Empirical exploration of air traffic and human dynamics in terminal airspaces

Air traffic is widely known as a complex, task-critical techno-social system, with numerous interactions between airspace, procedures, aircraft and air traffic controllers. In order to develop and deploy high-level operational concepts and automation systems scientifically and effectively, it is essential to conduct an in-depth investigation on the intrinsic traffic-human dynamics and characteristics, which is not widely seen in the literature. To fill this gap, we propose a multi-layer network to model and analyze air traffic systems. A Route-based Airspace Network (RAN) and Flight Trajectory Network (FTN) encapsulate critical physical and operational characteristics; an Integrated Flow-Driven Network (IFDN) and Interrelated Conflict-Communication Network (ICCN) are formulated to represent air traffic flow transmissions and intervention from air traffic controllers, respectively. Furthermore, a set of analytical metrics including network variables, complex network attributes, controllers' cognitive complexity, and chaotic metrics are introduced and applied in a case study of Guangzhou terminal airspace. Empirical results show the existence of fundamental diagram and macroscopic fundamental diagram at the route, sector and terminal levels. Moreover, the dynamics and underlying mechanisms of "ATCOs-flow" interactions are revealed and interpreted by adaptive meta-cognition strategies based on network analysis of the ICCN. Finally, at the system level, chaos is identified in conflict system and human behavioral system when traffic switch to the semi-stable or congested phase. This study offers analytical tools for understanding the complex human-flow interactions at potentially a broad range of air traffic systems, and underpins future developments and automation of intelligent air traffic management systems.Comment: 30 pages, 28 figures, currently under revie

Active Learning: Effects of Core Training Design Elements on Self-Regulatory Processes, Learning, and Adaptability

This research describes a comprehensive examination of the cognitive, motivational, and emotional processes underlying active learning approaches, their effects on learning and transfer, and the core training design elements (exploration, training frame, emotion-control) and individual differences (cognitive ability, trait goal orientation, trait anxiety) that shape these processes. Participants (N = 350) were trained to operate a complex computer-based simulation. Exploratory learning and error-encouragement framing had a positive effect on adaptive transfer performance and interacted with cognitive ability and dispositional goal orientation to influence trainees’ metacognition and state goal orientation. Trainees who received the emotion-control strategy had lower levels of state anxiety. Implications for developing an integrated theory of active learning, learner-centered design, and research extensions are discussed

A Multilevel Analysis of the Effect of Prompting Self-Regulation in Technology-Delivered Instruction

We used a within-subjects design and multilevel modeling in two studies to examine the effect of prompting self-regulation, an intervention designed to improve learning from technology-delivered instruction. The results of two studies indicate trainees who were prompted to self-regulate gradually improved their knowledge and performance over time, relative to the control condition. In addition, Study 2 demonstrated that trainees’ cognitive ability and self-efficacy moderated the effect of the prompts. Prompting self-regulation resulted in stronger learning gains over time for trainees with higher ability or higher self-efficacy. Overall, the two studies demonstrate that prompting self-regulation had a gradual, positive effect on learning, and the strength of the effect increased as trainees progressed through training. The results are consistent with theory suggesting self-regulation is a cyclical process that has a gradual effect on learning and highlight the importance of using a within-subjects design in self-regulation. research

Toward Metacognitive Radars: Concept and Applications

We introduce a metacognitive approach to optimize the radar performance for a dynamic wireless channel. Similar to the origin of the cognitive radar in the neurobiological concept of cognition, metacognition also originates from neurobiological research on problem-solving and learning. Broadly defined as the process of learning to learn, metacognition improves the application of knowledge in domains beyond the immediate context in which it was learned. We describe basic features of a metacognitive radar and then illustrate its application with some examples such as antenna selection and resource sharing between radar and communications. Unlike previous works in communications that only focus on combining several existing algorithms to form a metacognitive radio, we also show the transfer of knowledge in a metacognitive radar. A metacognitive radar improves performance over individual cognitive radar algorithms, especially when both the channel and transmit/receive hardware are changed

Metacognition Process in Learning

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How Individual self-regulation affects group regulation and performance: A shared regulation intervention

This study explored the relationship between individual self-regulated learning (SRL), socially shared regulation of learning (SSRL), and group performance plus the effect of an intervention promoting SSRL. We hypothesized that SRL would influence SSRL and group performance as groups with high SRL students will be better regulated and that the intervention would promote SSRL over time. The results revealed a significant relationship between SRL and SSRL, but no significant effects of the intervention on group performance. The limitations of the intervention are discussed and form the basis for future design of environments to promote SSRL. The main conclusion is that SRL is an important predictor of SSRL and should be considered when designing small group activities and their environments

Information Visualization of Metacognitive Skills During the Software Development Process Based on an Adapted Engineering Design Metacognitive Questionnaire

In software development, either alone or in a team, there are many aspects that determine the success in developing the software, including each developer\u27s skills. Studies show that the application of metacognition can increase the effectiveness and efficiency of software development. To measure a metacognition skill, there need to be a metacognition measurement tools. One example of this measurement method is adapted engineering design metacognitive questionnaire. However, the respondents feel that existing tools still have not given them any benefits. This research is conducted to develop an information visualization tools for the metacognition measurement from an adapted engineering design metacognitive questionnaire. The research was performed using qualitative method adapted from the user-centered design approach, which is user requirement analysis, design alternatives, prototyping, and evaluation. The finding suggests that with information visualization, the students as the respondents feel the benefits of filling the EDMQ questionnaire. However, from the design standpoint, there are still numerous things that can be improved to make the visualization more informative

Third wave of measurement in the self-regulated learning field: when measurement and intervention come hand in hand

This is an Accepted Manuscript of an article published by Taylor & Francis Group in Scandinavian Journal of Educational Research on 24/07/2015, available online:http://www.tandfonline.com/10.1080/00313831.2015.1066436Measurement is a central issue for the self-regulated learning (SRL) field as SRL is a phenomenon difficult to measure in a reliable and valid way. Here, 3 waves in the history of SRL measurement are identified and profiled. Our focus lies on the third and newest one, which combines measurement and intervention within the same tools. The basis for this approach is located in the reactivity principle via students’ self-monitoring: when students are aware of their actions, they can react and change what is needed. That happens when the measurement tools promote students’ self-monitoring which turn part of the intervention then. Examples of this new approach to SRL measurement and guidelines for implementing it are presentedThe first author was funded via Spanish Ministerio de Economía y Competitividad, programa Ramón y Cajal [RYC-2013-13469]. The first and third author were funded via the Finnish Academy, project name PROSPECTS (PI: Sanna Järvelä, [grant number: 24301274]