Comparison of Eye Movement Data to Direct Measures of Situation Awareness for Development of a Novel Measurement Technique in Dynamic, Uncontrolled Test Environments

Situation awareness (SA) is a measure of an individual\u27s knowledge and understanding of the current and expected future states of a situation. While there are numerous options for SA measurement, none are currently suitable in dynamic, uncontrolled environments. Direct measures of SA are the most common, but require a large amount of researcher control as well as the ability to stop operators during a task in order to ask questions about their levels of SA. The current research explored the relationship between direct measures of SA and eye tracking measures as a first step in the development of an unobtrusive SA measure to be used in less controllable, dynamic environments. Two studies compared participant eye movements and SA in driving and air traffic control scenarios. Both studies showed that the more individuals fixated on an important, task-relevant event, the higher their SA for that event. The studies also provide evidence that the way operators allocate attention (i.e., distributed widely or narrowly) affects their SA as well as their task performance. In addition, study 2 results showed positive correlations between SA and task performance. The results indicate that eye tracking may be a viable option for measuring SA in environments not conducive to current direct SA measurement techniques. Future research should continue to explore which eye movement variables best predict participant SA, as well as to investigate the relationship between attention allocation and SA

Engaging the Digitally Engaged Student: Comparing Technology-Mediated Communication Use and Effects on Student Learning

The role of communication technologies in the learning process is both a dynamic and complex issue. Yet, we know surprisingly little about how the use of specific communication technologies may influence classroom performance, key learning outcomes, and other measures of course satisfaction. The research reported here attempts to add to our knowledge about the role of communication in the technology enhanced classroom (TEC) education and in technology-enhanced online (TEO) education through a direct comparison of two courses. Our findings indicate additional support for “The No Significant Difference Phenomenon.” Furthermore, we found that prior experiences lead students to gravitate towards their preferred learning environments, and that basic website elements are required in any learning environment to enhance student outcomes. Finally, we found that when used appropriately, the benefits of communication technology use in education outweigh many of the drawbacks

Continually Updating Generative Retrieval on Dynamic Corpora

Generative retrieval has recently been gaining a lot of attention from the research community for its simplicity, high performance, and the ability to fully leverage the power of deep autoregressive models. However, prior work on generative retrieval has mostly investigated on static benchmarks, while realistic retrieval applications often involve dynamic environments where knowledge is temporal and accumulated over time. In this paper, we introduce a new benchmark called STREAMINGIR, dedicated to quantifying the generalizability of retrieval methods to dynamically changing corpora derived from StreamingQA, that simulates realistic retrieval use cases. On this benchmark, we conduct an in-depth comparative evaluation of bi-encoder and generative retrieval in terms of performance as well as efficiency under varying degree of supervision. Our results suggest that generative retrieval shows (1) detrimental performance when only supervised data is used for fine-tuning, (2) superior performance over bi-encoders when only unsupervised data is available, and (3) lower performance to bi-encoders when both unsupervised and supervised data is used due to catastrophic forgetting; nevertheless, we show that parameter-efficient measures can effectively mitigate the issue and result in competitive performance and efficiency with respect to the bi-encoder baseline. Our results open up a new potential for generative retrieval in practical dynamic environments. Our work will be open-sourced.Comment: Work in progres

Approaches to Learning to Control Dynamic Uncertainty

In dynamic environments, when faced with a choice of which learning strategy to adopt, do people choose to mostly explore (maximizing their long term gains) or exploit (maximizing their short term gains)? More to the point, how does this choice of learning strategy influence one’s later ability to control the environment? In the present study, we explore whether people’s self-reported learning strategies and levels of arousal (i.e., surprise, stress) correspond to performance measures of controlling a Highly Uncertain or Moderately Uncertain dynamic environment. Generally, self-reports suggest a preference for exploring the environment to begin with. After which, those in the Highly Uncertain environment generally indicated they exploited more than those in the Moderately Uncertain environment; this difference did not impact on performance on later tests of people’s ability to control the dynamic environment. Levels of arousal were also differentially associated with the uncertainty of the environment. Going beyond behavioral data, our model of dynamic decision-making revealed that, in actual fact, there was no difference in exploitation levels between those in the highly uncertain or moderately uncertain environments, but there were differences based on sensitivity to negative reinforcement. We consider the implications of our findings with respect to learning and strategic approaches to controlling dynamic uncertainty.This study was supported by the Engineering and Physical Sciences Research Council

Explaining Implicit and Explicit Affective Linkages in IT Teams: Facial Recognition, Emotional Intelligence, and Affective Tone

Over 80 percent of task work in organizations is performed by teams. Most teams operate in a more fluid, dynamic, and complex environment than in the past. As a result, a growing body of research is beginning to focus on how teams’ emotional well-being can benefit the effectiveness of workplace team efforts. These teams are required to be adaptive, to operate in ill-structured environments, and to rely on technology more than ever before. However, teams have become so ubiquitous that many organizations and managers take them for granted and assume they will be effective and productive. Because of the increased use of team work and the lack of sufficient organizational and managerial sufficient best practices for teams, more research is required. Team Emotional Intelligence (TEI) is a collective skill that has been shown to benefit team performance. However, measures for TEI are relatively new and have not been widely studied. Results show TEI is a viable skill that affects performance in IT teams. In technology-rich environments, the teams’ coordination can vary on levels of the expertise needed when TEI behaviors are employed. Cooperative norms play an important role in team interactions and influence TEI. Physiological measures of team emotional contagion and TEI, as well as psychometric measures of team affective tone results show causal affective linkages in the emotional convergence model. These results suggest that combined physiological and psychometric measures of team emotion behavior provide explanatory power for these linkages in teams during IS technology system use. These findings offer new insights into the emotional states of IS teams that may advance the understanding team behaviors for improved performance outcomes and contribute to the NeuroIS literature

IS Cognitive Load: An Examination of Measurement Convergence

Despite the growth and interest in information processing research, understanding the supporting role of information systems (IS) has been limited. While cognitive processing of information has been examined in learning environments with traditional learning tasks, the investigation of cognitive load within complex simulated IS learning environments has received less attention. Traditional measurement allows for a broad user evaluation of the ISs and actual usage from a holistic perspective; however, detailed synchronous evaluation of cognitive load during the usage of the IS may allow for more accurate assessment of how system features influence cognitive load and subsequent performance outcomes. Therefore, this research attempts to integrate traditional subjective and physiological measurements to examine cognitive load within a dynamic simulated IS learning environment. This research study focuses on how subjective and objective physiological (galvanic skin response (GSR), heart rate variability (HRV), and electroencephalography (EEG) measures of cognitive load compare in simulated IS training environments

Cybersecurity Measures for Geocasting in Vehicular Cyber Physical System Environments

Geocasting in vehicular communication has witnessed significant attention due to the benefits of location oriented information dissemination in vehicular traffic environments. Various measures have been applied to enhance geocasting performance including dynamic relay area selection, junction nodes incorporation, caching integration, and geospatial distribution of nodes. However, the literature lacks towards geocasting under malicious relay vehicles leading to cybersecurity concern in vehicular traffic environments. In this context, this paper presents Cybersecurity Measures for Geocasting in Vehicular traffic environments (CMGV) focusing on security oriented vehicular connectivity. Specifically, a vehicular intrusion prevention technique is developed to measure the connectivity between the cache agent and cache user vehicles. The connectivity between static transport vehicles and cache agent/cache user is measured via vehicular intrusion detection approach. The performance of the proposed vehicular cybersecurity measure is evaluated in realistic traffic environments. The comparative performance evaluation attests the benefits of security oriented geocasting in vehicular traffic environments