Pedagogical strategies to enhance learning and awareness of acoustics within our engineering school community
Bibliographic record
Abstract
Acoustics is taught at the École de technologie supérieure (ÉTS, Montreal, Canada) in a single advanced specialization course during the final year of the mechanical engineering bachelor's program. This course aims to equip students with the skills needed to measure and reduce noise based on the theoretical foundations of industrial acoustics and associated experimental techniques. The fact that the science of acoustics is not well-known among engineering students, coupled with the optional nature of this course, results in an average enrollment of only about thirty students each year (across two distinct sessions), a number further reduced since 2020 due to the unfortunate impact of the pandemic. Paradoxically, Quebec lacks engineers trained in this discipline and often recruits them from abroad. This presentation will aim to showcase various strategies and pedagogical tools that have been used and experimented with in recent years (e.g., flipped classroom, in-class experiments, cellphone measurements, community service-oriented semester projects). The goal is to ensure the quality and enjoyment of student learning and to contribute to raising awareness about acoustics and noise-related issues within the ÉTS community.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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 teacher head, 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".