Problem- and Project-Based Learning in Engineering: A Focus on Electrical Vehicles
Why this work is in the frame
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Bibliographic record
Abstract
An innovative learning approach, qualified as Problem- and Project-Based Learning (PPBL), has been developed in the Department of Electrical and Computer Engineering of the Universite de Sherbrooke. PPBL is applied totally from the first term of our programs, instead of being applied gradually. Basically, the students are involved in two types of activities in each term. The first one consists of several (typically, six) consecutive Problem- Based Learning (PBL)-units, where each PBL-unit lasts generally two weeks and is focused around the resolution of an engineering problem. The second type of activities is to realize a project throughout the term, which requires the resolution of a more complex technical problem and the use of project management methods. The experience and learning obtained in solving the small consecutive engineering problems should be used in the resolution of the project. After a presentation of how PPBL is implemented in our department, its benefits are highlighted in an area that is becoming increasingly important: Electrical vehicles. We present in particular several capstone projects realized by our students that have led to the production of prototypes of electrical vehicles. Several prototypes have obtained prices in international competitions or will participate in competitions in a near future.
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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 | 0.000 | 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 | 0.000 |
| 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 it