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1. Learning from Earthquakes Using the Automatic Reconnaissance Image Organizer (ARIO)

   S. J. Dyke, X. Liu ( September 2021 , Proceeding of the 17th World Conference on Earthquake Engineering)

   null (Ed.)

   In the aftermath of earthquake events, reconnaissance teams are deployed to gather vast amounts of images, moving quickly to capture perishable data to document the performance of infrastructure before they are destroyed. Learning from such data enables engineers to gain new knowledge about the real-world performance of structures. This new knowledge, extracted from such visual data, is critical to mitigate the risks (e.g., damage and loss of life) associated with our built environment in future events. Currently, this learning process is entirely manual, requiring considerable time and expense. Thus, unfortunately, only a tiny portion of these images are shared, curated, and actually utilized. The power of computers and artificial intelligence enables a new approach to organize and catalog such visual data with minimal manual effort. Here we discuss the development and deployment of an organizational system to automate the analysis of large volumes of post-disaster visual data, images. Our application, named the Automated Reconnaissance Image Organizer (ARIO), allows a field engineer to rapidly and automatically categorize their reconnaissance images. ARIO exploits deep convolutional neural networks and trained classifiers, and yields a structured report combined with useful metadata. Classifiers are trained using our ground-truth visual database that includes over 140,000 images from past earthquake reconnaissance missions to study post-disaster buildings in the field. Here we discuss the novel deployment of the ARIO application within a cloud-based system that we named VISER (Visual Structural Expertise Replicator), a comprehensive cloud-based visual data analytics system with a novel Netflix-inspired technical search capability. Field engineers can exploit this research and our application to search an image repository for visual content. We anticipate that these tools will empower engineers to more rapidly learn new lessons from earthquakes using reconnaissance data. 

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2. The Precision-Bias Distinction for Evaluating Visual Decision Aids for Risk Perception

   https://doi.org/10.1177/0272989X20943516  

   Witt, Jessica_K ( July 2020 , Medical Decision Making)

   Risk communication is critically important, for both patients and providers. However, people struggle to understand risks because there are inherent biases and limitations to reasoning under uncertainty. A common strategy to enhance risk communication is the use of decision aids, such as charts or graphs, that depict the risk visually. A problem with prior research on visual decision aids is that it used a metric of performance that confounds 2 underlying constructs: precision and bias. Precision refers to a person’s sensitivity to the information, whereas bias refers to a general tendency to overestimate (or underestimate) the level of risk. A visual aid is effective for communicating risk only if it enhances precision or, once precision is suitably high, reduces bias. This article proposes a methodology for evaluating the effectiveness of visual decision aids. Empirical data further illustrate how the new methodology is a significant advancement over more traditional research designs.

    

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3. A Principal-Agent Model of Systems Engineering Processes with Application to Satellite Design

   Safarkhani, Salar ; Kattakuri, Vikranth ; Bilionis, I. ; Panchal, Jitesh H. ( July 2018 , Council of Engineering Systems Universities (CESUN) Global Conference)

   We present a principal-agent model of a one-shot, shallow, systems engineering process. The process is "one-shot" in the sense that decisions are made during a one-time step and that they are final. The term "shallow" refers to a one-layer hierarchy of the process. Specifically, we assume that the systems engineer has already decomposed the problem in subsystems and that each subsystem is assigned to a different subsystem engineer. Each subsystem engineer works independently to maximize their own expected payoff. The goal of the systems engineer is to maximize the system-level payoff by incentivizing the subsystem engineers. We restrict our attention to requirements-based system-level payoffs, i.e., the systems engineer makes a profit only if all the design requirements are met. We illustrate the model using the design of an Earth-orbiting satellite system where the systems engineer determines the optimum incentive structures and requirements for two subsystems: the propulsion subsystem and the power subsystem. The model enables the analysis of a systems engineer's decisions about optimal passed-down requirements and incentives for sub-system engineers under different levels of task difficulty and associated costs. Sample results, for the case of risk-neutral systems and subsystems engineers, show that it is not always in the best interest of the systems engineer to pass down the true requirements. As expected, the model predicts that for small to moderate task uncertainties the optimal requirements are higher than the true ones, effectively eliminating the probability of failure for the systems engineer. In contrast, the model predicts that for large task uncertainties the optimal requirements should be smaller than the true ones in order to lure the subsystem engineers into participation. 

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4. Board 121: Development of a Create-a-Lego-Engineer Activity to Examine Students’ Engineering Identity

   https://doi.org/10.18260/1-2--32212  

   Paul, Kelli ; Sung, Euisuk ; Maltese, Adam ; Miel, Karen ; Portsmore, Merredith ( June 2019 , ASEE Conferences)

   This paper describes the development of a Create-a-Lego-Engineer (CALE) activity which was created as an alternative to the Draw-a-Scientist (DAST) and Draw-an-Engineer Tests (DAET). While the DAST and DAET examine students’ (mis)conceptions of scientists and engineers, they provide limited information about whether students can envision themselves as scientists or engineers now or in the future. We drew from the Lego Serious Play (LSP) method which is grounded on the premise that hands-on learning results in a deeper understanding of the world and oneself in it. The LSP method is a process used to enhance innovation and business development, and it involves adults building metaphorical representations of their identity using Lego bricks. We adapted this process for use with elementary students (3rd-5th grade) in a specific context, namely students are asked to build themselves as engineers and a scene depicting what they would be doing as an engineer. Lego bricks were chosen as they are familiar to most students, are easy to use even without prior experience, and require no special skills or artistic abilities. The activity allows us to explore students’ creations of physical representations of themselves as engineers, including issues related to gender and physical characteristics (e.g., skin color, hair color and style), all of which students can customize using a variety of Lego options. Students are provided with a variety of Lego person pieces in order to try and build a representation of themselves using Legos. Additionally, a wide variety of Lego brick pieces were provided in order to allow for numerous ways in which students might represent engineers doing engineering work. Students were asked to imagine themselves as engineers and then to create their Lego engineer. Next, on a notecard, they described the type of work their Lego engineer would be doing, at which point they were then asked to create this scene using Lego bricks. Finally, after completing their creations, students reflected on the meaning of what they built and verbally described their creation and the choices they made. While these reflections provide additional insight into students’ beliefs about who can be an engineer and what engineers do, they also provide students an opportunity to imagine and see themselves in the role of an engineer. This activity was developed within the context of a multi-year, NSF-funded research project examining the dynamics between undergraduate outreach providers and elementary students to understand the impact of the program on students’ engineering identity and career aspirations. This paper will describe the development of the activity as well as preliminary findings from pilot testing and use with elementary students participating in the overall research project. Potential implications and limitations will be described. 

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5. Caregivers’ Multiple Roles in Supporting their Child through an Engineering Design Project

   Simpson, Amber ; Yang, Jing ; Knox, Peter N. ; Maltese, Adam V. ( January 2021 , American Society for Engineering Education)

   null (Ed.)

   Caregivers are one of the most significant influences in their children’s engineering engagement at a young age; however, the roles caregivers can play in supporting their children is less understood. Employing an intrinsic case study on a five-month engineering program conducted in an out-of-school context, we illustrate the multiple and different roles that three caregivers enacted, and the contextual factors of the program that influenced and shaped their role enactment. We observed 12 dynamic, complex, and evolving roles that caregivers endorsed to support their child throughout the engineering design process. These roles were situated within preexisting rules and expectations as caregivers while also developing an understanding of the rules and expectations of an engineer through their social interactions with volunteer engineers and makers. This work contributes to our understanding of how to create environments to enable caregivers to best support their children’s STEM learning process. 

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