ADDRESSING DIVERSITY AND GENDER ISSUES IN A CORNERSTONE DESIGN COURSE
Bibliographic record
Abstract
In the cornerstone engineering design course for Mechanical and Industrial Engineering undergraduates at Ryerson University, students’ design approaches were being negatively affected by gender and other biases. Therefore, the course was modified to encourage students to explore these biases, with an initial emphasis on gender so that they may design with a fuller sense of women’s issues. This novel endeavour aimed to change the course’s culture via awareness, and by connecting equity, diversity, and inclusion to an engineering context. Qualitative analysis of student reports before and after these modifications showed that the intervention led to user groups that more closely matched actual demographics and included a higher number of women, LGBTQ, and elderly Personas than before. Furthermore, the qualitative descriptions showed less of a skewed tendency to attribute positive characteristics to men and negative characteristics to women after the course modifications were implemented. Student surveys indicated that there was a potential cultural shift within the course, and a broadening of student focus to include equity, diversity, and inclusion when undertaking an engineering design project.
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 | 0.000 |
| 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".