A DIVE INTO DESIGN INTEGRATION CHALLENGES FOR 1ST YEAR ENGINEERING STUDENTS
Bibliographic record
Abstract
Since 2010, Polytechnique Montréal offers the Aerospace Engineering four-year program. The introductory project “AER1110 - projet initial en génie aérospatial” is proposed to first year students who have completed a single semester. This course applies an innovative approach with better alignment with critical competencies identified by the aerospace industry. Among the course objectives, students learn and apply mechanical design methodology in an authentic design-build-test experience inspired from professional engineering design practice. This paper describes the motivations, framework and the characteristics of this course to achieve an effective project based learning experience inspired from industry practice for students. An “ask – don’t tell” approach is taken so project activities are built to generate open-ended questions to be answeredinstead of using knowledge learned from other courses to be applied on predefined problems. Multiple iterations of this introduction to engineering project have been tried. Until now, most experiences hadsignificant flaws: authenticity, high student uncertainty, motivation, assessment alignment with professionalpractice objectives, competition versus collaboration, etc. From all these iterations, a robust project framework has evolved. Teaching staff implication to build authentic projectexperiences is significant and can overwhelm academic systems rapidly. A step by step approach can manage the time issue, but to achieve the integration competency objective a more profound academic systemtransformation is needed that includes: assessment methods review, course load management, course systems and student-mentor interactions.
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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 | 0.014 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.007 | 0.004 |
| Scholarly communication | 0.015 | 0.009 |
| Open science | 0.003 | 0.013 |
| Research integrity | 0.005 | 0.010 |
| Insufficient payload (model declined to judge) | 0.014 | 0.005 |
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".