Aircraft Structures Projects Involving Aviation Museums Across Canada and the United States
Bibliographic record
Abstract
View Video Presentation: https://doi.org/10.2514/6.2023-0447.vid COVID-19 presented a unique challenge to the delivery of aerospace engineering education, and education as a whole. Many universities operated fully online courses for Spring 2020, Fall 2020, and Spring 2021 semesters which required a rapid re-development of these courses as many were not online courses previously. One challenge was to maintain student engagement in the course material, with each other, and with the course instructor through online platforms such as Zoom. An approach taken for the delivery of two, consecutive aircraft structures courses involved the collaboration of 10 aviation museums across Canada and the United States. The 75th anniversary of the Victory in Europe and Victory in Japan occurred in 2020, and a number of aviation museums intended to recognize this important anniversary. COVID-19 limited the events that the museums could provide the public; therefore, participation in the Aircraft Structure Museum Project provided a unique opportunity to commemorate these anniversaries. Each museum provided an aircraft from their collections for groups of 5 to 6 junior level engineering students to analyze. During Fall 2020, the groups analyzed the structures of the wings and stabilizers. The groups were reformed for Spring 2021 and the groups analyzed the fuselage structure. The project was continued in person for Fall 2021 and Spring 2022, this iteration commemorating diversity and inclusion in aerospace. Each group analyzed an aircraft flown by an under-represented minority and learned about the challenges encountered by that individual. The groups provided presentations and reports to the museums detailing their analyses. This interaction provided the opportunity for the students to connect with famous aircraft, famous people, communicate effectively to technical and lay audiences, and motivated the students to engage with each other frequently. Qualitative assessment of the course evaluations using NVIVO show strong alignment with the Wiggins' framework for authentic assessments, and a positive sentiment by the students toward the project. Preliminary surveys of the 2021-2022 students indicate a very positive reaction, with 76\% of students stating that the project helped with their conceptual learning.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.018 | 0.002 |
| Scholarly communication | 0.004 | 0.001 |
| Open science | 0.001 | 0.007 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.095 | 0.010 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".