Results
Displaying 61-72 of 286 Results
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PI Alberto Mello
CO-I Kais Jribi
CO-I Doug Neill (C.E.S. LLC)
CO-I Jon Gosse (C.E.S. LLC)
- The focus of this research is to provide advanced methods and tools to address damage tolerance in composite structure
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PI Matthew Ikle
CO-I Hong Liu
CO-I Michael Wolyniak
CO-I Raphael Isokpehi
- This project will develop a virtual department across four partner campuses to provide computer science education to students at campuses that are individually too small to support this kind of department. The new department will focus on the analysis of "big data" - large sets of computational and observational data - that are becoming increasingly prevalent in STEM. Cyber-learning techniques such as recorded lectures, archived materials, blog participation, and active learning approaches will be combined to offer a set of classes in big data science spanning meteorology, environmental science, biology and chemistry. By combining students from different campuses into the same courses, problems with minimal resources and limited potential enrollments on the individual campuses can be overcome. In particular, the project will focus on developing courses in biology and earth science, areas where students are not attracted by traditional computer science classes.
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PI Hever Moncayo
- This project aimed at gaining more insight into the mechanisms of pilot SD and LESA occurrence, capturing their dynamic fingerprint, and developing on-board intelligent schemes capable of predicting and detecting these dangerous phenomena associated to pilot behaviors.
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PI Troy Henderson
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This project will demonstrate the capability of an electrostatic dust shield, developed by NASA/KSC engineers, to remove dust from the lens of a camera after impact on the lunar surface.
- The verification process of safety-critical systems must ensure system design performs all intended functionality within the required output ranges and safety limits. It must also ensure that no intended functionality is present having a risk larger than the stated development assurance level.
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PI Stephanie Fussell, Ph.D.
CO-I Dothang Truong
- The goal of this research was to determine the factors that influence aviation students’ intention to use VR for flight training. An extended Technology Acceptance Model (TAM) was developed that incorporates elements of the Theory of Planned Behavior (TPB); factors derived from relevant, validated extended TAMs; and new factors that are theorized to impact use intention. These factors are related to aviation education, the use of VR technology in training environments, and using VR for flight training. The new model may explain flight students’ acceptance of VR for flight training as well as their intent to use the technology. A quantitative research method with a cross-sectional survey design was utilized. Descriptive statistical analysis, a confirmatory factor analysis (CFA), and a structural equation modeling (SEM) process were employed. Data were collected from aviation students enrolled in FAA-approved Part 141 pilot schools in early 2020 using a survey design. Results indicated a good model fit to answer the three research questions of the study. There were 14 hypotheses in the original model. Although one was removed, an additional relationship was discovered, validated, and added to the model. Nine of the hypotheses were supported. Eight of the nine predictor factors of the model were determined to directly or indirectly impact behavioral intention (BI). The original TAM factors had the strongest relationships. Relationships between factors particularly relevant to VR technology and aviation training were also supported.
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PI Joseph Cerreta
CO-I David Thirtyacre
CO-I Scott Burgess
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The capability of commercial off-the-shelf 3D printers has increased rapidly over the past few years, and the ability to design, print and assemble sUAS could save academic institution resources and provide students excellent training.
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PI Matthew Verleger
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This engineering education research project seeks to develop a proof-of-concept peer review matching algorithm and demonstrate if it is a valuable and viable methodology for conducting peer review. Peer review is a proven method that has positive impact on student learning. The project will test the algorithm on Model Eliciting Activities in the engineering classroom, and investigate how changing peer review can affect student learning.
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PI Darryl Chamberlain
- The overriding goal of this project is to investigate student knowledge in a Precalculus course at ERAU-W in order to construct autonomous, targeted feedback for free-responses questions to enhance students' online learning. This will be accomplished by analyzing student responses to exam questions and interviewing students to probe how their mathematical conceptions correspond to their exam responses.
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PI Jianhua Liu
CO-I Andrew Schneider
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The goal is to create an ATC ASR dataset for open access. We have obtained 300 hours of audio data and processed 30 hours using the bootstrap approach: Using Whisper to provide the initial transcripts, Correcting the transcripts by hired transcriber team, reviewing the corrected transcripts.
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PI Marisa Aguiar
CO-I Carolina Anderson
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Title 14 of the Code of Federal Regulations (CFR) Part 141 flight training organizations are actively pursuing ways to increase operational safety by introducing advanced risk assessment and decision-making techniques. The purpose of the dissertation was to create and validate a safety performance decision-making tool to transform a reactive safety model into a predictive, safety performance decision-making tool, specific to large, collegiate Title 14 CFR Part 141 flight training organizations, to increase safety and aid in operational decision-making. The validated safety decision-making tool uses what-if scenarios to assess how changes to the controllable input variables impact the overall level of operational risk within an organization’s flight department.