DEVELOPMENT AND INTEGRATION OF TECHNICAL WRITING SKILLS ORIENTED TOWARD ENGINEERS’ NEEDS
Bibliographic record
Abstract
Written communication is among the skills future engineers must develop and master in order to excel in their profession. Employers and the Canadian Engineering Accreditation Board also require this skill. Students in all Polytechnique Montréal programs have one course credit in their program devoted to written and oral communication. The training is provided by Polytechnique’s Centre d’études complémentaires (centre for complementary studies) for all programs. 
 Despite the implementation of this process, we noted that civil engineering students had difficulty employing good technical writing practices in their work, such as capstone projects, lab reports and hands-on assignments. The students saw written communication workshops as satellite training and employed their learning only to a small degree in their other courses. The students were essentially stagnating instead of making progress throughout the bachelor’s degree.
 In response to these issues, a common approach was put into place for the entire civil engineering program as a complement to the trainings provided by the Centre d’études complémentaires. This approach has been a success; student response has been positive and improvement has been observed in the courses where writing is required. The students especially appreciate this when they perform their mandatory internship, because they feel this training makes a difference and helps them distinguish themselves.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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 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".