DEVELOPMENT OF THE INDIVIDUAL AND TEAM WORK ATTRIBUTE AMONG UNDERGRADUATE ENGINEERING STUDENTS: TRENDS ACROSS 4 YEARS OF ASSESSMENT
Bibliographic record
Abstract
The Engineers Canada Accreditation Board outlines 12 Canadian Engineering Graduate Attributes required for program accreditation. One of these attributes is Individual and Team Work. Since 2016, at the University of Calgary, there has been a voluntary, undergraduate-wide survey administered to the Schulich School of Engineering students every spring via an online platform. The purpose of the survey is to assess students’ perceived development of teamwork skills during their program, and identify avenues to improve program offerings. After four consecutive years of this survey, with sample sizes ranging from 683-973 students, there are three main trends that can be identified: students perceive teamwork skills as highly important for their future careers, there are noticeable differences between male and female students regarding teamwork experiences, and students value teamwork skills training and opportunities for peer feedback. Implications of these findings are that there are gendered teamwork experiences among undergraduate engineering students and more research is needed to understand interventions that can mitigate this.
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 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 | 0.003 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".