Shifting gears: the impact of extracurricular exposure on girls' attitudes towards engineering
Bibliographic record
Abstract
This paper explores the impact of Ryerson’s WEMADEIT Youth Think Tank (YTT) on participating girls’ understanding of and attitudes toward engineering. According to recent research, most teens openly admit that they are not familiar with the specifics of a job in engineering (Intel, 2011), typically associating the field of engineering with independent work and a math and science focus; however, the Canadian Engineering Accreditation Board (CEAB) emphasizes teamwork, socially-conscious thinking and entrepreneurship. Existing professional engineering organizations, including Engineers Without Borders (EWB), are also working to introduce the broader concept of the “Global Engineer” – a socially and ethically conscious, teamwork-driven, creative engineer. These recent trends in engineering reveal a disparity between public perception of engineering and the realities of the industry. The WEMADEIT project was formed in order to increase girls’ interest in and exposure to engineering in three ways: by creating a brand that correlates with new trends in engineering; by getting girls involved through an in-person Youth Think Tank (YTT); and by creating a new website (WEMADEIT.ca). Through interviews with five YTT participants, as well as an analysis of the content participants produced for the WEMADEIT website, this paper traces the journeys of a purposive sample of five teenage girls who have participated in the YTT. The researcher’s autoethnographic insights as the daughter of a female engineer further enrich the paper’s analysis and discussion. The findings suggest that exposure to engineering through the YTT generated greater interest in engineering and stronger self-efficacy in participants, opened up post-secondary conversation between participants and their parents and created positive outcome expectations for a career in engineering.
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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 | 0.003 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.004 | 0.001 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.008 | 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".