From design as a socio-technological practice to design as an educational strategy
Bibliographic record
Abstract
Recent high school curriculum reforms worldwide have integrated engineering design. However, the implementation of engineering design (ED) into high school curricula faces challenges due to teachers' misconceptions regarding engineering as well as their lack of knowledge and training. This study examines how the course at Université de Sherbrooke (UdeS) impacted preservice science teachers (PSTs). The main purpose was to examine 13 student’s perceptions of engineers and ED. Also, the study investigates how such a course enables preservice teachers to acquire fundamental ED skills. The data were analyzed through qualitative tools and techniques. Results indicate high levels of course satisfaction and deepened understanding of engineering practice among students. Participants valued the experience, were actively engaged, and expressed positive outcomes including enhanced thinking and interpersonal skill. However, students also observed difficulties such as time management and teamwork collaboration. This research provides an overview of the effect of integrating an ED course within pre-service teacher training.
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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 | 0.009 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.004 | 0.054 |
| Scholarly communication | 0.016 | 0.008 |
| Open science | 0.002 | 0.008 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".