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

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

Foraging for spatial information: Patterns of orientation learning using desktop virtual reality

The purpose of the study was to provide a description of how learners use desktop VR systems for orientation learning that instructional designers could use to improve the technology. The study used a mixed method, content analysis approach based on a theoretical framework that included principles of self-regulated learning (SRL) and orientation learning. Twelve participants used desktop virtual reality (VR) systems to explore the virtual surround of a residential space. A screen-recording program captured participants' navigation movements and think-aloud verbalizations. Participants' recorded think-aloud verbalizations were coded to identify the orientation learning and SRL events they used during the session. Analysis of the participant movement data revealed that eight of the participants generally moved in a single direction through the surround, whereas the remaining four moved in a direction and then reversed that direction. Movement patterns of some participants were found to be different at the beginning and end of their VR session, and some participants tended to navigate through certain areas of the surround more slowly than through other areas. Some participants tended to view the scene at a constant field of view level, whereas other varied the level. Additionally, some participants tended to view a particular area of the scene with narrower or wider fields of view, but others varied the field of view level across the scene. A model of orientation learning events was derived from content analysis of the think-aloud transcripts showing that participants engaged in four major types of learning categories: identifying, locating, regulating, and contextualizing. Participants were classified into four groups according to relative frequency distributions of the event categories. The study concluded that use of SRL events varied amongst the participants, and that the participant used a diverse set of movement and learning event patterns. Further conclusions noted that virtual scene objects possessed meaning for learners, and that thought verbalizations indicated that some of the learners attained a sense of presence in the VR environment. Finally, the study concluded that qualitative techniques such as thought verbalizations may provide a new paradigm for measuring presence in virtual environments

Creating Tomorrow, Fall 2010

Annual magazine of the College of Engineering at Utah State University.https://digitalcommons.usu.edu/engineering_magazines/1002/thumbnail.jp

The role of metacognition in troubleshooting: an example from electronics

Students in physics laboratory courses, particularly at the upper division, are often expected to engage in troubleshooting. Although there are numerous ways in which students may proceed when diagnosing a problem, not all approaches are equivalent in terms of providing meaningful insight. It is reasonable to believe that metacognition, by assisting students in making informed decisions, is an integral component of effective troubleshooting. We report on an investigation of authentic student troubleshooting in the context of junior-level electronics courses at two institutions. Think-aloud interviews were conducted with pairs of students as they attempted to repair a malfunctioning operational-amplifier circuit. Video data from the interviews have been analyzed to examine the relationship between each group's troubleshooting activities and instances of socially mediated metacognition. We present an analysis of a short episode from one interview.Comment: 4 pages, 1 figure; Submitted to 2015 PERC Proceeding