Human Factors最新文献

Objective: We explore the relationships between objective communication patterns displayed during virtual team meetings and established, qualitative measures of team member effectiveness.

Background: A key component of teamwork is communication. Automated measures of objective communication patterns are becoming more feasible and offer the ability to measure and monitor communication in a scalable, consistent and continuous manner. However, their validity in reflecting meaningful measures of teamwork processes are not well established, especially in real-world settings.

Method: We studied real-world virtual student teams working on semester-long projects. We captured virtual team meetings using the Zoom video conferencing platform throughout the semester and periodic surveys comprising peer ratings of team member effectiveness. Leveraging audio transcripts, we examined relationships between objective measures of speaking time, silence gap duration and vocal turn-taking and peer ratings of team member effectiveness.

Results: Speaking time, speaking turn count, degree centrality and (marginally) speaking turn duration, but not silence gap duration, were positively related to individual-level team member effectiveness. Time in dyadic interactions and interaction count, but not interaction length, were positively related to dyad-level team member effectiveness.

Conclusion: Our study highlights the relevance of objective measures of speaking time and vocal turn-taking to team member effectiveness in virtual project-based teams, supporting the validity of these objective measures and their use in future research.

Application: Our approach offers a scalable, easy-to-use method for measuring communication patterns and team member effectiveness in virtual teams and opens the opportunity to study these patterns in a more continuous and dynamic manner.

Objective: To investigate the effect of gender transfer in virtual reality on implicit gender bias.

Background: Gender bias is a type of discrimination based on gender, which can lead to increased self-doubt and decreased self-esteem. Sexual harassment is a hostile form of gender bias that can cause anxiety, depression, and significant mental health issues. Virtual reality (VR) has been employed to help make people become aware of their biases and change their attitudes regarding gender, race, and age.

Methods: Forty participants were embodied in avatars of different genders and experienced sexual harassment scenarios in VR. A gender Implicit Association Test (IAT) was administered before and after the experience.

Results: There was a statistically significant main effect of participant gender (F (1,36) = 10.67, p = .002, partial η² = .23) on ΔIAT, where males and females reported a decrease (M = -.12, SD = .24) and an increase (M = .10, SD = .25) in IAT scores, respectively. A statistically significant two-way interaction between gender transfer and participant gender was revealed (F (1,36) = 6.32, p = .02, partial η² = .15). There was a significant simple effect of gender transfer for male participants (F (1,36) = 8.70, p = .006, partial η² = .19).

Conclusions: Implicit gender bias can be modified, at least temporarily, through embodiment in VR. Gender transfer through embodiment while encountering different sexual harassment scenarios helped reduce implicit gender bias. There was a tendency for individuals to increase bias for the gender of the avatar in which they embodied.

Applications: The current research provided promising evidence that a virtual environment system may be used as a potential training tool to improve implicit gender bias.

Objective: Discuss the human factors relevance of attention control (AC), a domain-general ability to regulate information processing functions in the service of goal-directed behavior.

Background: Working memory (WM) measures appear as predictors in various applied psychology studies. However, measures of WM reflect a mixture of memory storage and controlled attention making it difficult to interpret the meaning of significant WM-task relations for human factors. In light of new research, complex task performance may be better predicted or explained with new measures of attention control rather than WM.

Method: We briefly review the topic of individual differences in abilities in Human Factors. Next, we focus on WM, how it is measured, and what can be inferred from significant WM-task relations.

Results: The theoretical underpinnings of attention control as a high-level factor that affects complex thought and behavior make it useful in human factors, which often study performance in complex and dynamic task environments. To facilitate research on attention control in applied settings, we discuss a validated measure of attention control that predicts more variance in complex task performance than WM. In contrast to existing measures of WM or AC, our measures of attention control only require 3 minutes each (10 minutes total) and may be less culture-bound making them suitable for use in applied settings.

Conclusion: Explaining or predicting task performance relations with attention control rather than WM may have dramatically different implications for designing more specific, equitable task interfaces, or training.

Application: A highly efficient ability predictor can help researchers and practitioners better understand task requirements for human factors interventions or performance prediction.

Background: Historical biases in ergonomics-related studies have been attributed to lack of participant diversity and sensitivity of measurements to capture variability between diverse groups. We posit that a neuroergonomics approach, that is, study of brain-behavior relationships during fatiguing work, allows for unique insights on sex differences in fatigue mechanisms that are not available via traditional "neck down" measurement approaches.

Objective: This study examined the supraspinal mechanisms of exercise performance under fatigue and determined if there were any sex differences in these mechanisms.

Methods: Fifty-nine older adults performed submaximal handgrip contractions until voluntary fatigue. Traditional ergonomics measures, namely, force variability, electromyography (EMG) of arm muscles, and strength and endurance times, and prefrontal and motor cortex hemodynamic responses were recorded.

Results: There were no significant differences observed between older males and females in fatigability outcomes (i.e., endurance times, strength loss, and EMG activity) and brain activation. Effective connectivity from prefrontal to motor areas was significant for both sexes throughout the task, but during fatigue, males had higher interregional connectivity than females.

Discussion: While traditional metrics of fatigue were comparable between the sexes, we observed distinct sex-specific neuromotor strategies (i.e., information flow between frontal-motor regions) that were adopted by older adults to maintain motor performance.

Application: The findings from this study offer insights into the capabilities and adaptation strategies of older men and women under fatiguing conditions. This knowledge can facilitate in the development of effective and targeted ergonomic strategies that accommodate for the varying physical capacities of diverse worker demographics.

Objective: We aim to bridge the gap between naturalistic studies of driver behavior and modern cognitive and neuroscientific accounts of decision making by modeling the cognitive processes underlying left-turn gap acceptance by human drivers.

Background: Understanding decisions of human drivers is essential for the development of safe and efficient transportation systems. Current models of decision making in drivers provide little insight into the underlying cognitive processes. On the other hand, laboratory studies of abstract, highly controlled tasks point towards noisy evidence accumulation as a key mechanism governing decision making. However, it is unclear whether the cognitive processes implicated in these tasks are as paramount to decisions that are ingrained in more complex behaviors, such as driving.

Results: The drivers' probability of accepting the available gap increased with the size of the gap; importantly, response time increased with time gap but not distance gap. The generalized drift-diffusion model explained the observed decision outcomes and response time distributions, as well as substantial individual differences in those. Through cross-validation, we demonstrate that the model not only explains the data, but also generalizes to out-of-sample conditions.

Conclusion: Our results suggest that dynamic evidence accumulation is an essential mechanism underlying left-turn gap acceptance decisions in human drivers, and exemplify how simple cognitive process models can help to understand human behavior in complex real-world tasks.

Application: Potential applications of our results include real-time prediction of human behavior by automated vehicles and simulating realistic human-like behaviors in virtual environments for automated vehicles.

Objective: This study aimed to examine operator state variables (workload, fatigue, and trust in automation) that may predict return-to-manual (RTM) performance when automation fails in simulated air traffic control.

Background: Prior research has largely focused on triggering adaptive automation based on reactive indicators of performance degradation or operator strain. A more direct and effective approach may be to proactively engage/disengage automation based on predicted operator RTM performance (conflict detection accuracy and response time), which requires analyses of within-person effects.

Method: Participants accepted and handed-off aircraft from their sector and were assisted by imperfect conflict detection/resolution automation. To avoid aircraft conflicts, participants were required to intervene when automation failed to detect a conflict. Participants periodically rated their workload, fatigue and trust in automation.

Results: For participants with the same or higher average trust than the sample average, an increase in their trust (relative to their own average) slowed their subsequent RTM response time. For participants with lower average fatigue than the sample average, an increase in their fatigue (relative to own average) improved their subsequent RTM response time. There was no effect of workload on RTM performance.

Conclusions: RTM performance degraded as trust in automation increased relative to participants' own average, but only for individuals with average or high levels of trust.

Applications: Study outcomes indicate a potential for future adaptive automation systems to detect vulnerable operator states in order to predict subsequent RTM performance decrements.

Objective: This paper surveys the existing literature surrounding problem-solving and team dynamics in complex and unpredictable scenarios, and evaluates the applicability of studying Earth-based construction teams to identify training needs for Lunar construction crews.

Background: Lunar and other space exploration construction crews will work in extreme environments and face unpredictable challenges, necessitating real-time problem-solving to address unexpected contingencies. This work will require coordination with Mission Control and autonomous assistants, so crew training must account for multi-agent, distributed teamwork.

Method: A narrative literature review identified processes, attributes, and skills necessary for the success of Lunar construction teams. We summarized relevant frameworks and synthesized collective findings into over-arching trends and remaining research gaps.

Results: While significant literature exists surrounding team performance, very little systematic inquiry has been done with a focus on Lunar construction crews and operations, particularly with respect to dynamic problem-solving and team-based decision-making. Established and standardized metrics for evaluating team performance are lacking, resulting in significant variation in reported outcomes between studies.

Conclusion: Lunar and other space exploration construction teams will need training that focuses on developing the right approach to team-based problem-solving, rather than on preparing response execution for known contingencies. An investigation of successful Earth-based construction crews may facilitate the development of relevant metrics for training future Lunar construction crews.

Application: Metrics and team training protocols developed for future Lunar construction teams may be adaptable and applicable to a wide range of extreme teams facing uncertain challenges, such as aircrews, surgical teams, first responders, and construction crews.

Objective: The effects of asset degradation on trust in human-swarm interaction were investigated through the lens of system-wide trust theory.

Background: Researchers have begun investigating contextual features that shape human interactions with robotic swarms-systems comprising assets that coordinate behavior based on their nearest neighbors. Recent work has begun investigating how human trust toward swarms is affected by asset degradation through the lens of system-wide trust theory, but these studies have been marked by several limitations.

Method: In an online study, the current work manipulated asset degradation and measured trust-relevant criteria in a within-subjects design and addressed the limitations of past work.

Results: Controlling for swarm performance (i.e., target acquisition), asset degradation and trust (i.e., reliance intentions) in swarms were negatively related. In addition, as degradation increased, perceptions of swarm cohesion, obstacle avoidance, target acquisition, and terrain exploration efficiency decreased, the latter two of which (coupled with the reliance intentions criterion) support the tenets of system-wide trust theory as well as replicate and extend past work on the effects of asset degradation on trust in swarms.

Conclusion: Human-swarm interaction is a context in which system-wide trust is relevant, and future work ought to investigate how to calibrate human trust toward swarm systems.

Applications: Based on these findings, design professionals should prioritize ways to depict swarm performance and system health such that humans do not abandon trust in systems that are still functional yet not over-trust those systems which are indeed performing poorly.

Objective: The present work explores how the horizontal viewing angle of a virtual character's face influences perceptions of credibility and approachability.

Background: When encountering virtual characters, people rely both on credibility and approachability judgments to form a first impression of the depicted virtual character. Research shows that certain perceptions are preferred either on frontal or tilted faces, but not how approachability or credibility judgments relate to horizontal viewing angles in finer granularity between 0° and 45°.

Method: 52 participants performed a two-alternative forced choice (2AFC) task rating 240 pairwise comparisons of 20 virtual character faces shown in four horizontal viewing angles (0°, 15°, 30°, and 45°) on approachability and credibility. They also rated scales on individual differences based on the BIS-BAS framework (behavioral inhibition system, drive, and reward responsiveness), self-esteem, and personality traits (neuroticism, loneliness).

Results: Both approachability and credibility were negatively related to the horizontal viewing angle, but the negative relationship was less pronounced for approachability. Notably, 15° tilted faces were associated with higher approachability than frontal faces by people scoring high in reward responsiveness, drive, and self-esteem, and scoring low in neuroticism and loneliness.

Conclusion: Our findings highlight the conditions under which showing a virtual character's face is preferred in a horizontally 15° tilted over a frontal position.

Application: The differential impact of the horizontal viewing angle on approachability and credibility should be considered when displaying virtual character faces.

Objective: The objective of this work was to investigate if visuospatial attention and working memory load interact at a central control resource or at a task-specific, information processing resource during driving.

Background: In previous multitasking driving experiments, interactions between different cognitive concepts (e.g., attention and working memory) have been found. These interactions have been attributed to a central bottleneck or to the so-called problem-state bottleneck, related to working memory usage.

Method: We developed two different cognitive models in the cognitive architecture ACT-R, which implement the central vs. problem-state bottleneck. The models performed a driving task, during which we varied visuospatial attention and working memory load. We evaluated the model by conducting an experiment with human participants and compared the behavioral data to the model's behavior.

Results: The problem-state-bottleneck model could account for decreased driving performance due to working memory load as well as increased visuospatial attentional demands as compared to the central-bottleneck model, which could not account for effects of increased working memory load.

Conclusion: The interaction between working memory and visuospatial attention in our dual tasking experiment can be best characterized by a bottleneck in the working memory. The model results suggest that as working memory load becomes higher, drivers manage to perform fewer control actions, which leads to decreasing driving performance.

Application: Predictions about the effect of different mental loads can be used to quantify the contribution of each subtask allowing for precise assessments of the current overall mental load, which automated driving systems may adapt to.