From Physics to Where? Diagnosing the Effect of a Discovery-based Teaching Paradigm on Continued Barriers to Women’s Entry to the Physical Engineering Science Professions (RTP, Diversity)
Bibliographic record
Abstract
Abstract ABSTRACT: Girls and boys participate equally in Physics 11 classrooms in the Greater Victoria Region in British Columbia. Yet girls continue to comprise less than 20% of Physics 12 classrooms and less than 15% of most engineering education programs. This active research focuses on diagnosing and mitigating the invisible barriers in Physics 11 that preclude young women from continuing their studies in physics to the 12th grade and beyond. Three identified factors for the persisting gender gap in physics follow. The first factor is rooted in stereotypical beliefs about engineering as a gendered career. The second factor arises from student beliefs that there is little new to discover in physics. The third factor relates to an inability to visualize how physics applications can make the world a better place. This paper presents an alternative to additive outreach programs prevalent in universities and engineering societies. The proposed teaching paradigm is demonstrably simple to implement, eases teacher workload, enhances student learning and creates a significant improvement in perceptions and beliefs about self-efficacy in physics, an indicator of student success and motivation. The research identifies an unanticipated impact of introducing engineering design principles into Physics 11 classrooms. Physics 11 teachers participated in developing a lesson plan that guides facilitators of learning through the discovery- or inquiry-based activity. The mixed methods research methodology included surveys, observations and interviews to generate data testing the hypothesis that connecting physics applications to scenarios derived from the students’ life experiences enhances girls’ understanding of the social benefits attainable through engineering design. The resulting teaching paradigm uses team-based, project-based learning techniques that create knowledge using processes directly applicable to engineering. The findings demonstrate trends indicating that male students may also increase in self-efficacy using this paradigm. This paper outlines the generalizable lesson plan and teaching techniques, and examines the unexpected outcomes citing numerous relevant peer-reviewed studies and reports.
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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 | 0.011 | 0.043 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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 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".