INCREASING STUDENT AWARENESS OF PROFESSIONALISM USING THE PROFESSIONALISM ASSESSMENT TOOL (PAT) IN A SENIOR UNDERGRADUATE ENGINEERING DESIGN COURSE
Bibliographic record
Abstract
The Canadian Engineering Accreditation Board’s definition of professionalism, one of twelve graduate attributes, does not mention professional behaviour, but rather focuses on understanding the role of engineers in society. While difficult to define, challenging to teach, and even harder to assess, the engineering faculty at the University of Guelph felt professional behaviour was an important element of professionalism to consider in their curriculum. This study investigates how professional behaviour might be taught and assessed. The researchers developed course material on professional behaviour for the winter 2019 offering of a third-year multidisciplinary design course (369 students), using Kelley et al.’s (2011) Professionalism Assessment Tool (PAT). Using a quasi-experimental design, the researchers assessed whether student professionalism improved based on their change in PAT scores over the semester using a Wilcoxon Signed-Rank test. They also analyzed a sample of student final reflections on professional behaviour. Student PAT scores increased significantly over the semester (n = 340, p<0.05), but the effect sizes observed, using Cohen’s d, were small (0.14 to 0.29). The student reflections (n = 53) suggest that improvements to their professionalism were a result of working in a team, experience gained from their project, and individual efforts made to behave professionally. While infrequently discussed in the reflections, over half of the post-term survey responses revealed that students felt the lab activities helped improve their professional skills generally, and/or increased their awareness of these skills. The improved awareness aspect of student professionalism was an unexpected, but important outcome of the PAT-based course material and may have reinforced student ownership of their soft skill development.
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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 | 0.001 | 0.001 |
| 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".