Embedding Equity in an Undergraduate Introductory Course through Experiential Learning
Bibliographic record
Abstract
Equity has been newly introduced as an outcome that needs to be addressed and assessed in undergraduate engineering programs in North America.In Canada, the Canadian Engineering Accreditation Board has been emphasizing that equity and ethics be embedded in the curriculum through their accreditation visits.This required several programs within our institution to work on methods that can be included to make students more aware of equity issues and assess their understanding on the above subjects.This paper discusses how courses were changed to include equity as part of the curriculum.Equity discussions were focused through the introduction of universal design as applied in building design-making students experience first-hand what the implications of design choices are on a diverse (age, physical / cognitive ability, race, gender) user group.Three different first year engineering groups were assessed in their knowledge of equity.Group 1 was the group that were prompted with a presentation in class about the different aspects of requirements for building design to address mobility issues followed by an audio recording prompting the students to do a tour on campus and experience first-hand these effects.The second group has done a campus tour without the audio and have been exposed to only the presentation in class.The third group is the control group who has only done the campus tour with no prompts and did not have the presentation.All three groups were assessed later in their knowledge of equity issues in building designs.This paper will share these findings and the details of what the students were exposed to in the three different groups.It also discusses recommendations for future changes that could be done to better include equity discussions and assessments in the curriculum.The paper also states how this could be modified for any undergraduate program.
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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 | 0.006 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.002 | 0.006 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.008 | 0.002 |
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".