Novel Work-Integrated Learning Model Based on the German Education System: UQTR’s Dual Approach for its Mechanical Engineering Program.
Bibliographic record
Abstract
This paper presents the German-inspired education model called Dual, as pioneered by l'Université du Québec à Trois-Rivières (Drummondville Campus) for its mechanical engineering undergraduate degree. Focus is on the program structure itself and the ongoing research project which aims to determine and measure outcomes of this novel approach from the student, industry-supervisor and professor perspectives’, specifically pertaining to their respective experience, impact on academic performance, employability, and the development of work-related skill sets. The methodology is set forth in this paper and results from similar experiences across Europe are presented. Qualitative and quantitative data for this specific project are still being collected and analyzed. The proposed model for this research stems from studies on active, experiential and work-integrated Learning. Motivated by a desire to better prepare engineering students for the ever-changing realities of the profession and as a response to the shortage of qualified personnel faced by the industrial sector, the program combines parallel on- and off-site learning over a consecutive two-year period. This differs from the more commonly known co-op structure where students alternate between study terms and work terms. With the proposed dual model, students complete the program within 4 years earning 24 credits, of a total 120, through work-integrated learning directly at the workplace (off-site). Courses completed jointly at the school and in partnership with the company include a 9-credit capstone design project and two 3-credit complementary courses, where reflective journaling and mentorship are central to both. In addition, three 4-month internships are also completed. Since June 2021, the program is accredited by Engineers Canada.
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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 | 0.003 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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".