communication reduced reported workload and increased reported team collaboration, indicating that this team intent was beneficial. In addition, trust and acceptance of the AT were rated higher by individuals tasked with depending on the system to protect them from missile threats. The need for information from ATs is beneficial, however may vary depending on team type.","PeriodicalId":46342,"journal":{"name":"Journal of Cognitive Engineering and Decision Making","volume":null,"pages":null},"PeriodicalIF":2.0,"publicationDate":"2020-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1177/1555343419881563","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"48740647","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2020-06-01DOI: 10.1177/1555343419882595
Vanessa Cattermole-Terzic, T. Horberry
Effective traffic incident management requires separate responder agencies, with different and sometimes competing priorities and purposes, to come together as a team. Their priorities include optimizing casualty outcomes, minimizing the disruption to the flow of traffic, and maintaining responder team safety. In this study, team Cognitive Work Analysis was used in a desktop exercise setting to analyze a complex traffic incident management exercise. The study investigated decisions made at the scene of an incident to determine system issues and system support solutions. Participants were all senior officers and decision makers in traffic incident management environments. Results indicated that team Cognitive Work Analysis was highly beneficial in determining gaps in team coordination, communication, and structures. Information regarding shared and not shared work elements between agencies highlighted novel coordination and education requirements within and between agencies, such as disparate priorities at the scene creating the risk of interoperability issues. Analyses of operational, coordination, and structural strategies offered new insights into the traffic incident management work domain and recommendations for improvements to the safety and performance of the overall traffic incident management system.
{"title":"Improving Traffic Incident Management Using Team Cognitive Work Analysis","authors":"Vanessa Cattermole-Terzic, T. Horberry","doi":"10.1177/1555343419882595","DOIUrl":"https://doi.org/10.1177/1555343419882595","url":null,"abstract":"Effective traffic incident management requires separate responder agencies, with different and sometimes competing priorities and purposes, to come together as a team. Their priorities include optimizing casualty outcomes, minimizing the disruption to the flow of traffic, and maintaining responder team safety. In this study, team Cognitive Work Analysis was used in a desktop exercise setting to analyze a complex traffic incident management exercise. The study investigated decisions made at the scene of an incident to determine system issues and system support solutions. Participants were all senior officers and decision makers in traffic incident management environments. Results indicated that team Cognitive Work Analysis was highly beneficial in determining gaps in team coordination, communication, and structures. Information regarding shared and not shared work elements between agencies highlighted novel coordination and education requirements within and between agencies, such as disparate priorities at the scene creating the risk of interoperability issues. Analyses of operational, coordination, and structural strategies offered new insights into the traffic incident management work domain and recommendations for improvements to the safety and performance of the overall traffic incident management system.","PeriodicalId":46342,"journal":{"name":"Journal of Cognitive Engineering and Decision Making","volume":null,"pages":null},"PeriodicalIF":2.0,"publicationDate":"2020-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1177/1555343419882595","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"43237378","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2020-05-08DOI: 10.1177/1555343420918084
Ben W. Morrison, David Johnston, M. Naylor, Natalie M. V. Morrison, Daniel R. L. Forrest
Although skilled cue utilization is presumed to result primarily from domain-specific experience, individual differences in learning are theorized to play a significant role. Using a single-group correlational design, this study tested whether individuals’ domain-general associative learning capacity was related to performance in a complex real-world decision task presumed to rely heavily on cues: lie detection. A total of 21 participants completed an associative learning task in the form of a Space Invaders-like game. In the game, those who learn the cues are able to respond faster to the appearance of an enemy ship. Participants were also surveyed on their awareness of cues in the game. This was followed by a lie detection task. It was hypothesized that greater associative learning would be associated with greater awareness of cues in the learning task, and subsequently, superior accuracy in the lie detection task. Participants’ associative learning was correlated with their cue awareness (r pb = .782, p < .001). Further, learning was associated with better performance in the lie detection task (r = .544, p = .011); however, accuracy was found to be unrelated to the types of cues reportedly used during detection. These findings have implications for our understanding of cue acquisition and expertise development.
虽然熟练的线索利用被认为主要来自特定领域的经验，但学习中的个体差异在理论上起着重要作用。使用单组相关设计，本研究测试了个人的领域一般联想学习能力是否与在一个复杂的现实世界决策任务中的表现有关，该任务被认为严重依赖线索:测谎。共有21名参与者以类似太空入侵者的游戏形式完成了一项联想学习任务。在游戏中，那些了解线索的人能够更快地对敌舰的出现做出反应。参与者还被调查了他们对游戏中线索的意识。接下来是测谎任务。据推测，联想学习能力越强，在学习任务中对线索的意识越强，随后在测谎任务中的准确性就越高。被试的联想学习与线索意识相关(r pb = .782, p < .001)。此外，学习与更好的测谎任务表现相关(r = 0.544, p = 0.011);然而，准确性被发现与在检测过程中使用的线索类型无关。这些发现对我们理解线索习得和专业技能发展具有启示意义。
{"title":"“You Can’t Hide Your Lyin’ Eyes”: Investigating the Relationship Between Associative Learning, Cue Awareness, and Decision Performance in Detecting Lies","authors":"Ben W. Morrison, David Johnston, M. Naylor, Natalie M. V. Morrison, Daniel R. L. Forrest","doi":"10.1177/1555343420918084","DOIUrl":"https://doi.org/10.1177/1555343420918084","url":null,"abstract":"Although skilled cue utilization is presumed to result primarily from domain-specific experience, individual differences in learning are theorized to play a significant role. Using a single-group correlational design, this study tested whether individuals’ domain-general associative learning capacity was related to performance in a complex real-world decision task presumed to rely heavily on cues: lie detection. A total of 21 participants completed an associative learning task in the form of a Space Invaders-like game. In the game, those who learn the cues are able to respond faster to the appearance of an enemy ship. Participants were also surveyed on their awareness of cues in the game. This was followed by a lie detection task. It was hypothesized that greater associative learning would be associated with greater awareness of cues in the learning task, and subsequently, superior accuracy in the lie detection task. Participants’ associative learning was correlated with their cue awareness (r pb = .782, p < .001). Further, learning was associated with better performance in the lie detection task (r = .544, p = .011); however, accuracy was found to be unrelated to the types of cues reportedly used during detection. These findings have implications for our understanding of cue acquisition and expertise development.","PeriodicalId":46342,"journal":{"name":"Journal of Cognitive Engineering and Decision Making","volume":null,"pages":null},"PeriodicalIF":2.0,"publicationDate":"2020-05-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1177/1555343420918084","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"44592724","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2020-03-01DOI: 10.1177/1555343419872050
A. Jaunzemis, K. Feigh, M. Holzinger, D. Minotra, Moses W. Chan
Existing approaches for sensor network tasking in space situational awareness (SSA) rely on techniques from the 1950s and limited application areas while also requiring significant human-in-the-loop involvement. Increasing numbers of space objects, sensors, and decision-making needs create a demand for improved methods of gathering and fusing disparate information to resolve hypotheses about the space object environment. This work focuses on the cognitive work in SSA sensor tasking approaches. The application of a cognitive work analysis for the SSA domain highlights capabilities and constraints inherent to the domain that can drive SSA operations toward decision-maker goals. A control task analysis is also conducted to derive requirements for cognitive work and information relationships that support the information fusion and sensor allocation tasks of SSA. A prototype decision-support system is developed using a subset of the derived requirements. This prototype is evaluated in a human-in-the-loop experiment using both a hypothesis-based and covariance-based scheduling approaches. Results from this preliminary evaluation show operator ability to address SSA decision-maker hypotheses using the prototype decision-support system (DSS) using both scheduling approaches.
{"title":"Cognitive Systems Engineering Applied to Decision Support in Space Situational Awareness","authors":"A. Jaunzemis, K. Feigh, M. Holzinger, D. Minotra, Moses W. Chan","doi":"10.1177/1555343419872050","DOIUrl":"https://doi.org/10.1177/1555343419872050","url":null,"abstract":"Existing approaches for sensor network tasking in space situational awareness (SSA) rely on techniques from the 1950s and limited application areas while also requiring significant human-in-the-loop involvement. Increasing numbers of space objects, sensors, and decision-making needs create a demand for improved methods of gathering and fusing disparate information to resolve hypotheses about the space object environment. This work focuses on the cognitive work in SSA sensor tasking approaches. The application of a cognitive work analysis for the SSA domain highlights capabilities and constraints inherent to the domain that can drive SSA operations toward decision-maker goals. A control task analysis is also conducted to derive requirements for cognitive work and information relationships that support the information fusion and sensor allocation tasks of SSA. A prototype decision-support system is developed using a subset of the derived requirements. This prototype is evaluated in a human-in-the-loop experiment using both a hypothesis-based and covariance-based scheduling approaches. Results from this preliminary evaluation show operator ability to address SSA decision-maker hypotheses using the prototype decision-support system (DSS) using both scheduling approaches.","PeriodicalId":46342,"journal":{"name":"Journal of Cognitive Engineering and Decision Making","volume":null,"pages":null},"PeriodicalIF":2.0,"publicationDate":"2020-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1177/1555343419872050","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"44493101","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2020-03-01DOI: 10.1177/1555343419874248
M. Endsley
A review of 37 studies that included both objective and subjective measures of situation awareness (SA) was conducted. Objective and subjective measures of SA were found to diverge across a wide range of measurement techniques. Reasons for these differences include a lack of meta-awareness about one’s own SA, poor SA/confidence calibration, and confounds with workload among some measures. A model that shows how objective and subjective SA combine to affect performance is presented.
{"title":"The Divergence of Objective and Subjective Situation Awareness: A Meta-Analysis","authors":"M. Endsley","doi":"10.1177/1555343419874248","DOIUrl":"https://doi.org/10.1177/1555343419874248","url":null,"abstract":"A review of 37 studies that included both objective and subjective measures of situation awareness (SA) was conducted. Objective and subjective measures of SA were found to diverge across a wide range of measurement techniques. Reasons for these differences include a lack of meta-awareness about one’s own SA, poor SA/confidence calibration, and confounds with workload among some measures. A model that shows how objective and subjective SA combine to affect performance is presented.","PeriodicalId":46342,"journal":{"name":"Journal of Cognitive Engineering and Decision Making","volume":null,"pages":null},"PeriodicalIF":2.0,"publicationDate":"2020-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1177/1555343419874248","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"44910815","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2020-03-01DOI: 10.1177/1555343419871825
Matthew J. Miller, K. Feigh
This work presents the results of a laboratory-based study of prototype decision support systems (DSS) for envisioned human extravehicular activity (EVA). A central feature of this work is demonstrating the explicit linkages between DSS design requirements derived from work domain demands with the validation and verification process to examine the utility of specific DSS design solutions. Two DSS prototypes were developed—Baseline and Advanced—that addressed the same set of requirements derived through a cognitive systems engineering (CSE) definition process. The Baseline design was constructed as a minimum derivation from present-day technological standards while the Advanced design incorporated novel software solutions that currently do not exist in the EVA work domain. A representative future domain of human EVA operations was constructed and utilized to evaluate the DSS designs. Both DSS prototype designs were verified to satisfy their design requirements. Furthermore, each design was validated in favor of the Advanced DSS, which outperformed the Baseless DSS in nearly all measures of performance. This work illustrates how the same set of requirements can be satisfied in multiple ways to realize effective DSS solutions.
{"title":"Assessment of Decision Support Systems for Envisioned Human Extravehicular Activity Operations: From Requirements to Validation and Verification","authors":"Matthew J. Miller, K. Feigh","doi":"10.1177/1555343419871825","DOIUrl":"https://doi.org/10.1177/1555343419871825","url":null,"abstract":"This work presents the results of a laboratory-based study of prototype decision support systems (DSS) for envisioned human extravehicular activity (EVA). A central feature of this work is demonstrating the explicit linkages between DSS design requirements derived from work domain demands with the validation and verification process to examine the utility of specific DSS design solutions. Two DSS prototypes were developed—Baseline and Advanced—that addressed the same set of requirements derived through a cognitive systems engineering (CSE) definition process. The Baseline design was constructed as a minimum derivation from present-day technological standards while the Advanced design incorporated novel software solutions that currently do not exist in the EVA work domain. A representative future domain of human EVA operations was constructed and utilized to evaluate the DSS designs. Both DSS prototype designs were verified to satisfy their design requirements. Furthermore, each design was validated in favor of the Advanced DSS, which outperformed the Baseless DSS in nearly all measures of performance. This work illustrates how the same set of requirements can be satisfied in multiple ways to realize effective DSS solutions.","PeriodicalId":46342,"journal":{"name":"Journal of Cognitive Engineering and Decision Making","volume":null,"pages":null},"PeriodicalIF":2.0,"publicationDate":"2020-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1177/1555343419871825","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"65549144","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2020-03-01DOI: 10.1177/1555343419877719
Sudeep Hegde, A. Hettinger, R. Fairbanks, J. Wreathall, Seth Krevat, A. Bisantz
Resilience engineering (RE) has ushered new approaches to learning about work in complex sociotechnical systems. In terms of improving safety, RE marks a shift from the traditional approach of retrospectively investigating adverse events, toward learning proactively about patterns in everyday work, including how things go well. This study applied the RE framework to the health care domain, by developing and implementing a new knowledge-elicitation protocol to learn about how frontline care providers achieve safe and effective patient care in their everyday work. Eighteen participants, including physicians, nurses, residents, and clinical leaders from a range of specialties, were interviewed using the new protocol. Qualitative analysis of the data revealed multiple themes and patterns which underlie resilient functioning of individuals, teams, and the organization as a whole. Further, a Resilience Mapping Framework (RMF) was developed based on major thematic categories to systematically represent and map various resilient capabilities—monitoring, anticipating, responding, and learning—across different levels of system scale, from the individual to the organizational. This study demonstrates new methods to identify and represent resilience not just during salient and critical “events,” but across the continuum of situations, from the everyday “normal” functioning to the critical.
{"title":"Knowledge Elicitation to Understand Resilience: A Method and Findings From a Health Care Case Study","authors":"Sudeep Hegde, A. Hettinger, R. Fairbanks, J. Wreathall, Seth Krevat, A. Bisantz","doi":"10.1177/1555343419877719","DOIUrl":"https://doi.org/10.1177/1555343419877719","url":null,"abstract":"Resilience engineering (RE) has ushered new approaches to learning about work in complex sociotechnical systems. In terms of improving safety, RE marks a shift from the traditional approach of retrospectively investigating adverse events, toward learning proactively about patterns in everyday work, including how things go well. This study applied the RE framework to the health care domain, by developing and implementing a new knowledge-elicitation protocol to learn about how frontline care providers achieve safe and effective patient care in their everyday work. Eighteen participants, including physicians, nurses, residents, and clinical leaders from a range of specialties, were interviewed using the new protocol. Qualitative analysis of the data revealed multiple themes and patterns which underlie resilient functioning of individuals, teams, and the organization as a whole. Further, a Resilience Mapping Framework (RMF) was developed based on major thematic categories to systematically represent and map various resilient capabilities—monitoring, anticipating, responding, and learning—across different levels of system scale, from the individual to the organizational. This study demonstrates new methods to identify and represent resilience not just during salient and critical “events,” but across the continuum of situations, from the everyday “normal” functioning to the critical.","PeriodicalId":46342,"journal":{"name":"Journal of Cognitive Engineering and Decision Making","volume":null,"pages":null},"PeriodicalIF":2.0,"publicationDate":"2020-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1177/1555343419877719","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"48321146","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2020-02-24DOI: 10.1177/1555343420903212
F. E. Robinson, Markus A. Feufel, V. Shalin, Debra Steele-Johnson, B. Springer
Research and practice in medical decision making value consistency with standardized intervention, potentially neglecting the impact of various environmental features such as workload or the constraints of local work practice. This study presents both qualitative and quantitative analyses of emergency physicians’ decision-making processes in their natural work setting to examine the impact of contextual features. We study contextual effects on two separable decision-making processes identified in quantified observational data: goal enactment and goal establishment. Whereas goal enactment responds to hospital differences and patient difficulty as main effects, goal establishment responds to their interaction. Our emphasis on goal establishment expands the scope of a medical decision-making literature focused on diagnosis, and extends to other professions and the more general conceptualization of expertise. From a theoretical perspective, we emphasize the importance of accounting for contextual variability within the bounds of expert behavior. Practically, we provide real-world examples of context effects that bear on the standardization of care, cost differences between hospitals, and the conceptualization of quality medical care.
{"title":"Rational Adaptation: Contextual Effects in Medical Decision Making","authors":"F. E. Robinson, Markus A. Feufel, V. Shalin, Debra Steele-Johnson, B. Springer","doi":"10.1177/1555343420903212","DOIUrl":"https://doi.org/10.1177/1555343420903212","url":null,"abstract":"Research and practice in medical decision making value consistency with standardized intervention, potentially neglecting the impact of various environmental features such as workload or the constraints of local work practice. This study presents both qualitative and quantitative analyses of emergency physicians’ decision-making processes in their natural work setting to examine the impact of contextual features. We study contextual effects on two separable decision-making processes identified in quantified observational data: goal enactment and goal establishment. Whereas goal enactment responds to hospital differences and patient difficulty as main effects, goal establishment responds to their interaction. Our emphasis on goal establishment expands the scope of a medical decision-making literature focused on diagnosis, and extends to other professions and the more general conceptualization of expertise. From a theoretical perspective, we emphasize the importance of accounting for contextual variability within the bounds of expert behavior. Practically, we provide real-world examples of context effects that bear on the standardization of care, cost differences between hospitals, and the conceptualization of quality medical care.","PeriodicalId":46342,"journal":{"name":"Journal of Cognitive Engineering and Decision Making","volume":null,"pages":null},"PeriodicalIF":2.0,"publicationDate":"2020-02-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1177/1555343420903212","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"45511074","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2020-01-30DOI: 10.1177/1555343419892184
N. Moacdieh, S. Devlin, H. Jundi, S. L. Riggs
High mental workload, in addition to changes in workload, can negatively affect operators, but it is not clear how sudden versus gradual workload transitions influence performance and visual attention allocation. This knowledge is important as sudden shifts in workload are common in multitasking domains. The objective of this study was to investigate, using performance and eye tracking metrics, how constant versus variable levels of workload affect operators in the context of a dual-task paradigm. An unmanned aerial vehicle command and control simulation varied task load between low, high, gradually transitioning from low to high, and suddenly transitioning from low to high. Performance on a primary and secondary task and several eye tracking measures were calculated. There was no significant difference between sudden and gradual workload transitions in terms of performance or attention allocation overall; however, both sudden and gradual workload transitions changed participants’ strategy in dealing with the primary and secondary task as compared to low/high workload. Also, eye tracking metrics that are not frequently used, such as transition rate and stationary entropy, provided more insight into performance differences. These metrics can potentially be used to better understand operators’ strategies and could form the basis of an adaptive display.
{"title":"Effects of Workload and Workload Transitions on Attention Allocation in a Dual-Task Environment: Evidence From Eye Tracking Metrics","authors":"N. Moacdieh, S. Devlin, H. Jundi, S. L. Riggs","doi":"10.1177/1555343419892184","DOIUrl":"https://doi.org/10.1177/1555343419892184","url":null,"abstract":"High mental workload, in addition to changes in workload, can negatively affect operators, but it is not clear how sudden versus gradual workload transitions influence performance and visual attention allocation. This knowledge is important as sudden shifts in workload are common in multitasking domains. The objective of this study was to investigate, using performance and eye tracking metrics, how constant versus variable levels of workload affect operators in the context of a dual-task paradigm. An unmanned aerial vehicle command and control simulation varied task load between low, high, gradually transitioning from low to high, and suddenly transitioning from low to high. Performance on a primary and secondary task and several eye tracking measures were calculated. There was no significant difference between sudden and gradual workload transitions in terms of performance or attention allocation overall; however, both sudden and gradual workload transitions changed participants’ strategy in dealing with the primary and secondary task as compared to low/high workload. Also, eye tracking metrics that are not frequently used, such as transition rate and stationary entropy, provided more insight into performance differences. These metrics can potentially be used to better understand operators’ strategies and could form the basis of an adaptive display.","PeriodicalId":46342,"journal":{"name":"Journal of Cognitive Engineering and Decision Making","volume":null,"pages":null},"PeriodicalIF":2.0,"publicationDate":"2020-01-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1177/1555343419892184","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"44727392","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2019-12-01DOI: 10.1177/1555343419890722
{"title":"Acknowledgments","authors":"","doi":"10.1177/1555343419890722","DOIUrl":"https://doi.org/10.1177/1555343419890722","url":null,"abstract":"","PeriodicalId":46342,"journal":{"name":"Journal of Cognitive Engineering and Decision Making","volume":null,"pages":null},"PeriodicalIF":2.0,"publicationDate":"2019-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1177/1555343419890722","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"48908040","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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